Feedback control logic synthesis for non safe Petri nets

Abstract: This paper addresses the problem of forbidden states of non safe Petri Net (PN) modelling discrete events systems. To prevent the forbidden states, it is possible to use conditions or predicates associated with transitions. Generally, there are many forbidden states, thus many complex conditions are associated with the transitions. A new idea for computing predicates in non safe Petri nets will be presented. Using this method, we can construct a maximally permissive controller if it exists.


Perceptual analyses of action-related impact sounds

Abstract: Among environmental sounds, we have chosen to study a class of action-related impact sounds: automobile door closure sounds. We propose to describe these sounds using a model composed of perceptual properties. The development of the perceptual model was derived from the evaluation of many door closure sounds measured under controlled laboratory listening conditions. However, listening to such sounds normally occurs within a natural context, which probably modifies their perception. We therefore need to study differences between the real situation and the laboratory situation by following standard practices in order to specify the precise listening conditions and observe the influence of previous learning, expectations, action-perception interactions, and attention given to sounds. Our process consists in doing in situ experiments that are compared with specific laboratory experiments in order to isolate certain influential, context dependent components.


Doubly Perfect Nonlinear Boolean Permutations

Abstract: Due to implementation constraints the XOR operation is widely used in order to combine plaintext and key bit-strings in secret-key block ciphers. This choice directly induces the classical version of the differential attack by the use of XOR-kind differences. While very natural, there are many alternatives to the XOR. Each of them inducing a new form for its corresponding differential attack (using the appropriate notion of difference) and therefore block-ciphers need to use S-boxes that are resistant against these nonstandard differential cryptanalysis. In this contribution we study the functions that offer the best resistance against a differential attack based on a finite field multiplication. We also show that in some particular cases, there are robust permutations which offers the best resistant against both multiplication and exponentiation base differential attacks. We call them doubly perfect nonlinear permutations.


Common Frame of reference in collaborative virtual environments and their impact on presence

Abstract: Virtual collaborative environment are 3D shared spaces in which people can work together. To collaborate through these systems, users must have a shared comprehension of the environment. The objective of this experimental study was to determine if visual stable landmarks improve the construction of a common representation of the virtual environment and thus facilitate collaboration. This seems to increase the awareness of the partner's presence.


Approximate Dynamic Programming using Halfspace Queries and Multiscale Monge decomposition

Abstract: Let $P=(P_1, P_2, \ldots, P_n)$, $P_i \in \field{R}$ for all $i$, be a signal and let $C$ be a constant. In this work our goal is to find a function $F:[n]\rightarrow \field{R}$ which optimizes the following objective function: $$ \min_{F} \sum_{i=1}^n (P_i-F_i)^2 + C\times |\{i:F_i \neq F_{i+1} \} | $$ The above optimization problem reduces to solving the following recurrence, which can be done efficiently using dynamic programming in $O(n^2)$ time: $$ OPT_i = \min_{0 \leq j \leq i-1} [ OPT_j + \sum_{k=j+1}^i (P_k - (\sum_{m=j+1}^i P_m)/(i-j) )^2 ]+ C $$ The above recurrence arises naturally in applications where we wish to approximate the original signal $P$ with another signal $F$ which consists ideally of few piecewise constant segments. Such applications include database (e.g., histogram construction), speech recognition, biology (e.g., denoising aCGH data) applications and many more. In this work we present two new techniques for optimizing dynamic programming that can handle cost functions not treated by other standard methods. The basis of our first algorithm is the definition of a constant-shifted variant of the objective function that can be efficiently approximated using state of the art methods for range searching. Our technique approximates the optimal value of our objective function within additive $\epsilon$ error and runs in $\tilde{O}(n^{1.5} \log{(\frac{U}{\epsilon}))}$ time, where $U = \max_i f_i$. The second algorithm we provide solves a similar recurrence within a factor of $\epsilon$ and runs in $O(n \log^2n / \epsilon)$. The new technique introduced by our algorithm is the decomposition of the initial problem into a small (logarithmic) number of Monge optimization subproblems which we can speed up using existing techniques.


Bounded Degree Planar Geometric Spanners

Abstract: Given a set $P$ of $n$ points in the plane, we show how to compute in $O(n \log n)$ time a subgraph of their Delaunay triangulation that has maximum degree 7 and is a strong planar $t$-spanner of $P$ with $t =(1+ \sqrt{2})^2 *\delta$, where $\delta$ is the spanning ratio of the Delaunay triangulation. Furthermore, given a Delaunay triangulation, we show a distributed algorithm that computes the same bounded degree planar spanner in O(n) time.


Local Popularity based Page Link Analysis

Abstract: In this paper we introduce the concept of dynamic link pages. A web site/page contains a number of links to other pages. All the links are not equally important. Few links are more frequently visited and few rarely visited. In this scenario, identifying the frequently used links and placing them in the top left corner of the page will increase the user's satisfaction. This process will reduce the time spent by a visitor on the page, as most of the times, the popular links are presented in the visible part of the screen itself. Also, a site can be indexed based on the popular links in that page. This will increase the efficiency of the retrieval system. We presented a model to display the popular links, and also proposed a method to increase the quality of retrieval system.


Cubes convexes

Abstract: In various approaches, data cubes are pre-computed in order to answer efficiently OLAP queries. The notion of data cube has been declined in various ways: iceberg cubes, range cubes or differential cubes. In this paper, we introduce the concept of convex cube which captures all the tuples of a datacube satisfying a constraint combination. It can be represented in a very compact way in order to optimize both computation time and required storage space. The convex cube is not an additional structure appended to the list of cube variants but we propose it as a unifying structure that we use to characterize, in a simple, sound and homogeneous way, the other quoted types of cubes. Finally, we introduce the concept of emerging cube which captures the significant trend inversions. characterizations.


Transparent Anonymization: Thwarting Adversaries Who Know the Algorithm

Abstract: Numerous generalization techniques have been proposed for privacy preserving data publishing. Most existing techniques, however, implicitly assume that the adversary knows little about the anonymization algorithm adopted by the data publisher. Consequently, they cannot guard against privacy attacks that exploit various characteristics of the anonymization mechanism. This paper provides a practical solution to the above problem. First, we propose an analytical model for evaluating disclosure risks, when an adversary knows everything in the anonymization process, except the sensitive values. Based on this model, we develop a privacy principle, transparent l-diversity, which ensures privacy protection against such powerful adversaries. We identify three algorithms that achieve transparent l-diversity, and verify their effectiveness and efficiency through extensive experiments with real data.


Resilient networking in wireless sensor networks

Abstract: This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR).


Towards increasing diversity for the relaying of LT Fountain Codes in Wireless Sensor Networks

Abstract: Diversity is a powerful means to increase the transmission performance of wireless communications. For the case of fountain codes relaying, it has been shown previously that introducing diversity is also beneficial since it counteracts transmission losses on the channel. Instead of simply hop-by-hop forwarding information, each sensor node diversifies the information flow using XOR combinations of stored packets. This approach has been shown to be efficient for random linear fountain codes. However, random linear codes exhibit high decoding complexity. In this paper, we propose diversity increased relaying strategies for the more realistic Luby Transform code in order to maintain high transmission performance with low decoding computational complexity in a linear network. Results are provided herein for a linear network assuming uniform imperfect channel states.


LEXSYS: Architecture and Implication for Intelligent Agent systems

Abstract: LEXSYS, (Legume Expert System) was a project conceived at IITA (International Institute of Tropical Agriculture) Ibadan Nigeria. It was initiated by the COMBS (Collaborative Group on Maize-Based Systems Research in the 1990. It was meant for a general framework for characterizing on-farm testing for technology design for sustainable cereal-based cropping system. LEXSYS is not a true expert system as the name would imply, but simply a user-friendly information system. This work is an attempt to give a formal representation of the existing system and then present areas where intelligent agent can be applied.


Lazy Evaluation and Delimited Control

Abstract: The call-by-need lambda calculus provides an equational framework for reasoning syntactically about lazy evaluation. This paper examines its operational characteristics. By a series of reasoning steps, we systematically unpack the standard-order reduction relation of the calculus and discover a novel abstract machine definition which, like the calculus, goes "under lambdas." We prove that machine evaluation is equivalent to standard-order evaluation. Unlike traditional abstract machines, delimited control plays a significant role in the machine's behavior. In particular, the machine replaces the manipulation of a heap using store-based effects with disciplined management of the evaluation stack using control-based effects. In short, state is replaced with control. To further articulate this observation, we present a simulation of call-by-need in a call-by-value language using delimited control operations.


Active Testing for Face Detection and Localization

Abstract: We provide a novel search technique, which uses a hierarchical model and a mutual information gain heuristic to efficiently prune the search space when localizing faces in images. We show exponential gains in computation over traditional sliding window approaches, while keeping similar performance levels.


