A Pseudo DNA Cryptography Method

Abstract: The DNA cryptography is a new and very promising direction in cryptography research. DNA can be used in cryptography for storing and transmitting the information, as well as for computation. Although in its primitive stage, DNA cryptography is shown to be very effective. Currently, several DNA computing algorithms are proposed for quite some cryptography, cryptanalysis and steganography problems, and they are very powerful in these areas. However, the use of the DNA as a means of cryptography has high tech lab requirements and computational limitations, as well as the labor intensive extrapolation means so far. These make the efficient use of DNA cryptography difficult in the security world now. Therefore, more theoretical analysis should be performed before its real applications. In this project, We do not intended to utilize real DNA to perform the cryptography process; rather, We will introduce a new cryptography method based on central dogma of molecular biology. Since this method simulates some critical processes in central dogma, it is a pseudo DNA cryptography method. The theoretical analysis and experiments show this method to be efficient in computation, storage and transmission; and it is very powerful against certain attacks. Thus, this method can be of many uses in cryptography, such as an enhancement insecurity and speed to the other cryptography methods. There are also extensions and variations to this method, which have enhanced security, effectiveness and applicability.


Dynamic Multi-Vehicle Routing with Multiple Classes of Demands

Abstract: In this paper we study a dynamic vehicle routing problem in which there are multiple vehicles and multiple classes of demands. Demands of each class arrive in the environment randomly over time and require a random amount of on-site service that is characteristic of the class. To service a demand, one of the vehicles must travel to the demand location and remain there for the required on-site service time. The quality of service provided to each class is given by the expected delay between the arrival of a demand in the class, and that demand's service completion. The goal is to design a routing policy for the service vehicles which minimizes a convex combination of the delays for each class. First, we provide a lower bound on the achievable values of the convex combination of delays. Then, we propose a novel routing policy and analyze its performance under heavy load conditions (i.e., when the fraction of time the service vehicles spend performing on-site service approaches one). The policy performs within a constant factor of the lower bound (and thus the optimal), where the constant depends only on the number of classes, and is independent of the number of vehicles, the arrival rates of demands, the on-site service times, and the convex combination coefficients.


On Hadwiger's Number of a graph with partial information

Abstract: We investigate the possibility of proving upper bounds on Hadwiger's number of a graph with partial information, mirroring several known upper bounds for the chromatic number. For each such bound we determine whether the corresponding bound for Hadwiger's number holds. Our results suggest that the ``locality'' of an inequality accounts for the existence of such an extension.


A Note on Preconditioning by Low-Stretch Spanning Trees

Abstract: Boman and Hendrickson observed that one can solve linear systems in Laplacian matrices in time $\bigO{m^{3/2 + o (1)} \ln (1/\epsilon)}$ by preconditioning with the Laplacian of a low-stretch spanning tree. By examining the distribution of eigenvalues of the preconditioned linear system, we prove that the preconditioned conjugate gradient will actually solve the linear system in time $\softO{m^{4/3} \ln (1/\epsilon)}$.


On the Computational Complexity of Satisfiability Solving for String Theories

Abstract: Satisfiability solvers are increasingly playing a key role in software verification, with particularly effective use in the analysis of security vulnerabilities. String processing is a key part of many software applications, such as browsers and web servers. These applications are susceptible to attacks through malicious data received over network. Automated tools for analyzing the security of such applications, thus need to reason about strings. For efficiency reasons, it is desirable to have a solver that treats strings as first-class types. In this paper, we present some theories of strings that are useful in a software security context and analyze the computational complexity of the presented theories. We use this complexity analysis to motivate a byte-blast approach which employs a Boolean encoding of the string constraints to a corresponding Boolean satisfiability problem.


A parameter-free hedging algorithm

Abstract: We study the problem of decision-theoretic online learning (DTOL). Motivated by practical applications, we focus on DTOL when the number of actions is very large. Previous algorithms for learning in this framework have a tunable learning rate parameter, and a barrier to using online-learning in practical applications is that it is not understood how to set this parameter optimally, particularly when the number of actions is large. In this paper, we offer a clean solution by proposing a novel and completely parameter-free algorithm for DTOL. We introduce a new notion of regret, which is more natural for applications with a large number of actions. We show that our algorithm achieves good performance with respect to this new notion of regret; in addition, it also achieves performance close to that of the best bounds achieved by previous algorithms with optimally-tuned parameters, according to previous notions of regret.


Tracking using explanation-based modeling

Abstract: We study the tracking problem, namely, estimating the hidden state of an object over time, from unreliable and noisy measurements. The standard framework for the tracking problem is the generative framework, which is the basis of solutions such as the Bayesian algorithm and its approximation, the particle filters. However, the problem with these solutions is that they are very sensitive to model mismatches. In this paper, motivated by online learning, we introduce a new framework -- an {\em explanatory} framework -- for tracking. We provide an efficient tracking algorithm for this framework. We provide experimental results comparing our algorithm to the Bayesian algorithm on simulated data. Our experiments show that when there are slight model mismatches, our algorithm vastly outperforms the Bayesian algorithm.


On $p$-adic Classification

Abstract: A $p$-adic modification of the split-LBG classification method is presented in which first clusterings and then cluster centers are computed which locally minimise an energy function. The outcome for a fixed dataset is independent of the prime number $p$ with finitely many exceptions. The methods are applied to the construction of $p$-adic classifiers in the context of learning.


A decidable policy language for history-based transaction monitoring

Abstract: Online trading invariably involves dealings between strangers, so it is important for one party to be able to judge objectively the trustworthiness of the other. In such a setting, the decision to trust a user may sensibly be based on that user's past behaviour. We introduce a specification language based on linear temporal logic for expressing a policy for categorising the behaviour patterns of a user depending on its transaction history. We also present an algorithm for checking whether the transaction history obeys the stated policy. To be useful in a real setting, such a language should allow one to express realistic policies which may involve parameter quantification and quantitative or statistical patterns. We introduce several extensions of linear temporal logic to cater for such needs: a restricted form of universal and existential quantification; arbitrary computable functions and relations in the term language; and a "counting" quantifier for counting how many times a formula holds in the past. We then show that model checking a transaction history against a policy, which we call the history-based transaction monitoring problem, is PSPACE-complete in the size of the policy formula and the length of the history. The problem becomes decidable in polynomial time when the policies are fixed. We also consider the problem of transaction monitoring in the case where not all the parameters of actions are observable. We formulate two such "partial observability" monitoring problems, and show their decidability under certain restrictions.


Introducing Hierarchy in Energy Games

Abstract: In this work we introduce hierarchy in wireless networks that can be modeled by a decentralized multiple access channel and for which energy-efficiency is the main performance index. In these networks users are free to choose their power control strategy to selfishly maximize their energy-efficiency. Specifically, we introduce hierarchy in two different ways: 1. Assuming single-user decoding at the receiver, we investigate a Stackelberg formulation of the game where one user is the leader whereas the other users are assumed to be able to react to the leader's decisions; 2. Assuming neither leader nor followers among the users, we introduce hierarchy by assuming successive interference cancellation at the receiver. It is shown that introducing a certain degree of hierarchy in non-cooperative power control games not only improves the individual energy efficiency of all the users but can also be a way of insuring the existence of a non-saturated equilibrium and reaching a desired trade-off between the global network performance at the equilibrium and the requested amount of signaling. In this respect, the way of measuring the global performance of an energy-efficient network is shown to be a critical issue.


Optimistic Simulated Exploration as an Incentive for Real Exploration

Abstract: Many reinforcement learning exploration techniques are overly optimistic and try to explore every state. Such exploration is impossible in environments with the unlimited number of states. I propose to use simulated exploration with an optimistic model to discover promising paths for real exploration. This reduces the needs for the real exploration.


Spatial Skyline Queries: An Efficient Geometric Algorithm

Abstract: As more data-intensive applications emerge, advanced retrieval semantics, such as ranking or skylines, have attracted attention. Geographic information systems are such an application with massive spatial data. Our goal is to efficiently support skyline queries over massive spatial data. To achieve this goal, we first observe that the best known algorithm VS2, despite its claim, may fail to deliver correct results. In contrast, we present a simple and efficient algorithm that computes the correct results. To validate the effectiveness and efficiency of our algorithm, we provide an extensive empirical comparison of our algorithm and VS2 in several aspects.


A Unified Theory of Time-Frequency Reassignment

Abstract: Time-frequency representations such as the spectrogram are commonly used to analyze signals having a time-varying distribution of spectral energy, but the spectrogram is constrained by an unfortunate tradeoff between resolution in time and frequency. A method of achieving high-resolution spectral representations has been independently introduced by several parties. The technique has been variously named reassignment and remapping, but while the implementations have differed in details, they are all based on the same theoretical and mathematical foundation. In this work, we present a brief history of work on the method we will call the method of time-frequency reassignment, and present a unified mathematical description of the technique and its derivation. We will focus on the development of time-frequency reassignment in the context of the spectrogram, and conclude with a discussion of some current applications of the reassigned spectrogram.


