Relating timed and register automata

Abstract: Timed automata and register automata are well-known models of computation over timed and data words respectively. The former has clocks that allow to test the lapse of time between two events, whilst the latter includes registers that can store data values for later comparison. Although these two models behave in appearance differently, several decision problems have the same (un)decidability and complexity results for both models. As a prominent example, emptiness is decidable for alternating automata with one clock or register, both with non-primitive recursive complexity. This is not by chance. This work confirms that there is indeed a tight relationship between the two models. We show that a run of a timed automaton can be simulated by a register automaton, and conversely that a run of a register automaton can be simulated by a timed automaton. Our results allow to transfer complexity and decidability results back and forth between these two kinds of models. We justify the usefulness of these reductions by obtaining new results on register automata.


A Process Calculus for Expressing Finite Place/Transition Petri Nets

Abstract: We introduce the process calculus Multi-CCS, which extends conservatively CCS with an operator of strong prefixing able to model atomic sequences of actions as well as multiparty synchronization. Multi-CCS is equipped with a labeled transition system semantics, which makes use of a minimal structural congruence. Multi-CCS is also equipped with an unsafe P/T Petri net semantics by means of a novel technique. This is the first rich process calculus, including CCS as a subcalculus, which receives a semantics in terms of unsafe, labeled P/T nets. The main result of the paper is that a class of Multi-CCS processes, called finite-net processes, is able to represent all finite (reduced) P/T nets.


Models for CSP with availability information

Abstract: We consider models of CSP based on recording what events are available as possible alternatives to the events that are actually performed. We present many different varieties of such models. For each, we give a compositional semantics, congruent to the operational semantics, and prove full abstraction and no-junk results. We compare the expressiveness of the different models.


Robustness of Equations Under Operational Extensions

Abstract: Sound behavioral equations on open terms may become unsound after conservative extensions of the underlying operational semantics. Providing criteria under which such equations are preserved is extremely useful; in particular, it can avoid the need to repeat proofs when extending the specified language. This paper investigates preservation of sound equations for several notions of bisimilarity on open terms: closed-instance (ci-)bisimilarity and formal-hypothesis (fh-)bisimilarity, both due to Robert de Simone, and hypothesis-preserving (hp-)bisimilarity, due to Arend Rensink. For both fh-bisimilarity and hp-bisimilarity, we prove that arbitrary sound equations on open terms are preserved by all disjoint extensions which do not add labels. We also define slight variations of fh- and hp-bisimilarity such that all sound equations are preserved by arbitrary disjoint extensions. Finally, we give two sets of syntactic criteria (on equations, resp. operational extensions) and prove each of them to be sufficient for preserving ci-bisimilarity.


Multiparty Symmetric Sum Types

Abstract: This paper introduces a new theory of multiparty session types based on symmetric sum types, by which we can type non-deterministic orchestration choice behaviours. While the original branching type in session types can represent a choice made by a single participant and accepted by others determining how the session proceeds, the symmetric sum type represents a choice made by agreement among all the participants of a session. Such behaviour can be found in many practical systems, including collaborative workflow in healthcare systems for clinical practice guidelines (CPGs). Processes using the symmetric sums can be embedded into the original branching types using conductor processes. We show that this type-driven embedding preserves typability, satisfies semantic soundness and completeness, and meets the encodability criteria adapted to the typed setting. The theory leads to an efficient implementation of a prototypical tool for CPGs which automatically translates the original CPG specifications from a representation called the Process Matrix to symmetric sum types, type checks programs and executes them.


Breaking Symmetries

Abstract: A well-known result by Palamidessi tells us that \pimix (the \pi-calculus with mixed choice) is more expressive than \pisep (its subset with only separate choice). The proof of this result argues with their different expressive power concerning leader election in symmetric networks. Later on, Gorla offered an arguably simpler proof that, instead of leader election in symmetric networks, employed the reducibility of incestual processes (mixed choices that include both enabled senders and receivers for the same channel) when running two copies in parallel. In both proofs, the role of breaking (initial) symmetries is more or less apparent. In this paper, we shed more light on this role by re-proving the above result - based on a proper formalization of what it means to break symmetries without referring to another layer of the distinguishing problem domain of leader election. Both Palamidessi and Gorla rephrased their results by stating that there is no uniform and reasonable encoding from \pimix into \pisep. We indicate how the respective proofs can be adapted and exhibit the consequences of varying notions of uniformity and reasonableness. In each case, the ability to break initial symmetries turns out to be essential.


Process Behaviour: Formulae vs. Tests (Extended Abstract)

Abstract: Process behaviour is often defined either in terms of the tests they satisfy, or in terms of the logical properties they enjoy. Here we compare these two approaches, using extensional testing in the style of DeNicola, Hennessy, and a recursive version of the property logic HML. We first characterise subsets of this property logic which can be captured by tests. Then we show that those subsets of the property logic capture precisely the power of tests.


Precisely Analyzing Loss in Interface Adapter Chains

Abstract: Interface adaptation allows code written for one interface to be used with a software component with another interface. When multiple adapters are chained together to make certain adaptations possible, we need a way to analyze how well the adaptation is done in case there are more than one chains that can be used. We introduce an approach to precisely analyzing the loss in an interface adapter chain using a simple form of abstract interpretation.


A near optimal algorithm for finding Euclidean shortest path in polygonal domain

Abstract: We present an algorithm to find an {\it Euclidean Shortest Path} from a source vertex $s$ to a sink vertex $t$ in the presence of obstacles in $\Re^2$. Our algorithm takes $O(T+m(\lg{m})(\lg{n}))$ time and $O(n)$ space. Here, $O(T)$ is the time to triangulate the polygonal region, $m$ is the number of obstacles, and $n$ is the number of vertices. This bound is close to the known lower bound of $O(n+m\lg{m})$ time and $O(n)$ space. Our approach involve progressing shortest path wavefront as in continuous Dijkstra-type method, and confining its expansion to regions of interest.


An introduction to finite automata and their connection to logic

Abstract: This is a tutorial on finite automata. We present the standard material on determinization and minimization, as well as an account of the equivalence of finite automata and monadic second-order logic. We conclude with an introduction to the syntactic monoid, and as an application give a proof of the equivalence of first-order definability and aperiodicity.


A Calculus of Consistent Component-based Software Updates

Abstract: It is important to enable reasoning about the meaning and possible effects of updates to ensure that the updated system operates correctly. A formal, mathematical model of dynamic update should be developed, in order to understand by both users and implementors of update technology what design choices can be considered. In this paper, we define a formal calculus $update\pi$, a variant extension of higher-order $\pi$ calculus, to model dynamic updates of component-based software, which is language and technology independent. The calculus focuses on following main concepts: proper granularity of update, timing of dynamic update, state transformation between versions, update failure check and recovery. We describe a series of rule on safe component updates to model some general processes of dynamic update and discuss its reduction semantics coincides with a labelled transition system semantics that illustrate the expressive power of these calculi.


Approximate Shortest Path through a Weighted Planar Subdivision

Abstract: This paper presents an approximation algorithm for finding a shortest path between two points $s$ and $t$ in a weighted planar subdivision $\PS$. Each face $f$ of $\PS$ is associated with a weight $w_f$, and the cost of travel along a line segment on $f$ is $w_f$ multiplied by the Euclidean norm of that line segment. The cost of a path which traverses across several faces of the subdivision is the sum of the costs of travel along each face. Our algorithm progreeses the discretized shortest path wavefront from source $s$, and takes polynomial time in finding an $\epsilon$-approximate shortest path.


Efficient Characteristic Set Algorithms for Equation Solving in Finite Fields and Applications in Cryptanalysis

Abstract: Efficient characteristic set methods for computing solutions of polynomial equation systems in a finite field are proposed. The concept of proper triangular sets is introduced and an explicit formula for the number of solutions of a proper and monic (or regular) triangular set is given. An improved zero decomposition algorithm which can be used to reduce the zero set of an equation system in general form to the union of zero sets of monic proper triangular sets is proposed. As a consequence, we can give an explicit formula for the number of solutions of an equation system. Bitsize complexity for the algorithm is given in the case of Boolean polynomials. We also give a multiplication free characteristic set method for Boolean polynomials, where the sizes of the polynomials are effectively controlled. The algorithms are implemented in the case of Boolean polynomials and extensive experiments show that they are quite efficient for solving certain classes of Boolean equations.


Multi-Hop Bandwidth Management Protocol for Mobile Ad Hoc Networks

Abstract: An admission control scheme should play the role of a coordinator for flows in a data communication network, to provide the guarantees as the medium is shared. The nodes of a wired network can monitor the medium to know the available bandwidth at any point of time. But, in wireless ad hoc networks, a node must consume the bandwidth of neighboring nodes, during a communication. Hence, the consumption of bandwidth by a flow and the availability of resources to any wireless node strictly depend upon the neighboring nodes within its transmission range. We present a scalable and efficient admission control scheme, Multi-hop Bandwidth Management Protocol (MBMP), to support the QoS requirements in multi-hop ad hoc networks. We simulate several options to design MBMP and compare the performances of these options through mathematical analysis and simulation results, and compare its effectiveness with the existing admission control schemes through extensive simulations.