Enforcing the non-negativity constraint and maximum principles for diffusion with decay on general computational grids

Abstract: In this paper, we consider anisotropic diffusion with decay, and the diffusivity coefficient to be a second-order symmetric and positive definite tensor. It is well-known that this particular equation is a second-order elliptic equation, and satisfies a maximum principle under certain regularity assumptions. However, the finite element implementation of the classical Galerkin formulation for both anisotropic and isotropic diffusion with decay does not respect the maximum principle. We first show that the numerical accuracy of the classical Galerkin formulation deteriorates dramatically with increase in the decay coefficient for isotropic medium and violates the discrete maximum principle. However, in the case of isotropic medium, the extent of violation decreases with mesh refinement. We then show that, in the case of anisotropic medium, the classical Galerkin formulation for anisotropic diffusion with decay violates the discrete maximum principle even at lower values of decay coefficient and does not vanish with mesh refinement. We then present a methodology for enforcing maximum principles under the classical Galerkin formulation for anisotropic diffusion with decay on general computational grids using optimization techniques. Representative numerical results (which take into account anisotropy and heterogeneity) are presented to illustrate the performance of the proposed formulation.


Determinating Timing Channels in Compute Clouds

Abstract: Timing side-channels represent an insidious security challenge for cloud computing, because: (a) massive parallelism in the cloud makes timing channels pervasive and hard to control; (b) timing channels enable one customer to steal information from another without leaving a trail or raising alarms; (c) only the cloud provider can feasibly detect and report such attacks, but the provider's incentives are not to; and (d) resource partitioning schemes for timing channel control undermine statistical sharing efficiency, and, with it, the cloud computing business model. We propose a new approach to timing channel control, using provider-enforced deterministic execution instead of resource partitioning to eliminate timing channels within a shared cloud domain. Provider-enforced determinism prevents execution timing from affecting the results of a compute task, however large or parallel, ensuring that a task's outputs leak no timing information apart from explicit timing inputs and total compute duration. Experiments with a prototype OS for deterministic cloud computing suggest that such an approach may be practical and efficient. The OS supports deterministic versions of familiar APIs such as processes, threads, shared memory, and file systems, and runs coarse-grained parallel tasks as efficiently and scalably as current timing channel-ridden systems.


Review of Lattice-based Public key Cryptography(Russian)

Abstract: This article presets a review of the achievements rapidly developing field of cryptography - public-key cryptography based on the lattice theory. Paper contains the necessary basic concepts and the major problems of the lattice theory, as well as together with the description on the benefits of this cryptography class - the properties of the reliability to quantum computers and full homomorphism, the shortcomings of specific implementations.


Rational Value of Information Estimation for Measurement Selection

Abstract: Computing value of information (VOI) is a crucial task in various aspects of decision-making under uncertainty, such as in meta-reasoning for search; in selecting measurements to make, prior to choosing a course of action; and in managing the exploration vs. exploitation tradeoff. Since such applications typically require numerous VOI computations during a single run, it is essential that VOI be computed efficiently. We examine the issue of anytime estimation of VOI, as frequently it suffices to get a crude estimate of the VOI, thus saving considerable computational resources. As a case study, we examine VOI estimation in the measurement selection problem. Empirical evaluation of the proposed scheme in this domain shows that computational resources can indeed be significantly reduced, at little cost in expected rewards achieved in the overall decision problem.


The Video Genome

Abstract: Fast evolution of Internet technologies has led to an explosive growth of video data available in the public domain and created unprecedented challenges in the analysis, organization, management, and control of such content. The problems encountered in video analysis such as identifying a video in a large database (e.g. detecting pirated content in YouTube), putting together video fragments, finding similarities and common ancestry between different versions of a video, have analogous counterpart problems in genetic research and analysis of DNA and protein sequences. In this paper, we exploit the analogy between genetic sequences and videos and propose an approach to video analysis motivated by genomic research. Representing video information as video DNA sequences and applying bioinformatic algorithms allows to search, match, and compare videos in large-scale databases. We show an application for content-based metadata mapping between versions of annotated video.


Stable Nash equilibria of medium access games under symmetric, socially altruistic behavior

Abstract: We consider the effects of altruistic behavior on random medium access control (slotted ALOHA) for local area communication networks. For an idealized, synchronously iterative, two-player game with asymmetric player demands, we find a Hamiltonian governing the Jacobi dynamics under purely altruistic behavior. Though the positions of the interior Nash equilibrium points do not change in the presence of altruistic behavior, the nature of their local asymptotic stability does. There is a region of partially altruistic behavior for which neither interior Nash equilibrium point is locally asymptotically stable. Also, for a power control game with a single Nash equilibrium, we show how its stability changes as a function of the altruism parameter. Variations of these altruistic game frameworks are discussed considering power (instead of throughput) based costs and linear utility functions.


Truth and Envy in Capacitated Allocation Games

Abstract: We study auctions with additive valuations where agents have a limit on the number of goods they may receive. We refer to such valuations as {\em capacitated} and seek mechanisms that maximize social welfare and are simultaneously incentive compatible, envy-free, individually rational, and have no positive transfers. If capacities are infinite, then sequentially repeating the 2nd price Vickrey auction meets these requirements. In 1983, Leonard showed that for unit capacities, VCG with Clarke Pivot payments is also envy free. For capacities that are all unit or all infinite, the mechanism produces a Walrasian pricing (subject to capacity constraints). Here, we consider general capacities. For homogeneous capacities (all capacities equal) we show that VCG with Clarke Pivot payments is envy free (VCG with Clarke Pivot payments is always incentive compatible, individually rational, and has no positive transfers). Contrariwise, there is no incentive compatible Walrasian pricing. For heterogeneous capacities, we show that there is no mechanism with all 4 properties, but at least in some cases, one can achieve both incentive compatibility and envy freeness.


On the Interplay between Incentive Compatibility and Envy Freeness

Abstract: We study mechanisms for an allocation of goods among agents, where agents have no incentive to lie about their true values (incentive compatible) and for which no agent will seek to exchange outcomes with another (envy-free). Mechanisms satisfying each requirement separately have been studied extensively, but there are few results on mechanisms achieving both. We are interested in those allocations for which there exist payments such that the resulting mechanism is simultaneously incentive compatible and envy-free. Cyclic monotonicity is a characterization of incentive compatible allocations, local efficiency is a characterization for envy-free allocations. We combine the above to give a characterization for allocations which are both incentive compatible and envy free. We show that even for allocations that allow payments leading to incentive compatible mechanisms, and other payments leading to envy free mechanisms, there may not exist any payments for which the mechanism is simultaneously incentive compatible and envy-free. The characterization that we give lets us compute the set of Pareto-optimal mechanisms that trade off envy freeness for incentive compatibility.


Lin-Kernighan Heuristic Adaptations for the Generalized Traveling Salesman Problem

Abstract: The Lin-Kernighan heuristic is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). It has also proven its efficiency in application to some other problems. In this paper we discuss possible adaptations of TSP heuristics for the Generalized Traveling Salesman Problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first, we provide an easy-to-understand description of the original Lin-Kernighan heuristic. Then we propose several adaptations, both trivial and complicated. Finally, we conduct a fair competition between all the variations of the Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success of the original heuristic. Different variations of our adaptation outperform all other heuristics in a wide range of trade-offs between solution quality and running time, making Lin-Kernighan the state-of-the-art GTSP local search.


Improving Waiting Time of Tasks Scheduled Under Preemptive Round Robin Using Changeable Time Quantum

Abstract: Minimizing waiting time for tasks waiting in the queue for execution is one of the important scheduling cri-teria which took a wide area in scheduling preemptive tasks. In this paper we present Changeable Time Quan-tum (CTQ) approach combined with the round-robin algorithm, we try to adjust the time quantum according to the burst times of the tasks in the ready queue. There are two important benefits of using (CTQ) approach: minimizing the average waiting time of the tasks, consequently minimizing the average turnaround time, and keeping the number of context switches as low as possible, consequently minimizing the scheduling overhead. In this paper, we consider the scheduling problem for preemptive tasks, where the time costs of these tasks are known a priori. Our experimental results demonstrate that CTQ can provide much lower scheduling overhead and better scheduling criteria.


An Improved Algorithm for Generating Database Transactions from Relational Algebra Specifications

Abstract: Alloy is a lightweight modeling formalism based on relational algebra. In prior work with Fisler, Giannakopoulos, Krishnamurthi, and Yoo, we have presented a tool, Alchemy, that compiles Alloy specifications into implementations that execute against persistent databases. The foundation of Alchemy is an algorithm for rewriting relational algebra formulas into code for database transactions. In this paper we report on recent progress in improving the robustness and efficiency of this transformation.


Proceedings FM-09 Workshop on Formal Methods for Aerospace

Abstract: The main workshop objective was to promote a holistic view and interdisciplinary methods for design, verification and co-ordination of aerospace systems, by combining formal methods with techniques from control engineering and artificial intelligence. The very demanding safety, robustness and performance requirements of these systems require unprecedented integration of heterogeneous techniques and models. The aim of FMA was to bring together active researchers from all the above areas to discuss and present their work.


Learning Recursive Segments for Discourse Parsing

Abstract: Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a linear sequence (i.e., they can never be nested). Unfortunately, this assumption turns out to be too strong, for some theories of discourse like SDRT allows for nested discourse units. In this paper, we present a simple approach to discourse segmentation that is able to produce nested EDUs. Our approach builds on standard multi-class classification techniques combined with a simple repairing heuristic that enforces global coherence. Our system was developed and evaluated on the first round of annotations provided by the French Annodis project (an ongoing effort to create a discourse bank for French). Cross-validated on only 47 documents (1,445 EDUs), our system achieves encouraging performance results with an F-score of 73% for finding EDUs.