Efficiently Learning a Detection Cascade with Sparse Eigenvectors

Abstract: In this work, we first show that feature selection methods other than boosting can also be used for training an efficient object detector. In particular, we introduce Greedy Sparse Linear Discriminant Analysis (GSLDA) \cite{Moghaddam2007Fast} for its conceptual simplicity and computational efficiency; and slightly better detection performance is achieved compared with \cite{Viola2004Robust}. Moreover, we propose a new technique, termed Boosted Greedy Sparse Linear Discriminant Analysis (BGSLDA), to efficiently train a detection cascade. BGSLDA exploits the sample re-weighting property of boosting and the class-separability criterion of GSLDA.


Stabilizing Maximal Independent Set in Unidirectional Networks is Hard

Abstract: A distributed algorithm is self-stabilizing if after faults and attacks hit the system and place it in some arbitrary global state, the system recovers from this catastrophic situation without external intervention in finite time. In this paper, we consider the problem of constructing self-stabilizingly a \emph{maximal independent set} in uniform unidirectional networks of arbitrary shape. On the negative side, we present evidence that in uniform networks, \emph{deterministic} self-stabilization of this problem is \emph{impossible}. Also, the \emph{silence} property (\emph{i.e.} having communication fixed from some point in every execution) is impossible to guarantee, either for deterministic or for probabilistic variants of protocols. On the positive side, we present a deterministic protocol for networks with arbitrary unidirectional networks with unique identifiers that exhibits polynomial space and time complexity in asynchronous scheduling. We complement the study with probabilistic protocols for the uniform case: the first probabilistic protocol requires infinite memory but copes with asynchronous scheduling, while the second probabilistic protocol has polynomial space complexity but can only handle synchronous scheduling. Both probabilistic solutions have expected polynomial time complexity.


A Generic Framework for Reasoning about Dynamic Networks of Infinite-State Processes

Abstract: We propose a framework for reasoning about unbounded dynamic networks of infinite-state processes. We propose Constrained Petri Nets (CPN) as generic models for these networks. They can be seen as Petri nets where tokens (representing occurrences of processes) are colored by values over some potentially infinite data domain such as integers, reals, etc. Furthermore, we define a logic, called CML (colored markings logic), for the description of CPN configurations. CML is a first-order logic over tokens allowing to reason about their locations and their colors. Both CPNs and CML are parametrized by a color logic allowing to express constraints on the colors (data) associated with tokens. We investigate the decidability of the satisfiability problem of CML and its applications in the verification of CPNs. We identify a fragment of CML for which the satisfiability problem is decidable (whenever it is the case for the underlying color logic), and which is closed under the computations of post and pre images for CPNs. These results can be used for several kinds of analysis such as invariance checking, pre-post condition reasoning, and bounded reachability analysis.


Smart Antenna Based Broadband communication in Intelligent Transportation system

Abstract: This paper presents a review for the development of Intelligent Transportation System (ITS) world wide and the use of Smart Antennas in ITS. This review work also discusses the usual problems in ITS and proposes the solution of such problems using smart antennas.


Automated Vehicle Location (AVL) Using Global Positioning System (GPS)

Abstract: this is a review paper. this describes how DGPS is helpful for lane detection and to avoid collission.


Finding matching initial states for equivalent NLFSRs in the fibonacci and the galois configurations

Abstract: In this paper, a mapping between initial states of the Fibonacci and the Galois configurations of NLFSRs is established. We show how to choose initial states for two configurations so that the resulting output sequences are equivalent.


TR02: State dependent oracle masks for improved dynamical features

Abstract: Using the AURORA-2 digit recognition task, we show that recognition accuracies obtained with classical, SNR based oracle masks can be substantially improved by using a state-dependent mask estimation technique.


Nation-State Routing: Censorship, Wiretapping, and BGP

Abstract: The treatment of Internet traffic is increasingly affected by national policies that require the ISPs in a country to adopt common protocols or practices. Examples include government enforced censorship, wiretapping, and protocol deployment mandates for IPv6 and DNSSEC. If an entire nation's worth of ISPs apply common policies to Internet traffic, the global implications could be significant. For instance, how many countries rely on China or Great Britain (known traffic censors) to transit their traffic? These kinds of questions are surprisingly difficult to answer, as they require combining information collected at the prefix, Autonomous System, and country level, and grappling with incomplete knowledge about the AS-level topology and routing policies. In this paper we develop the first framework for country-level routing analysis, which allows us to answer questions about the influence of each country on the flow of international traffic. Our results show that some countries known for their national policies, such as Iran and China, have relatively little effect on interdomain routing, while three countries (the United States, Great Britain, and Germany) are central to international reachability, and their policies thus have huge potential impact.


A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data

Abstract: Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection methods are ineffective on scattered real-world datasets due to implicit data patterns and parameter setting issues. We define a novel "Local Distance-based Outlier Factor" (LDOF) to measure the {outlier-ness} of objects in scattered datasets which addresses these issues. LDOF uses the relative location of an object to its neighbours to determine the degree to which the object deviates from its neighbourhood. Properties of LDOF are theoretically analysed including LDOF's lower bound and its false-detection probability, as well as parameter settings. In order to facilitate parameter settings in real-world applications, we employ a top-n technique in our outlier detection approach, where only the objects with the highest LDOF values are regarded as outliers. Compared to conventional approaches (such as top-n KNN and top-n LOF), our method top-n LDOF is more effective at detecting outliers in scattered data. It is also easier to set parameters, since its performance is relatively stable over a large range of parameter values, as illustrated by experimental results on both real-world and synthetic datasets.


De-anonymizing Social Networks

Abstract: Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by anonymization, i.e., removing names, addresses, etc. We present a framework for analyzing privacy and anonymity in social networks and develop a new re-identification algorithm targeting anonymized social-network graphs. To demonstrate its effectiveness on real-world networks, we show that a third of the users who can be verified to have accounts on both Twitter, a popular microblogging service, and Flickr, an online photo-sharing site, can be re-identified in the anonymous Twitter graph with only a 12% error rate. Our de-anonymization algorithm is based purely on the network topology, does not require creation of a large number of dummy "sybil" nodes, is robust to noise and all existing defenses, and works even when the overlap between the target network and the adversary's auxiliary information is small.


On Oligopoly Spectrum Allocation Game in Cognitive Radio Networks with Capacity Constraints

Abstract: Dynamic spectrum sharing is a promising technology to improve spectrum utilization in the future wireless networks. The flexible spectrum management provides new opportunities for licensed primary user and unlicensed secondary users to reallocate the spectrum resource efficiently. In this paper, we present an oligopoly pricing framework for dynamic spectrum allocation in which the primary users sell excessive spectrum to the secondary users for monetary return. We present two approaches, the strict constraints (type-I) and the QoS penalty (type-II), to model the realistic situation that the primary users have limited capacities. In the oligopoly model with strict constraints, we propose a low-complexity searching method to obtain the Nash Equilibrium and prove its uniqueness. When reduced to a duopoly game, we analytically show the interesting gaps in the leader-follower pricing strategy. In the QoS penalty based oligopoly model, a novel variable transformation method is developed to derive the unique Nash Equilibrium. When the market information is limited, we provide three myopically optimal algorithms "StrictBEST", "StrictBR" and "QoSBEST" that enable price adjustment for duopoly primary users based on the Best Response Function (BRF) and the bounded rationality (BR) principles. Numerical results validate the effectiveness of our analysis and demonstrate the fast convergence of "StrictBEST" as well as "QoSBEST" to the Nash Equilibrium. For the "StrictBR" algorithm, we reveal the chaotic behaviors of dynamic price adaptation in response to the learning rates.


Hyperbolic Voronoi diagrams made easy

Abstract: We present a simple framework to compute hyperbolic Voronoi diagrams of finite point sets as affine diagrams. We prove that bisectors in Klein's non-conformal disk model are hyperplanes that can be interpreted as power bisectors of Euclidean balls. Therefore our method simply consists in computing an equivalent clipped power diagram followed by a mapping transformation depending on the selected representation of the hyperbolic space (e.g., Poincar\'e conformal disk or upper-plane representations). We discuss on extensions of this approach to weighted and $k$-order diagrams, and describe their dual triangulations. Finally, we consider two useful primitives on the hyperbolic Voronoi diagrams for designing tailored user interfaces of an image catalog browsing application in the hyperbolic disk: (1) finding nearest neighbors, and (2) computing smallest enclosing balls.


Discovering Matching Dependencies

Abstract: The concept of matching dependencies (mds) is recently pro- posed for specifying matching rules for object identification. Similar to the functional dependencies (with conditions), mds can also be applied to various data quality applications such as violation detection. In this paper, we study the problem of discovering matching dependencies from a given database instance. First, we formally define the measures, support and confidence, for evaluating utility of mds in the given database instance. Then, we study the discovery of mds with certain utility requirements of support and confidence. Exact algorithms are developed, together with pruning strategies to improve the time performance. Since the exact algorithm has to traverse all the data during the computation, we propose an approximate solution which only use some of the data. A bound of relative errors introduced by the approximation is also developed. Finally, our experimental evaluation demonstrates the efficiency of the proposed methods.


Fault-Tolerant Consensus in Unknown and Anonymous Networks

Abstract: This paper investigates under which conditions information can be reliably shared and consensus can be solved in unknown and anonymous message-passing networks that suffer from crash-failures. We provide algorithms to emulate registers and solve consensus under different synchrony assumptions. For this, we introduce a novel pseudo leader-election approach which allows a leader-based consensus implementation without breaking symmetry.


