On the Practicality of Atomic MWMR Register Implementations

Abstract: Multiple-writer/multiple-reader (MWMR) atomic register implementations provide precise consistency guarantees, in the asynchronous, crash-prone, message passing environment. Fast MWMR atomic register implementations were first introduced in Englert et al. 2009. Fastness is measured in terms of the number of single round read and write operations that does not sacrifice correctness. In Georgiou et al. 2011 was shown, however, that decreasing the communication cost is not enough in these implementations. In particular, considering that the performance is measured in terms of the latency of read and write operations due to both (a) communication delays and (b)local computation, they introduced two new algorithms that traded communication for reducing computation. As computation is still part of the algorithms, someone may wonder: What is the trade-off between communication and local computation in real-time systems? In this work we conduct an experimental performance evaluation of four MWMR atomic register implementations: SFW from Englert et al. 2009, APRX-SFW and CWFR from Georgiou at al. 2011, and the generalization of the traditional algorithm of Attiya et al. 1996 in the MWMR environment, which we call SIMPLE. We implement and evaluate the algorithms on NS2, a single-processor simulator, and on PlanetLab, a planetary-scale real-time network platform. Our comparison provides an empirical answer to the above question and demonstrates the practicality of atomic MWMR register implementations.


The asymptotic behavior of Grassmannian codes

Abstract: The iterated Johnson bound is the best known upper bound on a size of an error-correcting code in the Grassmannian $\mathcal{G}_q(n,k)$. The iterated Sch\"{o}nheim bound is the best known lower bound on the size of a covering code in $\mathcal{G}_q(n,k)$. We use probabilistic methods to prove that both bounds are asymptotically attained for fixed $k$ and fixed radius, as $n$ approaches infinity. We also determine the asymptotics of the size of the best Grassmannian codes and covering codes when $n-k$ and the radius are fixed, as $n$ approaches infinity.


Cryptanalysis of Song's advanced smart card based password authentication protocol

Abstract: Song \cite{Song10} proposed very recently a password-based authentication and key establishment protocol using smart cards which attempts to solve some weaknesses found in a previous scheme suggested by Xu, Zhu, and Feng \cite{XZF09}. In this paper, we present attacks on the improved protocol, showing that it fails to achieve the claimed security goals.


Finite State Machine Based Evaluation Model for Web Service Reliability Analysis

Abstract: Now-a-days they are very much considering about the changes to be done at shorter time since the reaction time needs are decreasing every moment. Business Logic Evaluation Model (BLEM) are the proposed solution targeting business logic automation and facilitating business experts to write sophisticated business rules and complex calculations without costly custom programming. BLEM is powerful enough to handle service manageability issues by analyzing and evaluating the computability and traceability and other criteria of modified business logic at run time. The web service and QOS grows expensively based on the reliability of the service. Hence the service provider of today things that reliability is the major factor and any problem in the reliability of the service should overcome then and there in order to achieve the expected level of reliability. In our paper we propose business logic evaluation model for web service reliability analysis using Finite State Machine (FSM) where FSM will be extended to analyze the reliability of composed set of service i.e., services under composition, by analyzing reliability of each participating service of composition with its functional work flow process. FSM is exploited to measure the quality parameters. If any change occurs in the business logic the FSM will automatically measure the reliability.


Quantitative Analysis of Information Leakage in Probabilistic and Nondeterministic Systems

Abstract: This thesis addresses the foundational aspects of formal methods for applications in security and in particular in anonymity. More concretely, we develop frameworks for the specification of anonymity properties and propose algorithms for their verification. Since in practice anonymity protocols always leak some information, we focus on quantitative properties, which capture the amount of information leaked by a protocol. The main contribution of this thesis is cpCTL, the first temporal logic that allows for the specification and verification of conditional probabilities (which are the key ingredient of most anonymity properties). In addition, we have considered several prominent definitions of information-leakage and developed the first algorithms allowing us to compute (and even approximate) the information leakage of anonymity protocols according to these definitions. We have also studied a well-known problem in the specification and analysis of distributed anonymity protocols, namely full-information scheduling. To overcome this problem, we have proposed an alternative notion of scheduling and adjusted accordingly several anonymity properties from the literature. Our last major contribution is a debugging technique that helps on the detection of flaws in security protocols.


8-Valent Fuzzy Logic for Iris Recognition and Biometry

Abstract: This paper shows that maintaining logical consistency of an iris recognition system is a matter of finding a suitable partitioning of the input space in enrollable and unenrollable pairs by negotiating the user comfort and the safety of the biometric system. In other words, consistent enrollment is mandatory in order to preserve system consistency. A fuzzy 3-valued disambiguated model of iris recognition is proposed and analyzed in terms of completeness, consistency, user comfort and biometric safety. It is also shown here that the fuzzy 3-valued model of iris recognition is hosted by an 8-valued Boolean algebra of modulo 8 integers that represents the computational formalization in which a biometric system (a software agent) can achieve the artificial understanding of iris recognition in a logically consistent manner.


Graded CTL Model Checking for Test Generation

Abstract: Recently there has been a great attention from the scientific community towards the use of the model-checking technique as a tool for test generation in the simulation field. This paper aims to provide a useful mean to get more insights along these lines. By applying recent results in the field of graded temporal logics, we present a new efficient model-checking algorithm for Hierarchical Finite State Machines (HSM), a well established symbolism long and widely used for representing hierarchical models of discrete systems. Performing model-checking against specifications expressed using graded temporal logics has the peculiarity of returning more counterexamples within a unique run. We think that this can greatly improve the efficacy of automatically getting test cases. In particular we verify two different models of HSM against branching time temporal properties.


Towards Automated Verification of Web Services

Abstract: This paper proposes the use of model-checking software technology for the verification of workflows and business processes behaviour based on web services, namely the use of the SPIN model checker. Since the specification of a business process behaviour based on web services can be decomposed into patterns, it is proposed a translation of a well known collection of workflow patterns into PROMELA, the input specification language of SPIN. The use of this translation is illustrated with one business process example, which demonstrates how its translation to a PROMELA model can be useful in the web service specification and verification.


Model-Based Trace-Checking

Abstract: Trace analysis can be a useful way to discover problems in a program under test. Rather than writing a special purpose trace analysis tool, this paper proposes that traces can usefully be analysed by checking them against a formal model using a standard model-checker or else an animator for executable specifications. These techniques are illustrated using a Travel Agent case study implemented in J2EE. We added trace beans to this code that write trace information to a database. The traces are then extracted and converted into a form suitable for analysis by Spin, a popular model-checker, and Pro-B, a model-checker and animator for the B notation. This illustrates the technique, and also the fact that such a system can have a variety of models, in different notations, that capture different features. These experiments have demonstrated that model-based trace-checking is feasible. Future work is focussed on scaling up the approach to larger systems by increasing the level of automation.


Concurrent Development of Model and Implementation

Abstract: This paper considers how a formal mathematically-based model can be used in support of evolutionary software development, and in particular how such a model can be kept consistent with the implementation as it changes to meet new requirements. A number of techniques are listed can make use of such a model to enhance the development process, and also ways to keep model and implementation consistent. The effectiveness of these techniques is investigated through two case studies concerning the development of small e-business applications, a travel agent and a mortgage broker. Some successes are reported, notably in the use of rapid throwaway modelling to investigate design alternatives, and also in the use of close team working and modelbased trace-checking to maintain synchronisation between model and implementation throughout the development. The main areas of weakness were seen to derive from deficiencies in tool support. Recommendations are therefore made for future improvements to tools supporting formal models which would, in principle, make this co-evolutionary approach attractive to industrial software developers. It is claimed that in fact tools already exist that provide the desired facilities, but these are not necessarily production-quality, and do not all support the same notations, and hence cannot be used together.


Principles of Distributed Data Management in 2020?

Abstract: With the advents of high-speed networks, fast commodity hardware, and the web, distributed data sources have become ubiquitous. The third edition of the \"Ozsu-Valduriez textbook Principles of Distributed Database Systems [10] reflects the evolution of distributed data management and distributed database systems. In this new edition, the fundamental principles of distributed data management could be still presented based on the three dimensions of earlier editions: distribution, heterogeneity and autonomy of the data sources. In retrospect, the focus on fundamental principles and generic techniques has been useful not only to understand and teach the material, but also to enable an infinite number of variations. The primary application of these generic techniques has been obviously for distributed and parallel DBMS versions. Today, to support the requirements of important data-intensive applications (e.g. social networks, web data analytics, scientific applications, etc.), new distributed data management techniques and systems (e.g. MapReduce, Hadoop, SciDB, Peanut, Pig latin, etc.) are emerging and receiving much attention from the research community. Although they do well in terms of consistency/flexibility/performance trade-offs for specific applications, they seem to be ad-hoc and might hurt data interoperability. The key questions I discuss are: What are the fundamental principles behind the emerging solutions? Is there any generic architectural model, to explain those principles? Do we need new foundations to look at data distribution?