Ethical Dilemma of Governmental Wiretapping

Abstract: USA Government wiretapping activities is a very controversial issue. Undoubtedly this technology can assist law enforced authority to detect / identify unlawful or hostile activities; however, this task raises severe privacy concerns. In this paper, we have discussed this complex information technology issue of governmental wiretapping and how it effects both public and private liberties. Legislation has had a major impact on the uses and the stigma of wiretapping for the war on terrorism. This paper also analyzes the ethical and legal concerns inherent when discussing the benefits and concerns of wiretapping. The analysis has concluded with the effects of wiretapping laws as they relate to future government actions in their fight against terrorists.


Generating functions partitioning algorithm for computing power indices in weighted voting games

Abstract: In this paper new algorithm for calculating power indices is described. The complexity class of the problem is #P-complete and even calculating power index of the biggest player is NP-hard task. Constructed algorithm is a mix of ideas of two algorithms: Klinz & Woeginger partitioning algorithm and Mann & Shapley generating functions algorithm. Time and space complexities of the algorithm are analysed and compared with other known algorithms for the problem. Constructed algorithm has pessimistic time complexity O(n 2^(n/2))and pseudopolynomial complexity O(nq), where q is quota of the voting game. This paper also solves open problem stated by H. Aziz and M. Paterson - existence of the algorithm for calculating Banzhaf power indices of all players with time complexity lower than O(n^2 2^(n/2)). Not only is the answer positive but this can be done keeping the pseudopolynomial complexity of generating functions algorithm in case weights are integers. New open problems are stated.


Extending ArXiv.org to Achieve Open Peer Review and Publishing

Abstract: Today's peer review process for scientific articles is unnecessarily opaque and offers few incentives to referees. Likewise, the publishing process is unnecessarily inefficient and its results are only rarely made freely available to the public. Here we outline a comparatively simple extension of arXiv.org, an online preprint archive widely used in the mathematical and physical sciences, that addresses both of these problems. Under the proposal, editors invite referees to write public and signed reviews to be attached to the posted preprints, and then elevate selected articles to "published" status.


On the Benefit of Virtualization: Strategies for Flexible Server Allocation

Abstract: Virtualization technology facilitates a dynamic, demand-driven allocation and migration of servers. This paper studies how the flexibility offered by network virtualization can be used to improve Quality-of-Service parameters such as latency, while taking into account allocation costs. A generic use case is considered where both the overall demand issued for a certain service (for example, an SAP application in the cloud, or a gaming application) as well as the origins of the requests change over time (e.g., due to time zone effects or due to user mobility), and we present online and optimal offline strategies to compute the number and location of the servers implementing this service. These algorithms also allow us to study the fundamental benefits of dynamic resource allocation compared to static systems. Our simulation results confirm our expectations that the gain of flexible server allocation is particularly high in scenarios with moderate dynamics.


Dependability in Aggregation by Averaging

Abstract: Aggregation is an important building block of modern distributed applications, allowing the determination of meaningful properties (e.g. network size, total storage capacity, average load, majorities, etc.) that are used to direct the execution of the system. However, the majority of the existing aggregation algorithms exhibit relevant dependability issues, when prospecting their use in real application environments. In this paper, we reveal some dependability issues of aggregation algorithms based on iterative averaging techniques, giving some directions to solve them. This class of algorithms is considered robust (when compared to common tree-based approaches), being independent from the used routing topology and providing an aggregation result at all nodes. However, their robustness is strongly challenged and their correctness often compromised, when changing the assumptions of their working environment to more realistic ones. The correctness of this class of algorithms relies on the maintenance of a fundamental invariant, commonly designated as "mass conservation". We will argue that this main invariant is often broken in practical settings, and that additional mechanisms and modifications are required to maintain it, incurring in some degradation of the algorithms performance. In particular, we discuss the behavior of three representative algorithms Push-Sum Protocol, Push-Pull Gossip protocol and Distributed Random Grouping under asynchronous and faulty (with message loss and node crashes) environments. More specifically, we propose and evaluate two new versions of the Push-Pull Gossip protocol, which solve its message interleaving problem (evidenced even in a synchronous operation mode).


Learning sparse representations of depth

Abstract: This paper introduces a new method for learning and inferring sparse representations of depth (disparity) maps. The proposed algorithm relaxes the usual assumption of the stationary noise model in sparse coding. This enables learning from data corrupted with spatially varying noise or uncertainty, typically obtained by laser range scanners or structured light depth cameras. Sparse representations are learned from the Middlebury database disparity maps and then exploited in a two-layer graphical model for inferring depth from stereo, by including a sparsity prior on the learned features. Since they capture higher-order dependencies in the depth structure, these priors can complement smoothness priors commonly used in depth inference based on Markov Random Field (MRF) models. Inference on the proposed graph is achieved using an alternating iterative optimization technique, where the first layer is solved using an existing MRF-based stereo matching algorithm, then held fixed as the second layer is solved using the proposed non-stationary sparse coding algorithm. This leads to a general method for improving solutions of state of the art MRF-based depth estimation algorithms. Our experimental results first show that depth inference using learned representations leads to state of the art denoising of depth maps obtained from laser range scanners and a time of flight camera. Furthermore, we show that adding sparse priors improves the results of two depth estimation methods: the classical graph cut algorithm by Boykov et al. and the more recent algorithm of Woodford et al.


Functional Categories of Support to Operations in Military Information Systems

Abstract: In order to group the functional requirements for support to operations by modern information systems systematically, the NATO Code of best Practise (COBP) for C2 Assessment defines three domain areas: Battlespace Visualization, Decision Making, and Battle Management Functions. In addition, within an domain overlapping information grid of the information system, necessary functions for assessing and disseminating the information are capsulated. For all three domains, including the overlapping information grid, the respective requirements for functional support have to be met be future command, control, communications, and intelligence (C3I) systems. The paper describes the functional categories of the three domains having been defined for article 5 operations, extends them to meet the requirements for operations other than war (OOTW), and gives some examples how modules of simulation systems can deliver respective support functions. In addition, references defining migration procedures for legacy systems to enable a smooth change from the old to the new C3I paradigm are given.


Avoiding another Green Elephant - A Proposal for the Next Generation HLA based on the Model Driven Architecture

Abstract: When looking through the proceedings of the recent Simulation Interoperability Workshops, a lot of papers - some of them even awarded by the committee - are dealing with alternative concepts outside or beyond the High Level Architecture (HLA): Web Services, the extensible Markup Language (XML), Java Beans, Simple Object Access Protocol (SOAP), etc. Similarly, requirements driven by interoperability issues have resulted in the need to use meta modeling, adaptive models, and common repositories. The use of the Unified Modeling Language (UML) as a model description language is also rapidly becoming a standard. All these concepts have relations to the HLA, but they are not part of it. There seems to be the danger that HLA is overrun by respective developments of the free market and will become irrelevant finally. ... This paper introduces the MDA concept and shows, how the HLA can be integrated to become a standard stub for simulation applications of legacy systems, systems under development, and systems of the future.


Engineering Multilevel Graph Partitioning Algorithms

Abstract: We present a multi-level graph partitioning algorithm using novel local improvement algorithms and global search strategies transferred from the multi-grid community. Local improvement algorithms are based max-flow min-cut computations and more localized FM searches. By combining these techniques, we obtain an algorithm that is fast on the one hand and on the other hand is able to improve the best known partitioning results for many inputs. For example, in Walshaw's well known benchmark tables we achieve 317 improvements for the tables 1%, 3% and 5% imbalance. Moreover, in 118 additional cases we have been able to reproduce the best cut in this benchmark.


Domination When the Stars Are Out

Abstract: We algorithmize the recent structural characterization for claw-free graphs by Chudnovsky and Seymour. Building on this result, we show that Dominating Set on claw-free graphs is (i) fixed-parameter tractable and (ii) even possesses a polynomial kernel. To complement these results, we establish that Dominating Set is not fixed-parameter tractable on the slightly larger class of graphs that exclude K_{1,4} as an induced subgraph (K_{1,4}-free graphs). We show that our algorithmization can also be used to show that the related Connected Dominating Set problem is fixed-parameter tractable on claw-free graphs. To complement that result, we show that Connected Dominating Set has no polynomial kernel on claw-free graphs and is not fixed-parameter tractable on K_{1,4}-free graphs. Combined, our results provide a dichotomy for Dominating Set and Connected Dominating Set on K_{1,L}-free graphs and show that the problem is fixed-parameter tractable if and only if L <= 3.


Is Light-Tree Structure Optimal for Multicast Routing in Sparse Light Splitting WDM Networks?

Abstract: To minimize the number of wavelengths required by a multicast session in sparse light splitting wavelength division multiplexing (WDM) networks, a light-hierarchy structure, which occupies the same wavelength on all links, is proposed to span as many destinations as possible. Different from a light-tree, a light-hierarchy accepts cycles, which are used to traverse crosswise a 4-degree (or above) multicast incapable (MI) node twice (or above) and switch two light signals on the same wavelengths to two destinations in the same multicast session. In this paper, firstly, a graph renewal and distance priority light-tree algorithm (GRDP-LT) is introduced to improve the quality of light-trees built for a multicast request. Then, it is extended to compute light-hierarchies. Obtained numerical results demonstrate the GRDP-LT light-trees can achieve a much lower links stress, better wavelength channel cost, and smaller average end-to-end delay as well as diameter than the currently most efficient algorithm. Furthermore, compared to light-trees, the performance in terms of link stress and network throughput is greatly improved again by employing the light-hierarchy, while consuming the same amount of wavelength channel cost.


