An Agent Based Classification Model

Abstract: The major function of this model is to access the UCI Wisconsin Breast Can- cer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classifi cation can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artifi cial Immune Sys- tems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to prob- lem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifi cally for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based mod- elling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environ- ment called AnyLogic, where the immune entities in the DCA are represented by intelligent agents. If this model can be successfully implemented, it makes it possible to implement more complicated and adaptive AIS models in the agent-based simulation environment.


Average-Time Games on Timed Automata

Abstract: An average-time game is played on the infinite graph of configurations of a finite timed automaton. The two players, Min and Max, construct an infinite run of the automaton by taking turns to perform a timed transition. Player Min wants to minimise the average time per transition and player Max wants to maximise it. A solution of average-time games is presented using a reduction to average-price game on a finite graph. A direct consequence is an elementary proof of determinacy for average-time games. This complements our results for reachability-time games and partially solves a problem posed by Bouyer et al., to design an algorithm for solving average-price games on priced timed automata. The paper also establishes the exact computational complexity of solving average-time games: the problem is EXPTIME-complete for timed automata with at least two clocks.


Behavior Subtraction

Abstract: Background subtraction has been a driving engine for many computer vision and video analytics tasks. Although its many variants exist, they all share the underlying assumption that photometric scene properties are either static or exhibit temporal stationarity. While this works in some applications, the model fails when one is interested in discovering {\it changes in scene dynamics} rather than those in a static background; detection of unusual pedestrian and motor traffic patterns is but one example. We propose a new model and computational framework that address this failure by considering stationary scene dynamics as a ``background'' with which observed scene dynamics are compared. Central to our approach is the concept of an {\it event}, that we define as short-term scene dynamics captured over a time window at a specific spatial location in the camera field of view. We compute events by time-aggregating motion labels, obtained by background subtraction, as well as object descriptors (e.g., object size). Subsequently, we characterize events probabilistically, but use a low-memory, low-complexity surrogates in practical implementation. Using these surrogates amounts to {\it behavior subtraction}, a new algorithm with some surprising properties. As demonstrated here, behavior subtraction is an effective tool in anomaly detection and localization. It is resilient to spurious background motion, such as one due to camera jitter, and is content-blind, i.e., it works equally well on humans, cars, animals, and other objects in both uncluttered and highly-cluttered scenes. Clearly, treating video as a collection of events rather than colored pixels opens new possibilities for video analytics.


Critical Analysis of Middleware Architectures for Large Scale Distributed Systems

Abstract: Distributed computing is increasingly being viewed as the next phase of Large Scale Distributed Systems (LSDSs). However, the vision of large scale resource sharing is not yet a reality in many areas - Grid computing is an evolving area of computing, where standards and technology are still being developed to enable this new paradigm. Hence, in this paper we analyze the current development of middleware tools for LSDS, from multiple perspectives: architecture, applications and market research. For each perspective we are interested in relevant technologies used in undergoing projects, existing products or services and useful design issues. In the end, based on this approach, we draw some conclusions regarding the future research directions in this area.


An Evolutionary Squeaky Wheel Optimisation Approach to Personnel Scheduling

Abstract: The quest for robust heuristics that are able to solve more than one problem is ongoing. In this paper, we present, discuss and analyse a technique called Evolutionary Squeaky Wheel Optimisation and apply it to two different personnel scheduling problems. Evolutionary Squeaky Wheel Optimisation improves the original Squeaky Wheel Optimisation's effectiveness and execution speed by incorporating two extra steps (Selection and Mutation) for added evolution. In the Evolutionary Squeaky Wheel Optimisation, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The aim of the Analysis step is to identify below average solution components by calculating a fitness value for all components. The Selection step then chooses amongst these underperformers and discards some probabilistically based on fitness. The Mutation step further discards a few components at random. Solutions can become incomplete and thus repairs may be required. The repairs are carried out by using the Prioritization to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, improvement in the Evolutionary Squeaky Wheel Optimisation is achieved by selective solution disruption mixed with interative improvement and constructive repair. Strong experimental results are reported on two different domains of personnel scheduling: bus and rail driver scheduling and hospital nurse scheduling.


Guarded Second-Order Logic, Spanning Trees, and Network Flows

Abstract: According to a theorem of Courcelle monadic second-order logic and guarded second-order logic (where one can also quantify over sets of edges) have the same expressive power over the class of all countable $k$-sparse hypergraphs. In the first part of the present paper we extend this result to hypergraphs of arbitrary cardinality. In the second part, we present a generalisation dealing with methods to encode sets of vertices by single vertices.


An Idiotypic Immune Network as a Short Term Learning Architecture for Mobile Robots

Abstract: A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours. These sets are then transferred to an idiotypic Artificial Immune System (AIS), which forms the STL phase, and the system is said to be seeded. The combined LTL-STL approach is compared with using STL only, and with using a handdesigned controller. In addition, the STL phase is tested when the idiotypic mechanism is turned off. The results provide substantial evidence that the best option is the seeded idiotypic system, i.e. the architecture that merges LTL with an idiotypic AIS for the STL. They also show that structurally different environments can be used for the two phases without compromising transferability


An Immune Inspired Approach to Anomaly Detection

Abstract: The immune system provides a rich metaphor for computer security: anomaly detection that works in nature should work for machines. However, early artificial immune system approaches for computer security had only limited success. Arguably, this was due to these artificial systems being based on too simplistic a view of the immune system. We present here a second generation artificial immune system for process anomaly detection. It improves on earlier systems by having different artificial cell types that process information. Following detailed information about how to build such second generation systems, we find that communication between cells types is key to performance. Through realistic testing and validation we show that second generation artificial immune systems are capable of anomaly detection beyond generic system policies. The paper concludes with a discussion and outline of the next steps in this exciting area of computer security.