Privacy Auctions for Recommender Systems

Abstract: We study a market for private data in which a data analyst publicly releases a statistic over a database of private information. Individuals that own the data incur a cost for their loss of privacy proportional to the differential privacy guarantee given by the analyst at the time of the release. The analyst incentivizes individuals by compensating them, giving rise to a \emph{privacy auction}. Motivated by recommender systems, the statistic we consider is a linear predictor function with publicly known weights. The statistic can be viewed as a prediction of the unknown data of a new individual, based on the data of individuals in the database. We formalize the trade-off between privacy and accuracy in this setting, and show that a simple class of estimates achieves an order-optimal trade-off. It thus suffices to focus on auction mechanisms that output such estimates. We use this observation to design a truthful, individually rational, proportional-purchase mechanism under a fixed budget constraint. We show that our mechanism is 5-approximate in terms of accuracy compared to the optimal mechanism, and that no truthful mechanism can achieve a $2-\varepsilon$ approximation, for any $\varepsilon > 0$.


Adaptive Regret Minimization in Bounded-Memory Games

Abstract: Online learning algorithms that minimize regret provide strong guarantees in situations that involve repeatedly making decisions in an uncertain environment, e.g. a driver deciding what route to drive to work every day. While regret minimization has been extensively studied in repeated games, we study regret minimization for a richer class of games called bounded memory games. In each round of a two-player bounded memory-m game, both players simultaneously play an action, observe an outcome and receive a reward. The reward may depend on the last m outcomes as well as the actions of the players in the current round. The standard notion of regret for repeated games is no longer suitable because actions and rewards can depend on the history of play. To account for this generality, we introduce the notion of k-adaptive regret, which compares the reward obtained by playing actions prescribed by the algorithm against a hypothetical k-adaptive adversary with the reward obtained by the best expert in hindsight against the same adversary. Roughly, a hypothetical k-adaptive adversary adapts her strategy to the defender's actions exactly as the real adversary would within each window of k rounds. Our definition is parametrized by a set of experts, which can include both fixed and adaptive defender strategies. We investigate the inherent complexity of and design algorithms for adaptive regret minimization in bounded memory games of perfect and imperfect information. We prove a hardness result showing that, with imperfect information, any k-adaptive regret minimizing algorithm (with fixed strategies as experts) must be inefficient unless NP=RP even when playing against an oblivious adversary. In contrast, for bounded memory games of perfect and imperfect information we present approximate 0-adaptive regret minimization algorithms against an oblivious adversary running in time n^{O(1)}.


Optimal Crowdsourcing Contests

Abstract: We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to enter. Unlike all-pay auctions where a usual design objective would be to maximize revenue, in crowdsourcing contests, the principal only benefits from the submission with the highest quality. We give a theory for optimal crowdsourcing contests that mirrors the theory of optimal auction design: the optimal crowdsourcing contest is a virtual valuation optimizer (the virtual valuation function depends on the distribution of contestant skills and the number of contestants). We also compare crowdsourcing contests with more conventional means of procurement. In this comparison, crowdsourcing contests are relatively disadvantaged because the effort of losing contestants is wasted. Nonetheless, we show that crowdsourcing contests are 2-approximations to conventional methods for a large family of "regular" distributions, and 4-approximations, otherwise.


Spatio-Temporal Analysis of Topic Popularity in Twitter

Abstract: We present the first comprehensive characterization of the diffusion of ideas on Twitter, studying more than 4000 topics that include both popular and less popular topics. On a data set containing approximately 10 million users and a comprehensive scraping of all the tweets posted by these users between June 2009 and August 2009 (approximately 200 million tweets), we perform a rigorous temporal and spatial analysis, investigating the time-evolving properties of the subgraphs formed by the users discussing each topic. We focus on two different notions of the spatial: the network topology formed by follower-following links on Twitter, and the geospatial location of the users. We investigate the effect of initiators on the popularity of topics and find that users with a high number of followers have a strong impact on popularity. We deduce that topics become popular when disjoint clusters of users discussing them begin to merge and form one giant component that grows to cover a significant fraction of the network. Our geospatial analysis shows that highly popular topics are those that cross regional boundaries aggressively.


Localized Geometric Query Problems

Abstract: A new class of geometric query problems are studied in this paper. We are required to preprocess a set of geometric objects $P$ in the plane, so that for any arbitrary query point $q$, the largest circle that contains $q$ but does not contain any member of $P$, can be reported efficiently. The geometric sets that we consider are point sets and boundaries of simple polygons.


A Simple Network Management Architecture for Supporting Network Administrator and QoS Requirements

Abstract: In this paper, a simple network management architecture for supporting both QoS requirements and organization network management policies is purposed. By grouping the traffic flows according to the QoS requirements or certain network management policies, the network resources are effectively controlled. The purposed architecture is easy to deploy; the gateway is the only equipment that needs installation, leaving the rest of the system untouched. The architecture has not significantly degraded the overall system utilization when applying it to the outgoing bound of the gateway. The architecture can also be implemented on the wireless LAN at the access point because the architecture is designed in such the way that it is independent to both the lower and upper protocol layers.


Down the Rabbit Hole: Robust Proximity Search and Density Estimation in Sublinear Space

Abstract: For a set of $n$ points in $\Re^d$, and parameters $k$ and $\eps$, we present a data structure that answers $(1+\eps,k)$-\ANN queries in logarithmic time. Surprisingly, the space used by the data-structure is $\Otilde (n /k)$; that is, the space used is sublinear in the input size if $k$ is sufficiently large. Our approach provides a novel way to summarize geometric data, such that meaningful proximity queries on the data can be carried out using this sketch. Using this, we provide a sublinear space data-structure that can estimate the density of a point set under various measures, including: \begin{inparaenum}[(i)] \item sum of distances of $k$ closest points to the query point, and \item sum of squared distances of $k$ closest points to the query point. \end{inparaenum} Our approach generalizes to other distance based estimation of densities of similar flavor. We also study the problem of approximating some of these quantities when using sampling. In particular, we show that a sample of size $\Otilde (n /k)$ is sufficient, in some restricted cases, to estimate the above quantities. Remarkably, the sample size has only linear dependency on the dimension.


Using Contextual Information as Virtual Items on Top-N Recommender Systems

Abstract: Traditionally, recommender systems for the Web deal with applications that have two dimensions, users and items. Based on access logs that relate these dimensions, a recommendation model can be built and used to identify a set of N items that will be of interest to a certain user. In this paper we propose a method to complement the information in the access logs with contextual information without changing the recommendation algorithm. The method consists in representing context as virtual items. We empirically test this method with two top-N recommender systems, an item-based collaborative filtering technique and association rules, on three data sets. The results show that our method is able to take advantage of the context (new dimensions) when it is informative.


Application of PSO, Artificial Bee Colony and Bacterial Foraging Optimization algorithms to economic load dispatch: An analysis

Abstract: This paper illustrates successful implementation of three evolutionary algorithms, namely- Particle Swarm Optimization(PSO), Artificial Bee Colony (ABC) and Bacterial Foraging Optimization (BFO) algorithms to economic load dispatch problem (ELD). Power output of each generating unit and optimum fuel cost obtained using all three algorithms have been compared. The results obtained show that ABC and BFO algorithms converge to optimal fuel cost with reduced computational time when compared to PSO for the two example problems considered.


A Survey on Web-based AR Applications

Abstract: Due to the increase of interest in Augmented Reality (AR), the potential uses of AR are increasing also. It can benefit the user in various fields such as education, business, medicine, and other. Augmented Reality supports the real environment with synthetic environment to give more details and meaning to the objects in the real word. AR refers to a situation in which the goal is to supplement a user's perception of the real-world through the addition of virtual objects. This paper is an attempt to make a survey of web-based Augmented Reality applications and make a comparison among them.


Performance Evaluation of Different Scheduling Algorithms in WiMAX

Abstract: Worldwide Interoperability for Microwave Access (WiMAX) networks were expected to be the main Broadband Wireless Access (BWA) technology that provided several services such as data, voice, and video services including different classes of Quality of Services (QoS), which in turn were defined by IEEE 802.16 standard. Scheduling in WiMAX became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users; this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, we presenedt a simulation study to measure the performance of several scheduling algorithms in WiMAX, which were Strict Priority algorithm, Round-Robin (RR), Weighted Round Robin (WRR), Weighted Fair Queuing (WFQ), Self-Clocked Fair (SCF), and Diff-Serv Algorithm.


A Comprehensive Study of Commonly Practiced Heavy and Light Weight Software Methodologies

Abstract: Software has been playing a key role in the development of modern society. Software industry has an option to choose suitable methodology/process model for its current needs to provide solutions to give problems. Though some companies have their own customized methodology for developing their software but majority agrees that software methodologies fall under two categories that are heavyweight and lightweight. Heavyweight methodologies (Waterfall Model, Spiral Model) are also known as the traditional methodologies, and their focuses are detailed documentation, inclusive planning, and extroverted design. Lightweight methodologies (XP, SCRUM) are, referred as agile methodologies. Light weight methodologies focused mainly on short iterative cycles, and rely on the knowledge within a team. The aim of this paper is to describe the characteristics of popular heavyweight and lightweight methodologies that are widely practiced in software industries. We have discussed the strengths and weakness of the selected models. Further we have discussed the strengths and weakness between the two opponent methodologies and some criteria is also illustrated that help project managers for the selection of suitable model for their projects.