Light-Hierarchy: The Optimal Structure for Multicast Routing in WDM Mesh Networks

Abstract: Based on the false assumption that multicast incapable (MI) nodes could not be traversed twice on the same wavelength, the light-tree structure was always thought to be optimal for multicast routing in sparse splitting Wavelength Division Multiplexing (WDM) networks. In fact, for establishing a multicast session, an MI node could be crosswise visited more than once to switch a light signal towards several destinations with only one wavelength through different input and output pairs. This is called Cross Pair Switching (CPS). Thus, a new multicast routing structure light-hierarchy is proposed for all-optical multicast routing, which permits the cycles introduced by the CPS capability of MI nodes. We proved that the optimal structure for minimizing the cost of multicast routing is a set of light-hierarchies rather than the light-trees in sparse splitting WDM networks. Integer linear programming (ILP) formulations are developed to search the optimal light-hierarchies. Numerical results verified that the light-hierarchy structure could save more cost than the light-tree structure.


Pumping lemmas for linear and nonlinear context-free languages

Abstract: Pumping lemmas are created to prove that given languages are not belong to certain language classes. There are several known pumping lemmas for the whole class and some special classes of the context-free languages. In this paper we prove new, interesting pumping lemmas for special linear and context-free language classes. Some of them can be used to pump regular languages in two place simultaneously. Other lemma can be used to pump context-free languages in arbitrary many places.


Avoidance of multicast incapable branching nodes for multicast routing in WDM networks

Abstract: In this articlewestudy themulticast routing problem in all-opticalWDMnetworks under the spare light splitting constraint. To implement a multicast session, several light-trees may have to be used due to the limited fanouts of network nodes. Although many multicast routing algorithms have been proposed in order to reduce the total number of wavelength channels used (total cost) for a multicast session, the maximum number of wavelengths required in one fiber link (link stress) and the end-to-end delay are two parameters which are not always taken into consideration. It is known that the shortest path tree (SPT) results in the optimal end-to-end delay, but it can not be employed directly for multicast routing in sparse light splitting WDM networks. Hence, we propose a novel wavelength routing algorithm which tries to avoid the multicast incapable branching nodes (MIBs, branching nodes without splitting capability) in the shortest-path-based multicast tree to diminish the link stress. Good parts of the shortest-path-tree are retained by the algorithm to reduce the end-to-end delay. The algorithm consists of tree steps: (1) aDijkstraPro algorithmwith priority assignment and node adoption is introduced to produce a SPT with up to 38% fewer MIB nodes in the NSF topology and 46% fewerMIB nodes in the USA Longhaul topology, (2) critical articulation and deepest branch heuristics are used to process the MIB nodes, (3) a distance-based light-tree reconnection algorithm is proposed to create the multicast light-trees. Extensive simulations demonstrate the algorithm's efficiency in terms of link stress and end-to-end delay.


Testing of sequences by simulation

Abstract: Let $\xi$ be a random integer vector, having uniform distribution \[\mathbf{P} \{\xi = (i_1,i_2,...,i_n) = 1/n^n \} \ \hbox{for} \ 1 \leq i_1,i_2,...,i_n\leq n.\] A realization $(i_1,i_2,...,i_n)$ of $\xi$ is called \textit{good}, if its elements are different. We present algorithms \textsc{Linear}, \textsc{Backward}, \textsc{Forward}, \textsc{Tree}, \textsc{Garbage}, \textsc{Bucket} which decide whether a given realization is good. We analyse the number of comparisons and running time of these algorithms using simulation gathering data on all possible inputs for small values of $n$ and generating random inputs for large values of $n$.


Score lists in multipartite hypertournaments

Abstract: Given non-negative integers $n_{i}$ and $\alpha_{i}$ with $0 \leq \alpha_{i} \leq n_i$ $(i=1,2,...,k)$, an $[\alpha_{1},\alpha_{2},...,\alpha_{k}]$-$k$-partite hypertournament on $\sum_{1}^{k}n_{i}$ vertices is a $(k+1)$-tuple $(U_{1},U_{2},...,U_{k},E)$, where $U_{i}$ are $k$ vertex sets with $|U_{i}|=n_{i}$, and $E$ is a set of $\sum_{1}^{k}\alpha_{i}$-tuples of vertices, called arcs, with exactly $\alpha_{i}$ vertices from $U_{i}$, such that any $\sum_{1}^{k}\alpha_{i}$ subset $\cup_{1}^{k}U_{i}^{\prime}$ of $\cup_{1}^{k}U_{i}$, $E$ contains exactly one of the $(\sum_{1}^{k} \alpha_{i})!$ $\sum_{1}^{k}\alpha_{i}$-tuples whose entries belong to $\cup_{1}^{k}U_{i}^{\prime}$. We obtain necessary and sufficient conditions for $k$ lists of non-negative integers in non-decreasing order to be the losing score lists and to be the score lists of some $k$-partite hypertournament.


Hypo-Steiner heuristic for multicast routing in all-optical WDM mesh networks

Abstract: In sparse light splitting all-optical WDM networks, the more destinations a light-tree can accommodate, the fewer light-trees andwavelengths amulticast session will require. In this article, a Hypo-Steiner light-tree algorithm (HSLT) is proposed to construct a HSLT light-tree to include as many destinations as possible. The upper bound cost of the light-trees built by HSLT is given as N(N -1)/2, where N is the number of nodes in the network. The analytical model proves that, under the same condition, more destinations could be held in a HSLT than a Member-Only (Zhang et al., J. Lightware Technol, 18(12), 1917-1927 2000.) light-tree. Extensive simulations not only validate the proof but also show that the proposed heuristic outperforms the existing multicast routing algorithms by a large margin in terms of link stress, throughput, and efficiency ofwavelength usage.


Testing by C++ template metaprograms

Abstract: Testing is one of the most indispensable tasks in software engineering. The role of testing in software development has grown significantly because testing is able to reveal defects in the code in an early stage of development. Many unit test frameworks compatible with C/C++ code exist, but a standard one is missing. Unfortunately, many unsolved problems can be mentioned with the existing methods, for example usually external tools are necessary for testing C++ programs. In this paper we present a new approach for testing C++ programs. Our solution is based on C++ template metaprogramming facilities, so it can work with the standard-compliant compilers. The metaprogramming approach ensures that the overhead of testing is minimal at runtime. This approach also supports that the specification language can be customized among other advantages. Nevertheless, the only necessary tool is the compiler itself.


Computerized adaptive testing: implementation issues

Abstract: One of the fastest evolving field among teaching and learning research is students' performance evaluation. Computer based testing systems are increasingly adopted by universities. However, the implementation and maintenance of such a system and its underlying item bank is a challenge for an inexperienced tutor. Therefore, this paper discusses the advantages and disadvantages of Computer Adaptive Test (CAT) systems compared to Computer Based Test systems. Furthermore, a few item selection strategies are compared in order to overcome the item exposure drawback of such systems. The paper also presents our CAT system along its development steps. Besides, an item difficulty estimation technique is presented based on data taken from our self-assessment system.


Communication model of emuStudio emulation platform

Abstract: Within the paper a description of communication model of plug-in based emuStudio emulation platform is given. The platform mentioned above allows the emulation of whole computer systems, configurable to the level of its components, represented by the plug-in modules of the platform. Development tasks still are in progress at the home institution of the authors. Currently the platform is exploited for teaching purposes within subjects aimed at machine-oriented languages and computer architectures. Versatility of the platform, given by its plug-in based architecture is a big advantage, when used as a teaching support tool. The paper briefly describes the emuStudio platform at its introductory part and then the mechanisms of inter-module communication are described.


Modelling dynamic programming problems by generalized d-graphs

Abstract: In this paper we introduce the concept of generalized d-graph (admitting cycles) as special dependency-graphs for modelling dynamic programming (DP) problems. We describe the d-graph versions of three famous single-source shortest algorithms (The algorithm based on the topological order of the vertices, Dijkstra algorithm and Bellman-Ford algorithm), which can be viewed as general DP strategies in the case of three different class of optimization problems. The new modelling method also makes possible to classify DP problems and the corresponding DP strategies in term of graph theory.


Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence

Abstract: Gesture recognition is mainly apprehensive on analyzing the functionality of human wits. The main goal of gesture recognition is to create a system which can recognize specific human gestures and use them to convey information or for device control. Hand gestures provide a separate complementary modality to speech for expressing ones ideas. Information associated with hand gestures in a conversation is degree,discourse structure, spatial and temporal structure. The approaches present can be mainly divided into Data-Glove Based and Vision Based approaches. An important face feature point is the nose tip. Since nose is the highest protruding point from the face. Besides that, it is not affected by facial expressions.Another important function of the nose is that it is able to indicate the head pose. Knowledge of the nose location will enable us to align an unknown 3D face with those in a face database. Eye detection is divided into eye position detection and eye contour detection. Existing works in eye detection can be classified into two major categories: traditional image-based passive approaches and the active IR based approaches. The former uses intensity and shape of eyes for detection and the latter works on the assumption that eyes have a reflection under near IR illumination and produce bright/dark pupil effect. The traditional methods can be broadly classified into three categories: template based methods,appearance based methods and feature based methods. The purpose of this paper is to compare various human Gesture recognition systems for interfacing machines directly to human wits without any corporeal media in an ambient environment.