Wee LCP

Abstract: We prove that longest common prefix (LCP) information can be stored in much less space than previously known. More precisely, we show that in the presence of the text and the suffix array, o(n) additional bits are sufficient to answer LCP-queries asymptotically in the same time that is needed to retrieve an entry from the suffix array. This yields the smallest compressed suffix tree with sub-logarithmic navigation time.


An Immune Inspired Network Intrusion Detection System Utilising Correlation Context

Abstract: Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.


Parameterized Complexity of the k-anonymity Problem

Abstract: The problem of publishing personal data without giving up privacy is becoming increasingly important. An interesting formalization that has been recently proposed is the $k$-anonymity. This approach requires that the rows of a table are partitioned in clusters of size at least $k$ and that all the rows in a cluster become the same tuple, after the suppression of some entries. The natural optimization problem, where the goal is to minimize the number of suppressed entries, is known to be APX-hard even when the records values are over a binary alphabet and $k=3$, and when the records have length at most 8 and $k=4$ . In this paper we study how the complexity of the problem is influenced by different parameters. In this paper we follow this direction of research, first showing that the problem is W[1]-hard when parameterized by the size of the solution (and the value $k$). Then we exhibit a fixed parameter algorithm, when the problem is parameterized by the size of the alphabet and the number of columns. Finally, we investigate the computational (and approximation) complexity of the $k$-anonymity problem, when restricting the instance to records having length bounded by 3 and $k=3$. We show that such a restriction is APX-hard.


Towards a Semantic Preservation System

Abstract: Preserving access to file content requires preserving not just bits but also meaningful logical structures. The ongoing development of the Data Format Description Language (DFDL) is a completely general standard that addresses this need. The Defuddle parser is a generic parser that can use DFDL-style format descriptions to extract logical structures from ASCII or binary files written in those formats. DFDL and Defuddle provide a preservation capability that has minimal format-specific software and cleanly separates issues related to bits, formats, and logical content. Such a system has the potential to greatly reduce overall system development and maintenance costs as well as the per-file-format costs for long term preservation.


Testing Distribution Identity Efficiently

Abstract: We consider the problem of testing distribution identity. Given a sequence of independent samples from an unknown distribution on a domain of size n, the goal is to check if the unknown distribution approximately equals a known distribution on the same domain. While Batu, Fortnow, Fischer, Kumar, Rubinfeld, and White (FOCS 2001) proved that the sample complexity of the problem is O~(sqrt(n) * poly(1/epsilon)), the running time of their tester is much higher: O(n) + O~(sqrt(n) * poly(1/epsilon)). We modify their tester to achieve a running time of O~(sqrt(n) * poly(1/epsilon)).


Adaptive Concurrent Non-Malleability with Bare Public-Keys

Abstract: Concurrent non-malleability (CNM) is central for cryptographic protocols running concurrently in environments such as the Internet. In this work, we formulate CNM in the bare public-key (BPK) model, and show that round-efficient concurrent non-malleable cryptography with full adaptive input selection can be established, in general, with bare public-keys (where, in particular, no trusted assumption is made). Along the way, we clarify the various subtleties of adaptive concurrent non-malleability in the bare public-key model.


The 1.375 Approximation Algorithm for Sorting by Transpositions Can Run in $O(n\log n)$ Time

Abstract: Sorting a Permutation by Transpositions (SPbT) is an important problem in Bioinformtics. In this paper, we improve the running time of the best known approximation algorithm for SPbT. We use the permutation tree data structure of Feng and Zhu and improve the running time of the 1.375 Approximation Algorithm for SPbT of Elias and Hartman to $O(n\log n)$. The previous running time of EH algorithm was $O(n^2)$.


Faster Algorithms for Max-Product Message-Passing

Abstract: Maximum A Posteriori inference in graphical models is often solved via message-passing algorithms, such as the junction-tree algorithm, or loopy belief-propagation. The exact solution to this problem is well known to be exponential in the size of the model's maximal cliques after it is triangulated, while approximate inference is typically exponential in the size of the model's factors. In this paper, we take advantage of the fact that many models have maximal cliques that are larger than their constituent factors, and also of the fact that many factors consist entirely of latent variables (i.e., they do not depend on an observation). This is a common case in a wide variety of applications, including grids, trees, and ring-structured models. In such cases, we are able to decrease the exponent of complexity for message-passing by 0.5 for both exact and approximate inference.


Iterators, Recursors and Interaction Nets

Abstract: We propose a method for encoding iterators (and recursion operators in general) using interaction nets (INs). There are two main applications for this: the method can be used to obtain a visual nota- tion for functional programs; and it can be used to extend the existing translations of the lambda-calculus into INs to languages with recursive types.


Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

Abstract: Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.


b-Bit Minwise Hashing

Abstract: This paper establishes the theoretical framework of b-bit minwise hashing. The original minwise hashing method has become a standard technique for estimating set similarity (e.g., resemblance) with applications in information retrieval, data management, social networks and computational advertising. By only storing the lowest $b$ bits of each (minwise) hashed value (e.g., b=1 or 2), one can gain substantial advantages in terms of computational efficiency and storage space. We prove the basic theoretical results and provide an unbiased estimator of the resemblance for any b. We demonstrate that, even in the least favorable scenario, using b=1 may reduce the storage space at least by a factor of 21.3 (or 10.7) compared to using b=64 (or b=32), if one is interested in resemblance > 0.5.