A Multi-Factor Security Protocol for Wireless Payment - Secure Web Authentication using Mobile Devices

Abstract: Previous Web access authentication systems often use either the Web or the Mobile channel individually to confirm the claimed identity of the remote user. This paper proposes a new protocol using multifactor authentication system that is both secure and highly usable. It uses a novel approach based on Transaction Identification Code and SMS to enforce extra security level with the traditional Login/password system. The system provides a highly secure environment that is simple to use and deploy, that does not require any change in infrastructure or protocol of wireless networks. This Protocol for Wireless Payment is extended to provide two way authentications.


Formal approaches to information hiding: An analysis of interactive systems, statistical disclosure control, and refinement of specifications

Abstract: In this thesis we consider the problem of information hiding in the scenarios of interactive systems, statistical disclosure control, and refinement of specifications. We apply quantitative approaches to information flow in the first two cases, and we propose improvements for the usual solutions based on process equivalences for the third case. In the first scenario we consider the problem of defining the information leakage in interactive systems where secrets and observables can alternate during the computation and influence each other. We show that the information-theoretic approach which interprets such systems as (simple) noisy channels is not valid. The principle can be recovered if we consider channels with memory and feedback. We also propose the use of directed information from input to output as the real measure of leakage in interactive systems. In the second scenario we consider the problem of statistical disclosure control, which concerns how to reveal accurate statistics about a set of respondents while preserving the privacy of individuals. We focus on the concept of differential privacy, a notion that has become very popular in the database community. We show how to model the query system in terms of an information-theoretic channel, and we compare the notion of differential privacy with that of min-entropy leakage.In the third scenario we address the problem of using process equivalences to characterize information-hiding properties. We show that, in the presence of nondeterminism, this approach may rely on the assumption that the scheduler "works for the benefit of the protocol", and this is often not a safe assumption. We present a formalism in which we can specify admissible schedulers and, correspondingly, safe versions of complete-trace equivalence and bisimulation, and we show that safe equivalences can be used to establish information-hiding properties.


Design of a Sliding Window over Asynchronous Event Streams

Abstract: The proliferation of sensing and monitoring applications motivates adoption of the event stream model of computation. Though sliding windows are widely used to facilitate effective event stream processing, it is greatly challenged when the event sources are distributed and asynchronous. To address this challenge, we first show that the snapshots of the asynchronous event streams within the sliding window form a convex distributive lattice (denoted by Lat-Win). Then we propose an algorithm to maintain Lat-Win at runtime. The Lat-Win maintenance algorithm is implemented and evaluated on the open-source context-aware middleware we developed. The evaluation results first show the necessity of adopting sliding windows over asynchronous event streams. Then they show the performance of detecting specified predicates within Lat-Win, even when faced with dynamic changes in the computing environment.


Intelligent Distributed Production Control

Abstract: This editorial introduces the special issue of the Springer journal, Journal of Intelligent Manufacturing, on intelligent distributed production control. This special issue contains selected papers presented at the 13th IFAC Symposium on Information Control Problems in Manufacturing - INCOM'2009 (Bakhtadze and Dolgui, 2009). The papers in this special issue were selected because of their high quality and their specific way of addressing the variety of issues dealing with intelligent distributed production control. Previous global discussions about the state of the art in intelligent distributed production control are provided, as well as exploratory guidelines for future research in this area.


Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Abstract: Cognitive Radio Networks allow unlicensed users to opportunistically access the licensed spectrum without causing disruptive interference to the primary users (PUs). One of the main challenges in CRNs is the ability to detect PU transmissions. Recent works have suggested the use of secondary user (SU) cooperation over individual sensing to improve sensing accuracy. In this paper, we consider a CRN consisting of a single PU and multiple SUs to study the problem of maximizing the total expected system throughput. We propose a Bayesian decision rule based algorithm to solve the problem optimally with a constant time complexity. To prioritize PU transmissions, we re-formulate the throughput maximization problem by adding a constraint on the PU throughput. The constrained optimization problem is shown to be NP-hard and solved via a greedy algorithm with pseudo-polynomial time complexity that achieves strictly greater than 1/2 of the optimal solution. We also investigate the case for which a constraint is put on the sensing time overhead, which limits the number of SUs that can participate in cooperative sensing. We reveal that the system throughput is monotonic over the number of SUs chosen for sensing. We illustrate the efficacy of the performance of our algorithms via a numerical investigation.


Performance of Cache Memory Subsystems for Multicore Architectures

Abstract: Advancements in multi-core have created interest among many research groups in finding out ways to harness the true power of processor cores. Recent research suggests that on-board component such as cache memory plays a crucial role in deciding the performance of multi-core systems. In this paper, performance of cache memory is evaluated through the parameters such as cache access time, miss rate and miss penalty. The influence of cache parameters over execution time is also discussed. Results obtained from simulated studies of multi-core environments with different instruction set architectures (ISA) like ALPHA and X86 are produced.


An Approach using Demisubmartingales for the Stochastic Analysis of Networks

Abstract: Stochastic network calculus is the probabilistic version of the network calculus, which uses envelopes to perform probabilistic analysis of queueing networks. The accuracy of probabilistic end-to-end delay or backlog bounds computed using network calculus has always been a concern. In this paper, we propose novel end-to-end probabilistic bounds based on demisubmartingale inequalities which improve the existing bounds for the tandem networks of GI/GI/1 queues. In particular, we show that reasonably accurate bounds are achieved by comparing the new bounds with the existing results for a network of M/M/1 queues.


A fusion algorithm for joins based on collections in Odra (Object Database for Rapid Application development)

Abstract: In this paper we present the functionality of a currently under development database programming methodology called ODRA (Object Database for Rapid Application development) which works fully on the object oriented principles. The database programming language is called SBQL (Stack based query language). We discuss some concepts in ODRA for e.g. the working of ODRA, how ODRA runtime environment operates, the interoperability of ODRA with .net and java .A view of ODRA's working with web services and xml. Currently the stages under development in ODRA are query optimization. So we present the prior work that is done in ODRA related to Query optimization and we also present a new fusion algorithm of how ODRA can deal with joins based on collections like set, lists, and arrays for query optimization.


vFlow: A GUI-Based Tool for Building Batch Applications for Cloud Computing

Abstract: In this paper we introduce vFlow - A framework for rapid designing of batch processing applications for Cloud Computing environment. vFlow batch processing system extracts tasks from the vPlans diagrams, systematically captures the dynamics in batch application management tasks, and translates them to Cloud environment API, named vDocuments, that can be used to execute batch processing applications. vDocuments do not only enable the complete execution of low-level configuration management tasks, but also allow the construction of more sophisticated tasks, while imposing additional reasoning logic to realize batch application management objectives in Cloud environments. We present the design of the vFlow framework and illustrate its utility by presenting the implementation of several sophisticated operational tasks.


The tile assembly model is intrinsically universal

Abstract: We prove that the abstract Tile Assembly Model (aTAM) of nanoscale self-assembly is intrinsically universal. This means that there is a single tile assembly system U that, with proper initialization, simulates any tile assembly system T. The simulation is "intrinsic" in the sense that the self-assembly process carried out by U is exactly that carried out by T, with each tile of T represented by an m x m "supertile" of U. Our construction works for the full aTAM at any temperature, and it faithfully simulates the deterministic or nondeterministic behavior of each T. Our construction succeeds by solving an analog of the cell differentiation problem in developmental biology: Each supertile of U, starting with those in the seed assembly, carries the "genome" of the simulated system T. At each location of a potential supertile in the self-assembly of U, a decision is made whether and how to express this genome, i.e., whether to generate a supertile and, if so, which tile of T it will represent. This decision must be achieved using asynchronous communication under incomplete information, but it achieves the correct global outcome(s).


Practical Distributed Control Synthesis

Abstract: Classic distributed control problems have an interesting dichotomy: they are either trivial or undecidable. If we allow the controllers to fully synchronize, then synthesis is trivial. In this case, controllers can effectively act as a single controller with complete information, resulting in a trivial control problem. But when we eliminate communication and restrict the supervisors to locally available information, the problem becomes undecidable. In this paper we argue in favor of a middle way. Communication is, in most applications, expensive, and should hence be minimized. We therefore study a solution that tries to communicate only scarcely and, while allowing communication in order to make joint decision, favors local decisions over joint decisions that require communication.


Trees over Infinite Structures and Path Logics with Synchronization

Abstract: We provide decidability and undecidability results on the model-checking problem for infinite tree structures. These tree structures are built from sequences of elements of infinite relational structures. More precisely, we deal with the tree iteration of a relational structure M in the sense of Shelah-Stupp. In contrast to classical results where model-checking is shown decidable for MSO-logic, we show decidability of the tree model-checking problem for logics that allow only path quantifiers and chain quantifiers (where chains are subsets of paths), as they appear in branching time logics; however, at the same time the tree is enriched by the equal-level relation (which holds between vertices u, v if they are on the same tree level). We separate cleanly the tree logic from the logic used for expressing properties of the underlying structure M. We illustrate the scope of the decidability results by showing that two slight extensions of the framework lead to undecidability. In particular, this applies to the (stronger) tree iteration in the sense of Muchnik-Walukiewicz.