Channel Estimation And Multiuser Detection In Asynchronous Satellite Communications

Abstract: In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.


A Joint Initiative to Support the Semantic Interoperability within the GIIDA Project

Abstract: The GIIDA project aims to develop a digital infrastructure for the spatial information within CNR. It is foreseen to use semantic-oriented technologies to ease information modeling and connecting, according to international standards like the ISO/IEC 11179. Complex information management systems, like GIIDA, will take benefit from the use of terminological tools like thesauri that make available a reference lexicon for the indexing and retrieval of information. Within GIIDA the goal is to make available the EARTh thesaurus (Environmental Applications Reference Thesaurus), developed by the CNR-IIA-EKOLab. A web-based software, developed by the CNR-Water Research Institute (IRSA) was implemented to allow consultation and utilization of thesaurus through the web. This service is a useful tool to ensure interoperability between thesaurus and other systems of the indexing, with, the idea of cooperating to develop a comprehensive system of knowledge organization, that could be defined integrated, open, multi-functional and multilingual. Currently the system is available in multiple languages mode (Italian - English) and navigation can be done in the following ways: Alphabetical, Hierarchical and for Themes. A full search allows to find any term by searching for the whole term or a part of it and as well as allows to filter the results by themes. Within a collaborative initiative with the CNR-Institute of Applied Mathematics and Information Technology (IMATI) a SKOS (Simple Knowledge Organization System) version of EARTh was developed. This will ensure the possibility to support the use of the thesaurus within the framework of the Semantic Web in order to be used in decentralized metadata applications


From Social Data Mining to Forecasting Socio-Economic Crisis

Abstract: Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.


An Effective Method of Image Retrieval using Image Mining Techniques

Abstract: The present research scholars are having keen interest in doing their research activities in the area of Data mining all over the world. Especially, [13]Mining Image data is the one of the essential features in this present scenario since image data plays vital role in every aspect of the system such as business for marketing, hospital for surgery, engineering for construction, Web for publication and so on. The other area in the Image mining system is the Content-Based Image Retrieval (CBIR) which performs retrieval based on the similarity defined in terms of extracted features with more objectiveness. The drawback in CBIR is the features of the query image alone are considered. Hence, a new technique called Image retrieval based on optimum clusters is proposed for improving user interaction with image retrieval systems by fully exploiting the similarity information. The index is created by describing the images according to their color characteristics, with compact feature vectors, that represent typical color distributions [12].


Improved Algorithms for the Point-Set Embeddability problem for Plane 3-Trees

Abstract: In the point set embeddability problem, we are given a plane graph $G$ with $n$ vertices and a point set $S$ with $n$ points. Now the goal is to answer the question whether there exists a straight-line drawing of $G$ such that each vertex is represented as a distinct point of $S$ as well as to provide an embedding if one does exist. Recently, in \cite{DBLP:conf/gd/NishatMR10}, a complete characterization for this problem on a special class of graphs known as the plane 3-trees was presented along with an efficient algorithm to solve the problem. In this paper, we use the same characterization to devise an improved algorithm for the same problem. Much of the efficiency we achieve comes from clever uses of the triangular range search technique. We also study a generalized version of the problem and present improved algorithms for this version of the problem as well.


Kolmogorov-Loveland Sets and Advice Complexity Classes

Abstract: Loveland complexity is a variant of Kolmogorov complexity, where it is asked to output separately the bits of the desired string, instead of the string itself. Similarly to the resource-bounded Kolmogorov sets we define Loveland sets. We highlight a structural connection between resource-bounded Loveland sets and some advice complexity classes. This structural connection enables us to map to advice complexity classes some properties of Kolmogorov sets first noticed by Hartmanis and thoroughly investigated in Longpr\'e's thesis: 1. Non-inclusion properties of Loveland sets result in hierarchy properties on the corresponding advice complexity classes; 2. Immunity properties of Loveland sets result in the non-existence of natural proofs between the corresponding advice complexity classes, in the sense of Razborov & Rudich.


An Algorithm for the Graph Crossing Number Problem

Abstract: We study the Minimum Crossing Number problem: given an $n$-vertex graph $G$, the goal is to find a drawing of $G$ in the plane with minimum number of edge crossings. This is one of the central problems in topological graph theory, that has been studied extensively over the past three decades. The first non-trivial efficient algorithm for the problem, due to Leighton and Rao, achieved an $O(n\log^4n)$-approximation for bounded degree graphs. This algorithm has since been improved by poly-logarithmic factors, with the best current approximation ratio standing on $O(n \poly(d) \log^{3/2}n)$ for graphs with maximum degree $d$. In contrast, only APX-hardness is known on the negative side. In this paper we present an efficient randomized algorithm to find a drawing of any $n$-vertex graph $G$ in the plane with $O(OPT^{10}\cdot \poly(d \log n))$ crossings, where $OPT$ is the number of crossings in the optimal solution, and $d$ is the maximum vertex degree in $G$. This result implies an $\tilde{O}(n^{9/10} \poly(d))$-approximation for Minimum Crossing Number, thus breaking the long-standing $\tilde{O}(n)$-approximation barrier for bounded-degree graphs.


Weighted Random Sampling over Data Streams

Abstract: In this work, we present a comprehensive treatment of weighted random sampling (WRS) over data streams. More precisely, we examine two natural interpretations of the item weights, describe an existing algorithm for each case ([2, 4]), discuss sampling with and without replacement and show adaptations of the algorithms for several WRS problems and evolving data streams.


(\alpha, \beta) Fibonacci Search

Abstract: Knuth [12, Page 417] states that "the (program of the) Fibonaccian search technique looks very mysterious at first glance" and that "it seems to work by magic". In this work, we show that there is even more magic in Fibonaccian (or else Fibonacci) search. We present a generalized Fibonacci procedure that follows perfectly the implicit optimal decision tree for search problems where the cost of each comparison depends on its outcome.


String Matching with Inversions and Translocations in Linear Average Time (Most of the Time)

Abstract: We present an efficient algorithm for finding all approximate occurrences of a given pattern $p$ of length $m$ in a text $t$ of length $n$ allowing for translocations of equal length adjacent factors and inversions of factors. The algorithm is based on an efficient filtering method and has an $\bigO(nm\max(\alpha, \beta))$-time complexity in the worst case and $\bigO(\max(\alpha, \beta))$-space complexity, where $\alpha$ and $\beta$ are respectively the maximum length of the factors involved in any translocation and inversion. Moreover we show that under the assumptions of equiprobability and independence of characters our algorithm has a $\bigO(n)$ average time complexity, whenever $\sigma = \Omega(\log m / \log\log^{1-\epsilon} m)$, where $\epsilon > 0$ and $\sigma$ is the dimension of the alphabet. Experiments show that the new proposed algorithm achieves very good results in practical cases.


A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems

Abstract: Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) models assists experts to interpret causal relations and find factors of the uncertainty. Bayesian averaging also allows experts to estimate the uncertainty accurately when a priori information on the favored structure of DTs is available. Then an expert can select a single DT model, typically the Maximum a Posteriori model, for interpretation purposes. Unfortunately, a priori information on favored structure of DTs is not always available. For this reason, we suggest a new prior on DTs for the Bayesian MCMC technique. We also suggest a new procedure of selecting a single DT and describe an application scenario. In our experiments on the Short-Term Conflict Alert data our technique outperforms the existing Bayesian techniques in predictive accuracy of the selected single DTs.


Towards a Spiking Neural P Systems OS

Abstract: This paper is an attempt to incorporate the idea of spiking neural P systems as an early seed into the area of Operating System Design, regarding their capability to solve some classical computer science problems. It is reflecting the power of such systems to simulate well known parallel computational models, like logic gates, arithmetic operation, and sorting. In these devices, the time (when the neurons fire and/or spike) plays an essential role. For instance, the result of a computation is the time between the moments when a specified neuron spikes. Seen as number computing devices, SN P systems are shown to be computationally complete, and with such capabilities, arithmetic operations, logic, and timing, some first steps could be taken towards an OS design.


Faster Query Answering in Probabilistic Databases using Read-Once Functions

Abstract: A boolean expression is in read-once form if each of its variables appears exactly once. When the variables denote independent events in a probability space, the probability of the event denoted by the whole expression in read-once form can be computed in polynomial time (whereas the general problem for arbitrary expressions is #P-complete). Known approaches to checking read-once property seem to require putting these expressions in disjunctive normal form. In this paper, we tell a better story for a large subclass of boolean event expressions: those that are generated by conjunctive queries without self-joins and on tuple-independent probabilistic databases. We first show that given a tuple-independent representation and the provenance graph of an SPJ query plan without self-joins, we can, without using the DNF of a result event expression, efficiently compute its co-occurrence graph. From this, the read-once form can already, if it exists, be computed efficiently using existing techniques. Our second and key contribution is a complete, efficient, and simple to implement algorithm for computing the read-once forms (whenever they exist) directly, using a new concept, that of co-table graph, which can be significantly smaller than the co-occurrence graph.