Composition and Inversion of Schema Mappings

Abstract: In the recent years, a lot of attention has been paid to the development of solid foundations for the composition and inversion of schema mappings. In this paper, we review the proposals for the semantics of these crucial operators. For each of these proposals, we concentrate on the three following problems: the definition of the semantics of the operator, the language needed to express the operator, and the algorithmic issues associated to the problem of computing the operator. It should be pointed out that we primarily consider the formalization of schema mappings introduced in the work on data exchange. In particular, when studying the problem of computing the composition and inverse of a schema mapping, we will be mostly interested in computing these operators for mappings specified by source-to-target tuple-generating dependencies.


Least and Greatest Fixed Points in Linear Logic

Abstract: The first-order theory of MALL (multiplicative, additive linear logic) over only equalities is an interesting but weak logic since it cannot capture unbounded (infinite) behavior. Instead of accounting for unbounded behavior via the addition of the exponentials (! and ?), we add least and greatest fixed point operators. The resulting logic, which we call muMALL, satisfies two fundamental proof theoretic properties: we establish weak normalization for it, and we design a focused proof system that we prove complete. That second result provides a strong normal form for cut-free proof structures that can be used, for example, to help automate proof search. We show how these foundations can be applied to intuitionistic logic.


A Scalable VLSI Architecture for Soft-Input Soft-Output Depth-First Sphere Decoding

Abstract: Multiple-input multiple-output (MIMO) wireless transmission imposes huge challenges on the design of efficient hardware architectures for iterative receivers. A major challenge is soft-input soft-output (SISO) MIMO demapping, often approached by sphere decoding (SD). In this paper, we introduce the - to our best knowledge - first VLSI architecture for SISO SD applying a single tree-search approach. Compared with a soft-output-only base architecture similar to the one proposed by Studer et al. in IEEE J-SAC 2008, the architectural modifications for soft input still allow a one-node-per-cycle execution. For a 4x4 16-QAM system, the area increases by 57% and the operating frequency degrades by 34% only.


A Fuzzy Petri Nets Model for Computing With Words

Abstract: Motivated by Zadeh's paradigm of computing with words rather than numbers, several formal models of computing with words have recently been proposed. These models are based on automata and thus are not well-suited for concurrent computing. In this paper, we incorporate the well-known model of concurrent computing, Petri nets, together with fuzzy set theory and thereby establish a concurrency model of computing with words--fuzzy Petri nets for computing with words (FPNCWs). The new feature of such fuzzy Petri nets is that the labels of transitions are some special words modeled by fuzzy sets. By employing the methodology of fuzzy reasoning, we give a faithful extension of an FPNCW which makes it possible for computing with more words. The language expressiveness of the two formal models of computing with words, fuzzy automata for computing with words and FPNCWs, is compared as well. A few small examples are provided to illustrate the theoretical development.


Searching a bitstream in linear time for the longest substring of any given density

Abstract: Given an arbitrary bitstream, we consider the problem of finding the longest substring whose ratio of ones to zeroes equals a given value. The central result of this paper is an algorithm that solves this problem in linear time. The method involves (i) reformulating the problem as a constrained walk through a sparse matrix, and then (ii) developing a data structure for this sparse matrix that allows us to perform each step of the walk in amortised constant time. We also give a linear time algorithm to find the longest substring whose ratio of ones to zeroes is bounded below by a given value. Both problems have practical relevance to cryptography and bioinformatics.


Stealth-MITM DoS Attacks on Secure Channels

Abstract: We define stealth Man-in-the-Middle adversaries, and analyse their ability to launch denial and degradation of service (DoS) attacks on secure channels. We show realistic attacks, disrupting TCP communication over secure VPNs using IPsec. We present: First amplifying DoS attack on IPsec, when deployed without anti-replay window. First amplifying attack on IPsec, when deployed with a `small' anti-replay window, and analysis of `sufficient' window size. First amplifying attack on IPsec, when deployed with `sufficient' window size. This attack (as the previous) is realistic: attacker needs only to duplicate and speed-up few packets. We also suggest a solution designed to prevent the presented attacks, and to provide secure channel immune to degradation and other DoS attacks. Our solution involves changes (only) to the two gateway machines running IPsec. In addition to their practical importance, our results also raise the challenge of formally defining secure channels immune to DoS and degradation attacks, and providing provably-secure implementations.


Set-Rationalizable Choice and Self-Stability

Abstract: A common assumption in modern microeconomic theory is that choice should be rationalizable via a binary preference relation, which \citeauthor{Sen71a} showed to be equivalent to two consistency conditions, namely $\alpha$ (contraction) and $\gamma$ (expansion). Within the context of \emph{social} choice, however, rationalizability and similar notions of consistency have proved to be highly problematic, as witnessed by a range of impossibility results, among which Arrow's is the most prominent. Since choice functions select \emph{sets} of alternatives rather than single alternatives, we propose to rationalize choice functions by preference relations over sets (set-rationalizability). We also introduce two consistency conditions, $\hat\alpha$ and $\hat\gamma$, which are defined in analogy to $\alpha$ and $\gamma$, and find that a choice function is set-rationalizable if and only if it satisfies $\hat\alpha$. Moreover, a choice function satisfies $\hat\alpha$ and $\hat\gamma$ if and only if it is \emph{self-stable}, a new concept based on earlier work by \citeauthor{Dutt88a}. The class of self-stable social choice functions contains a number of appealing Condorcet extensions such as the minimal covering set and the essential set.


