Encoding models for scholarly literature

Abstract: We examine the issue of digital formats for document encoding, archiving and publishing, through the specific example of "born-digital" scholarly journal articles. We will begin by looking at the traditional workflow of journal editing and publication, and how these practices have made the transition into the online domain. We will examine the range of different file formats in which electronic articles are currently stored and published. We will argue strongly that, despite the prevalence of binary and proprietary formats such as PDF and MS Word, XML is a far superior encoding choice for journal articles. Next, we look at the range of XML document structures (DTDs, Schemas) which are in common use for encoding journal articles, and consider some of their strengths and weaknesses. We will suggest that, despite the existence of specialized schemas intended specifically for journal articles (such as NLM), and more broadly-used publication-oriented schemas such as DocBook, there are strong arguments in favour of developing a subset or customization of the Text Encoding Initiative (TEI) schema for the purpose of journal-article encoding; TEI is already in use in a number of journal publication projects, and the scale and precision of the TEI tagset makes it particularly appropriate for encoding scholarly articles. We will outline the document structure of a TEI-encoded journal article, and look in detail at suggested markup patterns for specific features of journal articles.


New Instability Results for High Dimensional Nearest Neighbor Search

Abstract: Consider a dataset of n(d) points generated independently from R^d according to a common p.d.f. f_d with support(f_d) = [0,1]^d and sup{f_d([0,1]^d)} growing sub-exponentially in d. We prove that: (i) if n(d) grows sub-exponentially in d, then, for any query point q^d in [0,1]^d and any epsilon>0, the ratio of the distance between any two dataset points and q^d is less that 1+epsilon with probability -->1 as d-->infinity; (ii) if n(d)>[4(1+epsilon)]^d for large d, then for all q^d in [0,1]^d (except a small subset) and any epsilon>0, the distance ratio is less than 1+epsilon with limiting probability strictly bounded away from one. Moreover, we provide preliminary results along the lines of (i) when f_d=N(mu_d,Sigma_d).


Dynamic Data Flow Analysis via Virtual Code Integration (aka The SpiderPig case)

Abstract: Paper addresses the process of dynamic data flow analysis using virtual code integration (VCI), often refered to as dynamic binary rewriting. This article will try to demonstrate all of the techniques that were applied in the SpiderPig project. It will also discuss the main differences between the methods that were employed and those used in other available software, as well as introducing other related work. SpiderPig's approach was found to be very fast and was transparent enough for reliable and usable data flow analysis. It was created with the purpose of providing a tool which would aid vulnerability and security researchers with tracing and analyzing any necessary data and its further propagation through a program. At the current state it works on IA-32 platforms with Microsoft Windows systems and it supports FPU, SSE, MMX and all of the IA-32 general instructions. SpiderPig also demonstrates the usage of a virtual code integration (VCI) framework which allows for modifying the target application code at the instruction level. By this I mean that the VCI framework allows for custom code insertion, original code modification and full customization of the original application's code. Instructions can be swapped out, deleted or modified at a whim, without corrupting the surrounding code and side-effects of the modification are resolved.


Distributed elections in an Archimedean ring of processors

Abstract: Unlimited asynchronism is intolerable in real physically distributed computer systems. Such systems, synchronous or not, use clocks and timeouts. Therefore the magnitudes of elapsed absolute time in the system need to satisfy the axiom of Archimedes. Under this restriction of asynchronicity logically time-independent solutions can be derived which are nonetheless better (in number of message passes) than is possible otherwise. The use of clocks by the individual processors, in elections in a ring of asynchronous processors without central control, allows a deterministic solution which requires but a linear number of message passes. To obtain the result it has to be assumed that the clocks measure finitely proportional absolute time-spans for their time units, that is, the magnitudes of elapsed time in the ring network satisfy the axiom of Archimedes. As a result, some basic subtilities associated with distributed computations are highlighted. For instance, the known nonlinear lower bound on the required number of message passes is cracked. For the synchronous case, in which the necessary assumptions hold a fortiori, the method is -asymptotically- the most efficient one yet, and of optimal order of magnitude. The deterministic algorithm is of -asymptotically- optimal bit complexity, and, in the synchronous case, also yields an optimal method to determine the ring size. All of these results improve the known ones.


Single Neuron Memories and the Network's Proximity Matrix

Abstract: This paper extends the treatment of single-neuron memories obtained by the B-matrix approach. The spreading of the activity within the network is determined by the network's proximity matrix which represents the separations amongst the neurons through the neural pathways.


Analyzing of MOS and Codec Selection for Voice over IP Technology

Abstract: In this research, we propose an architectural solution to implement the voice over IP (VoIP) service in campus environment network. Voice over IP (VoIP) technology has become a discussion issue for this time being. Today, the deployment of this technology on an organization truly can give a great financial benefit over traditional telephony. Therefore, this study is to analyze the VoIP Codec selection and investigate the Mean Opinion Score (MOS) performance areas evolved with the quality of service delivered by soft phone and IP phone. This study focuses on quality of voice prediction such as i) accuracy of MOS between automated system and human perception and ii) different types of codec performance measurement via human perception using MOS technique. In this study, network management system (NMS) is used to monitor and capture the performance of VoIP in campus environment. In addition, the most apparent of implementing soft phone and IP phone in campus environment is to define the best codec selection that can be used in operational environment. Based on the finding result, the MOS measurement through automated and manual system is able to predict and evaluate VoIP performance. In addition, based on manual MOS measurement, VoIP conversations over LAN contribute more reliability and availability performance compare to WAN.


Specific Characteristics of Applying the Paired Comparison Method for Parameterization of Consumer Wants

Abstract: The article describes the main problems concerned with using expert assessment method in consumer preference researches. The author proved the expediency of using a 3-point measurement scale. The author suggested an algorithm for controlling the judgments' consistency that includes analyzing and correcting the input estimates in real-time mode.


2D cellular automata: dynamics and undecidability

Abstract: In this paper we introduce the notion of quasi-expansivity for 2D CA and we show that it shares many properties with expansivity (that holds only for 1D CA). Similarly, we introduce the notions of quasi-sensitivity and prove that the classical dichotomy theorem holds in this new setting. Moreover, we show a tight relation between closingness and openness for 2D CA. Finally, the undecidability of closingness property for 2D CA is proved.


A Partial Order on Bipartite Graphs with n Vertices

Abstract: The paper examines a partial order on bipartite graphs (X1, X2, E) with n vertices, X1UX2={1,2,...,n}. This partial order is a natural partial order of subobjects of an object in a triangular category with bipartite graphs as morphisms.


Using Genetic Algorithms for Texts Classification Problems

Abstract: The avalanche quantity of the information developed by mankind has led to concept of automation of knowledge extraction - Data Mining ([1]). This direction is connected with a wide spectrum of problems - from recognition of the fuzzy set to creation of search machines. Important component of Data Mining is processing of the text information. Such problems lean on concept of classification and clustering ([2]). Classification consists in definition of an accessory of some element (text) to one of in advance created classes. Clustering means splitting a set of elements (texts) on clusters which quantity are defined by localization of elements of the given set in vicinities of these some natural centers of these clusters. Realization of a problem of classification initially should lean on the given postulates, basic of which - the aprioristic information on primary set of texts and a measure of affinity of elements and classes.


A Memetic Algorithm for the Multidimensional Assignment Problem

Abstract: The Multidimensional Assignment Problem (MAP or s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s have also a number of applications. In this paper we propose a memetic algorithm for MAP that is a combination of a genetic algorithm with a local search procedure. The main contribution of the paper is an idea of dynamically adjusted generation size, that yields an outstanding flexibility of the algorithm to perform well for both small and large fixed running times. The results of computational experiments for several instance families show that the proposed algorithm produces solutions of very high quality in a reasonable time and outperforms the state-of-the art 3-AP memetic algorithm.


Decision Support Systems Architectures

Abstract: This paper presents the main components of the decision assisting systems. Further on three types of architectures of these systems are described, analyzed, and respectively compared, namely: the network architecture, the centralized architecture and the hierarchical architecture.


Web Publishing of the Files Obtained by Flash

Abstract: The aim of this article is to familiarize the user with the Web publishing of the files obtained by Flash. The article contains an overview of Macromedia Flash 5, as well as the running of a Playing Flash movie, information on Flash and Generator, the publishing of Flash movies, a HTLM publishing for Flash Player files and publishing by Generator templates.


PDF/A standard for long term archiving

Abstract: PDF/A is defined by ISO 19005-1 as a file format based on PDF format. The standard provides a mechanism for representing electronic documents in a way that preserves their visual appearance over time, independent of the tools and systems used for creating or storing the files.


Adobe AIR, Bringing Rich Internet Applications to the Desktop

Abstract: Rich Internet Applications are the new trend in software development today. Adobe AIR offers the possibility to create cross-platform desktop applications using popular Web technologies like HTML, JavaScript, Flash and Flex. This article is focused on presenting the advantages that this new environment has to offer for the web development community and how quickly you can develop a desktop application using Adobe AIR.