Synthesis of Switching Rules for Ensuring Reachability Properties of Sampled Linear Systems

Abstract: We consider here systems with piecewise linear dynamics that are periodically sampled with a given period {\tau} . At each sampling time, the mode of the system, i.e., the parameters of the linear dynamics, can be switched, according to a switching rule. Such systems can be modelled as a special form of hybrid automata, called "switched systems", that are automata with an infinite real state space. The problem is to find a switching rule that guarantees the system to still be in a given area V at the next sampling time, and so on indefinitely. In this paper, we will consider two approaches: the indirect one that abstracts the system under the form of a finite discrete event system, and the direct one that works on the continuous state space. Our methods rely on previous works, but we specialize them to a simplified context (linearity, periodic switching instants, absence of control input), which is motivated by the features of a focused case study: a DC-DC boost converter built by electronics laboratory SATIE (ENS Cachan). Our enhanced methods allow us to treat successfully this real-life example.


A coinductive semantics of the Unlimited Register Machine

Abstract: We exploit (co)inductive specifications and proofs to approach the evaluation of low-level programs for the Unlimited Register Machine (URM) within the Coq system, a proof assistant based on the Calculus of (Co)Inductive Constructions type theory. Our formalization allows us to certify the implementation of partial functions, thus it can be regarded as a first step towards the development of a workbench for the formal analysis and verification of both converging and diverging computations.


Model Checking Probabilistic Real-Time Properties for Service-Oriented Systems with Service Level Agreements

Abstract: The assurance of quality of service properties is an important aspect of service-oriented software engineering. Notations for so-called service level agreements (SLAs), such as the Web Service Level Agreement (WSLA) language, provide a formal syntax to specify such assurances in terms of (legally binding) contracts between a service provider and a customer. On the other hand, formal methods for verification of probabilistic real-time behavior have reached a level of expressiveness and efficiency which allows to apply them in real-world scenarios. In this paper, we suggest to employ the recently introduced model of Interval Probabilistic Timed Automata (IPTA) for formal verification of QoS properties of service-oriented systems. Specifically, we show that IPTA in contrast to Probabilistic Timed Automata (PTA) are able to capture the guarantees specified in SLAs directly. A particular challenge in the analysis of IPTA is the fact that their naive semantics usually yields an infinite set of states and infinitely-branching transitions. However, using symbolic representations, IPTA can be analyzed rather efficiently. We have developed the first implementation of an IPTA model checker by extending the PRISM tool and show that model checking IPTA is only slightly more expensive than model checking comparable PTA.


A Probabilistic Temporal Logic with Frequency Operators and Its Model Checking

Abstract: Probabilistic Computation Tree Logic (PCTL) and Continuous Stochastic Logic (CSL) are often used to describe specifications of probabilistic properties for discrete time and continuous time, respectively. In PCTL and CSL, the possibility of executions satisfying some temporal properties can be quantitatively represented by the probabilistic extension of the path quantifiers in their basic Computation Tree Logic (CTL), however, path formulae of them are expressed via the same operators in CTL. For this reason, both of them cannot represent formulae with quantitative temporal properties, such as those of the form "some properties hold to more than 80% of time points (in a certain bounded interval) on the path." In this paper, we introduce a new temporal operator which expressed the notion of frequency of events, and define probabilistic frequency temporal logic (PFTL) based on CTL\star. As a result, we can easily represent the temporal properties of behavior in probabilistic systems. However, it is difficult to develop a model checker for the full PFTL, due to rich expressiveness. Accordingly, we develop a model-checking algorithm for the CTL-like fragment of PFTL against finite-state Markov chains, and an approximate model-checking algorithm for the bounded Linear Temporal Logic (LTL) -like fragment of PFTL against countable-state Markov chains.


ESLO: from transcription to speakers' personal information annotation

Abstract: This paper presents the preliminary works to put online a French oral corpus and its transcription. This corpus is the Socio-Linguistic Survey in Orleans, realized in 1968. First, we numerized the corpus, then we handwritten transcribed it with the Transcriber software adding different tags about speakers, time, noise, etc. Each document (audio file and XML file of the transcription) was described by a set of metadata stored in an XML format to allow an easy consultation. Second, we added different levels of annotations, recognition of named entities and annotation of personal information about speakers. This two annotation tasks used the CasSys system of transducer cascades. We used and modified a first cascade to recognize named entities. Then we built a second cascade to annote the designating entities, i.e. information about the speaker. These second cascade parsed the named entity annotated corpus. The objective is to locate information about the speaker and, also, what kind of information can designate him/her. These two cascades was evaluated with precision and recall measures.


\'Evaluation de lexiques syntaxiques par leur int\'egartion dans l'analyseur syntaxiques FRMG

Abstract: In this paper, we evaluate various French lexica with the parser FRMG: the Lefff, LGLex, the lexicon built from the tables of the French Lexicon-Grammar, the lexicon DICOVALENCE and a new version of the verbal entries of the Lefff, obtained by merging with DICOVALENCE and partial manual validation. For this, all these lexica have been converted to the format of the Lefff, Alexina format. The evaluation was made on the part of the EASy corpus used in the first evaluation campaign Passage.


Construction du lexique LGLex \`a partir des tables du Lexique-Grammaire des verbes du grec moderne

Abstract: In this paper, we summerize the work done on the resources of Modern Greek on the Lexicon-Grammar of verbs. We detail the definitional features of each table, and all changes made to the names of features to make them consistent. Through the development of the table of classes, including all the features, we have considered the conversion of tables in a syntactic lexicon: LGLex. The lexicon, in plain text format or XML, is generated by the LGExtract tool (Constant & Tolone, 2010). This format is directly usable in applications of Natural Language Processing (NLP).


Effective Ways of Secure, Private and Trusted Cloud Computing

Abstract: Cloud computing is an Internet-based computing, where shared resources, software and information, are provided to computers and devices on-demand. It provides people the way to share distributed resources and services that belong to different organization. Since cloud computing uses distributed resources in open environment, thus it is important to provide the security and trust to share the data for developing cloud computing applications. In this paper we assess how can cloud providers earn their customers' trust and provide the security, privacy and reliability, when a third party is processing sensitive data in a remote machine located in various countries? A concept of utility cloud has been represented to provide the various services to the users. Emerging technologies can help address the challenges of Security, Privacy and Trust in cloud computing.


Faster fully compressed pattern matching by recompression

Abstract: In this paper, a fully compressed pattern matching problem is studied. The compression is represented by straight-line programs (SLPs), i.e. a context-free grammars generating exactly one string; the term fully means that both the pattern and the text are given in the compressed form. The problem is approached using a recently developed technique of local recompression: the SLPs are refactored, so that substrings of the pattern and text are encoded in both SLPs in the same way. To this end, the SLPs are locally decompressed and then recompressed in a uniform way. This technique yields an O((n+m)log M) algorithm for compressed pattern matching, assuming that M fits in O(1) machine words, where n (m) is the size of the compressed representation of the text (pattern, respectively), while M is the size of the decompressed pattern. If only m+n fits in O(1) machine words, the running time increases to O((n+m)log M log(n+m)). The previous best algorithm due to Lifshits had O(n^2m) running time.


Mining Biclusters of Similar Values with Triadic Concept Analysis

Abstract: Biclustering numerical data became a popular data-mining task in the beginning of 2000's, especially for analysing gene expression data. A bicluster reflects a strong association between a subset of objects and a subset of attributes in a numerical object/attribute data-table. So called biclusters of similar values can be thought as maximal sub-tables with close values. Only few methods address a complete, correct and non redundant enumeration of such patterns, which is a well-known intractable problem, while no formal framework exists. In this paper, we introduce important links between biclustering and formal concept analysis. More specifically, we originally show that Triadic Concept Analysis (TCA), provides a nice mathematical framework for biclustering. Interestingly, existing algorithms of TCA, that usually apply on binary data, can be used (directly or with slight modifications) after a preprocessing step for extracting maximal biclusters of similar values.


A prototype system for handwritten sub-word recognition: Toward Arabic-manuscript transliteration

Abstract: A prototype system for the transliteration of diacritics-less Arabic manuscripts at the sub-word or part of Arabic word (PAW) level is developed. The system is able to read sub-words of the input manuscript using a set of skeleton-based features. A variation of the system is also developed which reads archigraphemic Arabic manuscripts, which are dot-less, into archigraphemes transliteration. In order to reduce the complexity of the original highly multiclass problem of sub-word recognition, it is redefined into a set of binary descriptor classifiers. The outputs of trained binary classifiers are combined to generate the sequence of sub-word letters. SVMs are used to learn the binary classifiers. Two specific Arabic databases have been developed to train and test the system. One of them is a database of the Naskh style. The initial results are promising. The systems could be trained on other scripts found in Arabic manuscripts.


On Erd\H{o}s-Gallai and Havel-Hakimi algorithms

Abstract: Havel in 1955, Erd\H{o}s and Gallai in 1960, Hakimi in 1962, Ruskey, Cohen, Eades and Scott in 1994, Barnes and Savage in 1997, Kohnert in 2004, Tripathi, Venugopalan and West in 2010 proposed a method to decide, whether a sequence of nonnegative integers can be the degree sequence of a simple graph. The running time of their algorithms is $\Omega(n^2)$ in worst case. In this paper we propose a new algorithm called EGL (Erd\H{o}s-Gallai Linear algorithm), whose worst running time is $\Theta(n).$ As an application of this quick algorithm we computed the number of the different degree sequences of simple graphs for $24, ...,29$ vertices.