Fractional counting of citations in research evaluation: An option for cross- and interdisciplinary assessments

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


Some Important Aspects of Source Location Protection in Globally Attacked Sensor Networks

Abstract: In the problem of location anonymity of the events exposed to a global eavesdropper, we highlight and analyze some aspects that are missing in the prior work, which is especially relevant for the quality of secure sensing in delay-intolerant applications monitoring rare and spatially sparse events, and deployed as large wireless sensor networks with single data collector. We propose an efficient scheme for generating fake network traffic to disguise the real event notification. The efficiency of the scheme that provides statistical source location anonymity is achieved by partitioning network nodes randomly into several dummy source groups. Members of the same group collectively emulate both temporal and spatial distribution of the event. Under such dummy-traffic framework of the source anonymity protection, we aim to better model the global eavesdropper, especially her way of using statistical tests to detect the real event, and to present the quality of the location protection as relative to the adversary's strength. In addition, our approach aims to reduce the per-event work spent to generate the fake traffic while, most importantly, providing a guaranteed latency in reporting the event. The latency is controlled by decoupling the routing from the fake-traffic schedule. A good dummy source group design also provides a robust protection of event bursts. This is achieved at the expense of the significant overhead as the number of dummy source groups must be increased to the reciprocal value of the false alarm parameter used in the statistical test. We believe that the proposed source anonymity protection strategy, and the evaluation framework, are well justified by the abundance of the applications that monitor a rare event with known temporal statistics, and uniform spatial distribution.


A proposed Optimized Spline Interpolation

Abstract: The goal of this paper is to design compact support basis spline functions that best approximate a given filter (e.g., an ideal Lowpass filter). The optimum function is found by minimizing the least square problem ($\ell$2 norm of the difference between the desired and the approximated filters) by means of the calculus of variation; more precisely, the introduced splines give optimal filtering properties with respect to their time support interval. Both mathematical analysis and simulation results confirm the superiority of these splines.


MT4j - A Cross-platform Multi-touch Development Framework

Abstract: This article describes requirements and challenges of crossplatform multi-touch software engineering, and presents the open source framework Multi-Touch for Java (MT4j) as a solution. MT4j is designed for rapid development of graphically rich applications on a variety of contemporary hardware, from common PCs and notebooks to large-scale ambient displays, as well as different operating systems. The framework has a special focus on making multi-touch software development easier and more efficient. Architecture and abstractions used by MT4j are described, and implementations of several common use cases are presented.


Estimating Probabilities in Recommendation Systems

Abstract: Recommendation systems are emerging as an important business application with significant economic impact. Currently popular systems include Amazon's book recommendations, Netflix's movie recommendations, and Pandora's music recommendations. In this paper we address the problem of estimating probabilities associated with recommendation system data using non-parametric kernel smoothing. In our estimation we interpret missing items as randomly censored observations and obtain efficient computation schemes using combinatorial properties of generating functions. We demonstrate our approach with several case studies involving real world movie recommendation data. The results are comparable with state-of-the-art techniques while also providing probabilistic preference estimates outside the scope of traditional recommender systems.


Design of QoS-aware Provisioning Systems

Abstract: We present an architecture of a hosting system consisting of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run users demand. The traffic is session-based, while provider and users agree on SLAs specifying the expected level of service performance such that the service provider is liable to compensate his/her customers if the level of performance is not satisfactory. The system is driven by a utility function which tries to optimize the average earned revenue per unit time. The middleware collects demand and performance statistics, and estimates traffic parameters in order to make dynamic decisions concerning server allocation and admission control. We empirically evaluate the effects of admission policies, resource allocation and service differentiation schemes on the achieved revenues, and we find that our system is robust enough to successfully deal with session-based traffic under different conditions.


A Center Transversal Theorem for Hyperplanes and Applications to Graph Drawing

Abstract: Motivated by an open problem from graph drawing, we study several partitioning problems for line and hyperplane arrangements. We prove a ham-sandwich cut theorem: given two sets of n lines in R^2, there is a line l such that in both line sets, for both halfplanes delimited by l, there are n^{1/2} lines which pairwise intersect in that halfplane, and this bound is tight; a centerpoint theorem: for any set of n lines there is a point such that for any halfplane containing that point there are (n/3)^{1/2} of the lines which pairwise intersect in that halfplane. We generalize those results in higher dimension and obtain a center transversal theorem, a same-type lemma, and a positive portion Erdos-Szekeres theorem for hyperplane arrangements. This is done by formulating a generalization of the center transversal theorem which applies to set functions that are much more general than measures. Back to Graph Drawing (and in the plane), we completely solve the open problem that motivated our search: there is no set of n labelled lines that are universal for all n-vertex labelled planar graphs. As a side note, we prove that every set of n (unlabelled) lines is universal for all n-vertex (unlabelled) planar graphs.


A Note on Nonuniform versus Uniform ACC^k Circuits for NE

Abstract: We note that for each k \in {0,1,2, ...} the following holds: NE has (nonuniform) ACC^k circuits if and only if NE has P^{NE}-uniform ACC^k circuits. And we mention how to get analogous results for other circuit and complexity classes.


Counting Plane Graphs: Flippability and its Applications

Abstract: We generalize the notions of flippable and simultaneously flippable edges in a triangulation of a set S of points in the plane to so-called \emph{pseudo-simultaneously flippable edges}. Such edges are related to the notion of convex decompositions spanned by S. We prove a worst-case tight lower bound for the number of pseudo-simultaneously flippable edges in a triangulation in terms of the number of vertices. We use this bound for deriving new upper bounds for the maximal number of crossing-free straight-edge graphs that can be embedded on any fixed set of N points in the plane. We obtain new upper bounds for the number of spanning trees and forests as well. Specifically, let tr(N) denote the maximum number of triangulations on a set of N points in the plane. Then we show (using the known bound tr(N) < 30^N) that any N-element point set admits at most 6.9283^N * tr(N) < 207.85^N crossing-free straight-edge graphs, O(4.7022^N) * tr(N) = O(141.07^N) spanning trees, and O(5.3514^N) * tr(N) = O(160.55^N) forests. We also obtain upper bounds for the number of crossing-free straight-edge graphs that have cN, fewer than cN, or more than cN edges, for any constant parameter c, in terms of c and N.


Novel Mechanism to Defend DDoS Attacks Caused by Spam

Abstract: Corporate mail services are designed to perform better than public mail services. Fast mail delivery, large size file transfer as an attachments, high level spam and virus protection, commercial advertisement free environment are some of the advantages worth to mention. But these mail services are frequent target of hackers and spammers. Distributed Denial of service attacks are becoming more common and sophisticated. The researchers have proposed various solutions to the DDOS attacks. Can we stop these kinds of attacks with available technology? These days the DDoS attack through spam has increased and disturbed the mail services of various organizations. Spam penetrates through all the filters to establish DDoS attacks, which causes serious problems to users and the data. In this paper we propose a novel approach to defend DDoS attack caused by spam mails. This approach is a combination of fine tuning of source filters, content filters, strictly implementing mail policies,educating user, network monitoring and logical solutions to the ongoing attack. We have conducted several experiments in corporate mail services; the results show that this approach is highly effective to prevent DDoS attack caused by spam. The novel defense mechanism reduced 60% of the incoming spam traffic and repelled many DDoS attacks caused by spam.


Quickest Path Queries on Transportation Network

Abstract: This paper considers the problem of finding a quickest path between two points in the Euclidean plane in the presence of a transportation network. A transportation network consists of a planar network where each road (edge) has an individual speed. A traveller may enter and exit the network at any point on the roads. Along any road the traveller moves with a fixed speed depending on the road, and outside the network the traveller moves at unit speed in any direction. We give an exact algorithm for the basic version of the problem: given a transportation network of total complexity n in the Euclidean plane, a source point s and a destination point t, and the quickest path between s and t. We also show how the transportation network can be preprocessed in time O(n^2 log n) into a data structure of size O(n^2) such that (1 + \epsilon)-approximate cheapest path cost queries between any two points in the plane can be answered in time O(1\epsilon^4 log n).


An Effective Clustering Approach to Web Query Log Anonymization

Abstract: Web query log data contain information useful to research; however, release of such data can re-identify the search engine users issuing the queries. These privacy concerns go far beyond removing explicitly identifying information such as name and address, since non-identifying personal data can be combined with publicly available information to pinpoint to an individual. In this work we model web query logs as unstructured transaction data and present a novel transaction anonymization technique based on clustering and generalization techniques to achieve the k-anonymity privacy. We conduct extensive experiments on the AOL query log data. Our results show that this method results in a higher data utility compared to the state of-the-art transaction anonymization methods.


Agnostic Learning of Monomials by Halfspaces is Hard

Abstract: We prove the following strong hardness result for learning: Given a distribution of labeled examples from the hypercube such that there exists a monomial consistent with $(1-\eps)$ of the examples, it is NP-hard to find a halfspace that is correct on $(1/2+\eps)$ of the examples, for arbitrary constants $\eps > 0$. In learning theory terms, weak agnostic learning of monomials is hard, even if one is allowed to output a hypothesis from the much bigger concept class of halfspaces. This hardness result subsumes a long line of previous results, including two recent hardness results for the proper learning of monomials and halfspaces. As an immediate corollary of our result we show that weak agnostic learning of decision lists is NP-hard. Our techniques are quite different from previous hardness proofs for learning. We define distributions on positive and negative examples for monomials whose first few moments match. We use the invariance principle to argue that regular halfspaces (all of whose coefficients have small absolute value relative to the total $\ell_2$ norm) cannot distinguish between distributions whose first few moments match. For highly non-regular subspaces, we use a structural lemma from recent work on fooling halfspaces to argue that they are ``junta-like'' and one can zero out all but the top few coefficients without affecting the performance of the halfspace. The top few coefficients form the natural list decoding of a halfspace in the context of dictatorship tests/Label Cover reductions. We note that unlike previous invariance principle based proofs which are only known to give Unique-Games hardness, we are able to reduce from a version of Label Cover problem that is known to be NP-hard. This has inspired follow-up work on bypassing the Unique Games conjecture in some optimal geometric inapproximability results.