A Nice Labelling for Tree-Like Event Structures of Degree 3 (Extended Version)

Abstract: We address the problem of finding nice labellings for event structures of degree 3. We develop a minimum theory by which we prove that the labelling number of an event structure of degree 3 is bounded by a linear function of the height. The main theorem we present in this paper states that event structures of degree 3 whose causality order is a tree have a nice labelling with 3 colors. Finally, we exemplify how to use this theorem to construct upper bounds for the labelling number of other event structures of degree 3.


Fuzzy Chemical Abstract Machines

Abstract: Fuzzy set theory opens new vistas in computability theory and here I show this by defining a new computational metaphor--the fuzzy chemical metaphor. This metaphor is an extension of the chemical metaphor. In particular, I introduce the idea of a state of a system as a solution of fuzzy molecules, that is molecules that are not just different but rather similar, that react according to a set of fuzzy reaction rules. These notions become precise by introducing fuzzy labeled transition systems. Solutions of fuzzy molecules and fuzzy reaction rules are used to define the general notion of a fuzzy chemical abstract machine, which is a {\em realization} of the fuzzy chemical metaphor. Based on the idea that these machines can be used to describe the operational semantics of process calculi and algebras that include fuzziness as a fundamental property, I present a toy calculus that is a fuzzy equivalent of the $\pi$-calculus.


Ambient Isotopic Meshing of Implicit Algebraic Surface with Singularities

Abstract: A complete method is proposed to compute a certified, or ambient isotopic, meshing for an implicit algebraic surface with singularities. By certified, we mean a meshing with correct topology and any given geometric precision. We propose a symbolic-numeric method to compute a certified meshing for the surface inside a box containing singularities and use a modified Plantinga-Vegter marching cube method to compute a certified meshing for the surface inside a box without singularities. Nontrivial examples are given to show the effectiveness of the algorithm. To our knowledge, this is the first method to compute a certified meshing for surfaces with singularities.


String comparison by transposition networks

Abstract: Computing string or sequence alignments is a classical method of comparing strings and has applications in many areas of computing, such as signal processing and bioinformatics. Semi-local string alignment is a recent generalisation of this method, in which the alignment of a given string and all substrings of another string are computed simultaneously at no additional asymptotic cost. In this paper, we show that there is a close connection between semi-local string alignment and a certain class of traditional comparison networks known as transposition networks. The transposition network approach can be used to represent different string comparison algorithms in a unified form, and in some cases provides generalisations or improvements on existing algorithms. This approach allows us to obtain new algorithms for sparse semi-local string comparison and for comparison of highly similar and highly dissimilar strings, as well as of run-length compressed strings. We conclude that the transposition network method is a very general and flexible way of understanding and improving different string comparison algorithms, as well as their efficient implementation.


Algorithmic Solutions to Some Transportation Optimization Problems with Applications in the Metallurgical Industry

Abstract: In this paper we address several constrained transportation optimization problems (e.g. vehicle routing, shortest Hamiltonian path), for which we present novel algorithmic solutions and extensions, considering several optimization objectives, like minimizing costs and resource usage. All the considered problems are motivated by practical situations arising, for instance, in the mining and metallurgical industry or in data communication. We restrict our attention to transportation networks with path, tree or geometric structures, for which the developed polynomial-time algorithms are optimal or nearly optimal.


Distributed and Adaptive Algorithms for Vehicle Routing in a Stochastic and Dynamic Environment

Abstract: In this paper we present distributed and adaptive algorithms for motion coordination of a group of m autonomous vehicles. The vehicles operate in a convex environment with bounded velocity and must service demands whose time of arrival, location and on-site service are stochastic; the objective is to minimize the expected system time (wait plus service) of the demands. The general problem is known as the m-vehicle Dynamic Traveling Repairman Problem (m-DTRP). The best previously known control algorithms rely on centralized a-priori task assignment and are not robust against changes in the environment, e.g. changes in load conditions; therefore, they are of limited applicability in scenarios involving ad-hoc networks of autonomous vehicles operating in a time-varying environment. First, we present a new class of policies for the 1-DTRP problem that: (i) are provably optimal both in light- and heavy-load condition, and (ii) are adaptive, in particular, they are robust against changes in load conditions. Second, we show that partitioning policies, whereby the environment is partitioned among the vehicles and each vehicle follows a certain set of rules in its own region, are optimal in heavy-load conditions. Finally, by combining the new class of algorithms for the 1-DTRP with suitable partitioning policies, we design distributed algorithms for the m-DTRP problem that (i) are spatially distributed, scalable to large networks, and adaptive to network changes, (ii) are within a constant-factor of optimal in heavy-load conditions and stabilize the system in any load condition. Simulation results are presented and discussed.


Combinatorial Ricci Curvature and Laplacians for Image Processing

Abstract: A new Combinatorial Ricci curvature and Laplacian operators for grayscale images are introduced and tested on 2D synthetic, natural and medical images. Analogue formulae for voxels are also obtained. These notions are based upon more general concepts developed by R. Forman. Further applications, in particular a fitting Ricci flow, are discussed.


Computations modulo regular chains

Abstract: The computation of triangular decompositions are based on two fundamental operations: polynomial GCDs modulo regular chains and regularity test modulo saturated ideals. We propose new algorithms for these core operations relying on modular methods and fast polynomial arithmetic. Our strategies take also advantage of the context in which these operations are performed. We report on extensive experimentation, comparing our code to pre-existing Maple implementations, as well as more optimized Magma functions. In most cases, our new code outperforms the other packages by several orders of magnitude.


GeoP2P: An adaptive peer-to-peer overlay for efficient search and update of spatial information

Abstract: This paper proposes a fully decentralized peer-to-peer overlay structure GeoP2P, to facilitate geographic location based search and retrieval of information. Certain limitations of centralized geographic indexes favor peer-to-peer organization of the information, which, in addition to avoiding performance bottleneck, allows autonomy over local information. Peer-to-peer systems for geographic or multidimensional range queries built on existing DHTs suffer from the inaccuracy in linearization of the multidimensional space. Other overlay structures that are based on hierarchical partitioning of the search space are not scalable because they use special super-peers to represent the nodes in the hierarchy. GeoP2P partitions the search space hierarchically, maintains the overlay structure and performs the routing without the need of any super-peers. Although similar fully-decentralized overlays have been previously proposed, they lack the ability to dynamically grow and retract the partition hierarchy when the number of peers change. GeoP2P provides such adaptive features with minimum perturbation of the system state. Such adaptation makes both the routing delay and the state size of each peer logarithmic to the total number of peers, irrespective of the size of the multidimensional space. Our analysis also reveals that the overlay structure and the routing algorithm are generic and independent of several aspects of the partitioning hierarchy, such as the geometric shape of the zones or the dimensionality of the search space.


Personal report of the 3rd ECMDA-FA'07 conference

Abstract: Manuscripts notes taken during the conference ECMDA 2008. I give the full conference program (title of the article and name of the person who introduced) detailing some of the presentations.


Using Structural Recursion for Corecursion

Abstract: We propose a (limited) solution to the problem of constructing stream values defined by recursive equations that do not respect the guardedness condition. The guardedness condition is imposed on definitions of corecursive functions in Coq, AGDA, and other higher-order proof assistants. In this paper, we concentrate in particular on those non-guarded equations where recursive calls appear under functions. We use a correspondence between streams and functions over natural numbers to show that some classes of non-guarded definitions can be modelled through the encoding as structural recursive functions. In practice, this work extends the class of stream values that can be defined in a constructive type theory-based theorem prover with inductive and coinductive types, structural recursion and guarded corecursion


Optimized Implementation of Elliptic Curve Based Additive Homomorphic Encryption for Wireless Sensor Networks

Abstract: When deploying wireless sensor networks (WSNs) in public environments it may become necessary to secure their data storage and transmission against possible attacks such as node-compromise and eavesdropping. The nodes feature only small computational and energy resources, thus requiring efficient algorithms. As a solution for this problem the TinyPEDS approach was proposed in [7], which utilizes the Elliptic Curve ElGamal (EC-ElGamal) cryptosystem for additive homomorphic encryption allowing concealed data aggregation. This work presents an optimized implementation of EC-ElGamal on a MicaZ mote, which is a typical sensor node platform with 8-bit processor for WSNs. Compared to the best previous result, our implementation is at least 44% faster for fixed-point multiplication. Because most parts of the algorithm are similar to standard Elliptic Curve algorithms, the results may be reused in other realizations on constrained devices as well.


Designing a GUI for Proofs - Evaluation of an HCI Experiment

Abstract: Often user interfaces of theorem proving systems focus on assisting particularly trained and skilled users, i.e., proof experts. As a result, the systems are difficult to use for non-expert users. This paper describes a paper and pencil HCI experiment, in which (non-expert) students were asked to make suggestions for a GUI for an interactive system for mathematical proofs. They had to explain the usage of the GUI by applying it to construct a proof sketch for a given theorem. The evaluation of the experiment provides insights for the interaction design for non-expert users and the needs and wants of this user group.