Upon the Modeling and the Optimization of the Debiting Process through Computer Aided Non-Conventional Technologies

Abstract: The debiting process of the remarkable properties materials can be managed through unconventional technologies as the complex electrical erosion. We present the modeling of the previous experimental results to obtain a mathematical dependence of the output parameters (processing time, surface quality) on the input parameters (voltage or current). All the experimental data are memorized on a database and for each particular debiting process a new dependence is built. Because all the experiments applied in the Romanian laboratories or practical applications of the nonconventional technological processes in the factories were based on the particular conditions of one activity, this papers presents the technical implementation of a computer-aided solution that keeps all previous experimental data, optimizes the processing conditions and eventual manage the driving gear. The flow-chart we present in this paper offers a solution for practitioners to reduce the electrical consumption while a technological processing of special materials is necessary. The computer program and the database can be easily adapted to any technological processes (conventional or not).


Fast Weak Learner Based on Genetic Algorithm

Abstract: An approach to the acceleration of parametric weak classifier boosting is proposed. Weak classifier is called parametric if it has fixed number of parameters and, so, can be represented as a point into multidimensional space. Genetic algorithm is used instead of exhaustive search to learn parameters of such classifier. Proposed approach also takes cases when effective algorithm for learning some of the classifier parameters exists into account. Experiments confirm that such an approach can dramatically decrease classifier training time while keeping both training and test errors small.


PayPal in Romania

Abstract: The present paper refers to the usefulness of online payment through PayPal and to the development of this payment manner in Romania. PayPal is an example of a payment intermediary service that facilitates worldwide e-commerce.


Mining Compressed Repetitive Gapped Sequential Patterns Efficiently

Abstract: Mining frequent sequential patterns from sequence databases has been a central research topic in data mining and various efficient mining sequential patterns algorithms have been proposed and studied. Recently, in many problem domains (e.g, program execution traces), a novel sequential pattern mining research, called mining repetitive gapped sequential patterns, has attracted the attention of many researchers, considering not only the repetition of sequential pattern in different sequences but also the repetition within a sequence is more meaningful than the general sequential pattern mining which only captures occurrences in different sequences. However, the number of repetitive gapped sequential patterns generated by even these closed mining algorithms may be too large to understand for users, especially when support threshold is low. In this paper, we propose and study the problem of compressing repetitive gapped sequential patterns. Inspired by the ideas of summarizing frequent itemsets, RPglobal, we develop an algorithm, CRGSgrow (Compressing Repetitive Gapped Sequential pattern grow), including an efficient pruning strategy, SyncScan, and an efficient representative pattern checking scheme, -dominate sequential pattern checking. The CRGSgrow is a two-step approach: in the first step, we obtain all closed repetitive sequential patterns as the candidate set of representative repetitive sequential patterns, and at the same time get the most of representative repetitive sequential patterns; in the second step, we only spend a little time in finding the remaining the representative patterns from the candidate set. An empirical study with both real and synthetic data sets clearly shows that the CRGSgrow has good performance.


On the Challenges of Collaborative Data Processing

Abstract: The last 30 years have seen the creation of a variety of electronic collaboration tools for science and business. Some of the best-known collaboration tools support text editing (e.g., wikis). Wikipedia's success shows that large-scale collaboration can produce highly valuable content. Meanwhile much structured data is being collected and made publicly available. We have never had access to more powerful databases and statistical packages. Is large-scale collaborative data analysis now possible? Using a quantitative analysis of Web 2.0 data visualization sites, we find evidence that at least moderate open collaboration occurs. We then explore some of the limiting factors of collaboration over data.


Course Material Selection Rubric for Creating Network Security Courses

Abstract: Teaching network security can be a difficult task for university teachers, especially for teachers at smaller universities where the course loads are more diverse. Creating a new course in network security requires investigation into multiple subject areas within the field and from multiple sources. This task can be daunting and overwhelming for teachers from smaller universities because of their requirement to teach multiple subjects, not just network security. Along with the requirement of teachers to understand the material that they wish to teach, the factors of obsolescence and the ability to build material off of core topics need to be addressed. These three factors are difficult for a smaller university teacher to address without a set of standards to analyze these areas. A rubric addressing these topic areas of timelessness, associability, and simplicity has been created to assist in the selection of materials based on the three criteria. The use of this rubric provides an effective means to choose material for a new course and help teachers to present the material they determine most appropriate to teach.


Spherical Distribution of 5 Points with Maximal Distance Sum

Abstract: In this paper, we mainly consider the problem of spherical distribution of 5 points, that is, how to configure 5 points on a sphere such that the mutual distance sum attains the maximum. It is conjectured that the sum of distances is maximal if 5 points form a bipyramid configuration in which case two points are positioned at two poles of the sphere and the other three are positioned uniformly on the equator. We study this problem using interval methods and related technics, and give a proof for the conjecture through computers in finite time.


Efficiency of (Revenue-)Optimal Mechanisms

Abstract: We compare the expected efficiency of revenue maximizing (or {\em optimal}) mechanisms with that of efficiency maximizing ones. We show that the efficiency of the revenue maximizing mechanism for selling a single item with k + log_{e/(e-1)} k + 1 bidders is at least as much as the efficiency of the efficiency maximizing mechanism with k bidders, when bidder valuations are drawn i.i.d. from a Monotone Hazard Rate distribution. Surprisingly, we also show that this bound is tight within a small additive constant of 5.7. In other words, Theta(log k) extra bidders suffice for the revenue maximizing mechanism to match the efficiency of the efficiency maximizing mechanism, while o(log k) do not. This is in contrast to the result of Bulow and Klemperer comparing the revenue of the two mechanisms, where only one extra bidder suffices. More precisely, they show that the revenue of the efficiency maximizing mechanism with k+1 bidders is no less than the revenue of the revenue maximizing mechanism with k bidders. We extend our result for the case of selling t identical items and show that 2.2 log k + t Theta(log log k) extra bidders suffice for the revenue maximizing mechanism to match the efficiency of the efficiency maximizing mechanism. In order to prove our results, we do a classification of Monotone Hazard Rate (MHR) distributions and identify a family of MHR distributions, such that for each class in our classification, there is a member of this family that is pointwise lower than every distribution in that class. This lets us prove interesting structural theorems about distributions with Monotone Hazard Rate.


Report on the current state of the French DMLs

Abstract: This is a survey of the existing digital collections of French mathematical literature, run by non-profit organizations. This includes research monographs, serials, proceedings, Ph. D. theses, collected works, books and personal websites.


Physical portrayal of computational complexity

Abstract: Computational complexity is examined using the principle of increasing entropy. To consider computation as a physical process from an initial instance to the final acceptance is motivated because many natural processes have been recognized to complete in non-polynomial time (NP). The irreversible process with three or more degrees of freedom is found intractable because, in terms of physics, flows of energy are inseparable from their driving forces. In computational terms, when solving problems in the class NP, decisions will affect subsequently available sets of decisions. The state space of a non-deterministic finite automaton is evolving due to the computation itself hence it cannot be efficiently contracted using a deterministic finite automaton that will arrive at a solution in super-polynomial time. The solution of the NP problem itself is verifiable in polynomial time (P) because the corresponding state is stationary. Likewise the class P set of states does not depend on computational history hence it can be efficiently contracted to the accepting state by a deterministic sequence of dissipative transformations. Thus it is concluded that the class P set of states is inherently smaller than the set of class NP. Since the computational time to contract a given set is proportional to dissipation, the computational complexity class P is a subset of NP.


On Fulkerson conjecture

Abstract: If $G$ is a bridgeless cubic graph, Fulkerson conjectured that we can find 6 perfect matchings (a{\em Fulkerson covering}) with the property that every edge of $G$ is contained in exactly two of them. A consequence of the Fulkerson conjecture would be that every bridgeless cubic graph has 3 perfect matchings with empty intersection (this problem is known as the Fan Raspaud Conjecture). A {\em FR-triple} is a set of 3 such perfect matchings. We show here how to derive a Fulkerson covering from two FR-triples. Moreover, we give a simple proof that the Fulkerson conjecture holds true for some classes of well known snarks.


Coloring the square of the Cartesian product of two cycles

Abstract: The square $G^2$ of a graph $G$ is defined on the vertex set of $G$ in such a way that distinct vertices with distance at most two in $G$ are joined by an edge. We study the chromatic number of the square of the Cartesian product $C_m\Box C_n$ of two cycles and show that the value of this parameter is at most 7 except when $m=n=3$, in which case the value is 9, and when $m=n=4$ or $m=3$ and $n=5$, in which case the value is 8. Moreover, we conjecture that whenever $G=C_m\Box C_n$, the chromatic number of $G^2$ equals $\lceil mn/\alpha(G^2) \rceil$, where $\alpha(G^2)$ denotes the size of a maximal independent set in $G^2$.


Enabling and Optimizing Pilot Jobs using Xen based Virtual Machines for the HPC Grid Applications

Abstract: The primary motivation for uptake of virtualization have been resource isolation, capacity management and resource customization: isolation and capacity management allow providers to isolate users from the site and control their resources usage while customization allows end-users to easily project the required environment onto a variety of sites. Various approaches have been taken to integrate virtualization with Grid technologies. In this paper, we propose an approach that combines virtualization on the existing software infrastructure such as Pilot Jobs with minimum change on the part of resource providers.