Automatic analysis of distance bounding protocols

Abstract: Distance bounding protocols are used by nodes in wireless networks to calculate upper bounds on their distances to other nodes. However, dishonest nodes in the network can turn the calculations both illegitimate and inaccurate when they participate in protocol executions. It is important to analyze protocols for the possibility of such violations. Past efforts to analyze distance bounding protocols have only been manual. However, automated approaches are important since they are quite likely to find flaws that manual approaches cannot, as witnessed in literature for analysis pertaining to key establishment protocols. In this paper, we use the constraint solver tool to automatically analyze distance bounding protocols. We first formulate a new trace property called Secure Distance Bounding (SDB) that protocol executions must satisfy. We then classify the scenarios in which these protocols can operate considering the (dis)honesty of nodes and location of the attacker in the network. Finally, we extend the constraint solver so that it can be used to test protocols for violations of SDB in these scenarios and illustrate our technique on some published protocols.


Protocol indepedence through disjoint encryption under Exclusive-OR

Abstract: Multi-protocol attacks due to protocol interaction has been a notorious problem for security. Gutman-Thayer proved that they can be prevented by ensuring that encrypted messages are distinguishable across protocols, under a free algebra. In this paper, we prove that a similar suggestion prevents these attacks under commonly used operators such as Exclusive-OR, that induce equational theories, breaking the free algebra assumption.


How to prevent type-flaw attacks on security protocols under algebraic properties

Abstract: Type-flaw attacks upon security protocols wherein agents are led to misinterpret message types have been reported frequently in the literature. Preventing them is crucial for protocol security and verification. Heather et al. proved that tagging every message field with it's type prevents all type-flaw attacks under a free message algebra and perfect encryption system. In this paper, we prove that type-flaw attacks can be prevented with the same technique even under the ACUN algebraic properties of XOR which is commonly used in "real-world" protocols such as SSL 3.0. Our proof method is general and can be easily extended to other monoidal operators that possess properties such as Inverse and Idempotence as well. We also discuss how tagging could be used to prevent type-flaw attacks under other properties such as associativity of pairing, commutative encryption, prefix property and homomorphic encryption.


Spatial logics with connectedness predicates

Abstract: We consider quantifier-free spatial logics, designed for qualitative spatial representation and reasoning in AI, and extend them with the means to represent topological connectedness of regions and restrict the number of their connected components. We investigate the computational complexity of these logics and show that the connectedness constraints can increase complexity from NP to PSpace, ExpTime and, if component counting is allowed, to NExpTime.


Disabling equational theories in unification for cryptographic protocol analysis through tagging

Abstract: In this paper, we show a new tagging scheme for cryptographic protocol messages. Under this tagging, equational theories of operators such as exclusive-or, binary addition etc. are effectively disabled, when terms are unified. We believe that this result has a significant impact on protocol analysis and security, since unification is at the heart of symbolic protocol analysis. Hence, disabling equational theories in unification implies disabling them altogether in protocol analysis for most operators and theories.


Modeling Multi-Point Transport Protocol in P2P Networks

Abstract: Traditional end-to-end congestion control mechanisms assume data transferring happens between each pair user. In contrast, in a P2P network, many peers may locally keep a copy of a specific data object. If the path between a pair of peers is congested, the requesting peer who wants to download data will switch to another peer in its neighbor peer list to fetch the data instead of decreasing the download rate from the current peer. Thus, it is critical to study the performance in multi-point-to-multi-point (M2M) transport protocol in a P2P network. In this paper, we build a mathematical model for identifying the key parameters for the M2M transport protocol and also the relationships among these parameters. Finally, we conduct simulation experiments to validate our model.


Preventing Distributed Denial-of-Service Attacks on the IMS Emergency Services Support through Adaptive Firewall Pinholing

Abstract: Emergency services are vital services that Next Generation Networks (NGNs) have to provide. As the IP Multimedia Subsystem (IMS) is in the heart of NGNs, 3GPP has carried the burden of specifying a standardized IMS-based emergency services framework. Unfortunately, like any other IP-based standards, the IMS-based emergency service framework is prone to Distributed Denial of Service (DDoS) attacks. We propose in this work, a simple but efficient solution that can prevent certain types of such attacks by creating firewall pinholes that regular clients will surely be able to pass in contrast to the attackers clients. Our solution was implemented, tested in an appropriate testbed, and its efficiency was proven.


Securing Internet Protocol (IP) Storage: A Case Study

Abstract: Storage networking technology has enjoyed strong growth in recent years, but security concerns and threats facing networked data have grown equally fast. Today, there are many potential threats that are targeted at storage networks, including data modification, destruction and theft, DoS attacks, malware, hardware theft and unauthorized access, among others. In order for a Storage Area Network (SAN) to be secure, each of these threats must be individually addressed. In this paper, we present a comparative study by implementing different security methods in IP Storage network.


Computer Network Topology Design in Limelight of Pascal Graph Property

Abstract: Constantly growing demands of high productivity and security of computer systems and computer networks call the interest of specialists in the environment of construction of optimum topologies of computer mediums. In earliest phases of design, the study of the topological influence of the processes that happen in computer systems and computer networks allows to obtain useful information which possesses a significant value in the subsequent design. It has always been tried to represent the different computer network topologies using appropriate graph models. Graphs have huge contributions towards the performance improvement factor of a network. Some major contributors are de-Bruijn, Hypercube, Mesh and Pascal. They had been studied a lot and different new features were always a part of research outcome. As per the definition of interconnection network it is equivalent that a suitable graph can represent the physical and logical layout very efficiently. In this present study Pascal graph is researched again and a new characteristics has been discovered. From the perspective of network topologies Pascal graph and its properties were first studied more than two decades back. Since then, a numerous graph models have emerged with potentials to be used as network topologies. This new property is guaranteed to make an everlasting mark towards the reliability of this graph to be used as a substantial contributor as a computer network topology. This shows its credentials over so many other topologies. This study reviews the characteristics of the Pascal graph and the new property is established using appropriate algorithm and the results.


Image Compression and Watermarking scheme using Scalar Quantization

Abstract: This paper presents a new compression technique and image watermarking algorithm based on Contourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantization is explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. The watermark image is embedded in the low pass image of contourlet decomposition. The watermark can be extracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.


Improved Packet Forwarding Approach in Vehicular Ad Hoc Networks Using RDGR Algorithm

Abstract: VANETs (Vehicular Ad hoc Networks) are highly mobile wireless ad hoc networks and will play an important role in public safety communications and commercial applications. Routing of data in VANETs is a challenging task due to rapidly changing topology and high speed mobility of vehicles. Position based routing protocols are becoming popular due to advancement and availability of GPS devices. One of the critical issues of VANETs are frequent path disruptions caused by high speed mobility of vehicle that leads to broken links which results in low throughput and high overhead . This paper argues the use of information on vehicles' movement information (e.g., position, direction, speed of vehicles) to predict a possible link-breakage event prior to its occurrence. So in this paper we propose a Reliable Directional Greedy routing (RDGR), a reliable position based routing approach which obtains position, speed and direction of its neighboring nodes from GPS. This approach incorporates potential score based strategy, which calculates link stability between neighbor nodes in distributed fashion for reliable forwarding of data packet.


A Performance Analysis for UMTS Packet Switched Network Based on Multivariate KPIS

Abstract: Mobile data services are penetrating mobile markets rapidly. The mobile industry relies heavily on data service to replace the traditional voice services with the evolution of the wireless technology and market. A reliable packet service network is critical to the mobile operators to maintain their core competence in data service market. Furthermore, mobile operators need to develop effective operational models to manage the varying mix of voice, data and video traffic on a single network. Application of statistical models could prove to be an effective approach. This paper first introduces the architecture of Universal Mobile Telecommunications System (UMTS) packet switched (PS) network and then applies multivariate statistical analysis to Key Performance Indicators (KPI) monitored from network entities in UMTS PS network to guide the long term capacity planning for the network. The approach proposed in this paper could be helpful to mobile operators in operating and maintaining their 3G packet switched networks for the long run.


Design of A Low Power Low Voltage CMOS Opamp

Abstract: In this paper a CMOS operational amplifier is presented which operates at 2V power supply and 1microA input bias current at 0.8 micron technology using non conventional mode of operation of MOS transistors and whose input is depended on bias current. The unique behaviour of the MOS transistors in subthreshold region not only allows a designer to work at low input bias current but also at low voltage. While operating the device at weak inversion results low power dissipation but dynamic range is degraded. Optimum balance between power dissipation and dynamic range results when the MOS transistors are operated at moderate inversion. Power is again minimised by the application of input dependant bias current using feedback loops in the input transistors of the differential pair with two current substractors. In comparison with the reported low power low voltage opamps at 0.8 micron technology, this opamp has very low standby power consumption with a high driving capability and operates at low voltage. The opamp is fairly small (0.0084 mm 2) and slew rate is more than other low power low voltage opamps reported at 0.8 um technology [1,2]. Vittoz at al [3] reported that slew rate can be improved by adaptive biasing technique and power dissipation can be reduced by operating the device in weak inversion. Though lower power dissipation is achieved the area required by the circuit is very large and speed is too small. So, operating the device in moderate inversion is a good solution. Also operating the device in subthreshold region not only allows lower power dissipation but also a lower voltage operation is achieved.