Improved Approximation of Linear Threshold Functions

Abstract: We prove two main results on how arbitrary linear threshold functions $f(x) = \sign(w\cdot x - \theta)$ over the $n$-dimensional Boolean hypercube can be approximated by simple threshold functions. Our first result shows that every $n$-variable threshold function $f$ is $\eps$-close to a threshold function depending only on $\Inf(f)^2 \cdot \poly(1/\eps)$ many variables, where $\Inf(f)$ denotes the total influence or average sensitivity of $f.$ This is an exponential sharpening of Friedgut's well-known theorem \cite{Friedgut:98}, which states that every Boolean function $f$ is $\eps$-close to a function depending only on $2^{O(\Inf(f)/\eps)}$ many variables, for the case of threshold functions. We complement this upper bound by showing that $\Omega(\Inf(f)^2 + 1/\epsilon^2)$ many variables are required for $\epsilon$-approximating threshold functions. Our second result is a proof that every $n$-variable threshold function is $\eps$-close to a threshold function with integer weights at most $\poly(n) \cdot 2^{\tilde{O}(1/\eps^{2/3})}.$ This is a significant improvement, in the dependence on the error parameter $\eps$, on an earlier result of \cite{Servedio:07cc} which gave a $\poly(n) \cdot 2^{\tilde{O}(1/\eps^{2})}$ bound. Our improvement is obtained via a new proof technique that uses strong anti-concentration bounds from probability theory. The new technique also gives a simple and modular proof of the original \cite{Servedio:07cc} result, and extends to give low-weight approximators for threshold functions under a range of probability distributions beyond just the uniform distribution.


A Fault-tolerant Structure for Reliable Multi-core Systems Based on Hardware-Software Co-design

Abstract: To cope with the soft errors and make full use of the multi-core system, this paper gives an efficient fault-tolerant hardware and software co-designed architecture for multi-core systems. And with a not large number of test patterns, it will use less than 33% hardware resources compared with the traditional hardware redundancy (TMR) and it will take less than 50% time compared with the traditional software redundancy (time redundant).Therefore, it will be a good choice for the fault-tolerant architecture for the future high-reliable multi-core systems.


Performance Evaluation of Security Protocols

Abstract: We propose a comparative performance evaluation of security protocols. The novelty of our approach lies in the use of a polynomial mathematical model that captures the performance of classes of cryptographic algorithms instead of capturing the performance of each algorithm separately, approach that is used in other papers. A major advantage of using such a model is that it does not require implementation-specific information, because the decision is based on comparing the estimated performances of protocols instead of actually evaluating them. The approach is validated by comparatively evaluating the performances of 1000 automatically generated security protocols against the performances of their actual implementations.


Comparison of Algorithms for Checking Emptiness on Buechi Automata

Abstract: We re-investigate the problem of LTL model-checking for finite-state systems. Typical solutions, like in Spin, work on the fly, reducing the problem to Buechi emptiness. This can be done in linear time, and a variety of algorithms with this property exist. Nonetheless, subtle design decisions can make a great difference to their actual performance in practice, especially when used on-the-fly. We compare a number of algorithms experimentally on a large benchmark suite, measure their actual run-time performance, and propose improvements. Compared with the algorithm implemented in Spin, our best algorithm is faster by about 33 % on average. We therefore recommend that, for on-the-fly explicit-state model checking, nested DFS should be replaced by better solutions.


Dynamics of the Orthoglide parallel robot

Abstract: Recursive matrix relations for kinematics and dynamics of the Orthoglide parallel robot having three concurrent prismatic actuators are established in this paper. These are arranged according to the Cartesian coordinate system with fixed orientation, which means that the actuating directions are normal to each other. Three identical legs connecting to the moving platform are located on three planes being perpendicular to each other too. Knowing the position and the translation motion of the platform, we develop the inverse kinematics problem and determine the position, velocity and acceleration of each element of the robot. Further, the principle of virtual work is used in the inverse dynamic problem. Some matrix equations offer iterative expressions and graphs for the input forces and the powers of the three actuators.


Variance Analysis of Randomized Consensus in Switching Directed Networks

Abstract: In this paper, we study the asymptotic properties of distributed consensus algorithms over switching directed random networks. More specifically, we focus on consensus algorithms over independent and identically distributed, directed Erdos-Renyi random graphs, where each agent can communicate with any other agent with some exogenously specified probability $p$. While it is well-known that consensus algorithms over Erdos-Renyi random networks result in an asymptotic agreement over the network, an analytical characterization of the distribution of the asymptotic consensus value is still an open question. In this paper, we provide closed-form expressions for the mean and variance of the asymptotic random consensus value, in terms of the size of the network and the probability of communication $p$. We also provide numerical simulations that illustrate our results.


How to Complete an Interactive Configuration Process?

Abstract: When configuring customizable software, it is useful to provide interactive tool-support that ensures that the configuration does not breach given constraints. But, when is a configuration complete and how can the tool help the user to complete it? We formalize this problem and relate it to concepts from non-monotonic reasoning well researched in Artificial Intelligence. The results are interesting for both practitioners and theoreticians. Practitioners will find a technique facilitating an interactive configuration process and experiments supporting feasibility of the approach. Theoreticians will find links between well-known formal concepts and a concrete practical application.


Improved Latin Square based Secret Sharing Scheme

Abstract: This paper first reviews some basic properties of cryptographic hash function, secret sharing scheme, and Latin square. Then we discuss why Latin square or its critical set is a good choice for secret representation and its relationship with secret sharing scheme. Further we enumerate the limitations of Latin square in a secret sharing scheme. Finally we propose how to apply cryptographic hash functions, herding attack technique to a Latin square based secret sharing scheme to overcome these limitations.