Gradient-based adaptive interpolation in super-resolution image restoration

Abstract: This paper presents a super-resolution method based on gradient-based adaptive interpolation. In this method, in addition to considering the distance between the interpolated pixel and the neighboring valid pixel, the interpolation coefficients take the local gradient of the original image into account. The smaller the local gradient of a pixel is, the more influence it should have on the interpolated pixel. And the interpolated high resolution image is finally deblurred by the application of wiener filter. Experimental results show that our proposed method not only substantially improves the subjective and objective quality of restored images, especially enhances edges, but also is robust to the registration error and has low computational complexity.


BLOGRANK: Ranking Weblogs Based On Connectivity And Similarity Features

Abstract: A large part of the hidden web resides in weblog servers. New content is produced in a daily basis and the work of traditional search engines turns to be insufficient due to the nature of weblogs. This work summarizes the structure of the blogosphere and highlights the special features of weblogs. In this paper we present a method for ranking weblogs based on the link graph and on several similarity characteristics between weblogs. First we create an enhanced graph of connected weblogs and add new types of edges and weights utilising many weblog features. Then, we assign a ranking to each weblog using our algorithm, BlogRank, which is a modified version of PageRank. For the validation of our method we run experiments on a weblog dataset, which we process and adapt to our search engine. (http://spiderwave.aueb.gr/Blogwave). The results suggest that the use of the enhanced graph and the BlogRank algorithm is preferred by the users.


Boolean Logic with Fault Tolerant Coding

Abstract: Error detectable and error correctable coding in Hamming space was researched to discover possible fault tolerant coding constellations, which can implement Boolean logic with fault tolerant property. Basic logic operators of the Boolean algebra were developed to apply fault tolerant coding in the logic circuits. It was shown that application of three-bit fault tolerant codes have provided the digital system skill of auto-recovery without need for designing additional-fault tolerance mechanisms.


The generating of Fractal Images Using MathCAD Program

Abstract: This paper presents the graphic representation in the z-plane of the first three iterations of the algorithm that generates the Sierpinski Gasket. It analyzes the influence of the f(z) map when we represent fractal images.


Decentralized Management of Bi-modal Network Resources in a Distributed Stream Processing Platform

Abstract: This paper presents resource management techniques for allocating communication and computational resources in a distributed stream processing platform. The platform is designed to exploit the synergy of two classes of network connections -- dedicated and opportunistic. Previous studies we conducted have demonstrated the benefits of such bi-modal resource organization that combines small pools of dedicated computers with a very large pool of opportunistic computing capacities of idle computers to serve high throughput computing applications. This paper extends the idea of bi-modal resource organization into the management of communication resources. Since distributed stream processing applications demand large volume of data transmission between processing sites at a consistent rate, adequate control over the network resources is important to assure a steady flow of processing. The system model used in this paper is a platform where stream processing servers at distributed sites are interconnected with a combination of dedicated and opportunistic communication links. Two pertinent resource allocation problems are analyzed in details and solved using decentralized algorithms. One is the mapping of the stream processing tasks on the processing and the communication resources. The other is the adaptive re-allocation of the opportunistic communication links due to the variations in their capacities. Overall optimization goal is higher task throughput and better utilization of the expensive dedicated links. The evaluation demonstrates that the algorithms are able to exploit the synergy of bi-modal communication links towards achieving the optimization goals.


Polylog space compression, pushdown compression, and Lempel-Ziv are incomparable

Abstract: The pressing need for efficient compression schemes for XML documents has recently been focused on stack computation, and in particular calls for a formulation of information-lossless stack or pushdown compressors that allows a formal analysis of their performance and a more ambitious use of the stack in XML compression, where so far it is mainly connected to parsing mechanisms. In this paper we introduce the model of pushdown compressor, based on pushdown transducers that compute a single injective function while keeping the widest generality regarding stack computation. We also consider online compression algorithms that use at most polylogarithmic space (plogon). These algorithms correspond to compressors in the data stream model. We compare the performance of these two families of compressors with each other and with the general purpose Lempel-Ziv algorithm. This comparison is made without any a priori assumption on the data's source and considering the asymptotic compression ratio for infinite sequences. We prove that in all cases they are incomparable.


Overlay Structure for Large Scale Content Sharing: Leveraging Geography as the Basis for Routing Locality

Abstract: In this paper we place our arguments on two related issues in the design of generalized structured peer-to-peer overlays. First, we argue that for the large-scale content-sharing applications, lookup and content transport functions need to be treated separately. Second, to create a location-based routing overlay suitable for content sharing and other applications, we argue that off-the-shelf geographic coordinates of Internet-connected hosts can be used as a basis. We then outline the design principles and present a design for the generalized routing overlay based on adaptive hierarchical partitioning of the geographical space.


Pairing Heaps with Costless Meld

Abstract: Improving the structure and analysis in \cite{elm0}, we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an $O(\log \log{n})$ in \cite{elm0}) and the same amortized bounds for all other operations. More precisely, the new pairing heap requires: no cost per meld, O(1) per find-min and insert, $O(\log{n})$ per delete-min, and $O(\log\log{n})$ per decrease-key. These bounds are the best known for any self-adjusting heap, and match the lower bound proved by Fredman for a family of such heaps. Moreover, the changes we have done make our structure even simpler than that in \cite{elm0}.


Conditional Probability Tree Estimation Analysis and Algorithms

Abstract: We consider the problem of estimating the conditional probability of a label in time $O(\log n)$, where $n$ is the number of possible labels. We analyze a natural reduction of this problem to a set of binary regression problems organized in a tree structure, proving a regret bound that scales with the depth of the tree. Motivated by this analysis, we propose the first online algorithm which provably constructs a logarithmic depth tree on the set of labels to solve this problem. We test the algorithm empirically, showing that it works succesfully on a dataset with roughly $10^6$ labels.


On the Use of Suffix Arrays for Memory-Efficient Lempel-Ziv Data Compression

Abstract: Much research has been devoted to optimizing algorithms of the Lempel-Ziv (LZ) 77 family, both in terms of speed and memory requirements. Binary search trees and suffix trees (ST) are data structures that have been often used for this purpose, as they allow fast searches at the expense of memory usage. In recent years, there has been interest on suffix arrays (SA), due to their simplicity and low memory requirements. One key issue is that an SA can solve the sub-string problem almost as efficiently as an ST, using less memory. This paper proposes two new SA-based algorithms for LZ encoding, which require no modifications on the decoder side. Experimental results on standard benchmarks show that our algorithms, though not faster, use 3 to 5 times less memory than the ST counterparts. Another important feature of our SA-based algorithms is that the amount of memory is independent of the text to search, thus the memory that has to be allocated can be defined a priori. These features of low and predictable memory requirements are of the utmost importance in several scenarios, such as embedded systems, where memory is at a premium and speed is not critical. Finally, we point out that the new algorithms are general, in the sense that they are adequate for applications other than LZ compression, such as text retrieval and forward/backward sub-string search.


SEPIA: Security through Private Information Aggregation

Abstract: Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that are practical in terms of computation and communication cost is still a major challenge. In this paper, we investigate the practical usefulness of MPC for multi-domain network security and monitoring. We first optimize MPC comparison operations for processing high volume data in near real-time. We then design privacy-preserving protocols for event correlation and aggregation of network traffic statistics, such as addition of volume metrics, computation of feature entropy, and distinct item count. Optimizing performance of parallel invocations, we implement our protocols along with a complete set of basic operations in a library called SEPIA. We evaluate the running time and bandwidth requirements of our protocols in realistic settings on a local cluster as well as on PlanetLab and show that they work in near real-time for up to 140 input providers and 9 computation nodes. Compared to implementations using existing general-purpose MPC frameworks, our protocols are significantly faster, requiring, for example, 3 minutes for a task that takes 2 days with general-purpose frameworks. This improvement paves the way for new applications of MPC in the area of networking. Finally, we run SEPIA's protocols on real traffic traces of 17 networks and show how they provide new possibilities for distributed troubleshooting and early anomaly detection.


On-Line Tests

Abstract: This paper presents an interactive implementation which makes the link between a human operator and a system of a administration of a relational databases MySQL. This application conceived as a multimedia presentations is illustrative for the way in which the transfer and the remaking of the information between the human operator, the module of data processing and the database which stores the informations can be solved (with help of the PHP language and the web use).


The Risk-Utility Tradeoff for IP Address Truncation

Abstract: Network operators are reluctant to share traffic data due to security and privacy concerns. Consequently, there is a lack of publicly available traces for validating and generalizing the latest results in network and security research. Anonymization is a possible solution in this context; however, it is unclear how the sanitization of data preserves characteristics important for traffic analysis. In addition, the privacy-preserving property of state-of-the-art IP address anonymization techniques has come into question by recent attacks that successfully identified a large number of hosts in anonymized traces. In this paper, we examine the tradeoff between data utility for anomaly detection and the risk of host identification for IP address truncation. Specifically, we analyze three weeks of unsampled and non-anonymized network traces from a medium-sized backbone network to assess data utility. The risk of de-anonymizing individual IP addresses is formally evaluated, using a metric based on conditional entropy. Our results indicate that truncation effectively prevents host identification but degrades the utility of data for anomaly detection. However, the degree of degradation depends on the metric used and whether network-internal or external addresses are considered. Entropy metrics are more resistant to truncation than unique counts and the detection quality of anomalies degrades much faster in internal addresses than in external addresses. In particular, the usefulness of internal address counts is lost even for truncation of only 4 bits whereas utility of external address entropy is virtually unchanged even for truncation of 20 bits.