QoS Based Capacity Enhancement for WCDMA Network with Coding Scheme

Abstract: The wide-band code division multiple access (WCDMA) based 3G and beyond cellular mobile wireless networks are expected to provide a diverse range of multimedia services to mobile users with guaranteed quality of service (QoS). To serve diverse quality of service requirements of these networks it necessitates new radio resource management strategies for effective utilization of network resources with coding schemes. Call admission control (CAC) is a significant component in wireless networks to guarantee quality of service requirements and also to enhance the network resilience. In this paper capacity enhancement for WCDMA network with convolutional coding scheme is discussed and compared with block code and without coding scheme to achieve a better balance between resource utilization and quality of service provisioning. The model of this network is valid for the real-time (RT) and non-real-time (NRT) services having different data rate. Simulation results demonstrate the effectiveness of the network using convolutional code in terms of capacity enhancement and QoS of the voice and video services.


Arithmetic Operations in Multi-Valued Logic

Abstract: This paper presents arithmetic operations like addition, subtraction and multiplications in Modulo-4 arithmetic, and also addition, multiplication in Galois field, using multi-valued logic (MVL). Quaternary to binary and binary to quaternary converters are designed using down literal circuits. Negation in modular arithmetic is designed with only one gate. Logic design of each operation is achieved by reducing the terms using Karnaugh diagrams, keeping minimum number of gates and depth of net in to consideration. Quaternary multiplier circuit is proposed to achieve required optimization. Simulation result of each operation is shown separately using Hspice.


Relating Nominal and Higher-order Abstract Syntax Specifications

Abstract: Nominal abstract syntax and higher-order abstract syntax provide a means for describing binding structure which is higher-level than traditional techniques. These approaches have spawned two different communities which have developed along similar lines but with subtle differences that make them difficult to relate. The nominal abstract syntax community has devices like names, freshness, name-abstractions with variable capture, and the new-quantifier, whereas the higher-order abstract syntax community has devices like lambda-binders, lambda-conversion, raising, and the nabla-quantifier. This paper aims to unify these communities and provide a concrete correspondence between their different devices. In particular, we develop a semantics-preserving translation from alpha-Prolog, a nominal abstract syntax based logic programming language, to G-, a higher-order abstract syntax based logic programming language. We also discuss higher-order judgments, a common and powerful tool for specifications with higher-order abstract syntax, and we show how these can be incorporated into G-. This establishes G- as a language with the power of higher-order abstract syntax, the fine-grained variable control of nominal specifications, and the desirable properties of higher-order judgments.


Seidel complementation on ($P_5$, $House$, $Bull$)-free graphs

Abstract: We consider the Seidel complementation on ($P_5, \bar{P_5}, Bull)$-free graphs


On a family of cubic graphs containing the flower snarks

Abstract: We consider cubic graphs formed with $k \geq 2$ disjoint claws $C_i \sim K_{1, 3}$ ($0 \leq i \leq k-1$) such that for every integer $i$ modulo $k$ the three vertices of degree 1 of $\ C_i$ are joined to the three vertices of degree 1 of $C_{i-1}$ and joined to the three vertices of degree 1 of $C_{i+1}$. Denote by $t_i$ the vertex of degree 3 of $C_i$ and by $T$ the set $\{t_1, t_2,..., t_{k-1}\}$. In such a way we construct three distinct graphs, namely $FS(1,k)$, $FS(2,k)$ and $FS(3,k)$. The graph $FS(j,k)$ ($j \in \{1, 2, 3\}$) is the graph where the set of vertices $\cup_{i=0}^{i=k-1}V(C_i) \setminus T$ induce $j$ cycles (note that the graphs $FS(2,2p+1)$, $p\geq2$, are the flower snarks defined by Isaacs \cite{Isa75}). We determine the number of perfect matchings of every $FS(j,k)$. A cubic graph $G$ is said to be {\em 2-factor hamiltonian} if every 2-factor of $G$ is a hamiltonian cycle. We characterize the graphs $FS(j,k)$ that are 2-factor hamiltonian (note that FS(1,3) is the "Triplex Graph" of Robertson, Seymour and Thomas \cite{RobSey}). A {\em strong matching} $M$ in a graph $G$ is a matching $M$ such that there is no edge of $E(G)$ connecting any two edges of $M$. A cubic graph having a perfect matching union of two strong matchings is said to be a {\em\Jaev}. We characterize the graphs $FS(j,k)$ that are \Jaesv.


A Note on Integer Factorization Using Lattices

Abstract: We revisit Schnorr's lattice-based integer factorization algorithm, now with an effective point of view. We present effective versions of Theorem 2 of Schnorr's "Factoring integers and computing discrete logarithms via diophantine approximation" paper, as well as new elementary properties of the Prime Number Lattice bases of Schnorr and Adleman.


Angle Tree: Nearest Neighbor Search in High Dimensions with Low Intrinsic Dimensionality

Abstract: We propose an extension of tree-based space-partitioning indexing structures for data with low intrinsic dimensionality embedded in a high dimensional space. We call this extension an Angle Tree. Our extension can be applied to both classical kd-trees as well as the more recent rp-trees. The key idea of our approach is to store the angle (the "dihedral angle") between the data region (which is a low dimensional manifold) and the random hyperplane that splits the region (the "splitter"). We show that the dihedral angle can be used to obtain a tight lower bound on the distance between the query point and any point on the opposite side of the splitter. This in turn can be used to efficiently prune the search space. We introduce a novel randomized strategy to efficiently calculate the dihedral angle with a high degree of accuracy. Experiments and analysis on real and synthetic data sets shows that the Angle Tree is the most efficient known indexing structure for nearest neighbor queries in terms of preprocessing and space usage while achieving high accuracy and fast search time.


Truthful Fair Division

Abstract: We address the problem of fair division, or cake cutting, with the goal of finding truthful mechanisms. In the case of a general measure space ("cake") and non-atomic, additive individual preference measures - or utilities - we show that there exists a truthful "mechanism" which ensures that each of the k players gets at least 1/k of the cake. This mechanism also minimizes risk for truthful players. Furthermore, in the case where there exist at least two different measures we present a different truthful mechanism which ensures that each of the players gets more than 1/k of the cake. We then turn our attention to partitions of indivisible goods with bounded utilities and a large number of goods. Here we provide similar mechanisms, but with slightly weaker guarantees. These guarantees converge to those obtained in the non-atomic case as the number of goods goes to infinity.


An LSB Data Hiding Technique Using Prime Numbers

Abstract: In this paper, a novel data hiding technique is proposed, as an improvement over the Fibonacci LSB data-hiding technique proposed by Battisti et al. First we mathematically model and generalize our approach. Then we propose our novel technique, based on decomposition of a number (pixel-value) in sum of prime numbers. The particular representation generates a different set of (virtual) bit-planes altogether, suitable for embedding purposes. They not only allow one to embed secret message in higher bit-planes but also do it without much distortion, with a much better stego-image quality, and in a reliable and secured manner, guaranteeing efficient retrieval of secret message. A comparative performance study between the classical Least Significant Bit (LSB)method, the Fibonacci LSB data-hiding technique and our proposed schemes has been done. Analysis indicates that image quality of the stego-image hidden by the technique using Fibonacci decomposition improves against that using simple LSB substitution method, while the same using the prime decomposition method improves drastically against that using Fibonacci decomposition technique. Experimental results show that, the stego-image is visually indistinguishable from the original cover-image.


EphPub: Toward Robust Ephemeral Publishing

Abstract: The increasing amount of personal and sensitive information disseminated over the Internet prompts commensurately growing privacy concerns. Digital data often lingers indefinitely and users lose its control. This motivates the desire to restrict content availability to an expiration time set by the data owner. This paper presents and formalizes the notion of Ephemeral Publishing (EphPub), to prevent the access to expired content. We propose an efficient and robust protocol that builds on the Domain Name System (DNS) and its caching mechanism. With EphPub, sensitive content is published encrypted and the key material is distributed, in a steganographic manner, to randomly selected and independent resolvers. The availability of content is then limited by the evanescence of DNS cache entries. The EphPub protocol is transparent to existing applications, and does not rely on trusted hardware, centralized servers, or user proactive actions. We analyze its robustness and show that it incurs a negligible overhead on the DNS infrastructure. We also perform a large-scale study of the caching behavior of 900K open DNS resolvers. Finally, we propose Firefox and Thunderbird extensions that provide ephemeral publishing capabilities, as well as a command-line tool to create ephemeral files.


Categorical Models for a Semantically Linear Lambda-calculus

Abstract: This paper is about a categorical approach to model a very simple Semantically Linear lambda calculus, named Sll-calculus. This is a core calculus underlying the programming language SlPCF. In particular, in this work, we introduce the notion of Sll-Category, which is able to describe a very large class of sound models of Sll-calculus. Sll-Category extends in the natural way Benton, Bierman, Hyland and de Paiva's Linear Category, in order to soundly interpret all the constructs of Sll-calculus. This category is general enough to catch interesting models in Scott Domains and Coherence Spaces.