Path placement optimization of manipulators based on energy consumption: application to the orthoglide 3-axis

Abstract: This paper deals with the optimal path placement for a manipulator based on energy consumption. It proposes a methodology to determine the optimal location of a given test path within the workspace of a manipulator with minimal electric energy used by the actuators while taking into account the geometric, kinematic and dynamic constraints. The proposed methodology is applied to the Orthoglide~3-axis, a three-degree-of-freedom translational parallel kinematic machine (PKM), as an illustrative example.


Singularity Analysis of Lower-Mobility Parallel Manipulators Using Grassmann-Cayley Algebra

Abstract: This paper introduces a methodology to analyze geometrically the singularities of manipulators, of which legs apply both actuation forces and constraint moments to their moving platform. Lower-mobility parallel manipulators and parallel manipulators, of which some legs do not have any spherical joint, are such manipulators. The geometric conditions associated with the dependency of six Pl\"ucker vectors of finite lines or lines at infinity constituting the rows of the inverse Jacobian matrix are formulated using Grassmann-Cayley Algebra. Accordingly, the singularity conditions are obtained in vector form. This study is illustrated with the singularity analysis of four manipulators.


VRAC: Simulation Results #1

Abstract: In order to make full use of geographic routing techniques developed for large scale networks, nodes must be localized. However, localization and virtual localization techniques in sensor networks are dependent either on expensive and sometimes unavailable hardware (e.g. GPS) or on sophisticated localization calculus (e.g. triangulation) which are both error-prone and with a costly overhead. Instead of localizing nodes in a traditional 2-dimensional space, we use directly the raw distance to a set of anchors to route messages in a multi-dimensional space. This should enable us to use any geographic routing protocol in a robust and efficient manner in a very large range of scenarios. We test this technique for two different geographic routing algorithms, namely GRIC and ROAM. The simulation results show that using the raw coordinates does not decrease their efficiency.


How to Work with Honest but Curious Judges? (Preliminary Report)

Abstract: The three-judges protocol, recently advocated by Mclver and Morgan as an example of stepwise refinement of security protocols, studies how to securely compute the majority function to reach a final verdict without revealing each individual judge's decision. We extend their protocol in two different ways for an arbitrary number of 2n+1 judges. The first generalisation is inherently centralised, in the sense that it requires a judge as a leader who collects information from others, computes the majority function, and announces the final result. A different approach can be obtained by slightly modifying the well-known dining cryptographers protocol, however it reveals the number of votes rather than the final verdict. We define a notion of conditional anonymity in order to analyse these two solutions. Both of them have been checked in the model checker MCMAS.


Virtual-Threading: Advanced General Purpose Processors Architecture

Abstract: The paper describes the new computers architecture, the main features of which has been claimed in the Russian Federation patent 2312388 and in the US patent application 11/991331. This architecture is intended to effective support of the General Purpose Parallel Computing (GPPC), the essence of which is extremely frequent switching of threads between states of activity and states of viewed in the paper the algorithmic latency. To emphasize the same impact of the architectural latency and the algorithmic latency upon GPPC, is introduced the new notion of the generalized latency and is defined its quantitative measure - the Generalized Latency Tolerance (GLT). It is shown that a well suited for GPPC implementation architecture should have high level of GLT and is described such architecture, which is called the Virtual-Threaded Machine. This architecture originates a processor virtualization in the direction of activities virtualization, which is orthogonal to the well-known direction of memory virtualization. The key elements of the architecture are 1) the distributed fine grain representation of the architectural register file, which elements are hardware swapped through levels of a microarchitectural memory, 2) the prioritized fine grain direct hardware multiprogramming, 3) the access controlled virtual addressing and 4) the hardware driven semaphores. The composition of these features lets to introduce new styles of operating system (OS) programming, which is free of interruptions, and of applied programming with a very rare using the OS services.


Heuristic Methods for Security Protocols

Abstract: Model checking is an automatic verification technique to verify hardware and software systems. However it suffers from state-space explosion problem. In this paper we address this problem in the context of cryptographic protocols by proposing a security property-dependent heuristic. The heuristic weights the state space by exploiting the security formulae; the weights may then be used to explore the state space when searching for attacks.


A User Model for Information Erasure

Abstract: Hunt and Sands (ESOP'08) studied a notion of information erasure for systems which receive secrets intended for limited-time use. Erasure demands that once a secret has fulfilled its purpose the subsequent behaviour of the system should reveal no information about the erased data. In this paper we address a shortcoming in that work: for erasure to be possible the user who provides data must also play his part, but previously that role was only specified informally. Here we provide a formal model of the user and a collection of requirements called erasure friendliness. We prove that an erasure-friendly user can be composed with an erasing system (in the sense of Hunt and Sands) to obtain a combined system which is jointly erasing in an appropriate sense. In doing so we identify stronger requirements on the user than those informally described in the previous work.


Infinitary Combinatory Reduction Systems: Confluence

Abstract: We study confluence in the setting of higher-order infinitary rewriting, in particular for infinitary Combinatory Reduction Systems (iCRSs). We prove that fully-extended, orthogonal iCRSs are confluent modulo identification of hypercollapsing subterms. As a corollary, we obtain that fully-extended, orthogonal iCRSs have the normal form property and the unique normal form property (with respect to reduction). We also show that, unlike the case in first-order infinitary rewriting, almost non-collapsing iCRSs are not necessarily confluent.