Collaborative filtering based on multi-channel diffusion

Abstract: In this paper, by applying a diffusion process, we propose a new index to quantify the similarity between two users in a user-object bipartite graph. To deal with the discrete ratings on objects, we use a multi-channel representation where each object is mapped to several channels with the number of channels being equal to the number of different ratings. Each channel represents a certain rating and a user having voted an object will be connected to the channel corresponding to the rating. Diffusion process taking place on such a user-channel bipartite graph gives a new similarity measure of user pairs, which is further demonstrated to be more accurate than the classical Pearson correlation coefficient under the standard collaborative filtering framework.


The CIFF Proof Procedure for Abductive Logic Programming with Constraints: Theory, Implementation and Experiments

Abstract: We present the CIFF proof procedure for abductive logic programming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logic programming, relaxing the original restrictions over variable quantification (allowedness conditions) and incorporating a constraint solver to deal with numerical constraints as in constraint logic programming. Finally, we describe the CIFF system, comparing it with state of the art abductive systems and answer set solvers and showing how to use it to program some applications. (To appear in Theory and Practice of Logic Programming - TPLP).


On the Decidability of (ground) Reachability Problems for Cryptographic Protocols (extended version)

Abstract: Analysis of cryptographic protocols in a symbolic model is relative to a deduction system that models the possible actions of an attacker regarding an execution of this protocol. We present in this paper a transformation algorithm for such deduction systems provided the equational theory has the finite variant property. the termination of this transformation entails the decidability of the ground reachability problems. We prove that it is necessary to add one other condition to obtain the decidability of non-ground problems, and provide one new such criterion.


Pipelined Algorithms to Detect Cheating in Long-Term Grid Computations

Abstract: This paper studies pipelined algorithms for protecting distributed grid computations from cheating participants, who wish to be rewarded for tasks they receive but don't perform. We present improved cheater detection algorithms that utilize natural delays that exist in long-term grid computations. In particular, we partition the sequence of grid tasks into two interleaved sequences of task rounds, and we show how to use those rounds to devise the first general-purpose scheme that can catch all cheaters, even when cheaters collude. The main idea of this algorithm might at first seem counter-intuitive--we have the participants check each other's work. A naive implementation of this approach would, of course, be susceptible to collusion attacks, but we show that by, adapting efficient solutions to the parallel processor diagnosis problem, we can tolerate collusions of lazy cheaters, even if the number of such cheaters is a fraction of the total number of participants. We also include a simple economic analysis of cheaters in grid computations and a parameterization of the main deterrent that can be used against them--the probability of being caught.


On the Complexity of Smooth Spline Surfaces from Quad Meshes

Abstract: This paper derives strong relations that boundary curves of a smooth complex of patches have to obey when the patches are computed by local averaging. These relations restrict the choice of reparameterizations for geometric continuity. In particular, when one bicubic tensor-product B-spline patch is associated with each facet of a quadrilateral mesh with n-valent vertices and we do not want segments of the boundary curves forced to be linear, then the relations dictate the minimal number and multiplicity of knots: For general data, the tensor-product spline patches must have at least two internal double knots per edge to be able to model a G^1-conneced complex of C^1 splines. This lower bound on the complexity of any construction is proven to be sharp by suitably interpreting an existing surface construction. That is, we have a tight bound on the complexity of smoothing quad meshes with bicubic tensor-product B-spline patches.


A Full Image of the Wormhole Attacks - Towards Introducing Complex Wormhole Attacks in wireless Ad Hoc Networks

Abstract: The paper analyzes wormhole attack modes and classes and point to its threat impacts on ad hoc networks. New improvements are suggested to these types of attacks.


Similarity Analysis in Automatic Performance Debugging of SPMD Parallel Programs

Abstract: Different from sequential programs, parallel programs possess their own characteristics which are difficult to analyze in the multi-process or multi-thread environment. This paper presents an innovative method to automatically analyze the SPMD programs. Firstly, with the help of clustering method focusing on similarity analysis, an algorithm is designed to locate performance problems in parallel programs automatically. Secondly a Rough Set method is used to uncover the performance problem and provide the insight into the micro-level causes. Lastly, we have analyzed a production parallel application to verify the effectiveness of our method and system.


Multidimensional Analysis of System Logs in Large-scale Cluster Systems

Abstract: It is effective to improve the reliability and availability of large-scale cluster systems through the analysis of failures. Existed failure analysis methods understand and analyze failures from one or few dimension. The analysis results are partial and with less precision because of the limitation of data source. This paper presents multidimensional analysis based on graph mining to analyze multi-source system logs, which is a promising failure analysis method to get more complete and precise failure knowledge.


Efficient Algorithms for Several Constrained Activity Scheduling Problems in the Time and Space Domains

Abstract: In this paper we consider several constrained activity scheduling problems in the time and space domains, like finding activity orderings which optimize the values of several objective functions (time scheduling) or finding optimal locations where certain types of activities will take place (space scheduling). We present novel, efficient algorithmic solutions for all the considered problems, based on the dynamic programming and greedy techniques. In each case we compute exact, optimal solutions.


Efficient Algorithms for Several Constrained Resource Allocation, Management and Discovery Problems

Abstract: In this paper we present efficient algorithmic solutions for several constrained resource allocation, management and discovery problems. We consider new types of resource allocation models and constraints, and we present new geometric techniques which are useful when the resources are mapped to points into a multidimensional feature space. We also consider a resource discovery problem for which we present a guessing game theoretical model.


Phoenix Cloud: Consolidating Different Computing Loads on Shared Cluster System for Large Organization

Abstract: Different departments of a large organization often run dedicated cluster systems for different computing loads, like HPC (high performance computing) jobs or Web service applications. In this paper, we have designed and implemented a cloud management system software Phoenix Cloud to consolidate heterogeneous workloads from different departments affiliated to the same organization on the shared cluster system. We have also proposed cooperative resource provisioning and management policies for a large organization and its affiliated departments, running HPC jobs and Web service applications, to share the consolidated cluster system. The experiments show that in comparison with the case that each department operates its dedicated cluster system, Phoenix Cloud significantly decreases the scale of the required cluster system for a large organization, improves the benefit of the scientific computing department, and at the same time provisions enough resources to the other department running Web services with varying loads.


A Step-indexed Semantics of Imperative Objects

Abstract: Step-indexed semantic interpretations of types were proposed as an alternative to purely syntactic proofs of type safety using subject reduction. The types are interpreted as sets of values indexed by the number of computation steps for which these values are guaranteed to behave like proper elements of the type. Building on work by Ahmed, Appel and others, we introduce a step-indexed semantics for the imperative object calculus of Abadi and Cardelli. Providing a semantic account of this calculus using more `traditional', domain-theoretic approaches has proved challenging due to the combination of dynamically allocated objects, higher-order store, and an expressive type system. Here we show that, using step-indexing, one can interpret a rich type discipline with object types, subtyping, recursive and bounded quantified types in the presence of state.


A Probabilistic Approach to Problems Parameterized Above or Below Tight Bounds

Abstract: We introduce a new approach for establishing fixed-parameter tractability of problems parameterized above tight lower bounds. To illustrate the approach we consider three problems of this type of unknown complexity that were introduced by Mahajan, Raman and Sikdar (J. Comput. Syst. Sci. 75, 2009). We show that a generalization of one of the problems and non-trivial special cases of the other two are fixed-parameter tractable.


Fixed-Parameter Algorithms in Analysis of Heuristics for Extracting Networks in Linear Programs

Abstract: We consider the problem of extracting a maximum-size reflected network in a linear program. This problem has been studied before and a state-of-the-art SGA heuristic with two variations have been proposed. In this paper we apply a new approach to evaluate the quality of SGA\@. In particular, we solve majority of the instances in the testbed to optimality using a new fixed-parameter algorithm, i.e., an algorithm whose runtime is polynomial in the input size but exponential in terms of an additional parameter associated with the given problem. This analysis allows us to conclude that the the existing SGA heuristic, in fact, produces solutions of a very high quality and often reaches the optimal objective values. However, SGA contain two components which leave some space for improvement: building of a spanning tree and searching for an independent set in a graph. In the hope of obtaining even better heuristic, we tried to replace both of these components with some equivalent algorithms. We tried to use a fixed-parameter algorithm instead of a greedy one for searching of an independent set. But even the exact solution of this subproblem improved the whole heuristic insignificantly. Hence, the crucial part of SGA is building of a spanning tree. We tried three different algorithms, and it appears that the Depth-First search is clearly superior to the other ones in building of the spanning tree for SGA. Thereby, by application of fixed-parameter algorithms, we managed to check that the existing SGA heuristic is of a high quality and selected the component which required an improvement. This allowed us to intensify the research in a proper direction which yielded a superior variation of SGA.


Cell-Probe Lower Bounds for Prefix Sums

Abstract: We prove that to store n bits x so that each prefix-sum query Sum(i) := sum_{k < i} x_k can be answered by non-adaptively probing q cells of log n bits, one needs memory > n + n/log^{O(q)} n. Our bound matches a recent upper bound of n + n/log^{Omega(q)} n by Patrascu (FOCS 2008), also non-adaptive. We also obtain a n + n/log^{2^{O(q)}} n lower bound for storing a string of balanced brackets so that each Match(i) query can be answered by non-adaptively probing q cells. To obtain these bounds we show that a too efficient data structure allows us to break the correlations between query answers.