Resource-Bound Quantification for Graph Transformation

Abstract: Graph transformation has been used to model concurrent systems in software engineering, as well as in biochemistry and life sciences. The application of a transformation rule can be characterised algebraically as construction of a double-pushout (DPO) diagram in the category of graphs. We show how intuitionistic linear logic can be extended with resource-bound quantification, allowing for an implicit handling of the DPO conditions, and how resource logic can be used to reason about graph transformation systems.


Uniqueness Typing for Resource Management in Message-Passing Concurrency

Abstract: We view channels as the main form of resources in a message-passing programming paradigm. These channels need to be carefully managed in settings where resources are scarce. To study this problem, we extend the pi-calculus with primitives for channel allocation and deallocation and allow channels to be reused to communicate values of different types. Inevitably, the added expressiveness increases the possibilities for runtime errors. We define a substructural type system which combines uniqueness typing and affine typing to reject these ill-behaved programs.


Labelled Lambda-calculi with Explicit Copy and Erase

Abstract: We present two rewriting systems that define labelled explicit substitution lambda-calculi. Our work is motivated by the close correspondence between Levy's labelled lambda-calculus and paths in proof-nets, which played an important role in the understanding of the Geometry of Interaction. The structure of the labels in Levy's labelled lambda-calculus relates to the multiplicative information of paths; the novelty of our work is that we design labelled explicit substitution calculi that also keep track of exponential information present in call-by-value and call-by-name translations of the lambda-calculus into linear logic proof-nets.


Competition with Dynamic Spectrum Leasing

Abstract: This paper presents a comprehensive analytical study of two competitive cognitive operators' spectrum leasing and pricing strategies, taking into account operators' heterogeneity in leasing costs and users' heterogeneity in transmission power and channel conditions. We model the interactions between operators and users as a three-stage dynamic game, where operators make simultaneous spectrum leasing and pricing decisions in Stages I and II, and users make purchase decisions in Stage III. Using backward induction, we are able to completely characterize the game's equilibria. We show that both operators make the equilibrium leasing and pricing decisions based on simple threshold policies. Moreover, two operators always choose the same equilibrium price despite their difference in leasing costs. Each user receives the same signal-to-noise-ratio (SNR) at the equilibrium, and the obtained payoff is linear in its transmission power and channel gain. We also compare the duopoly equilibrium with the coordinated case where two operators cooperate to maximize their total profit. We show that the maximum loss of total profit due to operators' competition is no larger than 25%. The users, however, always benefit from operators' competition in terms of their payoffs. We show that most of these insights are robust in the general SNR regime.


On Linear Information Systems

Abstract: Scott's information systems provide a categorically equivalent, intensional description of Scott domains and continuous functions. Following a well established pattern in denotational semantics, we define a linear version of information systems, providing a model of intuitionistic linear logic (a new-Seely category), with a "set-theoretic" interpretation of exponentials that recovers Scott continuous functions via the co-Kleisli construction. From a domain theoretic point of view, linear information systems are equivalent to prime algebraic Scott domains, which in turn generalize prime algebraic lattices, already known to provide a model of classical linear logic.


Searching publications on operating systems

Abstract: This note concerns a search for publications in which one can find statements that explain the concept of an operating system, reasons for introducing operating systems, a formalization of the concept of an operating system or theory about operating systems based on such a formalization. It reports on the way in which the search has been carried out and the outcome of the search. The outcome includes not only what the search was meant for, but also some added bonuses.


Flexible Authentication Technique for Ubiquitous Wireless Communication using Passport and Visa Tokens

Abstract: The development of mobile devices (CPU, memory, and storage) and the introduction of mobile networks (Ad-Hoc, Wi-Fi, WiMAX, and 3.5G) have opened new opportunities for next generation of mobile services. It becomes more convenience and desirable for mobile internet users to be connected everywhere. However, ubiquitous mobile access connectivity faces interoperation issues between wireless network providers and wireless network technologies. Although mobile users would like to get as many services as possible while they travel, there is a lack of technology to identify visited users in current foreign network authentication systems. This challenge lies in the fact that a foreign network provider does not initially have the authentication credentials of a mobile user. Existing approaches use roaming agreement to exchange authentication information between home network and foreign network. This paper proposes a roaming agreement-less approach designed based on our ubiquitous mobile access model. Our approach consist of two tokens, Passport (identification token) and Visa (authorisation token) to provide the mobile user with a flexible authentication method to access foreign network services. The security analysis indicates that our proposal is more suitable for ubiquitous mobile communication especially in roaming agreement-less environment.


Spoken Language Identification Using Hybrid Feature Extraction Methods

Abstract: This paper introduces and motivates the use of hybrid robust feature extraction technique for spoken language identification (LID) system. The speech recognizers use a parametric form of a signal to get the most important distinguishable features of speech signal for recognition task. In this paper Mel-frequency cepstral coefficients (MFCC), Perceptual linear prediction coefficients (PLP) along with two hybrid features are used for language Identification. Two hybrid features, Bark Frequency Cepstral Coefficients (BFCC) and Revised Perceptual Linear Prediction Coefficients (RPLP) were obtained from combination of MFCC and PLP. Two different classifiers, Vector Quantization (VQ) with Dynamic Time Warping (DTW) and Gaussian Mixture Model (GMM) were used for classification. The experiment shows better identification rate using hybrid feature extraction techniques compared to conventional feature extraction methods.BFCC has shown better performance than MFCC with both classifiers. RPLP along with GMM has shown best identification performance among all feature extraction techniques.


Wavelet-Based Mel-Frequency Cepstral Coefficients for Speaker Identification using Hidden Markov Models

Abstract: To improve the performance of speaker identification systems, an effective and robust method is proposed to extract speech features, capable of operating in noisy environment. Based on the time-frequency multi-resolution property of wavelet transform, the input speech signal is decomposed into various frequency channels. For capturing the characteristic of the signal, the Mel-Frequency Cepstral Coefficients (MFCCs) of the wavelet channels are calculated. Hidden Markov Models (HMMs) were used for the recognition stage as they give better recognition for the speaker's features than Dynamic Time Warping (DTW). Comparison of the proposed approach with the MFCCs conventional feature extraction method shows that the proposed method not only effectively reduces the influence of noise, but also improves recognition. A recognition rate of 99.3% was obtained using the proposed feature extraction technique compared to 98.7% using the MFCCs. When the test patterns were corrupted by additive white Gaussian noise with 20 dB S/N ratio, the recognition rate was 97.3% using the proposed method compared to 93.3% using the MFCCs.


Bit Error Rate Performance Analysis on Modulation Techniques of Wideband Code Division Multiple Access

Abstract: In the beginning of 21st century there has been a dramatic shift in the market dynamics of telecommunication services. The transmission from base station to mobile or downlink transmission using M-ary Quadrature Amplitude modulation (QAM) and Quadrature phase shift keying (QPSK) modulation schemes are considered in Wideband-Code Division Multiple Access (W-CDMA) system. We have done the performance analysis of these modulation techniques when the system is subjected to Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading are considered in the channel. The research has been performed by using MATLAB 7.6 for simulation and evaluation of Bit Error Rate (BER) and Signal-To-Noise Ratio (SNR) for W-CDMA system models. It is shows that the analysis of Quadrature phases shift key and 16-ary Quadrature Amplitude modulations which are being used in wideband code division multiple access system, Therefore, the system could go for more suitable modulation technique to suit the channel quality, thus we can deliver the optimum and efficient data rate to mobile terminal.


A Mobile Message Scheduling and Delivery System using m-Learning framework

Abstract: Wireless data communications in form of Short Message Service (SMS) and Wireless Access Protocols (WAP) browsers have gained global popularity, yet, not much has been done to extend the usage of these devices in electronic learning (e-learning) and information sharing. This project explores the extension of e learning into wireless/ handheld (W/H) computing devices with the help of a mobile learning (m-learning) framework. This framework provides the requirements to develop m-learning application that can be used to share academic and administrative information among people within the university campus. A prototype application has been developed to demonstrate the important functionality of the proposed system in simulated environment. This system is supposed to work both in bulk SMS and interactive SMS delivery mode. Here we have combined both Short Message Service (SMS) and Wireless Access Protocols (WAP) browsers. SMS is used for Short and in time information delivery and WAP is used for detailed information delivery like course content, training material, interactive evolution tests etc. The push model is used for sending personalized multicasting messages to a group of mobile users with a common profile thereby improving the effectiveness and usefulness of the cntent delivered. Again pull mechanism can be applied for sending information as SMS when requested by end user in interactive SMS delivery mode. The main strength of the system is that, the actual SMS delivery application can be hosted on a mobile device, which can operate even when the device is on move.


Performance Analysis of Best suited Adaptive Equalization Algorithm for Optical Communication

Abstract: Fiber optics is one of the highest bandwidth communication channel types in the current communication industry. The paper is to analyze a typical optical channel and perform channel equalization using an adaptive modified DFE with Activity Detection Guidance and Tap Decoupling algorithm. Evaluation can be made on the employment of the DFE algorithm and with enhancements, like Fractionally-Spaced equalization and Activity Detection Guidance, to improve its stability, steady-state error performance and convergence rate. The successful implementation of the Adaptive FS-DFE with ADG and TD technique offers an excellent alternative to linear equalization, which is known to be of little benefit for optical channels because of exorbitant noise enhancement. The FSE technique, when combined with the DFE, would offer improved effectiveness to amplitude distortion. As the impulse response of a typical optical link would have regions that are essentially zero, the employment of the activity detection scheme with Tap Decoupling would further enhance the steady-state error performance and convergence rate.