Lower bounds for finding the maximum and minimum elements with k lies

Abstract: In this paper we deal with the problem of finding the smallest and the largest elements of a totally ordered set of size $n$ using pairwise comparisons if $k$ of the comparisons might be erroneous where $k$ is a fixed constant. We prove that at least $(k+1.5)n+\Theta(k)$ comparisons are needed in the worst case thus disproving the conjecture that $(k+1+\epsilon)n$ comparisons are enough.


Cache optimized linear sieve

Abstract: Sieving is essential in different number theoretical algorithms. Sieving with large primes violates locality of memory access, thus degrading performance. Our suggestion on how to tackle this problem is to use cyclic data structures in combination with in-place bucket-sort. We present our results on the implementation of the sieve of Eratosthenes, using these ideas, which show that this approach is more robust and less affected by slow memory.


Approximating Fixation Probabilities in the Generalized Moran Process

Abstract: We consider the Moran process, as generalized by Lieberman, Hauert and Nowak (Nature, 433:312--316, 2005). A population resides on the vertices of a finite, connected, undirected graph and, at each time step, an individual is chosen at random with probability proportional to its assigned 'fitness' value. It reproduces, placing a copy of itself on a neighbouring vertex chosen uniformly at random, replacing the individual that was there. The initial population consists of a single mutant of fitness $r>0$ placed uniformly at random, with every other vertex occupied by an individual of fitness 1. The main quantities of interest are the probabilities that the descendants of the initial mutant come to occupy the whole graph (fixation) and that they die out (extinction); almost surely, these are the only possibilities. In general, exact computation of these quantities by standard Markov chain techniques requires solving a system of linear equations of size exponential in the order of the graph so is not feasible. We show that, with high probability, the number of steps needed to reach fixation or extinction is bounded by a polynomial in the number of vertices in the graph. This bound allows us to construct fully polynomial randomized approximation schemes (FPRAS) for the probability of fixation (when $r\geq 1$) and of extinction (for all $r>0$).


Fixing Data Anomalies with Prediction Based Algorithm in Wireless Sensor Networks

Abstract: Data inconsistencies are present in the data collected over a large wireless sensor network (WSN), usually deployed for any kind of monitoring applications. Before passing this data to some WSN applications for decision making, it is necessary to ensure that the data received are clean and accurate. In this paper, we have used a statistical tool to examine the past data to fit in a highly sophisticated prediction model i.e., ARIMA for a given sensor node and with this, the model corrects the data using forecast value if any data anomaly exists there. Another scheme is also proposed for detecting data anomaly at sink among the aggregated data in the data are received from a particular sensor node. The effectiveness of our methods are validated by data collected over a real WSN application consisting of Crossbow IRIS Motes \cite{Crossbow:2009}.


Privacy-Aware Mechanism Design

Abstract: In traditional mechanism design, agents only care about the utility they derive from the outcome of the mechanism. We look at a richer model where agents also assign non-negative dis-utility to the information about their private types leaked by the outcome of the mechanism. We present a new model for privacy-aware mechanism design, where we only assume an upper bound on the agents' loss due to leakage, as opposed to previous work where a full characterization of the loss was required. In this model, under a mild assumption on the distribution of how agents value their privacy, we show a generic construction of privacy-aware mechanisms and demonstrate its applicability to electronic polling and pricing of a digital good.


Speed scaling with power down scheduling for agreeable deadlines

Abstract: We consider the problem of scheduling on a single processor a given set of n jobs. Each job j has a workload w_j and a release time r_j. The processor can vary its speed and hibernate to reduce energy consumption. In a schedule minimizing overall consumed energy, it might be that some jobs complete arbitrarily far from their release time. So in order to guarantee some quality of service, we would like to impose a deadline d_j=r_j+F for every job j, where F is a guarantee on the *flow time*. We provide an O(n^3) algorithm for the more general case of *agreeable deadlines*, where jobs have release times and deadlines and can be ordered such that for every i<j, both r_i<=r_j and d_i<=d_j.


On context-free languages of scattered words

Abstract: It is known that if a B\"uchi context-free language (BCFL) consists of scattered words, then there is an integer $n$, depending only on the language, such that the Hausdorff rank of each word in the language is bounded by $n$. Every BCFL is a M\"uller context-free language (MCFL). In the first part of the paper, we prove that an MCFL of scattered words is a BCFL iff the rank of every word in the language is bounded by an integer depending only on the language. Then we establish operational characterizations of the BCFLs of well-ordered and scattered words. We prove that a language is a BCFL consisting of well-ordered words iff it can be generated from the singleton languages containing the letters of the alphabet by substitution into ordinary context-free languages and the $\omega$-power operation. We also establish a corresponding result for BCFLs of scattered words and define expressions denoting BCFLs of well-ordered and scattered words. In the final part of the paper we give some applications.


Extending the adverbial coverage of a NLP oriented resource for French

Abstract: This paper presents a work on extending the adverbial entries of LGLex: a NLP oriented syntactic resource for French. Adverbs were extracted from the Lexicon-Grammar tables of both simple adverbs ending in -ment '-ly' (Molinier and Levrier, 2000) and compound adverbs (Gross, 1986; 1990). This work relies on the exploitation of fine-grained linguistic information provided in existing resources. Various features are encoded in both LG tables and they haven't been exploited yet. They describe the relations of deleting, permuting, intensifying and paraphrasing that associate, on the one hand, the simple and compound adverbs and, on the other hand, different types of compound adverbs. The resulting syntactic resource is manually evaluated and freely available under the LGPL-LR license.


Preliminary Analysis of Google+'s Privacy

Abstract: In this paper we provide a preliminary analysis of Google+ privacy. We identified that Google+ shares photo metadata with users who can access the photograph and discuss its potential impact on privacy. We also identified that Google+ encourages the provision of other names including maiden name, which may help criminals performing identity theft. We show that Facebook lists are a superset of Google+ circles, both functionally and logically, even though Google+ provides a better user interface. Finally we compare the use of encryption and depth of privacy control in Google+ versus in Facebook.


Fully dynamic recognition of proper circular-arc graphs

Abstract: We present a fully dynamic algorithm for the recognition of proper circular-arc (PCA) graphs. The allowed operations on the graph involve the insertion and removal of vertices (together with its incident edges) or edges. Edge operations cost O(log n) time, where n is the number of vertices of the graph, while vertex operations cost O(log n + d) time, where d is the degree of the modified vertex. We also show incremental and decremental algorithms that work in O(1) time per inserted or removed edge. As part of our algorithm, fully dynamic connectivity and co-connectivity algorithms that work in O(log n) time per operation are obtained. Also, an O(\Delta) time algorithm for determining if a PCA representation corresponds to a co-bipartite graph is provided, where \Delta\ is the maximum among the degrees of the vertices. When the graph is co-bipartite, a co-bipartition of each of its co-components is obtained within the same amount of time.


Computing a visibility polygon using few variables

Abstract: We present several algorithms for computing the visibility polygon of a simple polygon $P$ from a viewpoint inside the polygon, when the polygon resides in read-only memory and only few working variables can be used. The first algorithm uses a constant number of variables, and outputs the vertices of the visibility polygon in $O(n\Rout)$ time, where $\Rout$ denotes the number of reflex vertices of $P$ that are part of the output. The next two algorithms use $O(\log \Rin)$ variables, and output the visibility polygon in $O(n\log \Rin)$ randomized expected time or $O(n\log^2 \Rin)$ deterministic time, where $\Rin$ is the number of reflex vertices of $P$.


Dynamic Tardos Traitor Tracing Schemes

Abstract: We construct binary dynamic traitor tracing schemes, where the number of watermark bits needed to trace and disconnect any coalition of pirates is quadratic in the number of pirates, and logarithmic in the total number of users and the error probability. Our results improve upon results of Tassa, and our schemes have several other advantages, such as being able to generate all codewords in advance, a simple accusation method, and flexibility when the feedback from the pirate network is delayed.


tym: Typed Matlab

Abstract: Although, many scientists and engineers use Octave or MATLAB as their preferred programming language, dynamic nature of these languages can lead to slower running-time of programs written in these languages compared to programs written in languages which are not as dynamic, like C, C++ and Fortran. In this work we developed a translator for a new programming language (tym) which tries to address performance issues, common in scientific programs, by adding new constructs to a subset of Octave/MATLAB language. Our translator compiles programs written in tym, to efficient C++ code.


The debts' clearing problem: a new approach

Abstract: The debts' clearing problem is about clearing all the debts in a group of $n$ entities (e.g. persons, companies) using a minimal number of money transaction operations. In our previous works we studied the problem, gave a dynamic programming solution solving it and proved that it is NP-hard. In this paper we adapt the problem to dynamic graphs and give a data structure to solve it. Based on this data structure we develop a new algorithm, that improves our previous one for the static version of the problem.


Modular exponentiation of matrices on FPGA-s

Abstract: We describe an efficient FPGA implementation for the exponentiation of large matrices. The research is related to an algorithm for constructing uniformly distributed linear recurring sequences. The design utilizes the special properties of both the FPGA and the used matrices to achieve a very significant speedup compared to traditional architectures.


Large primes in generalized Pascal triangles

Abstract: In this paper, after presenting the results of the generalization of Pascal triangle (using powers of base numbers), we examine some properties of the 112-based triangle, most of all regarding to prime numbers. Additionally, an effective implementation of ECPP method is presented which enables Magma computer algebra system to prove the primality of numbers with more than 1000 decimal digits.