Am\'eliorer les performances de l'industrie logicielle par une meilleure compr\'ehension des besoins

Abstract: Actual organization are structured and act with the help of their information systems. In spite of considerable progresses made by computer technology, we note that actors are very often critical on their information systems. Difficulties to product specifications enough detailed for functional profile and interpretable by information system expert is one of reason of this gap between hopes and reality. Our proposition wants to get over this obstacle by organizing user requirements in a common language of operational profile and technical expert.-- Les organisations actuelles se structurent et agissent en s'appuyant sur leurs syst\`emes d'information. Malgr\'e les progr\`es consid\'erables r\'ealis\'es par la technologie informatique, on constate que les acteurs restent tr\`es souvent critiques par rapport \`a leur syst\`emes d'information. Une des causes de cet \'ecart entre les espoirs et la r\'ealit\'e trouve sa source dans la difficult\'e \`a produire un cahier des charges suffisamment d\'etaill\'e pour les op\'erationnels et interpr\'etable par les sp\'ecialistes des syst\`emes d'information. Notre proposition vise \`a surmonter cet obstacle en organisant l'expression des besoins dans un langage commun aux op\'erationnels et aux experts techniques. Pour cela, le langage propos\'e pour exprimer les besoins est bas\'e sur la notion de but. L'ing\'enierie dirig\'ee par les mod\`eles est pr\'esente \`a toute les \'etapes, c'est-\`a-dire au moment de la capture et de l'interpr\'etation.


Algebraic methods for counting Euclidean embeddings of rigid graphs

Abstract: The study of (minimally) rigid graphs is motivated by numerous applications, mostly in robotics and bioinformatics. A major open problem concerns the number of embeddings of such graphs, up to rigid motions, in Euclidean space. We capture embeddability by polynomial systems with suitable structure, so that their mixed volume, which bounds the number of common roots, to yield interesting upper bounds on the number of embeddings. We focus on $\RR^2$ and $\RR^3$, where Laman graphs and 1-skeleta of convex simplicial polyhedra, respectively, admit inductive Henneberg constructions. We establish the first lower bound in $\RR^3$ of about $2.52^n$, where $n$ denotes the number of vertices. Moreover, our implementation yields upper bounds for $n \le 10$ in $\RR^2$ and $\RR^3$, which reduce the existing gaps, and tight bounds up to $n=7$ in $\RR^3$.


The Complexity of Satisfiability for Fragments of Hybrid Logic -- Part I

Abstract: The satisfiability problem of hybrid logics with the downarrow binder is known to be undecidable. This initiated a research program on decidable and tractable fragments. In this paper, we investigate the effect of restricting the propositional part of the language on decidability and on the complexity of the satisfiability problem over arbitrary, transitive, total frames, and frames based on equivalence relations. We also consider different sets of modal and hybrid operators. We trace the border of decidability and give the precise complexity of most fragments, in particular for all fragments including negation. For the monotone fragments, we are able to distinguish the easy from the hard cases, depending on the allowed set of operators.


Uniform unweighted set cover: The power of non-oblivious local search

Abstract: We are given n base elements and a finite collection of subsets of them. The size of any subset varies between p to k (p < k). In addition, we assume that the input contains all possible subsets of size p. Our objective is to find a subcollection of minimum-cardinality which covers all the elements. This problem is known to be NP-hard. We provide two approximation algorithms for it, one for the generic case, and an improved one for the special case of (p,k) = (2,4). The algorithm for the generic case is a greedy one, based on packing phases: at each phase we pick a collection of disjoint subsets covering i new elements, starting from i = k down to i = p+1. At a final step we cover the remaining base elements by the subsets of size p. We derive the exact performance guarantee of this algorithm for all values of k and p, which is less than Hk, where Hk is the k'th harmonic number. However, the algorithm exhibits the known improvement methods over the greedy one for the unweighted k-set cover problem (in which subset sizes are only restricted not to exceed k), and hence it serves as a benchmark for our improved algorithm. The improved algorithm for the special case of (p,k) = (2,4) is based on non-oblivious local search: it starts with a feasible cover, and then repeatedly tries to replace sets of size 3 and 4 so as to maximize an objective function which prefers big sets over small ones. For this case, our generic algorithm achieves an asymptotic approximation ratio of 1.5 + epsilon, and the local search algorithm achieves a better ratio, which is bounded by 1.458333... + epsilon.


On Defining 'I' "I logy"

Abstract: Could we define I? Throughout this article we give a negative answer to this question. More exactly, we show that there is no definition for I in a certain way. But this negative answer depends on our definition of definability. Here, we try to consider sufficient generalized definition of definability. In the middle of paper a paradox will arise which makes us to modify the way we use the concept of property and definability.


The morpho-topographic and cartographic analysis of the archaeological site Cornesti "Iarcuri", Timis County, Romania, using computer sciences methods (GIS and Remote Sensing techniques)

Abstract: The archaeological site Cornesti "Iarcuri" is the largest earth fortification in Romania, made out of four concentric compounds, spreading over 1780 hectares. It is known since 1700, but it had only a few small attempts of systematic research, the fortress gained interest only after the publishing of some satellite images by Google Earth. It is located in an area of high fields and it occupies three interfluves and contains two streams. Our paper contains a geomorphologic, topographic and cartographic analysis of the site in order to determine the limits, the structure, the morphology, the construction technique and the functionality of such a fortification.Our research is based on satellite image analysis, on archaeological topography, on soil, climate and vegetation analysis as a way to offer a complex image, through this interdisciplinary study of landscape archaeology. Through our work we try not to date the site as this objective will be achieved only after completing the systematic excavations which started in 2007, but only to analyze the co-relationship with the environment.


Analyser Framework to verify Software Component

Abstract: Today, it is important for software companies to build software systems in a short time-interval, to reduce costs and to have a good market position. Therefore well organized and systematic development approaches are required. Reusing software components, which are well tested, can be a good solution to develop software applications in effective manner. The reuse of software components is less expensive and less time consuming than a development from scratch. But it is dangerous to think that software components can be match together without any problems. Software components itself are well tested, of course, but even if they composed together problems occur. Most problems are based on interaction respectively communication. Avoiding such errors a framework has to be developed for analysing software components. That framework determines the compatibility of corresponding software components.The promising approach discussed here, presents a novel technique for analysing software components by applying an Abstract Syntax Language Tree (ASLT). A supportive environment will be designed that checks the compatibility of black-box software components. This article is concerned to the question how can be coupled software components verified by using an analyzer framework and determines the usage of the ASLT. Black-box Software Components and Abstract Syntax Language Tree are the basis for developing the proposed framework and are discussed here to provide the background knowledge. The practical implementation of this framework is discussed and shows the result by using a test environment.


Knowledge Management in Economic Intelligence with Reasoning on Temporal Attributes

Abstract: People have to make important decisions within a time frame. Hence, it is imperative to employ means or strategy to aid effective decision making. Consequently, Economic Intelligence (EI) has emerged as a field to aid strategic and timely decision making in an organization. In the course of attaining this goal: it is indispensable to be more optimistic towards provision for conservation of intellectual resource invested into the process of decision making. This intellectual resource is nothing else but the knowledge of the actors as well as that of the various processes for effecting decision making. Knowledge has been recognized as a strategic economic resource for enhancing productivity and a key for innovation in any organization or community. Thus, its adequate management with cognizance of its temporal properties is highly indispensable. Temporal properties of knowledge refer to the date and time (known as timestamp) such knowledge is created as well as the duration or interval between related knowledge. This paper focuses on the needs for a user-centered knowledge management approach as well as exploitation of associated temporal properties. Our perspective of knowledge is with respect to decision-problems projects in EI. Our hypothesis is that the possibility of reasoning about temporal properties in exploitation of knowledge in EI projects should foster timely decision making through generation of useful inferences from available and reusable knowledge for a new project.


Methodology for assessing system performance loss within a proactive maintenance framework

Abstract: Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product conditions. It suggests moving from conventional maintenance practices to predictive strategy. Indeed the maintenance action has to be done at the right time based on the system performance and component Remaining Useful Life (RUL) assessed by a prognostic process. In that way, this paper proposes a methodology in order to evaluate the performance loss of the system according to the degradation of component and the deviations of system input flows. This methodology is supported by the neuro-fuzzy tool ANFIS (Adaptive Neuro-Fuzzy Inference Systems) that allows to integrate knowledge from two different sources: expertise and real data. The feasibility and added value of such methodology is then highlighted through an application case extracted from the TELMA platform used for education and research.


Toward a Category Theory Design of Ontological Knowledge Bases

Abstract: I discuss (ontologies_and_ontological_knowledge_bases / formal_methods_and_theories) duality and its category theory extensions as a step toward a solution to Knowledge-Based Systems Theory. In particular I focus on the example of the design of elements of ontologies and ontological knowledge bases of next three electronic courses: Foundations of Research Activities, Virtual Modeling of Complex Systems and Introduction to String Theory.