Terminating Tableaux for Graded Hybrid Logic with Global Modalities and Role Hierarchies

Abstract: We present a terminating tableau calculus for graded hybrid logic with global modalities, reflexivity, transitivity and role hierarchies. Termination of the system is achieved through pattern-based blocking. Previous approaches to related logics all rely on chain-based blocking. Besides being conceptually simple and suitable for efficient implementation, the pattern-based approach gives us a NExpTime complexity bound for the decision procedure.


Handling Confidential Data on the Untrusted Cloud: An Agent-based Approach

Abstract: Cloud computing allows shared computer and storage facilities to be used by a multitude of clients. While cloud management is centralized, the information resides in the cloud and information sharing can be implemented via off-the-shelf techniques for multiuser databases. Users, however, are very diffident for not having full control over their sensitive data. Untrusted database-as-a-server techniques are neither readily extendable to the cloud environment nor easily understandable by non-technical users. To solve this problem, we present an approach where agents share reserved data in a secure manner by the use of simple grant-and-revoke permissions on shared data.


Interactive proofs with competing teams of no-signaling provers

Abstract: This paper studies a generalization of multi-prover interactive proofs in which a verifier interacts with two competing teams of provers: one team attempts to convince the verifier to accept while the other attempts to convince the verifier to reject. Each team consists of two provers who jointly implement a no-signaling strategy. No-signaling strategies are a curious class of joint strategy that cannot in general be implemented without communication between the provers, yet cannot be used as a black box to establish communication between them. Attention is restricted in this paper to two-turn interactions in which the verifier asks questions of each of the four provers and decides whether to accept or reject based on their responses. We prove that the complexity class of decision problems that admit two-turn interactive proofs with competing teams of no-signaling provers is a subset of PSPACE. This upper bound matches existing PSPACE lower bounds on the following two disparate and weaker classes of interactive proof: 1. Two-turn multi-prover interactive proofs with only one team of no-signaling provers. 2. Two-turn competing-prover interactive proofs with only one prover per team. Our result implies that the complexity of these two models is unchanged by the addition of a second competing team of no-signaling provers in the first case and by the addition of a second no-signaling prover to each team in the second case. Moreover, our result unifies and subsumes prior PSPACE upper bounds on these classes.


Using ASP with recent extensions for causal explanations

Abstract: We examine the practicality for a user of using Answer Set Programming (ASP) for representing logical formalisms. We choose as an example a formalism aiming at capturing causal explanations from causal information. We provide an implementation, showing the naturalness and relative efficiency of this translation job. We are interested in the ease for writing an ASP program, in accordance with the claimed ``declarative'' aspect of ASP. Limitations of the earlier systems (poor data structure and difficulty in reusing pieces of programs) made that in practice, the ``declarative aspect'' was more theoretical than practical. We show how recent improvements in working ASP systems facilitate a lot the translation, even if a few improvements could still be useful.


Automated Query Learning with Wikipedia and Genetic Programming

Abstract: Most of the existing information retrieval systems are based on bag of words model and are not equipped with common world knowledge. Work has been done towards improving the efficiency of such systems by using intelligent algorithms to generate search queries, however, not much research has been done in the direction of incorporating human-and-society level knowledge in the queries. This paper is one of the first attempts where such information is incorporated into the search queries using Wikipedia semantics. The paper presents an essential shift from conventional token based queries to concept based queries, leading to an enhanced efficiency of information retrieval systems. To efficiently handle the automated query learning problem, we propose Wikipedia-based Evolutionary Semantics (Wiki-ES) framework where concept based queries are learnt using a co-evolving evolutionary procedure. Learning concept based queries using an intelligent evolutionary procedure yields significant improvement in performance which is shown through an extensive study using Reuters newswire documents. Comparison of the proposed framework is performed with other information retrieval systems. Concept based approach has also been implemented on other information retrieval systems to justify the effectiveness of a transition from token based queries to concept based queries.


Semantic Content Filtering with Wikipedia and Ontologies

Abstract: The use of domain knowledge is generally found to improve query efficiency in content filtering applications. In particular, tangible benefits have been achieved when using knowledge-based approaches within more specialized fields, such as medical free texts or legal documents. However, the problem is that sources of domain knowledge are time-consuming to build and equally costly to maintain. As a potential remedy, recent studies on Wikipedia suggest that this large body of socially constructed knowledge can be effectively harnessed to provide not only facts but also accurate information about semantic concept-similarities. This paper describes a framework for document filtering, where Wikipedia's concept-relatedness information is combined with a domain ontology to produce semantic content classifiers. The approach is evaluated using Reuters RCV1 corpus and TREC-11 filtering task definitions. In a comparative study, the approach shows robust performance and appears to outperform content classifiers based on Support Vector Machines (SVM) and C4.5 algorithm.


Power and Delay Aware On-Demand Routing For Ad Hoc Networks

Abstract: Wide implementation of IEEE 802.11 based networks could lead to deployment of localized wireless data communication environments with a limited number of mobile hosts, called ad hoc networks. Implementation of a proper routing methodology in ad hoc networks makes it efficient in terms of performance. A wide spectrum of routing protocols has been contributed by several researchers. Real time applications have been most popular among the applications, run by ad hoc networks. Such applications strictly adhere to the Quality of Service (QoS) requirements such as overall throughput, end-toend delay and power level. Support of QoS requirements becomes more challenging due to dynamic nature of MANETs, where mobility of nodes results in frequent change in topology. QoS aware routing protocols can serve to the QoS support, which concentrate on determining a path between source and destination with the QoS requirements of the flow being satisfied. We propose a protocol, called Power and Delay aware Temporally Ordered Routing Algorithm (PDTORA), based on Temporally Ordered Routing Algorithm (TORA) Protocol, where verification of power and delay requirements is carried out with a query packet at each node along the path between source and destination. Simulations justify better performance of the proposed new protocol in terms of network lifetime, end-to-end delay and packet delivery ratio as compared to TORA.


Efficient Optimization of Performance Measures by Classifier Adaptation

Abstract: In practical applications, machine learning algorithms are often needed to learn classifiers that optimize domain specific performance measures. Previously, the research has focused on learning the needed classifier in isolation, yet learning nonlinear classifier for nonlinear and nonsmooth performance measures is still hard. In this paper, rather than learning the needed classifier by optimizing specific performance measure directly, we circumvent this problem by proposing a novel two-step approach called as CAPO, namely to first train nonlinear auxiliary classifiers with existing learning methods, and then to adapt auxiliary classifiers for specific performance measures. In the first step, auxiliary classifiers can be obtained efficiently by taking off-the-shelf learning algorithms. For the second step, we show that the classifier adaptation problem can be reduced to a quadratic program problem, which is similar to linear SVMperf and can be efficiently solved. By exploiting nonlinear auxiliary classifiers, CAPO can generate nonlinear classifier which optimizes a large variety of performance measures including all the performance measure based on the contingency table and AUC, whilst keeping high computational efficiency. Empirical studies show that CAPO is effective and of high computational efficiency, and even it is more efficient than linear SVMperf.


Faster Black-Box Algorithms Through Higher Arity Operators

Abstract: We extend the work of Lehre and Witt (GECCO 2010) on the unbiased black-box model by considering higher arity variation operators. In particular, we show that already for binary operators the black-box complexity of \leadingones drops from $\Theta(n^2)$ for unary operators to $O(n \log n)$. For \onemax, the $\Omega(n \log n)$ unary black-box complexity drops to O(n) in the binary case. For $k$-ary operators, $k \leq n$, the \onemax-complexity further decreases to $O(n/\log k)$.


A tight bound on the worst-case number of comparisons for Floyd's heap construction algorithm

Abstract: In this paper a tight bound on the worst-case number of comparisons for Floyd's well known heap construction algorithm, is derived. It is shown that at most 2n-2{\mu}(n)-{\sigma}(n) comparisons are executed in the worst case, where {\mu}(n) is the number of ones and {\sigma}(n) is the number of zeros after the last one in the binary representation of the number of keys n.


Hash function based on arithmetic coding and public-key cryptography

Abstract: We propose a hash function based on arithmetic coding and public-key cryptography. The resistance of the hash function to second preimage attack, collision and differential cryptanalysis is based on the properties of arithmetic coding as a non-linear dynamical system. The resistance of the hash function to first preimage attack is based on the public-key cryptography. The new hash function uses the strength of HMAC with the difference that it didn't need a secret key for calculating the hash (in this step, it uses one, two or three public -keys) and in the classical attack, an adversary need to break the public key algorithm or to have all the secret keys to perform his attack.