Web-Based Learning and Training for Virtual Metrology Lab

Abstract: The use of World Web Wide for distance education has received increasing attention over the past decades. The real challenge of adapting this technology for engineering education and training is to facilitate the laboratory experiments via Internet. In the sciences, measurement plays an important role. The accuracy of the measurement, as well as the units, help scientists to better understand phenomena occurring in nature. This paper introduces Metrology educators to the use and adoption of Java-applets in order to create virtual, online Metrology laboratories for students. These techniques have been used to successfully form a laboratory course which augments the more conventional lectures in concepts of Metrology course at Faculty of Engineering, Albaha University, KSA. Improvements of the package are still undergoing to incorporate Web-based technologies (Internet home page, HTML, Java programming etc...). This Web-based education and training has been successfully class-tested within an undergraduate preliminary year engineering course and students reported a positive experience with its use. The use of these labs should be self-explanatory and their reliable operation has been thoroughly tested.


Proceedings First International Workshop on Linearity

Abstract: This volume contains the proceedings of LINEARITY 2009: the first International Workshop on Linearity, which took place 12th September 2009 in Coimbra, Portugal. The workshop was a satellite event of CSL 2009, the 18th EACSL Annual Conference on Computer Science Logic.


BitTorrent Experiments on Testbeds: A Study of the Impact of Network Latencies

Abstract: In this paper, we study the impact of network latency on the time required to download a file distributed using BitTorrent. This study is essential to understand if testbeds can be used for experimental evaluation of BitTorrent. We observe that the network latency has a marginal impact on the time required to download a file; hence, BitTorrent experiments can performed on testbeds.


Etiqueter un corpus oral par apprentissage automatique \`a l'aide de connaissances linguistiques

Abstract: Thanks to the Eslo1 ("Enqu\^ete sociolinguistique d'Orl\'eans", i.e. "Sociolinguistic Inquiery of Orl\'eans") campain, a large oral corpus has been gathered and transcribed in a textual format. The purpose of the work presented here is to associate a morpho-syntactic label to each unit of this corpus. To this aim, we have first studied the specificities of the necessary labels, and their various possible levels of description. This study has led to a new original hierarchical structuration of labels. Then, considering that our new set of labels was different from the one used in every available software, and that these softwares usually do not fit for oral data, we have built a new labeling tool by a Machine Learning approach, from data labeled by Cordial and corrected by hand. We have applied linear CRF (Conditional Random Fields) trying to take the best possible advantage of the linguistic knowledge that was used to define the set of labels. We obtain an accuracy between 85 and 90%, depending of the parameters used.


Proceedings Tenth International Workshop on Rule-Based Programming

Abstract: This volume contains the proceedings of RULE 2009: the tenth International Workshop on Rule-Based Programming. It took place in June 28th 2009, Brasilia, Brazil, as a satellite event of RDP 2009. The first Rule workshop was held in Montreal in 2000, and subsequent editions took place in Firenze, Pittsburgh, Valencia, Aachen, Nara, Seattle, Paris, and Hagenberg.


The impact of cell site re-homing on the performance of umts core networks

Abstract: Mobile operators currently prefer optimizing their radio networks via re-homing or cutting over the cell sites in 2G or 3G networks. The core network, as the parental part of radio network, is inevitably impacted by the re-homing in radio domain. This paper introduces the cell site re-homing in radio network and analyzes its impact on the performance of GSM/UMTS core network. The possible re-homing models are created and analyzed for core networks. The paper concludes that appropriate re-homing in radio domain, using correct algorithms, not only optimizes the radio network but also helps improve the QoS of the core network and saves the carriers' OPEX and CAPEX on their core networks.


Specifying Reusable Components

Abstract: Reusable software components need expressive specifications. This paper outlines a rigorous foundation to model-based contracts, a method to equip classes with strong contracts that support accurate design, implementation, and formal verification of reusable components. Model-based contracts conservatively extend the classic Design by Contract with a notion of model, which underpins the precise definitions of such concepts as abstract equivalence and specification completeness. Experiments applying model-based contracts to libraries of data structures suggest that the method enables accurate specification of practical software.


Bricks and conjectures of Berge, Fulkerson and Seymour

Abstract: An $r$-graph is an $r$-regular graph where every odd set of vertices is connected by at least $r$ edges to the rest of the graph. Seymour conjectured that any $r$-graph is $r+1$-edge-colorable, and also that any $r$-graph contains $2r$ perfect matchings such that each edge belongs to two of them. We show that the minimum counter-example to either of these conjectures is a brick. Furthermore we disprove a variant of a conjecture of Fan, Raspaud.


Measures of edge-uncolorability

Abstract: The resistance $r(G)$ of a graph $G$ is the minimum number of edges that have to be removed from $G$ to obtain a graph which is $\Delta(G)$-edge-colorable. The paper relates the resistance to other parameters that measure how far is a graph from being $\Delta$-edge-colorable. The first part considers regular graphs and the relation of the resistance to structural properties in terms of 2-factors. The second part studies general (multi-) graphs $G$. Let $r_v(G)$ be the minimum number of vertices that have to be removed from $G$ to obtain a class 1 graph. We show that $\frac{r(G)}{r_v(G)} \leq \lfloor \frac{\Delta(G)}{2} \rfloor$, and that this bound is best possible.


A secured Cryptographic Hashing Algorithm

Abstract: Cryptographic hash functions for calculating the message digest of a message has been in practical use as an effective measure to maintain message integrity since a few decades. This message digest is unique, irreversible and avoids all types of collisions for any given input string. The message digest calculated from this algorithm is propagated in the communication medium along with the original message from the sender side and on the receiver side integrity of the message can be verified by recalculating the message digest of the received message and comparing the two digest values. In this paper we have designed and developed a new algorithm for calculating the message digest of any message and implemented t using a high level programming language. An experimental analysis and comparison with the existing MD5 hashing algorithm, which is predominantly being used as a cryptographic hashing tool, shows this algorithm to provide more randomness and greater strength from intrusion attacks. In this algorithm the plaintext message string is converted into binary string and fragmented into blocks of 128 bits after being padded with user defined padding bits. Then using a pseudo random number generator a key is generated for each block and operated with the respective block by a bitwise operator. This process is terated for the whole message and finally a fixed length message digest is obtained.


Scalable Group Management in Large-Scale Virtualized Clusters

Abstract: To save cost, recently more and more users choose to provision virtual machine resources in cluster systems, especially in data centres. Maintaining a consistent member view is the foundation of reliable cluster managements, and it also raises several challenge issues for large scale cluster systems deployed with virtual machines (which we call virtualized clusters). In this paper, we introduce our experiences in design and implementation of scalable member view management on large-scale virtual clusters. Our research contributions are three-fold: 1) we propose a scalable and reliable management infrastructure that combines a peer-to-peer structure and a hierarchy structure to maintain a consistent member view in virtual clusters; 2) we present a light-weighted group membership algorithm that can reach the consistent member view within a single round of message exchange; and 3) we design and implement a scalable membership service that can provision virtual machines and maintain a consistent member view in virtual clusters. Our work is verified on Dawning 5000A, which ranked No.10 of Top 500 super computers in November, 2008.


Why the Internet is so 'small'?

Abstract: During the last three decades the Internet has experienced fascinating evolution, both exponential growth in traffic and rapid expansion in topology. The size of the Internet becomes enormous, yet the network is very `small' in the sense that it is extremely efficient to route data packets across the global Internet. This paper provides a brief review on three fundamental properties of the Internet topology at the autonomous systems (AS) level. Firstly the Internet has a power-law degree distribution, which means the majority of nodes on the Internet AS graph have small numbers of links, whereas a few nodes have very large numbers of links. Secondly the Internet exhibits a property called disassortative mixing, which means poorly-connected nodes tend to link with well-connected nodes, and vice versa. Thirdly the best-connected nodes, or the rich nodes, are tightly interconnected with each other forming a rich-club. We explain that it is these structural properties that make the global Internet so 'small'.


Tuning CLD Maps

Abstract: The Coherence Length Diagram and the related maps have been shown to represent a useful tool for image analysis. Setting threshold parameters is one of the most important issues when dealing with such applications, as they affect both the computability, which is outlined by the support map, and the appearance of the coherence length diagram itself and of defect maps. A coupled optimization analysis, returning a range for the basic (saturation) threshold, and a histogram based method, yielding suitable values for a desired map appearance, are proposed for an effective control of the analysis process.


Robust multi-camera view face recognition

Abstract: This paper presents multi-appearance fusion of Principal Component Analysis (PCA) and generalization of Linear Discriminant Analysis (LDA) for multi-camera view offline face recognition (verification) system. The generalization of LDA has been extended to establish correlations between the face classes in the transformed representation and this is called canonical covariate. The proposed system uses Gabor filter banks for characterization of facial features by spatial frequency, spatial locality and orientation to make compensate to the variations of face instances occurred due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images produces Gabor face representations with high dimensional feature vectors. PCA and canonical covariate are then applied on the Gabor face representations to reduce the high dimensional feature spaces into low dimensional Gabor eigenfaces and Gabor canonical faces. Reduced eigenface vector and canonical face vector are fused together using weighted mean fusion rule. Finally, support vector machines (SVM) have trained with augmented fused set of features and perform the recognition task. The system has been evaluated with UMIST face database consisting of multiview faces. The experimental results demonstrate the efficiency and robustness of the proposed system for multi-view face images with high recognition rates. Complexity analysis of the proposed system is also presented at the end of the experimental results.


Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory

Abstract: This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising.


Stability of epsilon-Kernels

Abstract: Given a set P of n points in |R^d, an eps-kernel K subset P approximates the directional width of P in every direction within a relative (1-eps) factor. In this paper we study the stability of eps-kernels under dynamic insertion and deletion of points to P and by changing the approximation factor eps. In the first case, we say an algorithm for dynamically maintaining a eps-kernel is stable if at most O(1) points change in K as one point is inserted or deleted from P. We describe an algorithm to maintain an eps-kernel of size O(1/eps^{(d-1)/2}) in O(1/eps^{(d-1)/2} + log n) time per update. Not only does our algorithm maintain a stable eps-kernel, its update time is faster than any known algorithm that maintains an eps-kernel of size O(1/eps^{(d-1)/2}). Next, we show that if there is an eps-kernel of P of size k, which may be dramatically less than O(1/eps^{(d-1)/2}), then there is an (eps/2)-kernel of P of size O(min {1/eps^{(d-1)/2}, k^{floor(d/2)} log^{d-2} (1/eps)}). Moreover, there exists a point set P in |R^d and a parameter eps > 0 such that if every eps-kernel of P has size at least k, then any (eps/2)-kernel of P has size Omega(k^{floor(d/2)}).


Development of a multi-user handwriting recognition system using Tesseract open source OCR engine

Abstract: The objective of the paper is to recognize handwritten samples of lower case Roman script using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten data samples containing isolated and free-flow text were collected from different users. Tesseract is trained with user-specific data samples of both the categories of document pages to generate separate user-models representing a unique language-set. Each such language-set recognizes isolated and free-flow handwritten test samples collected from the designated user. On a three user model, the system is trained with 1844, 1535 and 1113 isolated handwritten character samples collected from three different users and the performance is tested on 1133, 1186 and 1204 character samples, collected form the test sets of the three users respectively. The user specific character level accuracies were obtained as 87.92%, 81.53% and 65.71% respectively. The overall character-level accuracy of the system is observed as 78.39%. The system fails to segment 10.96% characters and erroneously classifies 10.65% characters on the overall dataset.


Recognition of Handwritten Roman Script Using Tesseract Open source OCR Engine

Abstract: In the present work, we have used Tesseract 2.01 open source Optical Character Recognition (OCR) Engine under Apache License 2.0 for recognition of handwriting samples of lower case Roman script. Handwritten isolated and free-flow text samples were collected from multiple users. Tesseract is trained to recognize user-specific handwriting samples of both the categories of document pages. On a single user model, the system is trained with 1844 isolated handwritten characters and the performance is tested on 1133 characters, taken form the test set. The overall character-level accuracy of the system is observed as 83.5%. The system fails to segment 5.56% characters and erroneously classifies 10.94% characters.


Recognition of Handwritten Textual Annotations using Tesseract Open Source OCR Engine for information Just In Time (iJIT)

Abstract: Objective of the current work is to develop an Optical Character Recognition (OCR) engine for information Just In Time (iJIT) system that can be used for recognition of handwritten textual annotations of lower case Roman script. Tesseract open source OCR engine under Apache License 2.0 is used to develop user-specific handwriting recognition models, viz., the language sets, for the said system, where each user is identified by a unique identification tag associated with the digital pen. To generate the language set for any user, Tesseract is trained with labeled handwritten data samples of isolated and free-flow texts of Roman script, collected exclusively from that user. The designed system is tested on five different language sets with free- flow handwritten annotations as test samples. The system could successfully segment and subsequently recognize 87.92%, 81.53%, 92.88%, 86.75% and 90.80% handwritten characters in the test samples of five different users.


Development of a Multi-User Recognition Engine for Handwritten Bangla Basic Characters and Digits

Abstract: The objective of the paper is to recognize handwritten samples of basic Bangla characters using Tesseract open source Optical Character Recognition (OCR) engine under Apache License 2.0. Handwritten data samples containing isolated Bangla basic characters and digits were collected from different users. Tesseract is trained with user-specific data samples of document pages to generate separate user-models representing a unique language-set. Each such language-set recognizes isolated basic Bangla handwritten test samples collected from the designated users. On a three user model, the system is trained with 919, 928 and 648 isolated handwritten character and digit samples and the performance is tested on 1527, 14116 and 1279 character and digit samples, collected form the test datasets of the three users respectively. The user specific character/digit recognition accuracies were obtained as 90.66%, 91.66% and 96.87% respectively. The overall basic character-level and digit level accuracy of the system is observed as 92.15% and 97.37%. The system fails to segment 12.33% characters and 15.96% digits and also erroneously classifies 7.85% characters and 2.63% on the overall dataset.


Recognition of handwritten Roman Numerals using Tesseract open source OCR engine

Abstract: The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with data samples of different persons to generate one user-independent language model, representing the handwritten Roman digit-set. The system is trained with 1226 digit samples collected form the different users. The performance is tested on two different datasets, one consisting of samples collected from the known users (those who prepared the training data samples) and the other consisting of handwritten data samples of unknown users. The overall recognition accuracy is obtained as 92.1% and 86.59% on these test datasets respectively.


Geometric Algebra Model of Distributed Representations

Abstract: Formalism based on GA is an alternative to distributed representation models developed so far --- Smolensky's tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates recognition test results using both inner product and a clipped version of matrix representation. The influence of accidental blade equality on recognition is also studied. Finally, the efficiency of the GA model is compared to that of previously developed models.


Faster Approximation Schemes for Fractional Multicommodity Flow Problems via Dynamic Graph Algorithms

Abstract: We combine the work of Garg and Konemann, and Fleischer with ideas from dynamic graph algorithms to obtain faster (1-eps)-approximation schemes for various versions of the multicommodity flow problem. In particular, if eps is moderately small and the size of every number used in the input instance is polynomially bounded, the running times of our algorithms match - up to poly-logarithmic factors and some provably optimal terms - the Omega(mn) flow-decomposition barrier for single-commodity flow.


Optimal (v, 4, 2, 1) optical orthogonal codes with small parameters

Abstract: Optimal (v, 4, 2, 1) optical orthogonal codes (OOC) with $v<=75$ and $v\ne 71$ are classified up to equivalence. One $(v, 4, 2, 1)$ OOC is presented for all $v\le 181$, for which an optimal OOC exists.


Variable Threshold MOSFET Approach (Through Dynamic Threshold MOSFET) For Universal Logic Gates

Abstract: In this article, we proposed a Variable threshold MOSFET(VTMOS)approach which is realized from Dynamic Threshold MOSFET(DTMOS), suitable for sub-threshold digital circuit operation. Basically the principle of sub- threshold logics is operating MOSFET in sub-threshold region and using the leakage current in that region for switching action, there by drastically decreasing power. To reduce the power consumption of sub-threshold circuits further, a novel body biasing technique termed VTMOS is introduced .VTMOS approach is realized from DTMOS approach. Dynamic threshold MOS (DTMOS) circuits provide low leakage and high current drive, compared to CMOS circuits, operated at lower voltages. The VTMOS is based on operating the MOS devices with an appropriate substrate bias which varies with gate voltage, by connecting a positive bias voltage between gate and substrate for NMOS and negative bias voltage between gate and substrate for PMOS. With VTMOS, there is a considerable reduction in operating current and power dissipation, while the remaining characteristics are almost the same as those of DTMOS. Results of our investigations show that VTMOS circuits improves the power up to 50% when compared to CMOS and DTMOS circuits, in sub- threshold region.. The performance analysis and comparison of VTMOS, DTMOS and CMOS is made and test results of Power dissipation, Propagation delay and Power delay product are presented to justify the superiority of VTMOS logic over conventional sub-threshold logics using Hspice Tool. The dependency of these parameters on frequency of operation has also been investigated.


Development of an automated Red Light Violation Detection System (RLVDS) for Indian vehicles

Abstract: Integrated Traffic Management Systems (ITMS) are now implemented in different cities in India to primarily address the concerns of road-safety and security. An automated Red Light Violation Detection System (RLVDS) is an integral part of the ITMS. In our present work we have designed and developed a complete system for generating the list of all stop-line violating vehicle images automatically from video snapshots of road-side surveillance cameras. The system first generates adaptive background images for each camera view, subtracts captured images from the corresponding background images and analyses potential occlusions over the stop-line in a traffic signal. Considering round-the-clock operations in a real-life test environment, the developed system could successfully track 92% images of vehicles with violations on the stop-line in a "Red" traffic signal.


A novel scheme for binarization of vehicle images using hierarchical histogram equalization technique

Abstract: Automatic License Plate Recognition system is a challenging area of research now-a-days and binarization is an integral and most important part of it. In case of a real life scenario, most of existing methods fail to properly binarize the image of a vehicle in a congested road, captured through a CCD camera. In the current work we have applied histogram equalization technique over the complete image and also over different hierarchy of image partitioning. A novel scheme is formulated for giving the membership value to each pixel for each hierarchy of histogram equalization. Then the image is binarized depending on the net membership value of each pixel. The technique is exhaustively evaluated on the vehicle image dataset as well as the license plate dataset, giving satisfactory performances.