Segmentation of Facial Expressions Using Semi-Definite Programming and Generalized Principal Component Analysis

Abstract: In this paper, we use semi-definite programming and generalized principal component analysis (GPCA) to distinguish between two or more different facial expressions. In the first step, semi-definite programming is used to reduce the dimension of the image data and "unfold" the manifold which the data points (corresponding to facial expressions) reside on. Next, GPCA is used to fit a series of subspaces to the data points and associate each data point with a subspace. Data points that belong to the same subspace are claimed to belong to the same facial expression category. An example is provided.


Creating Textual Language Dialects Using Aspect-like Techniques

Abstract: Here we present a work aimed on efficiently creating textual language dialects and supporting tools for them (e.g. compiler front-ends, IDE support, pretty-printers, etc.). A dialect is a language which may be described with a (relatively small) set of changes to some other language (a parent language). For example we can consider SQL dialects used in DB-management systems. We propose to use aspects for grammars to define different features of the anguage and to transform grammars. A dialect is created by defining a syntactical spect which modifies the parent language. This technique is not dependent on any particular language design, AST structure or parsing technology and provides a uniform way for creating dialects, which extend or restrict languages.


Large-Margin kNN Classification Using a Deep Encoder Network

Abstract: KNN is one of the most popular classification methods, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. Linear feature transformation methods have been widely applied to extract class-relevant information to improve kNN classification, which is very limited in many applications. Kernels have been used to learn powerful non-linear feature transformations, but these methods fail to scale to large datasets. In this paper, we present a scalable non-linear feature mapping method based on a deep neural network pretrained with restricted boltzmann machines for improving kNN classification in a large-margin framework, which we call DNet-kNN. DNet-kNN can be used for both classification and for supervised dimensionality reduction. The experimental results on two benchmark handwritten digit datasets show that DNet-kNN has much better performance than large-margin kNN using a linear mapping and kNN based on a deep autoencoder pretrained with retricted boltzmann machines.


Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory. International Journal of Telemedicine and Applications

Abstract: Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.


Towards Improving Validation, Verification, Crash Investigations, and Event Reconstruction of Flight-Critical Systems with Self-Forensics

Abstract: This paper introduces a novel concept of self-forensics to complement the standard autonomic self-CHOP properties of the self-managed systems, to be specified in the Forensic Lucid language. We argue that self-forensics, with the forensics taken out of the cybercrime domain, is applicable to "self-dissection" for the purpose of verification of autonomous software and hardware systems of flight-critical systems for automated incident and anomaly analysis and event reconstruction by the engineering teams in a variety of incident scenarios during design and testing as well as actual flight data.


How deals with discrete data for the reduction of simulation models using neural network

Abstract: Simulation is useful for the evaluation of a Master Production/distribution Schedule (MPS). Also, the goal of this paper is the study of the design of a simulation model by reducing its complexity. According to theory of constraints, we want to build reduced models composed exclusively by bottlenecks and a neural network. Particularly a multilayer perceptron, is used. The structure of the network is determined by using a pruning procedure. This work focuses on the impact of discrete data on the results and compares different approaches to deal with these data. This approach is applied to sawmill internal supply chain


Ideal Stabilization

Abstract: We define and explore the concept of ideal stabilization. The program is ideally stabilizing if its every state is legitimate. Ideal stabilization allows the specification designer to prescribe with arbitrary degree of precision not only the fault-free program behavior but also its recovery operation. Specifications may or may not mention all possible states. We identify approaches to designing ideal stabilization to both kinds of specifications. For the first kind, we state the necessary condition for an ideally stabilizing solution. On the basis of this condition we prove that there is no ideally stabilizing solution to the leader election problem. We illustrate the utility of the concept by providing examples of well-known programs and proving them ideally stabilizing. Specifically, we prove ideal stabilization of the conflict manager, the alternator, the propagation of information with feedback and the alternating bit protocol.


An Exponential Time 2-Approximation Algorithm for Bandwidth

Abstract: The bandwidth of a graph G on n vertices is the minimum b such that the vertices of G can be labeled from 1 to n such that the labels of every pair of adjacent vertices differ by at most b. In this paper, we present a 2-approximation algorithm for the bandwidth problem that takes worst-case O(1.9797^n) time and uses polynomial space. This improves both the previous best 2- and 3-approximation algorithms of Cygan et al. which have an O(3^n) and O(2^n) worst-case time bounds, respectively. Our algorithm is based on constructing bucket decompositions of the input graph. A bucket decomposition partitions the vertex set of a graph into ordered sets (called buckets) of (almost) equal sizes such that all edges are either incident to vertices in the same bucket or to vertices in two consecutive buckets. The idea is to find the smallest bucket size for which there exists a bucket decomposition. The algorithm uses a simple divide-and-conquer strategy along with dynamic programming to achieve this improved time bound.


Evading network-level emulation

Abstract: Recently more and more attention has been paid to the intrusion detection systems (IDS) which don't rely on signature based detection approach. Such solutions try to increase their defense level by using heuristics detection methods like network-level emulation. This technique allows the intrusion detection systems to stop unknown threats, which normally couldn't be stopped by standard signature detection techniques. In this article author will describe general concepts of network-level emulation technique including its advantages and disadvantages (weak sides) together with providing potential countermeasures against this type of detection method.


Scheduling with Outliers

Abstract: In classical scheduling problems, we are given jobs and machines, and have to schedule all the jobs to minimize some objective function. What if each job has a specified profit, and we are no longer required to process all jobs -- we can schedule any subset of jobs whose total profit is at least a (hard) target profit requirement, while still approximately minimizing the objective function? We refer to this class of problems as scheduling with outliers. This model was initiated by Charikar and Khuller (SODA'06) on the minimum max-response time in broadcast scheduling. We consider three other well-studied scheduling objectives: the generalized assignment problem, average weighted completion time, and average flow time, and provide LP-based approximation algorithms for them. For the minimum average flow time problem on identical machines, we give a logarithmic approximation algorithm for the case of unit profits based on rounding an LP relaxation; we also show a matching integrality gap. For the average weighted completion time problem on unrelated machines, we give a constant factor approximation. The algorithm is based on randomized rounding of the time-indexed LP relaxation strengthened by the knapsack-cover inequalities. For the generalized assignment problem with outliers, we give a simple reduction to GAP without outliers to obtain an algorithm whose makespan is within 3 times the optimum makespan, and whose cost is at most (1 + \epsilon) times the optimal cost.


Minimizing Maximum Response Time and Delay Factor in Broadcast Scheduling

Abstract: We consider online algorithms for pull-based broadcast scheduling. In this setting there are n pages of information at a server and requests for pages arrive online. When the server serves (broadcasts) a page p, all outstanding requests for that page are satisfied. We study two related metrics, namely maximum response time (waiting time) and maximum delay-factor and their weighted versions. We obtain the following results in the worst-case online competitive model. - We show that FIFO (first-in first-out) is 2-competitive even when the page sizes are different. Previously this was known only for unit-sized pages [10] via a delicate argument. Our proof differs from [10] and is perhaps more intuitive. - We give an online algorithm for maximum delay-factor that is O(1/eps^2)-competitive with (1+\eps)-speed for unit-sized pages and with (2+\eps)-speed for different sized pages. This improves on the algorithm in [12] which required (2+\eps)-speed and (4+\eps)-speed respectively. In addition we show that the algorithm and analysis can be extended to obtain the same results for maximum weighted response time and delay factor. - We show that a natural greedy algorithm modeled after LWF (Longest-Wait-First) is not O(1)-competitive for maximum delay factor with any constant speed even in the setting of standard scheduling with unit-sized jobs. This complements our upper bound and demonstrates the importance of the tradeoff made in our algorithm.


Adding eScience Assets to the Data Web

Abstract: Aggregations of Web resources are increasingly important in scholarship as it adopts new methods that are data-centric, collaborative, and networked-based. The same notion of aggregations of resources is common to the mashed-up, socially networked information environment of Web 2.0. We present a mechanism to identify and describe aggregations of Web resources that has resulted from the Open Archives Initiative - Object Reuse and Exchange (OAI-ORE) project. The OAI-ORE specifications are based on the principles of the Architecture of the World Wide Web, the Semantic Web, and the Linked Data effort. Therefore, their incorporation into the cyberinfrastructure that supports eScholarship will ensure the integration of the products of scholarly research into the Data Web.


Dependable Distributed Computing for the International Telecommunication Union Regional Radio Conference RRC06

Abstract: The International Telecommunication Union (ITU) Regional Radio Conference (RRC06) established in 2006 a new frequency plan for the introduction of digital broadcasting in European, African, Arab, CIS countries and Iran. The preparation of the plan involved complex calculations under short deadline and required dependable and efficient computing capability. The ITU designed and deployed in-situ a dedicated PC farm, in parallel to the European Organization for Nuclear Research (CERN) which provided and supported a system based on the EGEE Grid. The planning cycle at the RRC06 required a periodic execution in the order of 200,000 short jobs, using several hundreds of CPU hours, in a period of less than 12 hours. The nature of the problem required dynamic workload-balancing and low-latency access to the computing resources. We present the strategy and key technical choices that delivered a reliable service to the RRC06.