Binary Inference for Primary User Separation in Cognitive Radio Networks

Abstract: Spectrum sensing receives much attention recently in the cognitive radio (CR) network research, i.e., secondary users (SUs) constantly monitor channel condition to detect the presence of the primary users (PUs). In this paper, we go beyond spectrum sensing and introduce the PU separation problem, which concerns with the issues of distinguishing and characterizing PUs in the context of collaborative spectrum sensing and monitor selection. The observations of monitors are modeled as boolean OR mixtures of underlying binary sources for PUs. We first justify the use of the binary OR mixture model as opposed to the traditional linear mixture model through simulation studies. Then we devise a novel binary inference algorithm for PU separation. Not only PU-SU relationship are revealed, but PUs' transmission statistics and activities at each time slot can also be inferred. Simulation results show that without any prior knowledge regarding PUs' activities, the algorithm achieves high inference accuracy even in the presence of noisy measurements.


Yet another aperiodic tile set

Abstract: We present here an elementary construction of an aperiodic tile set. Although there already exist dozens of examples of aperiodic tile sets we believe this construction introduces an approach that is different enough to be interesting and that the whole construction and the proof of aperiodicity are hopefully simpler than most existing techniques.


Weighted random generation of context-free languages: Analysis of collisions in random urn occupancy models

Abstract: The present work analyzes the redundancy of sets of combinatorial objects produced by a weighted random generation algorithm proposed by Denise et al. This scheme associates weights to the terminals symbols of a weighted context-free grammar, extends this weight definition multiplicatively on words, and draws words of length $n$ with probability proportional their weight. We investigate the level of redundancy within a sample of $k$ word, the proportion of the total probability covered by $k$ words (coverage), the time (number of generations) of the first collision, and the time of the full collection. For these four questions, we use an analytic urn analogy to derive asymptotic estimates and/or polynomially computable exact forms. We illustrate these tools by an analysis of an RNA secondary structure statistical sampling algorithm introduced by Ding et al.


A Log Auditing Approach for Trust Management in Peer-to-Peer Collaboration

Abstract: Nowadays we are faced with an increasing popularity of social software including wikis, blogs, micro-blogs and online social networks such as Facebook and MySpace. Unfortunately, the mostly used social services are centralized and personal information is stored at a single vendor. This results in potential privacy problems as users do not have much control over how their private data is disseminated. To overcome this limitation, some recent approaches envisioned replacing the single authority centralization of services by a peer-to-peer trust-based approach where users can decide with whom they want to share their private data. In this peer-to-peer collaboration it is very difficult to ensure that after data is shared with other peers, these peers will not misbehave and violate data privacy. In this paper we propose a mechanism that addresses the issue of data privacy violation due to data disclosure to malicious peers. In our approach trust values between users are adjusted according to their previous activities on the shared data. Users share their private data by specifying some obligations the receivers must follow. We log modifications done by users on the shared data as well as the obligations that must be followed when data is shared. By a log-auditing mechanism we detect users that misbehaved and we adjust their associated trust values by using any existing decentralized trust model.


Mobiles ortsbezogenes Projektmanagement

Abstract: Classic project management and its tools usually deal with the management of three variables, and their relationships with each other. These are the factors of time, resources (cost) and quality. If one of the variables is to be improved, it always has negative effects on the other two. However, these factors only partially describe the reality of project management. What current project management tools often only consider implicitly is the location of an activity. In this paper, the implications of using location data for project management are clarified and a system that offers mobile support in planning and implementing projects. ----- Klassisches Projektmanagement und seine Werkzeuge befassen sich meist mit der Verwaltung dreier Gr\"o{\ss}en und ihrer Zusammenh\"ange untereinander. Dabei handelt es sich um die Faktoren Zeit, Ressourcen (Kosten) und Qualit\"at. Falls eine der Gr\"o{\ss}en verbessert werden soll, hat dies immer negative Auswirkungen auf die anderen beiden Gr\"o{\ss}en. Diese Gr\"o{\ss}en beschreiben die Ph\"anomene des Projektmanagement jedoch nur unvollst\"andig. Was bei Projektmanagementwerkzeugen bis dato oft nur implizit durch den Projektleiter einbezogen wird ist ein Ortsbezug. In diesem Beitrag werden die Implikationen durch diesen Ortsbezug konkretisiert und ein System dargestellt, welches Projektleiter bei der Planung und Umsetzung von Projekten mobil wie auch station\"ar unterst\"utzt.


Lower Bounds for the Smoothed Number of Pareto optimal Solutions

Abstract: In 2009, Roeglin and Teng showed that the smoothed number of Pareto optimal solutions of linear multi-criteria optimization problems is polynomially bounded in the number $n$ of variables and the maximum density $\phi$ of the semi-random input model for any fixed number of objective functions. Their bound is, however, not very practical because the exponents grow exponentially in the number $d+1$ of objective functions. In a recent breakthrough, Moitra and O'Donnell improved this bound significantly to $O(n^{2d} \phi^{d(d+1)/2})$. An "intriguing problem", which Moitra and O'Donnell formulate in their paper, is how much further this bound can be improved. The previous lower bounds do not exclude the possibility of a polynomial upper bound whose degree does not depend on $d$. In this paper we resolve this question by constructing a class of instances with $\Omega ((n \phi)^{(d-\log{d}) \cdot (1-\Theta{1/\phi})})$ Pareto optimal solutions in expectation. For the bi-criteria case we present a higher lower bound of $\Omega (n^2 \phi^{1 - \Theta{1/\phi}})$, which almost matches the known upper bound of $O(n^2 \phi)$.


Functional Interpretations of Intuitionistic Linear Logic

Abstract: We present three different functional interpretations of intuitionistic linear logic ILL and show how these correspond to well-known functional interpretations of intuitionistic logic IL via embeddings of IL into ILL. The main difference from previous work of the second author is that in intuitionistic linear logic (as opposed to classical linear logic) the interpretations of !A are simpler and simultaneous quantifiers are no longer needed for the characterisation of the interpretations. We then compare our approach in developing these three proof interpretations with the one of de Paiva around the Dialectica category model of linear logic.


Image Deblurring and Super-resolution by Adaptive Sparse Domain Selection and Adaptive Regularization

Abstract: As a powerful statistical image modeling technique, sparse representation has been successfully used in various image restoration applications. The success of sparse representation owes to the development of l1-norm optimization techniques, and the fact that natural images are intrinsically sparse in some domain. The image restoration quality largely depends on whether the employed sparse domain can represent well the underlying image. Considering that the contents can vary significantly across different images or different patches in a single image, we propose to learn various sets of bases from a pre-collected dataset of example image patches, and then for a given patch to be processed, one set of bases are adaptively selected to characterize the local sparse domain. We further introduce two adaptive regularization terms into the sparse representation framework. First, a set of autoregressive (AR) models are learned from the dataset of example image patches. The best fitted AR models to a given patch are adaptively selected to regularize the image local structures. Second, the image non-local self-similarity is introduced as another regularization term. In addition, the sparsity regularization parameter is adaptively estimated for better image restoration performance. Extensive experiments on image deblurring and super-resolution validate that by using adaptive sparse domain selection and adaptive regularization, the proposed method achieves much better results than many state-of-the-art algorithms in terms of both PSNR and visual perception.


Automatic Image Segmentation by Dynamic Region Merging

Abstract: This paper addresses the automatic image segmentation problem in a region merging style. With an initially over-segmented image, in which the many regions (or super-pixels) with homogeneous color are detected, image segmentation is performed by iteratively merging the regions according to a statistical test. There are two essential issues in a region merging algorithm: order of merging and the stopping criterion. In the proposed algorithm, these two issues are solved by a novel predicate, which is defined by the sequential probability ratio test (SPRT) and the maximum likelihood criterion. Starting from an over-segmented image, neighboring regions are progressively merged if there is an evidence for merging according to this predicate. We show that the merging order follows the principle of dynamic programming. This formulates image segmentation as an inference problem, where the final segmentation is established based on the observed image. We also prove that the produced segmentation satisfies certain global properties. In addition, a faster algorithm is developed to accelerate the region merging process, which maintains a nearest neighbor graph in each iteration. Experiments on real natural images are conducted to demonstrate the performance of the proposed dynamic region merging algorithm.


Tight lower bounds for the size of epsilon-nets

Abstract: According to a well known theorem of Haussler and Welzl (1987), any range space of bounded VC-dimension admits an $\eps$-net of size $O\left(\frac{1}{\eps}\log\frac1{\eps}\right)$. Using probabilistic techniques, Pach and Woeginger (1990) showed that there exist range spaces of VC-dimension 2, for which the above bound can be attained. The only known range spaces of small VC-dimension, in which the ranges are geometric objects in some Euclidean space and the size of the smallest $\eps$-nets is superlinear in $\frac1{\eps}$, were found by Alon (2010). In his examples, the size of the smallest $\eps$-nets is $\Omega\left(\frac{1}{\eps}g(\frac{1}{\eps})\right)$, where $g$ is an extremely slowly growing function, closely related to the inverse Ackermann function. \smallskip We show that there exist geometrically defined range spaces, already of VC-dimension $2$, in which the size of the smallest $\eps$-nets is $\Omega\left(\frac{1}{\eps}\log\frac{1}{\eps}\right)$. We also construct range spaces induced by axis-parallel rectangles in the plane, in which the size of the smallest $\eps$-nets is $\Omega\left(\frac{1}{\eps}\log\log\frac{1}{\eps}\right)$. By a theorem of Aronov, Ezra, and Sharir (2010), this bound is tight.