A CF-Based Randomness Measure for Sequences

Abstract: This note examines the question of randomness in a sequence based on the continued fraction (CF) representation of its corresponding representation as a number, or as D sequence. We propose a randomness measure that is directly equal to the number of components of the CF representation. This provides a means of quantifying the randomness of the popular PN sequences as well. A comparison is made of representation as a fraction and as a continued fraction.


Expressiveness of Generic Process Shape Types

Abstract: Shape types are a general concept of process types which work for many process calculi. We extend the previously published Poly* system of shape types to support name restriction. We evaluate the expressiveness of the extended system by showing that shape types are more expressive than an implicitly typed pi-calculus and an explicitly typed Mobile Ambients. We demonstrate that the extended system makes it easier to enjoy advantages of shape types which include polymorphism, principal typings, and a type inference implementation.


Anonimos: An LP based Approach for Anonymizing Weighted Social Network Graphs

Abstract: The increasing popularity of social networks has initiated a fertile research area in information extraction and data mining. Anonymization of these social graphs is important to facilitate publishing these data sets for analysis by external entities. Prior work has concentrated mostly on node identity anonymization and structural anonymization. But with the growing interest in analyzing social networks as a weighted network, edge weight anonymization is also gaining importance. We present An\'onimos, a Linear Programming based technique for anonymization of edge weights that preserves linear properties of graphs. Such properties form the foundation of many important graph-theoretic algorithms such as shortest paths problem, k-nearest neighbors, minimum cost spanning tree, and maximizing information spread. As a proof of concept, we apply An\'onimos to the shortest paths problem and its extensions, prove the correctness, analyze complexity, and experimentally evaluate it using real social network data sets. Our experiments demonstrate that An\'onimos anonymizes the weights, improves k-anonymity of the weights, and also scrambles the relative ordering of the edges sorted by weights, thereby providing robust and effective anonymization of the sensitive edge-weights. Additionally, we demonstrate the composability of different models generated using An\'onimos, a property that allows a single anonymized graph to preserve multiple linear properties.


A Study of Bandwidth-Perception Management Mechanisms in IEEE 802.16 Networks

Abstract: Bandwidth request-grant mechanisms are used in 802.16 networks to manage the uplink bandwidth needs of subscriber stations (SSs). Requests may be sent by SSs to the base station (BS) by means of several mechanisms defined in the standard. Based on the incoming requests, the BS (which handles most of the bandwidth scheduling in the system) schedules the transmission of uplink traffic, by assigning transmission opportunities to the SSs in an implementation-dependent manner. In this paper we present a study of some bandwidth allocation issues, arising from the management of the perception of subscriber stations' bandwidth needs at the base station. We illustrate how the bandwidth perception varies depending on the policy used to handle requests and grants. By means of ns-2 simulations, we evaluate the potential impact of such policies on the system's aggregate throughput when the traffic is composed of Best-Effort TCP flows.


A Characterization of Combined Traces Using Labeled Stratified Order Structures

Abstract: This paper defines a class of labeled stratified order structures that characterizes exactly the notion of combined traces (i.e., comtraces) proposed by Janicki and Koutny in 1995. Our main technical contributions are the representation theorems showing that comtrace quotient monoid, combined dependency graph (Kleijn and Koutny 2008) and our labeled stratified order structure characterization are three different and yet equivalent ways to represent comtraces.


Quantitative Information Flow - Verification Hardness and Possibilities

Abstract: Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, and channel capacity. This paper investigates the hardness and possibilities of precisely checking and inferring quantitative information flow according to such definitions. We prove that, even for just comparing two programs on which has the larger flow, none of the definitions is a k-safety property for any k, and therefore is not amenable to the self-composition technique that has been successfully applied to precisely checking non-interference. We also show a complexity theoretic gap with non-interference by proving that, for loop-free boolean programs whose non-interference is coNP-complete, the comparison problem is #P-hard for all of the definitions. For positive results, we show that universally quantifying the distribution in the comparison problem, that is, comparing two programs according to the entropy based definitions on which has the larger flow for all distributions, is a 2-safety problem in general and is coNP-complete when restricted for loop-free boolean programs. We prove this by showing that the problem is equivalent to a simple relation naturally expressing the fact that one program is more secure than the other. We prove that the relation also refines the channel-capacity based definition, and that it can be precisely checked via the self-composition as well as the "interleaved" self-composition technique.


A New Proof for the Correctness of F5 (F5-Like) Algorithm

Abstract: The famous F5 algorithm for computing Gr\"obner basis was presented by Faug\`ere in 2002 without complete proofs for its correctness. The current authors have simplified the original F5 algorithm into an F5 algorithm in Buchberger's style (F5B algorithm), which is equivalent to original F5 algorithm and may deduce some F5-like versions. In this paper, the F5B algorithm is briefly revisited and a new complete proof for the correctness of F5B algorithm is proposed. This new proof is not limited to homogeneous systems and does not depend on the strategy of selecting critical pairs (i.e. the strategy deciding which critical pair is computed first) such that any strategy could be utilized in F5B (F5) algorithm. From this new proof, we find that the special reduction procedure (F5-reduction) is the key of F5 algorithm, so maintaining this special reduction, various variation algorithms become available. A natural variation of F5 algorithm, which transforms original F5 algorithm to a non-incremental algorithm, is presented and proved in this paper as well. This natural variation has been implemented over the Boolean ring. The two revised criteria in this natural variation are also able to reject almost all unnecessary computations and few polynomials reduce to 0 in most examples.


Maximal Intersection Queries in Randomized Input Models

Abstract: Consider a family of sets and a single set, called the query set. How can one quickly find a member of the family which has a maximal intersection with the query set? Time constraints on the query and on a possible preprocessing of the set family make this problem challenging. Such maximal intersection queries arise in a wide range of applications, including web search, recommendation systems, and distributing on-line advertisements. In general, maximal intersection queries are computationally expensive. We investigate two well-motivated distributions over all families of sets and propose an algorithm for each of them. We show that with very high probability an almost optimal solution is found in time which is logarithmic in the size of the family. Moreover, we point out a threshold phenomenon on the probabilities of intersecting sets in each of our two input models which leads to the efficient algorithms mentioned above.


Opportunistic Routing in Ad Hoc Networks: How many relays should there be? What rate should nodes use?

Abstract: Opportunistic routing is a multi-hop routing scheme which allows for selection of the best immediately available relay. In blind opportunistic routing protocols, where transmitters blindly broadcast without knowledge of the surrounding nodes, two fundamental design parameters are the node transmission probability and the transmission spectral efficiency. In this paper these parameters are selected to maximize end-to-end performance, characterized by the product of transmitter density, hop distance and rate. Due to the intractability of the problem as stated, an approximation function is examined which proves reasonably accurate. Our results show how the above design parameters should be selected based on inherent system parameters such as the path loss exponent and the noise level.


Interval Slopes as Numerical Abstract Domain for Floating-Point Variables

Abstract: The design of embedded control systems is mainly done with model-based tools such as Matlab/Simulink. Numerical simulation is the central technique of development and verification of such tools. Floating-point arithmetic, that is well-known to only provide approximated results, is omnipresent in this activity. In order to validate the behaviors of numerical simulations using abstract interpretation-based static analysis, we present, theoretically and with experiments, a new partially relational abstract domain dedicated to floating-point variables. It comes from interval expansion of non-linear functions using slopes and it is able to mimic all the behaviors of the floating-point arithmetic. Hence it is adapted to prove the absence of run-time errors or to analyze the numerical precision of embedded control systems.


Radio Interface for High Data Rate Wireless Sensor Networks

Abstract: This paper gives an overview of radio interfaces devoted for high data rate Wireless Sensor Networks. Four aerospace applications of WSN are presented to underline the importance of achieving high data rate. Then, two modulation schemes by which High Data Rate can be achieved are compared : Multi carrier approaches, represented by the popular Orthogonal Frequency Division Multiplexing (OFDM) and Single carrier methods, represented by Single Carrier Frequency division Equalization and its application for multiple access Single Carrier Frequency division multiple Access (SC-FDMA). SC-FDMA, with a very low Peak Average Power Ratio (PAPR), is as strong alternative to the OFDM scheme for highly power constraint application. The Chosen radio interface will be, finally, tested by a model based design approach based on Simulink and FPGA realization. SC-FDMA, with a very low Peak Average Power Ratio (PAPR), is as strong alternative to the OFDM scheme for highly power constraint application. The Chosen radio interface will be, finally, tested by a model based design approach based on Simulink and FPGA realization.


Psychophysiological Correlations with Gameplay Experience Dimensions

Abstract: In this paper, we report a case study using two easy-to-deploy psychophysiological measures - electrodermal activity (EDA) and heart rate (HR) - and correlating them with a gameplay experience questionnaire (GEQ) in an attempt to establish this mixed-methods approach for rapid application in a commercial game development context. Results indicate that there is a statistically significant correlation (p < 0.01) between measures of psychophysiological arousal (HR, EDA) and self-reported UX in games (GEQ), with some variation between the EDA and HR measures. Results are consistent across three major commercial First-Person Shooter (FPS) games.