Structure of Heterogeneous Networks

Abstract: Heterogeneous networks play a key role in the evolution of communities and the decisions individuals make. These networks link different types of entities, for example, people and the events they attend. Network analysis algorithms usually project such networks unto simple graphs composed of entities of a single type. In the process, they conflate relations between entities of different types and loose important structural information. We develop a mathematical framework that can be used to compactly represent and analyze heterogeneous networks that combine multiple entity and link types. We generalize Bonacich centrality, which measures connectivity between nodes by the number of paths between them, to heterogeneous networks and use this measure to study network structure. Specifically, we extend the popular modularity-maximization method for community detection to use this centrality metric. We also rank nodes based on their connectivity to other nodes. One advantage of this centrality metric is that it has a tunable parameter we can use to set the length scale of interactions. By studying how rankings change with this parameter allows us to identify important nodes in the network. We apply the proposed method to analyze the structure of several heterogeneous networks. We show that exploiting additional sources of evidence corresponding to links between, as well as among, different entity types yields new insights into network structure.


Characterising equilibrium logic and nested logic programs: Reductions and complexity

Abstract: Equilibrium logic is an approach to nonmonotonic reasoning that extends the stable-model and answer-set semantics for logic programs. In particular, it includes the general case of nested logic programs, where arbitrary Boolean combinations are permitted in heads and bodies of rules, as special kinds of theories. In this paper, we present polynomial reductions of the main reasoning tasks associated with equilibrium logic and nested logic programs into quantified propositional logic, an extension of classical propositional logic where quantifications over atomic formulas are permitted. We provide reductions not only for decision problems, but also for the central semantical concepts of equilibrium logic and nested logic programs. In particular, our encodings map a given decision problem into some formula such that the latter is valid precisely in case the former holds. The basic tasks we deal with here are the consistency problem, brave reasoning, and skeptical reasoning. Additionally, we also provide encodings for testing equivalence of theories or programs under different notions of equivalence, viz. ordinary, strong, and uniform equivalence. For all considered reasoning tasks, we analyse their computational complexity and give strict complexity bounds.


A Neural Network Classifier of Volume Datasets

Abstract: Many state-of-the art visualization techniques must be tailored to the specific type of dataset, its modality (CT, MRI, etc.), the recorded object or anatomical region (head, spine, abdomen, etc.) and other parameters related to the data acquisition process. While parts of the information (imaging modality and acquisition sequence) may be obtained from the meta-data stored with the volume scan, there is important information which is not stored explicitly (anatomical region, tracing compound). Also, meta-data might be incomplete, inappropriate or simply missing. This paper presents a novel and simple method of determining the type of dataset from previously defined categories. 2D histograms based on intensity and gradient magnitude of datasets are used as input to a neural network, which classifies it into one of several categories it was trained with. The proposed method is an important building block for visualization systems to be used autonomously by non-experts. The method has been tested on 80 datasets, divided into 3 classes and a "rest" class. A significant result is the ability of the system to classify datasets into a specific class after being trained with only one dataset of that class. Other advantages of the method are its easy implementation and its high computational performance.


Shopping Uncertainties in a Mobile and Social Context

Abstract: We conducted a qualitative user study with 77 consumers to investigate what social aspects are relevant when supporting customers during their shopping activities and particularly in situations when they are undecided. Twenty-five respondents (32%) reported seeking extra information on web pages and forums, in addition to asking their peers for advice (related to the nature of the item to be bought). Moreover, from the remaining 52 subjects, only 6 (8%) were confident enough to make prompt comparisons between items and an immediate purchasing choice, while 17 respondents (22%) expressed the need for being away from persuasive elements. The remaining 29 respondents (38%) reported having a suboptimal strategy for making their shopping decisions (i.e. buying all items, not buying, or choosing randomly). Therefore, the majority of our participants (70% = 32% + 38%) had social and information needs when making purchasing decisions. This result motivates the development of applications that would allow consumers to ask shopping questions to their social network while on-the-go.


A note on uniform power connectivity in the SINR model

Abstract: In this paper we study the connectivity problem for wireless networks under the Signal to Interference plus Noise Ratio (SINR) model. Given a set of radio transmitters distributed in some area, we seek to build a directed strongly connected communication graph, and compute an edge coloring of this graph such that the transmitter-receiver pairs in each color class can communicate simultaneously. Depending on the interference model, more or less colors, corresponding to the number of frequencies or time slots, are necessary. We consider the SINR model that compares the received power of a signal at a receiver to the sum of the strength of other signals plus ambient noise . The strength of a signal is assumed to fade polynomially with the distance from the sender, depending on the so-called path-loss exponent $\alpha$. We show that, when all transmitters use the same power, the number of colors needed is constant in one-dimensional grids if $\alpha>1$ as well as in two-dimensional grids if $\alpha>2$. For smaller path-loss exponents and two-dimensional grids we prove upper and lower bounds in the order of $\mathcal{O}(\log n)$ and $\Omega(\log n/\log\log n)$ for $\alpha=2$ and $\Theta(n^{2/\alpha-1})$ for $\alpha<2$ respectively. If nodes are distributed uniformly at random on the interval $[0,1]$, a \emph{regular} coloring of $\mathcal{O}(\log n)$ colors guarantees connectivity, while $\Omega(\log \log n)$ colors are required for any coloring.


Symbolic Script Programming for Java

Abstract: Computer algebra in Java is a promising field of development. It has not yet reached an industrial strength, in part because of a lack of good user interfaces. Using a general purpose scripting language can bring a natural mathematical notation, akin to the one of specialized interfaces included in most computer algebra systems. We present such an interface for Java computer algebra libraries, using scripts available in the JSR 223 framework. We introduce the concept of `symbolic programming' and show its usefulness by prototypes of symbolic polynomials and polynomial rings.


Revisiting Digital Straight Segment Recognition

Abstract: This paper presents new results about digital straight segments, their recognition and related properties. They come from the study of the arithmetically based recognition algorithm proposed by I. Debled-Rennesson and J.-P. Reveill\`es in 1995 [Debled95]. We indeed exhibit the relations describing the possible changes in the parameters of the digital straight segment under investigation. This description is achieved by considering new parameters on digital segments: instead of their arithmetic description, we examine the parameters related to their combinatoric description. As a result we have a better understanding of their evolution during recognition and analytical formulas to compute them. We also show how this evolution can be projected onto the Stern-Brocot tree. These new relations have interesting consequences on the geometry of digital curves. We show how they can for instance be used to bound the slope difference between consecutive maximal segments.


Properties of quasi-alphabetic tree bimorphisms

Abstract: We study the class of quasi-alphabetic relations, i.e., tree transformations defined by tree bimorphisms with two quasi-alphabetic tree homomorphisms and a regular tree language. We present a canonical representation of these relations; as an immediate consequence, we get the closure under union. Also, we show that they are not closed under intersection and complement, and do not preserve most common operations on trees (branches, subtrees, v-product, v-quotient, f-top-catenation). Moreover, we prove that the translations defined by quasi-alphabetic tree bimorphism are exactly products of context-free string languages. We conclude by presenting the connections between quasi-alphabetic relations, alphabetic relations and classes of tree transformations defined by several types of top-down tree transducers. Furthermore, we get that quasi-alphabetic relations preserve the recognizable and algebraic tree languages.


Longest Wait First for Broadcast Scheduling

Abstract: We consider online algorithms for broadcast scheduling. In the pull-based broadcast model there are $n$ unit-sized pages of information at a server and requests arrive online for pages. When the server transmits a page $p$, all outstanding requests for that page are satisfied. The longest-wait-first} (LWF) algorithm is a natural algorithm that has been shown to have good empirical performance. In this paper we make two main contributions to the analysis of LWF and broadcast scheduling. \begin{itemize} \item We give an intuitive and easy to understand analysis of LWF which shows that it is $O(1/\eps^2)$-competitive for average flow-time with $(4+\eps)$ speed. Using a more involved analysis, we show that LWF is $O(1/\eps^3)$-competitive for average flow-time with $(3.4+\epsilon)$ speed. \item We show that a natural extension of LWF is O(1)-speed O(1)-competitive for more general objective functions such as average delay-factor and $L_k$ norms of delay-factor (for fixed $k$). \end{itemize}


Without a 'doubt'? Unsupervised discovery of downward-entailing operators

Abstract: An important part of textual inference is making deductions involving monotonicity, that is, determining whether a given assertion entails restrictions or relaxations of that assertion. For instance, the statement 'We know the epidemic spread quickly' does not entail 'We know the epidemic spread quickly via fleas', but 'We doubt the epidemic spread quickly' entails 'We doubt the epidemic spread quickly via fleas'. Here, we present the first algorithm for the challenging lexical-semantics problem of learning linguistic constructions that, like 'doubt', are downward entailing (DE). Our algorithm is unsupervised, resource-lean, and effective, accurately recovering many DE operators that are missing from the hand-constructed lists that textual-inference systems currently use.