Delving into Transition to the Semantic Web

Abstract: The semantic technologies pose new challenge for the way in which we built and operate systems. They are tools used to represent significances, associations, theories, separated from data and code. Their goal is to create, to discover, to represent, to organize, to process, to manage, to ratiocinate, to represent, to share and use the significances and knowledge to fulfill the business, personal or social goals.


Analysis of some properties for a basic Petri net model

Abstract: The formalism of the models with Petri networks provides a sound theoretical base, supported by powerful mathematical methods able to extract information necessary for the formalism and simulation of the real system that provides features of competition and synchronization. The paper presents a model based on a Petri net, in order to extract information relative to the technological producing process of a food additive.


Pipeline Leak Detection Techniques

Abstract: Leak detection systems range from simple, visual line walking and checking ones to complex arrangements of hard-ware and software. No one method is universally applicable and operating requirements dictate which method is the most cost effective. The aim of the paper is to review the basic techniques of leak detection that are currently in use. The advantages and disadvantages of each method are discussed and some indications of applicability are outlined.


Computer Systems to Oil Pipeline Transporting

Abstract: Computer systems in the pipeline oil transporting that the greatest amount of data can be gathered, analyzed and acted upon in the shortest amount of time. Most operators now have some form of computer based monitoring system employing either commercially available or custom developed software to run the system. This paper presented the SCADA systems to oil pipeline in concordance to the Romanian environmental reglementations.


Non linear system become linear system

Abstract: The present paper refers to the theory and the practice of the systems regarding non-linear systems and their applications. We aimed the integration of these systems to elaborate their response as well as to highlight some outstanding features.


Token Ring Project

Abstract: Ring topology is a simple configuration used to connect processes that communicate among themselves. A number of network standards such as token ring, token bus, and FDDI are based on the ring connectivity. This article will develop an implementation of a ring of processes that communicate among themselves via pipe links. The processes are nodes in the ring. Each process reads from its standard input and writes in its standard output. N-1 process redirects the its standard output to a standard input of the process through a pipe. When the ring-structure is designed, the project can be extended to simulate networks or to implement algorithms for mutual exclusion.


ShopList: Programming PDA applications for Windows Mobile using C#

Abstract: This paper is focused on a C# and Sql Server Mobile 2005 application to keep evidence of a shop list. The purpose of the application is to offer to the user an easier way to manage his shopping options.


Evaluation d'une requete en SQL

Abstract: The objective of this paper is to show how the interrogation processor responds to SQL interrogation. The interrogation processor is split into two parts. The first, called the interrogation compiler translates an SQL query into a plan of physical execution. The second, called evaluation query runs the execution plan.


FISLAB - the Fuzzy Inference Tool-box for SCILAB

Abstract: The present study represents "The Fislab package of programs meant to develop the fuzzy regulators in the Scilab environment" in which we present some general issues, usage requirements and the working mode of the Fislab environment. In the second part of the article some features of the Scilab functions from the Fislab package are described.


The development of a fuzzy regulator with an entry and an output in Fislab

Abstract: The present article is a sequel of the article "Fislab the Fuzzy Inference Tool-Box for Scilab" and it represents the practical application of:"The development of the Fuzzy regulator with an input and an output in Fislab". The article contains, besides this application, some functions to be used in the program, namely Scilab functions for the fuzzification of the firm information, functions for the operation of de-fuzzification and functions for the implementation of.


Virtual Reality

Abstract: This paper is focused on the presentation of Virtual Reality principles together with the main implementation methods and techniques. An overview of the main development directions is included.


Sums of powers via integration

Abstract: Sum of powers 1^p+...+n^p, with n and p being natural numbers and n>=1, can be expressed as a polynomial function of n of degree p+1. Such representations are often called Faulhaber formulae. A simple recursive algorithm for computing coefficients of Faulhaber formulae is presented. The correctness of the algorithm is proved by giving a recurrence relation on Faulhaber formulae.


CliqueStream: an efficient and fault-resilient live streaming network on a clustered peer-to-peer overlay

Abstract: Several overlay-based live multimedia streaming platforms have been proposed in the recent peer-to-peer streaming literature. In most of the cases, the overlay neighbors are chosen randomly for robustness of the overlay. However, this causes nodes that are distant in terms of proximity in the underlying physical network to become neighbors, and thus data travels unnecessary distances before reaching the destination. For efficiency of bulk data transmission like multimedia streaming, the overlay neighborhood should resemble the proximity in the underlying network. In this paper, we exploit the proximity and redundancy properties of a recently proposed clique-based clustered overlay network, named eQuus, to build efficient as well as robust overlays for multimedia stream dissemination. To combine the efficiency of content pushing over tree structured overlays and the robustness of data-driven mesh overlays, higher capacity stable nodes are organized in tree structure to carry the long haul traffic and less stable nodes with intermittent presence are organized in localized meshes. The overlay construction and fault-recovery procedures are explained in details. Simulation study demonstrates the good locality properties of the platform. The outage time and control overhead induced by the failure recovery mechanism are minimal as demonstrated by the analysis.


Complexity of Fractran and Productivity

Abstract: In functional programming languages the use of infinite structures is common practice. For total correctness of programs dealing with infinite structures one must guarantee that every finite part of the result can be evaluated in finitely many steps. This is known as productivity. For programming with infinite structures, productivity is what termination in well-defined results is for programming with finite structures. Fractran is a simple Turing-complete programming language invented by Conway. We prove that the question whether a Fractran program halts on all positive integers is Pi^0_2-complete. In functional programming, productivity typically is a property of individual terms with respect to the inbuilt evaluation strategy. By encoding Fractran programs as specifications of infinite lists, we establish that this notion of productivity is Pi^0_2-complete even for the most simple specifications. Therefore it is harder than termination of individual terms. In addition, we explore possible generalisations of the notion of productivity in the framework of term rewriting, and prove that their computational complexity is Pi^1_1-complete, thus exceeding the expressive power of first-order logic.


Using Dedicated and Opportunistic Networks in Synergy for a Cost-effective Distributed Stream Processing Platform

Abstract: This paper presents a case for exploiting the synergy of dedicated and opportunistic network resources in a distributed hosting platform for data stream processing applications. Our previous studies have demonstrated the benefits of combining dedicated reliable resources with opportunistic resources in case of high-throughput computing applications, where timely allocation of the processing units is the primary concern. Since distributed stream processing applications demand large volume of data transmission between the processing sites at a consistent rate, adequate control over the network resources is important here to assure a steady flow of processing. In this paper, we propose a system model for the hybrid hosting platform where stream processing servers installed at distributed sites are interconnected with a combination of dedicated links and public Internet. Decentralized algorithms have been developed for allocation of the two classes of network resources among the competing tasks with an objective towards higher task throughput and better utilization of expensive dedicated resources. Results from extensive simulation study show that with proper management, systems exploiting the synergy of dedicated and opportunistic resources yield considerably higher task throughput and thus, higher return on investment over the systems solely using expensive dedicated resources.


Ranking Functions for Size-Change Termination II

Abstract: Size-Change Termination is an increasingly-popular technique for verifying program termination. These termination proofs are deduced from an abstract representation of the program in the form of "size-change graphs". We present algorithms that, for certain classes of size-change graphs, deduce a global ranking function: an expression that ranks program states, and decreases on every transition. A ranking function serves as a witness for a termination proof, and is therefore interesting for program certification. The particular form of the ranking expressions that represent SCT termination proofs sheds light on the scope of the proof method. The complexity of the expressions is also interesting, both practicaly and theoretically. While deducing ranking functions from size-change graphs has already been shown possible, the constructions in this paper are simpler and more transparent than previously known. They improve the upper bound on the size of the ranking expression from triply exponential down to singly exponential (for certain classes of instances). We claim that this result is, in some sense, optimal. To this end, we introduce a framework for lower bounds on the complexity of ranking expressions and prove exponential lower bounds.


Towards a decentralized algorithm for mapping network and computational resources for distributed data-flow computations

Abstract: Several high-throughput distributed data-processing applications require multi-hop processing of streams of data. These applications include continual processing on data streams originating from a network of sensors, composing a multimedia stream through embedding several component streams originating from different locations, etc. These data-flow computing applications require multiple processing nodes interconnected according to the data-flow topology of the application, for on-stream processing of the data. Since the applications usually sustain for a long period, it is important to optimally map the component computations and communications on the nodes and links in the network, fulfilling the capacity constraints and optimizing some quality metric such as end-to-end latency. The mapping problem is unfortunately NP-complete and heuristics have been previously proposed to compute the approximate solution in a centralized way. However, because of the dynamicity of the network, it is practically impossible to aggregate the correct state of the whole network in a single node. In this paper, we present a distributed algorithm for optimal mapping of the components of the data flow applications. We propose several heuristics to minimize the message complexity of the algorithm while maintaining the quality of the solution.