Complementary Space for Enhanced Uncertainty and Dynamics Visualization

Abstract: Given a computer model of a physical object, it is often quite difficult to visualize and quantify any global effects on the shape representation caused by local uncertainty and local errors in the data. This problem is further amplified when dealing with hierarchical representations containing varying levels of detail and / or shapes undergoing dynamic deformations. In this paper, we compute, quantify and visualize the complementary topological and geometrical features of 3D shape models, namely, the tunnels, pockets and internal voids of the object. We find that this approach sheds a unique light on how a model is affected by local uncertainty, errors or modifications and show how the presence or absence of complementary shape features can be essential to an object's structural form and function.


Swarm Intelligence

Abstract: Biologically inspired computing is an area of computer science which uses the advantageous properties of biological systems. It is the amalgamation of computational intelligence and collective intelligence. Biologically inspired mechanisms have already proved successful in achieving major advances in a wide range of problems in computing and communication systems. The consortium of bio-inspired computing are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, DNA computing and quantum computing, etc. This article gives an introduction to swarm intelligence.


Pseudorandom Generators for Polynomial Threshold Functions

Abstract: We study the natural question of constructing pseudorandom generators (PRGs) for low-degree polynomial threshold functions (PTFs). We give a PRG with seed-length log n/eps^{O(d)} fooling degree d PTFs with error at most eps. Previously, no nontrivial constructions were known even for quadratic threshold functions and constant error eps. For the class of degree 1 threshold functions or halfspaces, we construct PRGs with much better dependence on the error parameter eps and obtain a PRG with seed-length O(log n + log^2(1/eps)). Previously, only PRGs with seed length O(log n log^2(1/eps)/eps^2) were known for halfspaces. We also obtain PRGs with similar seed lengths for fooling halfspaces over the n-dimensional unit sphere. The main theme of our constructions and analysis is the use of invariance principles to construct pseudorandom generators. We also introduce the notion of monotone read-once branching programs, which is key to improving the dependence on the error rate eps for halfspaces. These techniques may be of independent interest.


Digital Curvatures Applied to 3D Object Analysis and Recognition: A Case Study

Abstract: In this paper, we propose using curvatures in digital space for 3D object analysis and recognition. Since direct adjacency has only six types of digital surface points in local configurations, it is easy to determine and classify the discrete curvatures for every point on the boundary of a 3D object. Unlike the boundary simplicial decomposition (triangulation), the curvature can take any real value. It sometimes makes difficulties to find a right value for threshold. This paper focuses on the global properties of categorizing curvatures for small regions. We use both digital Gaussian curvatures and digital mean curvatures to 3D shapes. This paper proposes a multi-scale method for 3D object analysis and a vector method for 3D similarity classification. We use these methods for face recognition and shape classification. We have found that the Gaussian curvatures mainly describe the global features and average characteristics such as the five regions of a human face. However, mean curvatures can be used to find local features and extreme points such as nose in 3D facial data.


Piercing translates and homothets of a convex body

Abstract: According to a classical result of Gr\"unbaum, the transversal number $\tau(\F)$ of any family $\F$ of pairwise-intersecting translates or homothets of a convex body $C$ in $\RR^d$ is bounded by a function of $d$. Denote by $\alpha(C)$ (resp. $\beta(C)$) the supremum of the ratio of the transversal number $\tau(\F)$ to the packing number $\nu(\F)$ over all families $\F$ of translates (resp. homothets) of a convex body $C$ in $\RR^d$. Kim et al. recently showed that $\alpha(C)$ is bounded by a function of $d$ for any convex body $C$ in $\RR^d$, and gave the first bounds on $\alpha(C)$ for convex bodies $C$ in $\RR^d$ and on $\beta(C)$ for convex bodies $C$ in the plane. Here we show that $\beta(C)$ is also bounded by a function of $d$ for any convex body $C$ in $\RR^d$, and present new or improved bounds on both $\alpha(C)$ and $\beta(C)$ for various convex bodies $C$ in $\RR^d$ for all dimensions $d$. Our techniques explore interesting inequalities linking the covering and packing densities of a convex body. Our methods for obtaining upper bounds are constructive and lead to efficient constant-factor approximation algorithms for finding a minimum-cardinality point set that pierces a set of translates or homothets of a convex body.


Revisiting Fermat's Factorization for the RSA Modulus

Abstract: We revisit Fermat's factorization method for a positive integer $n$ that is a product of two primes $p$ and $q$. Such an integer is used as the modulus for both encryption and decryption operations of an RSA cryptosystem. The security of RSA relies on the hardness of factoring this modulus. As a consequence of our analysis, two variants of Fermat's approach emerge. We also present a comparison between the two methods' effective regions. Though our study does not yield a new state-of-the-art algorithm for integer factorization, we believe that it reveals some interesting observations that are open for further analysis.


Media-TCP: A Quality-Centric TCP-Friendly Congestion Control for Multimedia Transmission

Abstract: In this paper, we propose a quality-centric congestion control for multimedia streaming over IP networks, which we refer to as media-TCP. Unlike existing congestion control schemes that adapt a user's sending rate merely to the network condition, our solution adapts the sending rate to both the network condition and the application characteristics by explicitly considering the distortion impacts, delay deadlines, and interdependencies of different video packet classes. Hence, our media-aware solution is able to provide differential services for transmitting various packet classes and thereby, further improves the multimedia streaming quality. We model this problem using a Finite-Horizon Markov Decision Process (FHMDP) and determine the optimal congestion control policy that maximizes the long-term multimedia quality, while adhering to the horizon- TCP-friendliness constraint, which ensures long-term fairness with existing TCP applications. We show that the FHMDP problem can be decomposed into multiple optimal stopping problems, which admit a low-complexity threshold-based solution. Moreover, unlike existing congestion control approaches, which focus on maintaining throughput-based fairness among users, the proposed media-TCP aims to achieve quality-based fairness among multimedia users. We also derive sufficient conditions for multiple multimedia users to achieve quality-based fairness using media-TCP congestion control. Our simulation results show that the proposed media-TCP achieves more than 3dB improvement in terms of PSNR over the conventional TCP congestion control approaches, with the largest improvements observed for real-time streaming applications requiring stringent playback delays.