Ftklipse - Design and Implementation of an Extendable Computer Forensics Environment: Software Requirements Specification Document

Abstract: The purpose behind this article is to describe the features of Ftklipse, an extendable platform for computer forensics. This document designed to provide a detailed specification for the developers of Ftklipse. Ftklipse is a thick-client solution for forensics investigation. It is designed to collect and preserve evidence, to analyze it and to report on it. It supports chain of custody management, access control policies, and batch operation of its included tools in order to facilitate and accelerate the investigation. The environment itself and its tools are configurable as well and is based on Eclipse.


Ftklipse - Design and Implementation of an Extendable Computer Forensics Environment: Specification Design Document

Abstract: The purpose of this work is to design and implement a plugin-based environment that allows to integrate forensic tools working together to support programming tasks and addition of new tools. Integration is done through GUI components. The end-system environment must have user friendly GUI, configuration capabilities, plug-in capabilities to insert/inject new tools, case management, and chain of custody capabilities, along with evidence gathering capabilities, evidence preservation capabilities, and, finally report generation capabilities. A subset of these requirements has been implemented in Ftklipse, an open-source project, which is detailed throughout the rest of this document.


The Limit of Convexity Based Isoperimetry: Sampling Harmonic-Concave Functions

Abstract: Logconcave functions represent the current frontier of efficient algorithms for sampling, optimization and integration in R^n. Efficient sampling algorithms to sample according to a probability density (to which the other two problems can be reduced) relies on good isoperimetry which is known to hold for arbitrary logconcave densities. In this paper, we extend this frontier in two ways: first, we characterize convexity-like conditions that imply good isoperimetry, i.e., what condition on function values along every line guarantees good isoperimetry? The answer turns out to be the set of (1/(n-1))-harmonic concave functions in R^n; we also prove that this is the best possible characterization along every line, of functions having good isoperimetry. Next, we give the first efficient algorithm for sampling according to such functions with complexity depending on a smoothness parameter. Further, noting that the multivariate Cauchy density is an important distribution in this class, we exploit certain properties of the Cauchy density to give an efficient sampling algorithm based on random walks with a mixing time that matches the current best bounds known for sampling logconcave functions.


Exact Indexing for Massive Time Series Databases under Time Warping Distance

Abstract: Among many existing distance measures for time series data, Dynamic Time Warping (DTW) distance has been recognized as one of the most accurate and suitable distance measures due to its flexibility in sequence alignment. However, DTW distance calculation is computationally intensive. Especially in very large time series databases, sequential scan through the entire database is definitely impractical, even with random access that exploits some index structures since high dimensionality of time series data incurs extremely high I/O cost. More specifically, a sequential structure consumes high CPU but low I/O costs, while an index structure requires low CPU but high I/O costs. In this work, we therefore propose a novel indexed sequential structure called TWIST (Time Warping in Indexed Sequential sTructure) which benefits from both sequential access and index structure. When a query sequence is issued, TWIST calculates lower bounding distances between a group of candidate sequences and the query sequence, and then identifies the data access order in advance, hence reducing a great number of both sequential and random accesses. Impressively, our indexed sequential structure achieves significant speedup in a querying process by a few orders of magnitude. In addition, our method shows superiority over existing rival methods in terms of query processing time, number of page accesses, and storage requirement with no false dismissal guaranteed.


Continuous Blooming of Convex Polyhedra

Abstract: We construct the first two continuous bloomings of all convex polyhedra. First, the source unfolding can be continuously bloomed. Second, any unfolding of a convex polyhedron can be refined (further cut, by a linear number of cuts) to have a continuous blooming.


Truthful Mechanisms via Greedy Iterative Packing

Abstract: An important research thread in algorithmic game theory studies the design of efficient truthful mechanisms that approximate the optimal social welfare. A fundamental question is whether an \alpha-approximation algorithm translates into an \alpha-approximate truthful mechanism. It is well-known that plugging an \alpha-approximation algorithm into the VCG technique may not yield a truthful mechanism. Thus, it is natural to investigate properties of approximation algorithms that enable their use in truthful mechanisms. The main contribution of this paper is to identify a useful and natural property of approximation algorithms, which we call loser-independence; this property is applicable in the single-minded and single-parameter settings. Intuitively, a loser-independent algorithm does not change its outcome when the bid of a losing agent increases, unless that agent becomes a winner. We demonstrate that loser-independent algorithms can be employed as sub-procedures in a greedy iterative packing approach while preserving monotonicity. A greedy iterative approach provides a good approximation in the context of maximizing a non-decreasing submodular function subject to independence constraints. Our framework gives rise to truthful approximation mechanisms for various problems. Notably, some problems arise in online mechanism design.


On the Representation of Finite Automata

Abstract: We give an unique string representation, up to isomorphism, for initially connected deterministic finite automata (ICDFAs) with n states over an alphabet of k symbols. We show how to generate all these strings for each n and k, and how its enumeration provides an alternative way to obtain the exact number of ICDFAs.


On Implementation of a Safer C Library, ISO/IEC TR 24731

Abstract: The functions standardized as part of ISO C 1999 and their addendums improved very little the security options from the previously available library. The largest flaw remained that no function asked for the buffer size of destination buffers for any function copying data into a user-supplied buffer. According to earlier research we performed, we know that error condition handling was the first solution to security vulnerabilities, followed by precondition validation. The standard C functions typically perform little precondition validation and error handling, allowing for a wide range of security issues to be introduced in their use. ISO/IEC TR 24731, titled as "TR 24731: Safer C library functions", defines 41 new library functions for memory copying, string handling (both for normal and wide character strings), time printing, sorting, searching etc. Another innovation it brings is a constraint handling architecture, forcing error handling when certain security-related preconditions are violated when the functions are called. It also specifies the null-termination of all strings manipulated through its function and introduces a new unsigned integer type that helps preventing integer overflows and underflows. It is currently implemented by Microsoft as part of their Visual Studio 2005 and above. We examine the architecture of our implementation of ISO/IEC TR 24731. We first introduce our architectural philosophy before informing the reader about the Siemens Four View Model, an architectural methodology for the conception of large-scale software systems. Afterwards, we examine each of the view, as architected for our library. Finally, we conclude with other software engineering matters that were of high importance in the development of our implementation.


On the Complexity of Branching-Time Logics

Abstract: We classify the complexity of the satisfiability problem for extensions of CTL and UB. The extensions we consider are Boolean combinations of path formulas, fairness properties, past modalities, and forgettable past. Our main result shows that satisfiability for CTL with all these extensions is still in 2-EXPTIME, which strongly contrasts with the nonelementary complexity of CTL* with forgettable past. We give a complete classification of combinations of these extensions, yielding a dichotomy between extensions with 2-EXPTIME-complete and those with EXPTIME-complete complexity. In particular, we show that satisfiability for the extension of UB with forgettable past is complete for 2-EXPTIME, contradicting a claim for a stronger logic in the literature. The upper bounds are established with the help of a new kind of pebble automata.


On the Hybrid Extension of CTL and CTL+

Abstract: The paper studies the expressivity, relative succinctness and complexity of satisfiability for hybrid extensions of the branching-time logics CTL and CTL+ by variables. Previous complexity results show that only fragments with one variable do have elementary complexity. It is shown that H1CTL+ and H1CTL, the hybrid extensions with one variable of CTL+ and CTL, respectively, are expressively equivalent but H1CTL+ is exponentially more succinct than H1CTL. On the other hand, HCTL+, the hybrid extension of CTL with arbitrarily many variables does not capture CTL*, as it even cannot express the simple CTL* property EGFp. The satisfiability problem for H1CTL+ is complete for triply exponential time, this remains true for quite weak fragments and quite strong extensions of the logic.


From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web

Abstract: In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).


Stability Properties of Networks with Interacting TCP Flows

Abstract: The equilibrium distributions of a Markovian model describing the interaction of several classes of permanent connections in a network are analyzed. It has been introduced by Graham and Robert. For this model each of the connections has a self-adaptive behavior in that its transmission rate along its route depends on the level of congestion of the nodes on its route. It has been shown that the invariant distributions are determined by the solutions of a fixed point equation in a finite dimensional space. In this paper, several examples of these fixed point equations are studied. The topologies investigated are rings, trees and a linear network, with various sets of routes through the nodes.


Bayesian History Reconstruction of Complex Human Gene Clusters on a Phylogeny

Abstract: Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analysis. Improved understanding of these clusters is of utmost importance, since they have been shown to be the source of evolutionary innovation, and have been linked to multiple diseases, including HIV and a variety of cancers. Previously, Zhang et al. (2008) developed an algorithm for reconstructing parsimonious evolutionary histories of such gene clusters, using only human genomic sequence data. In this paper, we propose a probabilistic model for the evolution of gene clusters on a phylogeny, and an MCMC algorithm for reconstruction of duplication histories from genomic sequences in multiple species. Several projects are underway to obtain high quality BAC-based assemblies of duplicated clusters in multiple species, and we anticipate that our method will be useful in analyzing these valuable new data sets.


Oscillations and Random Perturbations of a FitzHugh-Nagumo System

Abstract: We consider a stochastic perturbation of a FitzHugh-Nagumo system. We show that it is possible to generate oscillations for values of parameters which do not allow oscillations for the deterministic system. We also study the appearance of a new equilibrium point and new bifurcation parameters due to the noisy component.