URSA: A System for Uniform Reduction to SAT

Abstract: There are a huge number of problems, from various areas, being solved by reducing them to SAT. However, for many applications, translation into SAT is performed by specialized, problem-specific tools. In this paper we describe a new system for uniform solving of a wide class of problems by reducing them to SAT. The system uses a new specification language URSA that combines imperative and declarative programming paradigms. The reduction to SAT is defined precisely by the semantics of the specification language. The domain of the approach is wide (e.g., many NP-complete problems can be simply specified and then solved by the system) and there are problems easily solvable by the proposed system, while they can be hardly solved by using other programming languages or constraint programming systems. So, the system can be seen not only as a tool for solving problems by reducing them to SAT, but also as a general-purpose constraint solving system (for finite domains). In this paper, we also describe an open-source implementation of the described approach. The performed experiments suggest that the system is competitive to state-of-the-art related modelling systems.


Decomposition Complexity

Abstract: We consider a problem of decomposition of a ternary function into a composition of binary ones from the viewpoint of communication complexity and algorithmic information theory as well as some applications to cellular automata.


1D Effectively Closed Subshifts and 2D Tilings

Abstract: Michael Hochman showed that every 1D effectively closed subshift can be simulated by a 3D subshift of finite type and asked whether the same can be done in 2D. It turned out that the answer is positive and necessary tools were already developed in tilings theory. We discuss two alternative approaches: first, developed by N. Aubrun and M. Sablik, goes back to Leonid Levin; the second one, developed by the authors, goes back to Peter Gacs.


Slopes of Tilings

Abstract: We study here slopes of periodicity of tilings. A tiling is of slope if it is periodic along direction but has no other direction of periodicity. We characterize in this paper the set of slopes we can achieve with tilings, and prove they coincide with recursively enumerable sets of rationals.


Unary Subset-Sum is in Logspace

Abstract: We present a simple Logspace algorithm that solves the Unary Subset-Sum problem.


On Tuning the Bad-Character Rule: the Worst-Character Rule

Abstract: In this note we present the worst-character rule, an efficient variation of the bad-character heuristic for the exact string matching problem, firstly introduced in the well-known Boyer-Moore algorithm. Our proposed rule selects a position relative to the current shift which yields the largest average advancement, according to the characters distribution in the text. Experimental results show that the worst-character rule achieves very good results especially in the case of long patterns or small alphabets in random texts and in the case of texts in natural languages.


An Approximation Algorithm for the Euclidean Bottleneck Steiner Tree Problem

Abstract: Given two sets of points in the plane, $P$ of $n$ terminals and $S$ of $m$ Steiner points, a Steiner tree of $P$ is a tree spanning all points of $P$ and some (or none or all) points of $S$. A Steiner tree with length of longest edge minimized is called a bottleneck Steiner tree. In this paper, we study the Euclidean bottleneck Steiner tree problem: given two sets, $P$ and $S$, and a positive integer $k \le m$, find a bottleneck Steiner tree of $P$ with at most $k$ Steiner points. The problem has application in the design of wireless communication networks. We first show that the problem is NP-hard and cannot be approximated within factor $\sqrt{2}$, unless $P=NP$. Then, we present a polynomial-time approximation algorithm with performance ratio 2.


Considerate Equilibrium

Abstract: We consider the existence and computational complexity of coalitional stability concepts based on social networks. Our concepts represent a natural and rich combinatorial generalization of a recent approach termed partition equilibrium. We assume that players in a strategic game are embedded in a social network, and there are coordination constraints that restrict the potential coalitions that can jointly deviate in the game to the set of cliques in the social network. In addition, players act in a "considerate" fashion to ignore potentially profitable (group) deviations if the change in their strategy may cause a decrease of utility to their neighbors. We study the properties of such considerate equilibria in application to the class of resource selection games (RSG). Our main result proves existence of a considerate equilibrium in all symmetric RSG with strictly increasing delays, for any social network among the players. The existence proof is constructive and yields an efficient algorithm. In fact, the computed considerate equilibrium is a Nash equilibrium for the standard RSG showing that there exists a state that is stable against selfish and considerate behavior simultaneously. In addition, we show results on convergence of considerate dynamics.


Bridging the Gap between Reinforcement Learning and Knowledge Representation: A Logical Off- and On-Policy Framework

Abstract: Knowledge Representation is important issue in reinforcement learning. In this paper, we bridge the gap between reinforcement learning and knowledge representation, by providing a rich knowledge representation framework, based on normal logic programs with answer set semantics, that is capable of solving model-free reinforcement learning problems for more complex do-mains and exploits the domain-specific knowledge. We prove the correctness of our approach. We show that the complexity of finding an offline and online policy for a model-free reinforcement learning problem in our approach is NP-complete. Moreover, we show that any model-free reinforcement learning problem in MDP environment can be encoded as a SAT problem. The importance of that is model-free reinforcement


A Survey on Data Warehouse Evolution

Abstract: The data warehouse (DW) technology was developed to integrate heterogeneous information sources for analysis purposes. Information sources are more and more autonomous and they often change their content due to perpetual transactions (data changes) and may change their structure due to continual users' requirements evolving (schema changes). Handling properly all type of changes is a must. In fact, the DW which is considered as the core component of the modern decision support systems has to be update according to different type of evolution of information sources to reflect the real world subject to analysis. The goal of this paper is to propose an overview and a comparative study between different works related to the DW evolution problem.


Building conceptual spaces for exploring and linking biomedical resources

Abstract: The establishment of links between data (e.g., patient records) and Web resources (e.g., literature) and the proper visualization of such discovered knowledge is still a challenge in most Life Science domains (e.g., biomedicine). In this paper we present our contribution to the community in the form of an infrastructure to annotate information resources, to discover relationships among them, and to represent and visualize the new discovered knowledge. Furthermore, we have also implemented a Web-based prototype tool which integrates the proposed infrastructure.


Argudas: arguing with gene expression information

Abstract: In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information are often both incomplete and inconsistent. This paper examines a system, Argudas, designed to help tackle these issues. Argudas is an evolution of an existing system, and so that system is reviewed as a means of both explaining and justifying the behaviour of Argudas. Throughout the discussion of Argudas a number of issues will be raised including the appropriateness of argumentation in biology and the challenges faced when integrating apparently similar online biological databases.


User Centered and Ontology Based Information Retrieval System for Life Sciences

Abstract: Because of the increasing number of electronic data, designing efficient tools to retrieve and exploit documents is a major challenge. Current search engines suffer from two main drawbacks: there is limited interaction with the list of retrieved documents and no explanation for their adequacy to the query. Users may thus be confused by the selection and have no idea how to adapt their query so that the results match their expectations. This paper describes a request method and an environment based on aggregating models to assess the relevance of documents annotated by concepts of ontology. The selection of documents is then displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive exploration of data corpus.


Are SNOMED CT Browsers Ready for Institutions? Introducing MySNOM

Abstract: SNOMED Clinical Terms (SNOMED CT) is one of the most widespread ontologies in the life sciences, with more than 300,000 concepts and relationships, but is distributed with no associated software tools. In this paper we present MySNOM, a web-based SNOMED CT browser. MySNOM allows organizations to browse their own distribution of SNOMED CT under a controlled environment, focuses on navigating using the structure of SNOMED CT, and has diagramming capabilities.


YeastMed: an XML-Based System for Biological Data Integration of Yeast

Abstract: A key goal of bioinformatics is to create database systems and software platforms capable of storing and analysing large sets of biological data. Hundreds of biological databases are now available and provide access to huge amount of biological data. SGD, Yeastract, CYGD-MIPS, BioGrid and PhosphoGrid are five of the most visited databases by the yeast community. These sources provide complementary data on biological entities. Biologists are brought systematically to query these data sources in order to analyse the results of their experiments. Because of the heterogeneity of these sources, querying them separately and then manually combining the returned result is a complex and laborious task. To provide transparent and simultaneous access to these sources, we have developed a mediator-based system called YeastMed. In this paper, we present YeastMed focusing on its architecture.


FreePub: Collecting and Organizing Scientific Material Using Mindmaps

Abstract: This paper presents a creativity support tool, called FreePub, to collect and organize scientific material using mindmaps. Mindmaps are visual, graph-based represenations of concepts, ideas, notes, tasks, etc. They generally take a hierarchical or tree branch format, with ideas branching into their subsections. FreePub supports creativity cycles. A user starts such a cycle by setting up her domain of interest using mindmaps. Then, she can browse mindmaps and launch search tasks to gather relevant publications from several data sources. FreePub, besides publications, identifies helpful supporting material (e.g., blog posts, presentations). All retrieved information from FreePub can be imported and organized in mindmaps. FreePub has been fully implemented on top of FreeMind, a popular open-source, mindmapping tool.


Benchmarking triple stores with biological data

Abstract: We have compared the performance of five non-commercial triple stores, Virtuoso-open source, Jena SDB, Jena TDB, SWIFT-OWLIM and 4Store. We examined three performance aspects: the query execution time, scalability and run-to-run reproducibility. The queries we chose addressed different ontological or biological topics, and we obtained evidence that individual store performance was quite query specific. We identified three groups of queries displaying similar behavior across the different stores: 1) relatively short response time, 2) moderate response time and 3) relatively long response time. OWLIM proved to be a winner in the first group, 4Store in the second and Virtuoso in the third. Our benchmarking showed Virtuoso to be a very balanced performer - its response time was better than average for all the 24 queries; it showed a very good scalability and a reasonable run-to-run reproducibility.