Congestion games with resource reuse and applications in spectrum sharing

Abstract: In this paper we consider an extension to the classical definition of congestion games (CG) in which multiple users share the same set of resources and their payoff for using any resource is a function of the total number of users sharing it. The classical congestion games enjoy some very appealing properties, including the existence of a Nash equilibrium and that every improvement path is finite and leads to such a NE (also called the finite improvement property or FIP), which is also a local optimum to a potential function. On the other hand, this class of games does not model well the congestion or resource sharing in a wireless context, a prominent feature of which is spatial reuse. What this translates to in the context of a congestion game is that a users payoff for using a resource (interpreted as a channel) is a function of the its number of its interfering users sharing that channel, rather than the total number among all users. This makes the problem quite different. We will call this the congestion game with resource reuse (CG-RR). In this paper we study intrinsic properties of such a game; in particular, we seek to address under what conditions on the underlying network this game possesses the FIP or NE. We also discuss the implications of these results when applied to wireless spectrum sharing


Optimal bounds for sign-representing the intersection of two halfspaces by polynomials

Abstract: The threshold degree of a function f:{0,1}^n->{-1,+1} is the least degree of a real polynomial p with f(x)=sgn p(x). We prove that the intersection of two halfspaces on {0,1}^n has threshold degree Omega(n), which matches the trivial upper bound and completely answers a question due to Klivans (2002). The best previous lower bound was Omega(sqrt n). Our result shows that the intersection of two halfspaces on {0,1}^n only admits a trivial 2^{Theta(n)}-time learning algorithm based on sign-representation by polynomials, unlike the advances achieved in PAC learning DNF formulas and read-once Boolean formulas. The proof introduces a new technique of independent interest, based on Fourier analysis and matrix theory.


The Partition Bound for Classical Communication Complexity and Query Complexity

Abstract: We describe new lower bounds for randomized communication complexity and query complexity which we call the partition bounds. They are expressed as the optimum value of linear programs. For communication complexity we show that the partition bound is stronger than both the rectangle/corruption bound and the \gamma_2/generalized discrepancy bounds. In the model of query complexity we show that the partition bound is stronger than the approximate polynomial degree and classical adversary bounds. We also exhibit an example where the partition bound is quadratically larger than polynomial degree and classical adversary bounds.


An empirical study of spatial and transpatial social networks using Bluetooth and Facebook

Abstract: This study provides insights into the quantitative similarities, differences and relationships between users' spatial, face-to-face, urban social networks and their transpatial, online counterparts. We explore and map the social ties within a cohort of 2602 users, and how those ties are mediated via physical co-presence and online tools. Our analysis focused on isolating two distinct segments of the social network: one mediated by physical co-presence, and the other mediated by Facebook. Our results suggest that as a whole the networks exhibit homogeneous characteristics, but individuals' involvement in those networks varies considerably. Furthermore this study provides a methodological approach for jointly analysing spatial & transpatial networks utilising pervasive and ubiquitous technology.


A Geometric Approach to Solve Fuzzy Linear Systems of Differential Equations

Abstract: In this paper, systems of linear differential equations with crisp real coefficients and with initial condition described by a vector of fuzzy numbers are studied. A new method based on the geometric representations of linear transformations is proposed to find a solution. The most important difference between this method and methods offered in previous papers is that the solution is considered to be a fuzzy set of real vector-functions rather than a fuzzy vector-function. Each member of the set satisfies the given system with a certain possibility. It is shown that at any time the solution constitutes a fuzzy region in the coordinate space, alfa-cuts of which are nested parallelepipeds. Proposed method is illustrated on examples.


Putting Dots in Triangles

Abstract: Given a right-angled triangle of squares in a grid whose horizontal and vertical sides are $n$ squares long, let N(n) denote the maximum number of dots that can be placed into the cells of the triangle such that each row, each column, and each diagonal parallel to the long side of the triangle contains at most one dot. It has been proven that $N(n) = \lfloor \frac{2n+1}{3} \rfloor$. In this note, we give a new proof of this result using linear programming techniques.


Fair Exchange in Strand Spaces

Abstract: Many cryptographic protocols are intended to coordinate state changes among principals. Exchange protocols coordinate delivery of new values to the participants, e.g. additions to the set of values they possess. An exchange protocol is fair if it ensures that delivery of new values is balanced: If one participant obtains a new possession via the protocol, then all other participants will, too. Fair exchange requires progress assumptions, unlike some other protocol properties. The strand space model is a framework for design and verification of cryptographic protocols. A strand is a local behavior of a single principal in a single session of a protocol. A bundle is a partially ordered global execution built from protocol strands and adversary activities. The strand space model needs two additions for fair exchange protocols. First, we regard the state as a multiset of facts, and we allow strands to cause changes in this state via multiset rewriting. Second, progress assumptions stipulate that some channels are resilient-and guaranteed to deliver messages-and some principals are assumed not to stop at certain critical steps. This method leads to proofs of correctness that cleanly separate protocol properties, such as authentication and confidentiality, from invariants governing state evolution. G. Wang's recent fair exchange protocol illustrates the approach.