Tree decomposition and postoptimality analysis in discrete optimization

Abstract: Many real discrete optimization problems (DOPs) are $NP$-hard and contain a huge number of variables and/or constraints that make the models intractable for currently available solvers. Large DOPs can be solved due to their special tructure using decomposition approaches. An important example of decomposition approaches is tree decomposition with local decomposition algorithms using the special block matrix structure of constraints which can exploit sparsity in the interaction graph of a discrete optimization problem. In this paper, discrete optimization problems with a tree structural graph are solved by local decomposition algorithms. Local decomposition algorithms generate a family of related DO problems which have the same structure but differ in the right-hand sides. Due to this fact, postoptimality techniques in DO are applied.


Differentially Private Combinatorial Optimization

Abstract: Consider the following problem: given a metric space, some of whose points are "clients", open a set of at most $k$ facilities to minimize the average distance from the clients to these facilities. This is just the well-studied $k$-median problem, for which many approximation algorithms and hardness results are known. Note that the objective function encourages opening facilities in areas where there are many clients, and given a solution, it is often possible to get a good idea of where the clients are located. However, this poses the following quandary: what if the identity of the clients is sensitive information that we would like to keep private? Is it even possible to design good algorithms for this problem that preserve the privacy of the clients? In this paper, we initiate a systematic study of algorithms for discrete optimization problems in the framework of differential privacy (which formalizes the idea of protecting the privacy of individual input elements). We show that many such problems indeed have good approximation algorithms that preserve differential privacy; this is even in cases where it is impossible to preserve cryptographic definitions of privacy while computing any non-trivial approximation to even the_value_ of an optimal solution, let alone the entire solution. Apart from the $k$-median problem, we study the problems of vertex and set cover, min-cut, facility location, Steiner tree, and the recently introduced submodular maximization problem, "Combinatorial Public Projects" (CPP).


Building the information kernel and the problem of recognition

Abstract: At this point in time there is a need for a new representation of different information, to identify and organize descending its characteristics. Today, science is a powerful tool for the description of reality - the numbers. Why the most important property of numbers. Suppose we have a number 0.2351734, it is clear that the figures are there in order of importance. If necessary, we can round the number up to some value, eg 0.235. Arguably, the 0,235 - the most important information of 0.2351734. Thus, we can reduce the size of numbers is not losing much with the accuracy. Clearly, if learning to provide a graphical or audio information kernel, we can provide the most relevant information, discarding the rest. Introduction of various kinds of information in an information kernel, is an important task, to solve many problems in artificial intelligence and information theory.


Solving Dominating Set in Larger Classes of Graphs: FPT Algorithms and Polynomial Kernels

Abstract: We show that the k-Dominating Set problem is fixed parameter tractable (FPT) and has a polynomial kernel for any class of graphs that exclude K_{i,j} as a subgraph, for any fixed i, j >= 1. This strictly includes every class of graphs for which this problem has been previously shown to have FPT algorithms and/or polynomial kernels. In particular, our result implies that the problem restricted to bounded- degenerate graphs has a polynomial kernel, solving an open problem posed by Alon and Gutner.


Graph polynomials and approximation of partition functions with Loopy Belief Propagation

Abstract: The Bethe approximation, or loopy belief propagation algorithm is a successful method for approximating partition functions of probabilistic models associated with a graph. Chertkov and Chernyak derived an interesting formula called Loop Series Expansion, which is an expansion of the partition function. The main term of the series is the Bethe approximation while other terms are labeled by subgraphs called generalized loops. In our recent paper, we derive the loop series expansion in form of a polynomial with coefficients positive integers, and extend the result to the expansion of marginals. In this paper, we give more clear derivation for the results and discuss the properties of the polynomial which is introduced in the paper.


Nonnegative approximations of nonnegative tensors

Abstract: We study the decomposition of a nonnegative tensor into a minimal sum of outer product of nonnegative vectors and the associated parsimonious naive Bayes probabilistic model. We show that the corresponding approximation problem, which is central to nonnegative PARAFAC, will always have optimal solutions. The result holds for any choice of norms and, under a mild assumption, even Bregman divergences.


Computer- and robot-assisted Medical Intervention

Abstract: Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.


Multidimensional Online Robot Motion

Abstract: We consider three related problems of robot movement in arbitrary dimensions: coverage, search, and navigation. For each problem, a spherical robot is asked to accomplish a motion-related task in an unknown environment whose geometry is learned by the robot during navigation. The robot is assumed to have tactile and global positioning sensors. We view these problems from the perspective of (non-linear) competitiveness as defined by Gabriely and Rimon. We first show that in 3 dimensions and higher, there is no upper bound on competitiveness: every online algorithm can do arbitrarily badly compared to the optimal. We then modify the problems by assuming a fixed clearance parameter. We are able to give optimally competitive algorithms under this assumption.


Range Quantile Queries: Another Virtue of Wavelet Trees

Abstract: We show how to use a balanced wavelet tree as a data structure that stores a list of numbers and supports efficient {\em range quantile queries}. A range quantile query takes a rank and the endpoints of a sublist and returns the number with that rank in that sublist. For example, if the rank is half the sublist's length, then the query returns the sublist's median. We also show how these queries can be used to support space-efficient {\em coloured range reporting} and {\em document listing}.


Graph Homomorphisms with Complex Values: A Dichotomy Theorem

Abstract: Graph homomorphism has been studied intensively. Given an m x m symmetric matrix A, the graph homomorphism function is defined as \[Z_A (G) = \sum_{f:V->[m]} \prod_{(u,v)\in E} A_{f(u),f(v)}, \] where G = (V,E) is any undirected graph. The function Z_A can encode many interesting graph properties, including counting vertex covers and k-colorings. We study the computational complexity of Z_A for arbitrary symmetric matrices A with algebraic complex values. Building on work by Dyer and Greenhill, Bulatov and Grohe, and especially the recent beautiful work by Goldberg, Grohe, Jerrum and Thurley, we prove a complete dichotomy theorem for this problem. We show that Z_A is either computable in polynomial-time or #P-hard, depending explicitly on the matrix A. We further prove that the tractability criterion on A is polynomial-time decidable.


Act of CVT and EVT In The Formation of Number-Theoretic Fractals

Abstract: In this paper we have defined two functions that have been used to construct different fractals having fractal dimensions between 1 and 2. More precisely, we can say that one of our defined functions produce the fractals whose fractal dimension lies in [1.58, 2) and rest function produce the fractals whose fractal dimension lies in (1, 1.58]. Also we tried to calculate the amount of increment of fractal dimension in accordance with base of the number systems. And in switching of fractals from one base to another, the increment of fractal dimension is constant, which is 1.58, its quite surprising!


Fast FPT algorithms for vertex subset and vertex partitioning problems using neighborhood unions

Abstract: We introduce the graph parameter boolean-width, related to the number of different unions of neighborhoods across a cut of a graph. Boolean-width is similar to rank-width, which is related to the number of $GF[2]$-sums (1+1=0) of neighborhoods instead of the boolean-sums (1+1=1) used for boolean-width. We give algorithms for a large class of NP-hard vertex subset and vertex partitioning problems that are FPT when parameterized by either boolean-width, rank-width or clique-width, with runtime single exponential in either parameter if given the pertinent optimal decomposition. To compare boolean-width versus rank-width or clique-width, we first show that for any graph, the square root of its boolean-width is never more than its rank-width. Next, we exhibit a class of graphs, the Hsu-grids, for which we can solve NP-hard problems in polynomial time, if we use the right parameter. An $n \times \frac{n}{10}$ Hsu-grid on ${1/10}n^2$ vertices has boolean-width $\Theta(\log n)$ and rank-width $\Theta(n)$. Moreover, any optimal rank-decomposition of such a graph will have boolean-width $\Theta(n)$, i.e. exponential in the optimal boolean-width. A main open problem is to approximate the boolean-width better than what is given by the algorithm for rank-width [Hlin\v{e}n\'y and Oum, 2008]


A computational method for bounding the probability of reconstruction on trees

Abstract: For a tree Markov random field non-reconstruction is said to hold if as the depth of the tree goes to infinity the information that a typical configuration at the leaves gives about the value at the root goes to zero. The distribution of the measure at the root conditioned on a typical boundary can be computed using a distributional recurrence. However the exact computation is not feasible because the support of the distribution grows exponentially with the depth. In this work, we introduce a notion of a survey of a distribution over probability vectors which is a succinct representation of the true distribution. We show that a survey of the distribution of the measure at the root can be constructed by an efficient recursive algorithm. The key properties of surveys are that the size does not grow with the depth, they can be constructed recursively, and they still provide a good bound for the distance between the true conditional distribution and the unconditional distribution at the root. This approach applies to a large class of Markov random field models including randomly generated ones. As an application we show bounds on the reconstruction threshold for the Potts model on small-degree trees.


A Combinatorial Algorithm to Compute Regularization Paths

Abstract: For a wide variety of regularization methods, algorithms computing the entire solution path have been developed recently. Solution path algorithms do not only compute the solution for one particular value of the regularization parameter but the entire path of solutions, making the selection of an optimal parameter much easier. Most of the currently used algorithms are not robust in the sense that they cannot deal with general or degenerate input. Here we present a new robust, generic method for parametric quadratic programming. Our algorithm directly applies to nearly all machine learning applications, where so far every application required its own different algorithm. We illustrate the usefulness of our method by applying it to a very low rank problem which could not be solved by existing path tracking methods, namely to compute part-worth values in choice based conjoint analysis, a popular technique from market research to estimate consumers preferences on a class of parameterized options.