C++ Standard Template Library by template specialized containers

Abstract: The C++ Standard Template Library is the flagship example for libraries based on the generic programming paradigm. The usage of this library is intended to minimize the number of classical C/C++ errors, but does not warrant bug-free programs. Furthermore, many new kinds of errors may arise from the inaccurate use of the generic programming paradigm, like dereferencing invalid iterators or misunderstanding remove-like algorithms. In this paper we present some typical scenarios that may cause runtime or portability problems. We emit warnings and errors while these risky constructs are used. We also present a general approach to emit "customized" warnings. We support the so-called "believe-me marks" to disable warnings. We present another typical usage of our technique, when classes become deprecated during the software lifecycle.


CBLOCK: An Automatic Blocking Mechanism for Large-Scale De-duplication Tasks

Abstract: De-duplication---identification of distinct records referring to the same real-world entity---is a well-known challenge in data integration. Since very large datasets prohibit the comparison of every pair of records, {\em blocking} has been identified as a technique of dividing the dataset for pairwise comparisons, thereby trading off {\em recall} of identified duplicates for {\em efficiency}. Traditional de-duplication tasks, while challenging, typically involved a fixed schema such as Census data or medical records. However, with the presence of large, diverse sets of structured data on the web and the need to organize it effectively on content portals, de-duplication systems need to scale in a new dimension to handle a large number of schemas, tasks and data sets, while handling ever larger problem sizes. In addition, when working in a map-reduce framework it is important that canopy formation be implemented as a {\em hash function}, making the canopy design problem more challenging. We present CBLOCK, a system that addresses these challenges. CBLOCK learns hash functions automatically from attribute domains and a labeled dataset consisting of duplicates. Subsequently, CBLOCK expresses blocking functions using a hierarchical tree structure composed of atomic hash functions. The application may guide the automated blocking process based on architectural constraints, such as by specifying a maximum size of each block (based on memory requirements), impose disjointness of blocks (in a grid environment), or specify a particular objective function trading off recall for efficiency. As a post-processing step to automatically generated blocks, CBLOCK {\em rolls-up} smaller blocks to increase recall. We present experimental results on two large-scale de-duplication datasets at Yahoo!---consisting of over 140K movies and 40K restaurants respectively---and demonstrate the utility of CBLOCK.


New Candidates Welcome! Possible Winners with respect to the Addition of New Candidates

Abstract: In voting contexts, some new candidates may show up in the course of the process. In this case, we may want to determine which of the initial candidates are possible winners, given that a fixed number $k$ of new candidates will be added. We give a computational study of this problem, focusing on scoring rules, and we provide a formal comparison with related problems such as control via adding candidates or cloning.


Channel Reordering with Time-shifted Streams to Improve Channel Change Latency in IPTV Networks

Abstract: In IPTV networks, channel change latency is considered as a major obstacle in achieving broadcast-level quality video delivery. Because of the bandwidth limitations observed at the client side, users typically have access to a limited number of channels. As a result, channel change requests oftentimes need to go through the network, thereby leading to significant delays. In this paper, we address this problem by proposing a resource-efficient time-shifted channel reordering mechanism to minimize the channel change latency. The proposed framework exploits the differing key-frame delivery times for the adjacent sessions to dynamically arrange the switching order during the surfing periods. The simulation results show that, with the proposed framework, more than 50% improvement can be achieved in channel change latency without introducing any overhead in the network.


A Bayesian Model for Plan Recognition in RTS Games applied to StarCraft

Abstract: The task of keyhole (unobtrusive) plan recognition is central to adaptive game AI. "Tech trees" or "build trees" are the core of real-time strategy (RTS) game strategic (long term) planning. This paper presents a generic and simple Bayesian model for RTS build tree prediction from noisy observations, which parameters are learned from replays (game logs). This unsupervised machine learning approach involves minimal work for the game developers as it leverage players' data (com- mon in RTS). We applied it to StarCraft1 and showed that it yields high quality and robust predictions, that can feed an adaptive AI.


The function space to describe the dynamics of linear systems

Abstract: Usually, the dynamics of linear time-invariant systems described by an integral operator of convolution type, which is defined in the Hilbert space of Lebesgue square integrable functions on the whole line. Such a description leads to contradictions. It is shown that the transition to the Hilbert space of almost periodic functions leads to the elimination of the detected inconsistencies. Multiple signals and interference with discrete spectrum are systems of sets. The properties of these systems lead to a new more effective method to combat noise in this space. The method used to identify the differential equations for the airbus. Baseline data were obtained during automatic landing.


CompChall: Addressing Password Guessing Attacks

Abstract: Even though passwords are the most convenient means of authentication, they bring along themselves the threat of dictionary attacks. Dictionary attacks may be of two kinds: online and offline. While offline dictionary attacks are possible only if the adversary is able to collect data for a successful protocol execution by eavesdropping on the communication channel and can be successfully countered using public key cryptography, online dictionary attacks can be performed by anyone and there is no satisfactory solution to counter them. This paper presents a new authentication protocol which is called CompChall (computational challenge). The proposed protocol uses only one way hash functions as the building blocks and attempts to eliminate online dictionary attacks by implementing a challenge-response system. This challenge-response system is designed in a fashion that it does not pose any difficulty to a genuine user but is time consuming and computationally intensive for an adversary trying to launch a large number of login requests per unit time as in the case of an online dictionary attack. The protocol is stateless and thus less vulnerable to DoS (Denial of Service) attacks.


Steganography and Steganalysis: Different Approaches

Abstract: Steganography is the technique of hiding confidential information within any media. Steganography is often confused with cryptography because the two are similar in the way that they both are used to protect confidential information. The difference between the two is in the appearance in the processed output; the output of steganography operation is not apparently visible but in cryptography the output is scrambled so that it can draw attention. Steganlysis is process to detect of presence of steganography. In this article we have tried to elucidate the different approaches towards implementation of steganography using 'multimedia' file (text, static image, audio and video) and Network IP datagram as cover. Also some methods of steganalysis will be discussed.


Offloadable Apps using SmartDiet: Towards an analysis toolkit for mobile application developers

Abstract: Offloading work to cloud is one of the proposed solutions for increasing the battery life of mobile devices. Most prior research has focused on computation-intensive applications, even though such applications are not the most popular ones. In this paper, we first study the feasibility of method-level offloading in network-intensive applications, using an open source Twitter client as an example. Our key observation is that implementing offloading transparently to the developer is difficult: various constraints heavily limit the offloading possibilities, and estimation of the potential benefit is challenging. We then propose a toolkit, SmartDiet, to assist mobile application developers in creating code which is suitable for energy-efficient offloading. SmartDiet provides fine-grained offloading constraint identification and energy usage analysis for Android applications. In addition to outlining the overall functionality of the toolkit, we study some of its key mechanisms and identify the remaining challenges.


Good Pairs of Adjacency Relations in Arbitrary Dimensions

Abstract: In this text we show, that the notion of a "good pair" that was introduced in the paper "Digital Manifolds and the Theorem of Jordan-Brouwer" has actually known models. We will show, how to choose cubical adjacencies, the generalizations of the well known 4- and 8-neighborhood to arbitrary dimensions, in order to find good pairs. Furthermore, we give another proof for the well known fact that the Khalimsky-topology implies good pairs. The outcome is consistent with the known theory as presented by T.Y. Kong, A. Rosenfeld, G.T. Herman and M. Khachan et.al and gives new insights in higher dimensions.


Minimum degree, independence number and pseudo [2,b]-factors in graphs

Abstract: A pseudo [2,b]-factor of a graph G is a spanning subgraph in which each component C on at least three vertices is a [2,b]-graph. The main contibution of this paper, is to give an upper bound to the number of components that are edges or vertices in a pseudo [2,b]-factor of a graph G. This bound is sharp.


Equilibrium and Potential in Coalitional Congestion Games

Abstract: The model of congestion games is widely used to analyze games related to traffic and communication. A central property of these games is that they are potential games and hence posses a pure Nash equilibrium. In reality it is often the case that some players cooperatively decide on their joint action in order to maximize the coalition's total utility. This is by modeled by Coalitional Congestion Games. Typical settings include truck drivers who work for the same shipping company, or routers that belong to the same ISP. The formation of coalitions will typically imply that the resulting coalitional congestion game will no longer posses a pure Nash equilibrium. In this paper we provide conditions under which such games are potential games and posses a pure Nash equilibrium.


Model-based Utility Functions

Abstract: Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.


The Object Projection Feature Estimation Problem in Unsupervised Markerless 3D Motion Tracking

Abstract: 3D motion tracking is a critical task in many computer vision applications. Existing 3D motion tracking techniques require either a great amount of knowledge on the target object or specific hardware. These requirements discourage the wide spread of commercial applications based on 3D motion tracking. 3D motion tracking systems that require no knowledge on the target object and run on a single low-budget camera require estimations of the object projection features (namely, area and position). In this paper, we define the object projection feature estimation problem and we present a novel 3D motion tracking system that needs no knowledge on the target object and that only requires a single low-budget camera, as installed in most computers and smartphones. Our system estimates, in real time, the three-dimensional position of a non-modeled unmarked object that may be non-rigid, non-convex, partially occluded, self occluded, or motion blurred, given that it is opaque, evenly colored, and enough contrasting with the background in each frame. Our system is also able to determine the most relevant object to track in the screen. Our 3D motion tracking system does not impose hard constraints, therefore it allows a market-wide implementation of applications that use 3D motion tracking.