Maximal digital straight segments and convergence of discrete geometric estimators

Abstract: Discrete geometric estimators approach geometric quantities on digitized shapes without any knowledge of the continuous shape. A classical yet difficult problem is to show that an estimator asymptotically converges toward the true geometric quantity as the resolution increases. We study here the convergence of local estimators based on Digital Straight Segment (DSS) recognition. It is closely linked to the asymptotic growth of maximal DSS, for which we show bounds both about their number and sizes. These results not only give better insights about digitized curves but indicate that curvature estimators based on local DSS recognition are not likely to converge. We indeed invalidate an hypothesis which was essential in the only known convergence theorem of a discrete curvature estimator. The proof involves results from arithmetic properties of digital lines, digital convexity, combinatorics, continued fractions and random polytopes.


RPO, Second-order Contexts, and Lambda-calculus

Abstract: First, we extend Leifer-Milner RPO theory, by giving general conditions to obtain IPO labelled transition systems (and bisimilarities) with a reduced set of transitions, and possibly finitely branching. Moreover, we study the weak variant of Leifer-Milner theory, by giving general conditions under which the weak bisimilarity is a congruence. Then, we apply such extended RPO technique to the lambda-calculus, endowed with lazy and call by value reduction strategies. We show that, contrary to process calculi, one can deal directly with the lambda-calculus syntax and apply Leifer-Milner technique to a category of contexts, provided that we work in the framework of weak bisimilarities. However, even in the case of the transition system with minimal contexts, the resulting bisimilarity is infinitely branching, due to the fact that, in standard context categories, parametric rules such as the beta-rule can be represented only by infinitely many ground rules. To overcome this problem, we introduce the general notion of second-order context category. We show that, by carrying out the RPO construction in this setting, the lazy observational equivalence can be captured as a weak bisimilarity equivalence on a finitely branching transition system. This result is achieved by considering an encoding of lambda-calculus in Combinatory Logic.


Data Structures for Approximate Range Counting

Abstract: We present new data structures for approximately counting the number of points in orthogonal range. There is a deterministic linear space data structure that supports updates in O(1) time and approximates the number of elements in a 1-D range up to an additive term $k^{1/c}$ in $O(\log \log U\cdot\log \log n)$ time, where $k$ is the number of elements in the answer, $U$ is the size of the universe and $c$ is an arbitrary fixed constant. We can estimate the number of points in a two-dimensional orthogonal range up to an additive term $ k^{\rho}$ in $O(\log \log U+ (1/\rho)\log\log n)$ time for any $\rho>0$. We can estimate the number of points in a three-dimensional orthogonal range up to an additive term $k^{\rho}$ in $O(\log \log U + (\log\log n)^3+ (3^v)\log\log n)$ time for $v=\log \frac{1}{\rho}/\log {3/2}+2$.


Power Saving Strategies and Technologies in Network Equipment Opportunities and Challenges, Risk and Rewards

Abstract: Drawing from todays best-in-class solutions, we identify power-saving strategies that have succeeded in the past and look forward to new ideas and paradigms. We strongly believe that designing energy-efficient network equipment can be compared to building sports cars, task-oriented, focused and fast. However, unlike track-bound sports cars, ultra-fast and purpose-built silicon yields better energy efficiency when compared to more generic family sedan designs that mitigate go-to-market risks by being the masters of many tasks. Thus, we demonstrate that the best opportunities for power savings come via protocol simplification, best-of-breed technology, and silicon and software optimization, to achieve the least amount of processing necessary to move packets. We also look to the future of networking from a new angle, where energy efficiency and environmental concerns are viewed as fundamental design criteria and forces that need to be harnessed to continually create more powerful networking equipment.


Norms and Commitment for iOrgs(TM) Information Systems: Direct Logic(TM) and Participatory Grounding Checking

Abstract: The fundamental assumption of the Event Calculus is overly simplistic when it comes to organizations in which time-varying properties have to be actively maintained and managed in order to continue to hold and termination by another action is not required for a property to no longer hold. I.e., if active measures are not taken then things will go haywire by default. Similarly extension and revision is required for Grounding Checking properties of systems based on a set of ground inferences. Previously Model Checking as been performed using the model of nondeterministic automata based on states determined by time-points. These nondeterministic automata are not suitable for iOrgs, which are highly structured and operate asynchronously with only loosely bounded nondeterminism. iOrgs Information Systems have been developed as a technology in which organizations have people that are tightly integrated with information technology that enables them to function organizationally. iOrgs formalize existing practices to provide a framework for addressing issues of authority, accountability, scalability, and robustness using methods that are analogous to human organizations. In general -iOrgs are a natural extension Web Services, which are the standard for distributed computing and software application interoperability in large-scale Organizational Computing. -iOrgs are structured by Organizational Commitment that is a special case of Physical Commitment that is defined to be information pledged. iOrgs norms are used to illustrate the following: -Even a very simple microtheory for normative reasoning can engender inconsistency In practice, it is impossible to verify the consistency of a theory for a practical domain. -Improved Safety in Reasoning. It is not safe to use classical logic and probability theory in practical reasoning.


Constructing Two-Dimensional Voronoi Diagrams via Divide-and-Conquer of Envelopes in Space

Abstract: We present a general framework for computing two-dimensional Voronoi diagrams of different classes of sites under various distance functions. The framework is sufficiently general to support diagrams embedded on a family of two-dimensional parametric surfaces in $R^3$. The computation of the diagrams is carried out through the construction of envelopes of surfaces in 3-space provided by CGAL (the Computational Geometry Algorithm Library). The construction of the envelopes follows a divide-and-conquer approach. A straightforward application of the divide-and-conquer approach for computing Voronoi diagrams yields algorithms that are inefficient in the worst case. We prove that through randomization the expected running time becomes near-optimal in the worst case. We show how to employ our framework to realize various types of Voronoi diagrams with different properties by providing implementations for a vast collection of commonly used Voronoi diagrams. We also show how to apply the new framework and other existing tools from CGAL to compute minimum-width annuli of sets of disks, which requires the computation of two Voronoi diagrams of two different types, and of the overlay of the two diagrams. We do not assume general position. Namely, we handle degenerate input, and produce exact results.


Coding cells of digital spaces: a framework to write generic digital topology algorithms

Abstract: This paper proposes a concise coding of the cells of n-dimensional finite regular grids. It induces a simple, generic and efficient framework for implementing classical digital topology data structures and algorithms. Discrete subsets of multidimensional images (e.g. regions, digital surfaces, cubical cell complexes) have then a common and compact representation. Moreover, algorithms have a straightforward and efficient implementation, which is independent from the dimension or sizes of digital images. We illustrate that point with generic hypersurface boundary extraction algorithms by scanning or tracking. This framework has been implemented and basic operations as well as the presented applications have been benchmarked.


Combinatorial pyramids and discrete geometry for energy-minimizing segmentation

Abstract: This paper defines the basis of a new hierarchical framework for segmentation algorithms based on energy minimization schemes. This new framework is based on two formal tools. First, a combinatorial pyramid encode efficiently a hierarchy of partitions. Secondly, discrete geometric estimators measure precisely some important geometric parameters of the regions. These measures combined with photometrical and topological features of the partition allows to design energy terms based on discrete measures. Our segmentation framework exploits these energies to build a pyramid of image partitions with a minimization scheme. Some experiments illustrating our framework are shown and discussed.


What Does Artificial Life Tell Us About Death?

Abstract: Short philosophical essay


Employing Wikipedia's Natural Intelligence For Cross Language Information Retrieval

Abstract: In this paper we present a novel method for retrieving information in languages other than that of the query. We use this technique in combination with existing traditional Cross Language Information Retrieval (CLIR) techniques to improve their results. This method has a number of advantages over traditional techniques that rely on machine translation to translate the query and then search the target document space using a machine translation. This method is not limited to the availability of a machine translation algorithm for the desired language and uses already existing sources of readily available translated information on the internet as a "middle-man" approach. In this paper we use Wikipedia; however, any similar multilingual, cross referenced body of documents can be used. For evaluation and comparison purposes we also implemented a traditional machine translation approach separately as well as the Wikipedia approach separately.


Predicate Transformers, (co)Monads and Resolutions

Abstract: This short note contains random thoughts about a factorization theorem for closure/interior operators on a powerset which is reminiscent to the notion of resolution for a monad/comonad. The question originated from formal topology but is interesting in itself. The result holds constructively (even if it classically has several variations); but usually not predicatively (in the sense that the interpolant will no be given by a set). For those not familiar with predicativity issues, we look at a ``classical'' version where we bound the size of the interpolant.


Chebyshev Expansions for Solutions of Linear Differential Equations

Abstract: A Chebyshev expansion is a series in the basis of Chebyshev polynomials of the first kind. When such a series solves a linear differential equation, its coefficients satisfy a linear recurrence equation. We interpret this equation as the numerator of a fraction of linear recurrence operators. This interpretation lets us give a simple view of previous algorithms, analyze their complexity, and design a faster one for large orders.