Extensible Component Based Architecture for FLASH, A Massively Parallel, Multiphysics Simulation Code

Abstract: FLASH is a publicly available high performance application code which has evolved into a modular, extensible software system from a collection of unconnected legacy codes. FLASH has been successful because its capabilities have been driven by the needs of scientific applications, without compromising maintainability, performance, and usability. In its newest incarnation, FLASH3 consists of inter-operable modules that can be combined to generate different applications. The FLASH architecture allows arbitrarily many alternative implementations of its components to co-exist and interchange with each other, resulting in greater flexibility. Further, a simple and elegant mechanism exists for customization of code functionality without the need to modify the core implementation of the source. A built-in unit test framework providing verifiability, combined with a rigorous software maintenance process, allow the code to operate simultaneously in the dual mode of production and development. In this paper we describe the FLASH3 architecture, with emphasis on solutions to the more challenging conflicts arising from solver complexity, portable performance requirements, and legacy codes. We also include results from user surveys conducted in 2005 and 2007, which highlight the success of the code.


Asymptotic Optimality of the Static Frequency Caching in the Presence of Correlated Requests

Abstract: It is well known that the static caching algorithm that keeps the most frequently requested documents in the cache is optimal in case when documents are of the same size and requests are independent and equally distributed. However, it is hard to develop explicit and provably optimal caching algorithms when requests are statistically correlated. In this paper, we show that keeping the most frequently requested documents in the cache is still optimal for large cache sizes even if the requests are strongly correlated.


Time manipulation technique for speeding up reinforcement learning in simulations

Abstract: A technique for speeding up reinforcement learning algorithms by using time manipulation is proposed. It is applicable to failure-avoidance control problems running in a computer simulation. Turning the time of the simulation backwards on failure events is shown to speed up the learning by 260% and improve the state space exploration by 12% on the cart-pole balancing task, compared to the conventional Q-learning and Actor-Critic algorithms.


TCP over 3G links: Problems and Solutions

Abstract: This review paper presents analytical information regarding the transfer of TCP data flows on paths towards interconnected wireless systems, with emphasis on 3G cellular networks. The focus is on protocol modifications in face of problems arising from terminal mobility and wireless transmission. The objective of this paper is not to present an exhaustive review of the literature, but to filter out the causes of poor TCP performance in such systems and give a rationalized view of measures that can be taken against them.


Global Clock, Physical Time Order and Pending Period Analysis in Multiprocessor Systems

Abstract: In multiprocessor systems, various problems are treated with Lamport's logical clock and the resultant logical time orders between operations. However, one often needs to face the high complexities caused by the lack of logical time order information in practice. In this paper, we utilize the \emph{global clock} to infuse the so-called \emph{pending period} to each operation in a multiprocessor system, where the pending period is a time interval that contains the performed time of the operation. Further, we define the \emph{physical time order} for any two operations with disjoint pending periods. The physical time order is obeyed by any real execution in multiprocessor systems due to that it is part of the truly happened operation orders restricted by global clock, and it is then proven to be independent and consistent with traditional logical time orders. The above novel yet fundamental concepts enables new effective approaches for analyzing multiprocessor systems, which are named \emph{pending period analysis} as a whole. As a consequence of pending period analysis, many important problems of multiprocessor systems can be tackled effectively. As a significant application example, complete memory consistency verification, which was known as an NP-hard problem, can be solved with the complexity of $O(n^2)$ (where $n$ is the number of operations). Moreover, the two event ordering problems, which were proven to be Co-NP-Hard and NP-hard respectively, can both be solved with the time complexity of O(n) if restricted by pending period information.


Analysis Paralysis: when to stop?

Abstract: Analysis of a system constitutes the most important aspect of the systems development life cycle.But it is also the most confusing and time consuming of all the stages.The critical question always remains: How much and till when to analyse? Ed Yourdon has called this phenomenon as Analysis Paralysis. In this paper, I suggest a model which can actually help in arriving at a satisfactory answer to this problem.


Digital Restoration of Ancient Papyri

Abstract: Image processing can be used for digital restoration of ancient papyri, that is, for a restoration performed on their digital images. The digital manipulation allows reducing the background signals and enhancing the readability of texts. In the case of very old and damaged documents, this is fundamental for identification of the patterns of letters. Some examples of restoration, obtained with an image processing which uses edges detection and Fourier filtering, are shown. One of them concerns 7Q5 fragment of the Dead Sea Scrolls.


Flow of Activity in the Ouroboros Model

Abstract: The Ouroboros Model is a new conceptual proposal for an algorithmic structure for efficient data processing in living beings as well as for artificial agents. Its central feature is a general repetitive loop where one iteration cycle sets the stage for the next. Sensory input activates data structures (schemata) with similar constituents encountered before, thus expectations are kindled. This corresponds to the highlighting of empty slots in the selected schema, and these expectations are compared with the actually encountered input. Depending on the outcome of this consumption analysis different next steps like search for further data or a reset, i.e. a new attempt employing another schema, are triggered. Monitoring of the whole process, and in particular of the flow of activation directed by the consumption analysis, yields valuable feedback for the optimum allocation of attention and resources including the selective establishment of useful new memory entries.


A Constructive Generalization of Nash Equilibrium for Better Payoffs and Stability

Abstract: In a society of completely selfish individuals where everybody is only interested in maximizing his own payoff, does any equilibrium exist for the society? John Nash proved more than 50 years ago that an equilibrium always exists such that nobody would benefit from unilaterally changing his strategy. Nash Equilibrium is a central concept in game theory, which offers a mathematical foundation for social science and economy. However, it is important from both a theoretical and a practical point of view to understand game playing where individuals are less selfish. This paper offers a constructive generalization of Nash equilibrium to study n-person games where the selfishness of individuals can be defined at any level, including the extreme of complete selfishness. The generalization is constructive since it offers a protocol for individuals in a society to reach an equilibrium. Most importantly, this paper presents experimental results and theoretical investigation to show that the individuals in a society can reduce their selfishness level together to reach a new equilibrium where they can have better payoffs and the society is more stable at the same time. This study suggests that, for the benefit of everyone in a society (including the financial market), the pursuit of maximal payoff by each individual should be controlled at some level either by voluntary good citizenship or by imposed regulations.


Mathematical Model for Transformation of Sentences from Active Voice to Passive Voice

Abstract: Formal work in linguistics has both produced and used important mathematical tools. Motivated by a survey of models for context and word meaning, syntactic categories, phrase structure rules and trees, an attempt is being made in the present paper to present a mathematical model for structuring of sentences from active voice to passive voice, which is is the form of a transitive verb whose grammatical subject serves as the patient, receiving the action of the verb. For this purpose we have parsed all sentences of a corpus and have generated Boolean groups for each of them. It has been observed that when we take constituents of the sentences as subgroups, the sequences of phrases form permutation roups. Application of isomorphism property yields permutation mapping between the important subgroups. It has resulted in a model for transformation of sentences from active voice to passive voice. A computer program has been written to enable the software developers to evolve grammar software for sentence transformations.


RFID Authentication, Efficient Proactive Information Security within Computational Security

Abstract: We consider repeated communication sessions between a RFID Tag (e.g., Radio Frequency Identification, RFID Tag) and a RFID Verifier. A proactive information theoretic security scheme is proposed. The scheme is based on the assumption that the information exchanged during at least one of every n successive communication sessions is not exposed to an adversary. The Tag and the Verifier maintain a vector of n entries that is repeatedly refreshed by pairwise xoring entries, with a new vector of n entries that is randomly chosen by the Tag and sent to the Verifier as a part of each communication session. The general case in which the adversary does not listen in k > 0 sessions among any n successive communication sessions is also considered. A lower bound of n(k+1) for the number of random numbers used during any n successive communication sessions is proven. In other words, we prove that an algorithm must use at least n(k+1) new random numbers during any n successive communication sessions. Then a randomized scheme that uses only O(n log n) new random numbers is presented. A computational secure scheme which is based on the information theoretic secure scheme is used to ensure that even in the case that the adversary listens in all the information exchanges, the communication between the Tag and the Verifier is secure.


On the Necessary and Sufficient Condition of Greedy Routing Supporting Geographical Data Networks

Abstract: Large scale decentralized communication systems have introduced the new trend towards online routing where routing decisions are performed based on a limited and localized knowledge of the network. Geometrical greedy routing has been among the simplest and most common online routing schemes. A perfect geometrical routing scheme is expected to deliver each packet to the point in the network that is closest to the packet destination. However greedy routing fails to guarantee such delivery as the greedy forwarding decision sometimes leads the packets to localized minimums. This article investigates the necessary and sufficient properties of the greedy supporting graphs that provide the guaranteed delivery of packets when acting as a routing substrate.