A Tool for Model-Based Language Specification

Abstract: Formal languages let us define the textual representation of data with precision. Formal grammars, typically in the form of BNF-like productions, describe the language syntax, which is then annotated for syntax-directed translation and completed with semantic actions. When, apart from the textual representation of data, an explicit representation of the corresponding data structure is required, the language designer has to devise the mapping between the suitable data model and its proper language specification, and then develop the conversion procedure from the parse tree to the data model instance. Unfortunately, whenever the format of the textual representation has to be modified, changes have to propagated throughout the entire language processor tool chain. These updates are time-consuming, tedious, and error-prone. Besides, in case different applications use the same language, several copies of the same language specification have to be maintained. In this paper, we introduce a model-based parser generator that decouples language specification from language processing, hence avoiding many of the problems caused by grammar-driven parsers and parser generators.


The Numerical Generalized Least-Squares Estimator of an Unknown Constant Mean of Random Field

Abstract: We constraint on computer the best linear unbiased generalized statistics of random field for the best linear unbiased generalized statistics of an unknown constant mean of random field and derive the numerical generalized least-squares estimator of an unknown constant mean of random field. We derive the third constraint of spatial statistics and show that the classic generalized least-squares estimator of an unknown constant mean of the field is only an asymptotic disjunction of the numerical one.


Complexity of the path avoiding forbidden pairs problem revisited

Abstract: Let G = (V, E) be a directed acyclic graph with two distinguished vertices s, t and let F be a set of forbidden pairs of vertices. We say that a path in G is safe, if it contains at most one vertex from each pair {u, v} in F. Given G and F, the path avoiding forbidden pairs (PAFP) problem is to find a safe s-t path in G. We systematically study the complexity of different special cases of the PAFP problem defined according to the mutual positions of forbidden pairs. Fix one topological ordering of vertices; we say that pairs {u, v} and {x, y} are disjoint, if u, v < x, y, nested, if u < x, y < v, and halving, if u < x < v < y. The PAFP problem is known to be NP-hard in general or if no two pairs are disjoint; we prove that it remains NP-hard even when no two forbidden pairs are nested. On the other hand, if no two pairs are halving, the problem is known to be solvable in cubic time. We simplify and improve this result by showing an O(M(n)) time algorithm, where M(n) is the time to multiply two n \times n boolean matrices.


Proposed Cellular Network for Indian Conditions for Enhancement of Spectral Density and Reduction of Power Consumption & RF Pollution

Abstract: With the exponentially increasing demand for wireless communications the capacity of current cellular systems will soon become incapable of handling the growing traffic. Since radio frequencies are diminishing natural resources, there seems to be a fundamental barrier to further capacity increase. The solution can be found by using smart antenna systems. Smart or adaptive antenna arrays consist of an array of antenna elements with signal processing capability that optimizes the radiation and reception of a desired signal, dynamically. Smart antenna can place nulls in the direction of interferers via adapting adaptive updating of weights linked to each antenna element. They thus cancel out most of the cochannel interference resulting in better quality of reception and lower dropped calls. Smart antenna can also track the user within a cell via direction of arrival algorithms. This paper focuses on about the smart antenna in hierarchical cell clustering (overlay-underlay) with demand based frequency allocation techniques in cellular mobile radio networks in INDIA.


VoIP Call Optimization in Diverse Network Scenarios Using Learning Based State-Space Search Technique

Abstract: A VoIP based call has stringent QoS requirements with respect to delay, jitter, loss, MOS and R-Factor. Various QoS mechanisms implemented to satisfy these requirements must be adaptive under diverse network scenarios and applied in proper sequence, otherwise they may conflict with each other. The objective of this paper is to address the problem of adaptive QoS maintenance and sequential execution of available QoS implementation mechanisms with respect to VoIP under varying network conditions. In this paper, we generalize this problem as state-space problem and solve it. Firstly, we map the problem of QoS optimization into state-space domain and apply incremental heuristic search. We implement the proposed algorithm under various network and user scenarios in a VoIP test-bed for QoS enhancement. Then learning strategy is implemented for refinement of knowledge base to improve the performance of call quality over time. Finally, we discuss the advantages and uniqueness of our approach.


A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network

Abstract: Facial Expression Classification is an interesting research problem in recent years. There are a lot of methods to solve this problem. In this research, we propose a novel approach using Canny, Principal Component Analysis (PCA) and Artificial Neural Network. Firstly, in preprocessing phase, we use Canny for local region detection of facial images. Then each of local region's features will be presented based on Principal Component Analysis (PCA). Finally, using Artificial Neural Network (ANN)applies for Facial Expression Classification. We apply our proposal method (Canny_PCA_ANN) for recognition of six basic facial expressions on JAFFE database consisting 213 images posed by 10 Japanese female models. The experimental result shows the feasibility of our proposal method.


Unbiased Statistics of a CSP - A Controlled-Bias Generator

Abstract: We show that estimating the complexity (mean and distribution) of the instances of a fixed size Constraint Satisfaction Problem (CSP) can be very hard. We deal with the main two aspects of the problem: defining a measure of complexity and generating random unbiased instances. For the first problem, we rely on a general framework and a measure of complexity we presented at CISSE08. For the generation problem, we restrict our analysis to the Sudoku example and we provide a solution that also explains why it is so difficult.


Different types of attacks in Mobile ADHOC Network

Abstract: Security in mobile AD HOC network is a big challenge as it has no centralized authority which can supervise the individual nodes operating in the network. The attacks can come from both inside the network and from the outside. We are trying to classify the existing attacks into two broad categories: DATA traffic attacks and CONTROL traffic attacks. We will also be discussing the presently proposed methods of mitigating those attacks.


Unpredictability and Computational Irreducibility

Abstract: We explore several concepts for analyzing the intuitive notion of computational irreducibility and we propose a robust formal definition, first in the field of cellular automata and then in the general field of any computable function f from N to N. We prove that, through a robust definition of what means "to be unable to compute the nth step without having to follow the same path than simulating the automaton or the function", this implies genuinely, as intuitively expected, that if the behavior of an object is computationally irreducible, no computation of its nth state can be faster than the simulation itself.


Matrix Inversion Using Cholesky Decomposition

Abstract: In this paper we present a method for matrix inversion based on Cholesky decomposition with reduced number of operations by avoiding computation of intermediate results; further, we use fixed point simulations to compare the numerical accuracy of the method.


A Model of Spatial Thinking for Computational Intelligence

Abstract: Trying to be effective (no matter who exactly and in what field) a person face the problem which inevitably destroys all our attempts to easily get to a desired goal. The problem is the existence of some insuperable barriers for our mind, anotherwords barriers for principles of thinking. They are our clue and main reason for research. Here we investigate these barriers and their features exposing the nature of mental process. We start from special structures which reflect the ways to define relations between objects. Then we came to realizing about what is the material our mind uses to build thoughts, to make conclusions, to understand, to form reasoning, etc. This can be called a mental dynamics. After this the nature of mental barriers on the required level of abstraction as well as the ways to pass through them became clear. We begin to understand why thinking flows in such a way, with such specifics and with such limitations we can observe in reality. This can help us to be more optimal. At the final step we start to understand, what ma-thematical models can be applied to such a picture. We start to express our thoughts in a language of mathematics, developing an apparatus for our Spatial Theory of Mind, suitable to represent processes and infrastructure of thinking. We use abstract algebra and stay invariant in relation to the nature of objects.


Control Neuronal por Modelo Inverso de un Servosistema Usando Algoritmos de Aprendizaje Levenberg-Marquardt y Bayesiano

Abstract: In this paper we present the experimental results of the neural network control of a servo-system in order to control its speed. The control strategy is implemented by using an inverse-model control based on Artificial Neural Networks (ANNs). The network training was performed using two learning algorithms: Levenberg-Marquardt and Bayesian regularization. We evaluate the generalization capability for each method according to both the correct operation of the controller to follow the reference signal, and the control efforts developed by the ANN-based controller.


Elastic Fidelity: Trading-off Computational Accuracy for Energy Reduction

Abstract: Power dissipation and energy consumption have become one of the most important problems in the design of processors today. This is especially true in power-constrained environments, such as embedded and mobile computing. While lowering the operational voltage can reduce power consumption, there are limits imposed at design time, beyond which hardware components experience faulty operation. Moreover, the decrease in feature size has led to higher susceptibility to process variations, leading to reliability issues and lowering yield. However, not all computations and all data in a workload need to maintain 100% fidelity. In this paper, we explore the idea of employing functional or storage units that let go the conservative guardbands imposed on the design to guarantee reliable execution. Rather, these units exhibit Elastic Fidelity, by judiciously lowering the voltage to trade-off reliable execution for power consumption based on the error guarantees required by the executing code. By estimating the accuracy required by each computational segment of a workload, and steering each computation to different functional and storage units, Elastic Fidelity Computing obtains power and energy savings while reaching the reliability targets required by each computational segment. Our preliminary results indicate that even with conservative estimates, Elastic Fidelity can reduce the power and energy consumption of a processor by 11-13% when executing applications involving human perception that are typically included in modern mobile platforms, such as audio, image, and video decoding.