Computing Cylindrical Algebraic Decomposition via Triangular Decomposition

Abstract: Cylindrical algebraic decomposition is one of the most important tools for computing with semi-algebraic sets, while triangular decomposition is among the most important approaches for manipulating constructible sets. In this paper, for an arbitrary finite set $F \subset {\R}[y_1, ..., y_n]$ we apply comprehensive triangular decomposition in order to obtain an $F$-invariant cylindrical decomposition of the $n$-dimensional complex space, from which we extract an $F$-invariant cylindrical algebraic decomposition of the $n$-dimensional real space. We report on an implementation of this new approach for constructing cylindrical algebraic decompositions.


Comparing Bibliometric Statistics Obtained from the Web of Science and Scopus

Abstract: For more than 40 years, the Institute for Scientific Information (ISI, now part of Thomson Reuters) produced the only available bibliographic databases from which bibliometricians could compile large-scale bibliometric indicators. ISI's citation indexes, now regrouped under the Web of Science (WoS), were the major sources of bibliometric data until 2004, when Scopus was launched by the publisher Reed Elsevier. For those who perform bibliometric analyses and comparisons of countries or institutions, the existence of these two major databases raises the important question of the comparability and stability of statistics obtained from different data sources. This paper uses macro-level bibliometric indicators to compare results obtained from the WoS and Scopus. It shows that the correlations between the measures obtained with both databases for the number of papers and the number of citations received by countries, as well as for their ranks, are extremely high (R2 > .99). There is also a very high correlation when countries' papers are broken down by field. The paper thus provides evidence that indicators of scientific production and citations at the country level are stable and largely independent of the database.


A System of Interaction and Structure IV: The Exponentials and Decomposition

Abstract: We study a system, called NEL, which is the mixed commutative/non-commutative linear logic BV augmented with linear logic's exponentials. Equivalently, NEL is MELL augmented with the non-commutative self-dual connective seq. In this paper, we show a basic compositionality property of NEL, which we call decomposition. This result leads to a cut-elimination theorem, which is proved in the next paper of this series. To control the induction measure for the theorem, we rely on a novel technique that extracts from NEL proofs the structure of exponentials, into what we call !-?-Flow-Graphs.


Equitable Partitioning Policies for Mobile Robotic Networks

Abstract: The most widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and subregions, and (iii) each agent is responsible for service requests originating within its own subregion. In this paper, we design provably correct, spatially-distributed and adaptive policies that allow a team of agents to achieve a convex and equitable partition of a convex workspace, where each subregion has the same measure. We also consider the issue of achieving convex and equitable partitions where subregions have shapes similar to those of regular polygons. Our approach is related to the classic Lloyd algorithm, and exploits the unique features of power diagrams. We discuss possible applications to routing of vehicles in stochastic and dynamic environments. Simulation results are presented and discussed.


Heterogeneous knowledge representation using a finite automaton and first order logic: a case study in electromyography

Abstract: In a certain number of situations, human cognitive functioning is difficult to represent with classical artificial intelligence structures. Such a difficulty arises in the polyneuropathy diagnosis which is based on the spatial distribution, along the nerve fibres, of lesions, together with the synthesis of several partial diagnoses. Faced with this problem while building up an expert system (NEUROP), we developed a heterogeneous knowledge representation associating a finite automaton with first order logic. A number of knowledge representation problems raised by the electromyography test features are examined in this study and the expert system architecture allowing such a knowledge modeling are laid out.


Sequences close to periodic

Abstract: The paper is a survey of notions and results related to classical and new generalizations of the notion of a periodic sequence. The topics related to almost periodicity in combinatorics on words, symbolic dynamics, expressibility in logical theories, algorithmic computability, Kolmogorov complexity, number theory, are discussed.


Cooperative Update Exchange in the Youtopia System

Abstract: Youtopia is a platform for collaborative management and integration of relational data. At the heart of Youtopia is an update exchange abstraction: changes to the data propagate through the system to satisfy user-specified mappings. We present a novel change propagation model that combines a deterministic chase with human intervention. The process is fundamentally cooperative and gives users significant control over how mappings are repaired. An additional advantage of our model is that mapping cycles can be permitted without compromising correctness. We investigate potential harmful interference between updates in our model; we introduce two appropriate notions of serializability that avoid such interference if enforced. The first is very general and related to classical final-state serializability; the second is more restrictive but highly practical and related to conflict-serializability. We present an algorithm to enforce the latter notion. Our algorithm is an optimistic one, and as such may sometimes require updates to be aborted. We develop techniques for reducing the number of aborts and we test these experimentally.


Quasipolynomial Normalisation in Deep Inference via Atomic Flows and Threshold Formulae

Abstract: Je\v{r}\'abek showed that cuts in classical propositional logic proofs in deep inference can be eliminated in quasipolynomial time. The proof is indirect and it relies on a result of Atserias, Galesi and Pudl\'ak about monotone sequent calculus and a correspondence between that system and cut-free deep-inference proofs. In this paper we give a direct proof of Je\v{r}\'abek's result: we give a quasipolynomial-time cut-elimination procedure for classical propositional logic in deep inference. The main new ingredient is the use of a computational trace of deep-inference proofs called atomic flows, which are both very simple (they only trace structural rules and forget logical rules) and strong enough to faithfully represent the cut-elimination procedure.


Stochastic Models of User-Contributory Web Sites

Abstract: We describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measures of activity and how they arise from simple models of individual users. This approach provides a tractable method to understand user activity on the web site and how this activity depends on web site design choices, especially the choice of what information about other users' behaviors is shown to each user. We illustrate this modeling approach in the context of user-created content on the news rating site Digg.


On Solving Boolean Multilevel Optimization Problems

Abstract: Many combinatorial optimization problems entail a number of hierarchically dependent optimization problems. An often used solution is to associate a suitably large cost with each individual optimization problem, such that the solution of the resulting aggregated optimization problem solves the original set of hierarchically dependent optimization problems. This paper starts by studying the package upgradeability problem in software distributions. Straightforward solutions based on Maximum Satisfiability (MaxSAT) and pseudo-Boolean (PB) optimization are shown to be ineffective, and unlikely to scale for large problem instances. Afterwards, the package upgradeability problem is related to multilevel optimization. The paper then develops new algorithms for Boolean Multilevel Optimization (BMO) and highlights a large number of potential applications. The experimental results indicate that the proposed algorithms for BMO allow solving optimization problems that existing MaxSAT and PB solvers would otherwise be unable to solve.


Faith in the Algorithm, Part 2: Computational Eudaemonics

Abstract: Eudaemonics is the study of the nature, causes, and conditions of human well-being. According to the ethical theory of eudaemonia, reaping satisfaction and fulfillment from life is not only a desirable end, but a moral responsibility. However, in modern society, many individuals struggle to meet this responsibility. Computational mechanisms could better enable individuals to achieve eudaemonia by yielding practical real-world systems that embody algorithms that promote human flourishing. This article presents eudaemonic systems as the evolutionary goal of the present day recommender system.


Learning for Dynamic subsumption

Abstract: In this paper a new dynamic subsumption technique for Boolean CNF formulae is proposed. It exploits simple and sufficient conditions to detect during conflict analysis, clauses from the original formula that can be reduced by subsumption. During the learnt clause derivation, and at each step of the resolution process, we simply check for backward subsumption between the current resolvent and clauses from the original formula and encoded in the implication graph. Our approach give rise to a strong and dynamic simplification technique that exploits learning to eliminate literals from the original clauses. Experimental results show that the integration of our dynamic subsumption approach within the state-of-the-art SAT solvers Minisat and Rsat achieves interesting improvements particularly on crafted instances.


CCS-Based Dynamic Logics for Communicating Concurrent Programs

Abstract: This work presents three increasingly expressive Dynamic Logics in which the programs are CCS processes (sCCS-PDL, CCS-PDL and XCCS-PDL). Their goal is to reason about properties of concurrent programs and systems described using CCS. In order to accomplish that, CCS's operators and constructions are added to a basic modal logic in order to create dynamic logics that are suitable for the description and verification of properties of communicating, concurrent and non-deterministic programs and systems, in a similar way as PDL is used for the sequential case. We provide complete axiomatizations for the three logics. Unlike Peleg's Concurrent PDL with Channels, our logics have a simple Kripke semantics, complete axiomatizations and the finite model property.


Stiffness Analysis of Overconstrained Parallel Manipulators

Abstract: The paper presents a new stiffness modeling method for overconstrained parallel manipulators with flexible links and compliant actuating joints. It is based on a multidimensional lumped-parameter model that replaces the link flexibility by localized 6-dof virtual springs that describe both translational/rotational compliance and the coupling between them. In contrast to other works, the method involves a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations for the unloaded manipulator configuration, which allows computing the stiffness matrix for the overconstrained architectures, including singular manipulator postures. The advantages of the developed technique are confirmed by application examples, which deal with comparative stiffness analysis of two translational parallel manipulators of 3-PUU and 3-PRPaR architectures. Accuracy of the proposed approach was evaluated for a case study, which focuses on stiffness analysis of Orthoglide parallel manipulator.


Kinematics of A 3-PRP planar parallel robot

Abstract: Recursive modelling for the kinematics of a 3-PRP planar parallel robot is presented in this paper. Three planar chains connecting to the moving platform of the manipulator are located in a vertical plane. Knowing the motion of the platform, we develop the inverse kinematics and determine the positions, velocities and accelerations of the robot. Several matrix equations offer iterative expressions and graphs for the displacements, velocities and accelerations of three prismatic actuators.