Parametric Estimation of the Ultimate Size of Hypercomputers

Abstract: The performance of the emerging petaflops-scale supercomputers of the nearest future (hypercomputers) will be governed not only by the clock frequency of the processing nodes or by the width of the system bus, but also by such factors as the overall power consumption and the geometric size. In this paper, we study the influence of such parameters on one of the most important characteristics of a general purpose computer - on the degree of multithreading that must be present in an application to make the use of the hypercomputer justifiable. Our major finding is that for the class of applications with purely random memory access patterns "super-fast computing" and "high-performance computing" are essentially synonyms for "massively-parallel computing."


A Single Euler Number Feature for Multi-font Multi-size Kannada Numeral Recognition

Abstract: In this paper a novel approach is proposed based on single Euler number feature which is free from thinning and size normalization for multi-font and multi-size Kannada numeral recognition system. A nearest neighbor classification is used for classification of Kannada numerals by considering the Euclidian distance. A total 1500 numeral images with different font sizes between (10..84) are tested for algorithm efficiency and the overall the classification accuracy is found to be 99.00% .The said method is thinning free, fast, and showed encouraging results on varying font styles and sizes of Kannada numerals.


Multi-font Multi-size Kannada Numeral Recognition Based on Structural Features

Abstract: In this paper a fast and novel method is proposed for multi-font multi-size Kannada numeral recognition which is thinning free and without size normalization approach. The different structural feature are used for numeral recognition namely, directional density of pixels in four directions, water reservoirs, maximum profile distances, and fill hole density are used for the recognition of Kannada numerals. A Euclidian minimum distance criterion is used to find minimum distances and K-nearest neighbor classifier is used to classify the Kannada numerals by varying the size of numeral image from 16 to 50 font sizes for the 20 different font styles from NUDI and BARAHA popular word processing Kannada software. The total 1150 numeral images are tested and the overall accuracy of classification is found to be 100%. The average time taken by this method is 0.1476 seconds.


Battling the Internet Water Army: Detection of Hidden Paid Posters

Abstract: We initiate a systematic study to help distinguish a special group of online users, called hidden paid posters, or termed "Internet water army" in China, from the legitimate ones. On the Internet, the paid posters represent a new type of online job opportunity. They get paid for posting comments and new threads or articles on different online communities and websites for some hidden purposes, e.g., to influence the opinion of other people towards certain social events or business markets. Though an interesting strategy in business marketing, paid posters may create a significant negative effect on the online communities, since the information from paid posters is usually not trustworthy. When two competitive companies hire paid posters to post fake news or negative comments about each other, normal online users may feel overwhelmed and find it difficult to put any trust in the information they acquire from the Internet. In this paper, we thoroughly investigate the behavioral pattern of online paid posters based on real-world trace data. We design and validate a new detection mechanism, using both non-semantic analysis and semantic analysis, to identify potential online paid posters. Our test results with real-world datasets show a very promising performance.


The Feedback Arc Set Problem with Triangle Inequality is a Vertex Cover Problem

Abstract: We consider the (precedence constrained) Minimum Feedback Arc Set problem with triangle inequalities on the weights, which finds important applications in problems of ranking with inconsistent information. We present a surprising structural insight showing that the problem is a special case of the minimum vertex cover in hypergraphs with edges of size at most 3. This result leads to combinatorial approximation algorithms for the problem and opens the road to studying the problem as a vertex cover problem.


Star-Free Languages are Church-Rosser Congruential

Abstract: The class of Church-Rosser congruential languages has been introduced by McNaughton, Narendran, and Otto in 1988. A language L is Church-Rosser congruential (belongs to CRCL), if there is a finite, confluent, and length-reducing semi-Thue system S such that L is a finite union of congruence classes modulo S. To date, it is still open whether every regular language is in CRCL. In this paper, we show that every star-free language is in CRCL. In fact, we prove a stronger statement: For every star-free language L there exists a finite, confluent, and subword-reducing semi-Thue system S such that the total number of congruence classes modulo S is finite and such that L is a union of congruence classes modulo S. The construction turns out to be effective.


Homomorphic encryption from codes

Abstract: We propose a new homomorphic encryption scheme based on the hardness of decoding under independent random noise from certain affine families of codes. Unlike in previous lattice-based homomorphic encryption schemes, where the message is hidden in the noisy part of the ciphertext, our scheme carries the message in the affine part of the transformation and applies noise only to achieve security. Our scheme can tolerate noise of arbitrary magnitude, as long as the noise vector has sufficiently small hamming weight (and its entries are independent). Our design achieves "proto-homomorphic" properties in an elementary manner: message addition and multiplication are emulated by pointwise addition and multiplication of the ciphertext vectors. Moreover, the extremely simple nature of our decryption makes the scheme easily amenable to bootstrapping. However, some complications are caused by the inherent presence of noticeable encryption error. Our main technical contribution is the development of two new techniques for handling this error in the homomorphic evaluation process. We also provide a definitional framework for homomorphic encryption that may be useful elsewhere.


Semantic Navigation on the Web of Data: Specification of Routes, Web Fragments and Actions

Abstract: The massive semantic data sources linked in the Web of Data give new meaning to old features like navigation; introduce new challenges like semantic specification of Web fragments; and make it possible to specify actions relying on semantic data. In this paper we introduce a declarative language to face these challenges. Based on navigational features, it is designed to specify fragments of the Web of Data and actions to be performed based on these data. We implement it in a centralized fashion, and show its power and performance. Finally, we explore the same ideas in a distributed setting, showing their feasibility, potentialities and challenges.


Energy Aware Node Selection for Cluster-based Data Accuracy Estimation in Wireless Sensor Networks

Abstract: The main objective of this paper is to reduce the number of sensor nodes by estimating a trade off between data accuracy and energy consumption for selecting nodes in probabilistic approach in distributed networks. Design Procedure/Approach: Observed data are highly correlated among sensor nodes in the spatial domain due to deployment of high density of sensor nodes. These sensor nodes form non-overlapping distributed clusters due to high data correlation among them. We develop a probabilistic model for each distributed cluster to perform data accuracy and energy consumption model in the network. Finally we find a trade off between data accuracy and energy consumption model to select an optimal number of sensor nodes in each distributed cluster. We also compare the performance for our data accuracy estimation model with information accuracy model for each distributed cluster in the network. Practical Implementation: Measuring temperature in physical environment and measuring moisture content in agricultural field. Inventive /Novel Idea: Optimal node selection in probabilistic approach using the trade of between data accuracy and energy consumption in cluster-based distributed network.


Question Answering in a Natural Language Understanding System Based on Object-Oriented Semantics

Abstract: Algorithms of question answering in a computer system oriented on input and logical processing of text information are presented. A knowledge domain under consideration is social behavior of a person. A database of the system includes an internal representation of natural language sentences and supplemental information. The answer {\it Yes} or {\it No} is formed for a general question. A special question containing an interrogative word or group of interrogative words permits to find a subject, object, place, time, cause, purpose and way of action or event. Answer generation is based on identification algorithms of persons, organizations, machines, things, places, and times. Proposed algorithms of question answering can be realized in information systems closely connected with text processing (criminology, operation of business, medicine, document systems).


Incentive Mechanisms for Hierarchical Spectrum Markets

Abstract: In this paper, we study spectrum allocation mechanisms in hierarchical multi-layer markets which are expected to proliferate in the near future based on the current spectrum policy reform proposals. We consider a setting where a state agency sells spectrum channels to Primary Operators (POs) who subsequently resell them to Secondary Operators (SOs) through auctions. We show that these hierarchical markets do not result in a socially efficient spectrum allocation which is aimed by the agency, due to lack of coordination among the entities in different layers and the inherently selfish revenue-maximizing strategy of POs. In order to reconcile these opposing objectives, we propose an incentive mechanism which aligns the strategy and the actions of the POs with the objective of the agency, and thus leads to system performance improvement in terms of social welfare. This pricing-based scheme constitutes a method for hierarchical market regulation. A basic component of the proposed incentive mechanism is a novel auction scheme which enables POs to allocate their spectrum by balancing their derived revenue and the welfare of the SOs.


An additivity theorem for plain Kolmogorov complexity

Abstract: We prove the formula C(a,b) = K(a|C(a,b)) + C(b|a,C(a,b)) + O(1) that expresses the plain complexity of a pair in terms of prefix and plain conditional complexities of its components.


Model Checking CSL for Markov Population Models

Abstract: Markov population models (MPMs) are a widely used modelling formalism in the area of computational biology and related areas. The semantics of a MPM is an infinite-state continuous-time Markov chain. In this paper, we use the established continuous stochastic logic (CSL) to express properties of Markov population models. This allows us to express important measures of biological systems, such as probabilistic reachability, survivability, oscillations, switching times between attractor regions, and various others. Because of the infinite state space, available analysis techniques only apply to a very restricted subset of CSL properties. We present a full algorithm for model checking CSL for MPMs, and provide experimental evidence showing that our method is effective.


Practical Top-K Document Retrieval in Reduced Space

Abstract: Supporting top-k document retrieval queries on general text databases, that is, finding the k documents where a given pattern occurs most frequently, has become a topic of interest with practical applications. While the problem has been solved in optimal time and linear space, the actual space usage is a serious concern. In this paper we study various reduced-space structures that support top-k retrieval and propose new alternatives. Our experimental results show that our novel algorithms and data structures dominate almost all the space/time tradeoff.