Proceedings 7th International Workshop on Security Issues in Concurrency

Abstract: This volume contains the proceedings of the 7th Workshop on Security Issues in Concurrency (SecCo'09). The workshop was held in Bologna, Italy on September 5th 2009, as a satellite workshop of CONCUR'09. The aim of the SecCo workshop series is to cover the gap between the security and the concurrency communities. More precisely, the workshop promotes the exchange of ideas, trying to focus on common interests and stimulating discussions on central research questions. In particular, we called for papers dealing with security issues (such as authentication, integrity, privacy, confidentiality, access control, denial of service, service availability, safety aspects, fault tolerance, trust, language-based security, probabilistic and information theoretic models) in emerging fields like web services, mobile ad-hoc networks, agent-based infrastructures, peer-to-peer systems, context-aware computing, global/ubiquitous/pervasive computing.


Wiener index of binomial trees and Fibonacci trees

Abstract: We obtain a closed-form expression for the Wiener index of binomial trees. We outline efficient algorithms for computing the Wiener indices of Fibonacci and binary Fibonacci trees.


ECN verbose mode: a statistical method for network path congestion estimation

Abstract: This article introduces a simple and effective methodology to determine the level of congestion in a network with an ECN-like marking scheme. The purpose of the ECN bit is to notify TCP sources of an imminent congestion in order to react before losses occur. However, ECN is a binary indicator which does not reflect the congestion level (i.e. the percentage of queued packets) of the bottleneck, thus preventing any adapted reaction. In this study, we use a counter in place of the traditional ECN marking scheme to assess the number of times a packet has crossed a congested router. Thanks to this simple counter, we drive a statistical analysis to accurately estimate the congestion level of each router on a network path. We detail in this paper an analytical method validated by some preliminary simulations which demonstrate the feasibility and the accuracy of the concept proposed. We conclude this paper with possible applications and expected future work.


A History of Until

Abstract: Until is a notoriously difficult temporal operator as it is both existential and universal at the same time: A until B holds at the current time instant w iff either B holds at w or there exists a time instant w' in the future at which B holds and such that A holds in all the time instants between the current one and w'. This "ambivalent" nature poses a significant challenge when attempting to give deduction rules for until. In this paper, in contrast, we make explicit this duality of until to provide well-behaved natural deduction rules for linear-time logics by introducing a new temporal operator that allows us to formalize the "history" of until, i.e., the "internal" universal quantification over the time instants between the current one and w'. This approach provides the basis for formalizing deduction systems for temporal logics endowed with the until operator. For concreteness, we give here a labeled natural deduction system for a linear-time logic endowed with the new operator and show that, via a proper translation, such a system is also sound and complete with respect to the linear temporal logic LTL with until.


ScotGrid: Providing an Effective Distributed Tier-2 in the LHC Era

Abstract: ScotGrid is a distributed Tier-2 centre in the UK with sites in Durham, Edinburgh and Glasgow. ScotGrid has undergone a huge expansion in hardware in anticipation of the LHC and now provides more than 4MSI2K and 500TB to the LHC VOs. Scaling up to this level of provision has brought many challenges to the Tier-2 and we show in this paper how we have adopted new methods of organising the centres, from fabric management and monitoring to remote management of sites to management and operational procedures, to meet these challenges. We describe how we have coped with different operational models at the sites, where Glagsow and Durham sites are managed "in house" but resources at Edinburgh are managed as a central university resource. This required the adoption of a different fabric management model at Edinburgh and a special engagement with the cluster managers. Challenges arose from the different job models of local and grid submission that required special attention to resolve. We show how ScotGrid has successfully provided an infrastructure for ATLAS and LHCb Monte Carlo production. Special attention has been paid to ensuring that user analysis functions efficiently, which has required optimisation of local storage and networking to cope with the demands of user analysis. Finally, although these Tier-2 resources are pledged to the whole VO, we have established close links with our local physics user communities as being the best way to ensure that the Tier-2 functions effectively as a part of the LHC grid computing framework..


Optimised access to user analysis data using the gLite DPM

Abstract: The ScotGrid distributed Tier-2 now provides more that 4MSI2K and 500TB for LHC computing, which is spread across three sites at Durham, Edinburgh and Glasgow. Tier-2 sites have a dual role to play in the computing models of the LHC VOs. Firstly, their CPU resources are used for the generation of Monte Carlo event data. Secondly, the end user analysis data is distributed across the grid to the site's storage system and held on disk ready for processing by physicists' analysis jobs. In this paper we show how we have designed the ScotGrid storage and data management resources in order to optimise access by physicists to LHC data. Within ScotGrid, all sites use the gLite DPM storage manager middleware. Using the EGEE grid to submit real ATLAS analysis code to process VO data stored on the ScotGrid sites, we present an analysis of the performance of the architecture at one site, and procedures that may be undertaken to improve such. The results will be presented from the point of view of the end user (in terms of number of events processed/second) and from the point of view of the site, which wishes to minimise load and the impact that analysis activity has on other users of the system.


Preprocessing of Min Ones Problems: A Dichotomy

Abstract: A parameterized problem consists of a classical problem and an additional component, the so-called parameter. This point of view allows a formal definition of preprocessing: Given a parameterized instance (I,k), a polynomial kernelization computes an equivalent instance (I',k') of size and parameter bounded by a polynomial in k. We give a complete classification of Min Ones Constraint Satisfaction problems, i.e., Min Ones SAT(\Gamma), with respect to admitting or not admitting a polynomial kernelization (unless NP \subseteq coNP/poly). For this we introduce the notion of mergeability. If all relations of the constraint language \Gamma are mergeable, then a new variant of sunflower kernelization applies, based on non-zero-closed cores. We obtain a kernel with O(k^{d+1}) variables and polynomial total size, where d is the maximum arity of a constraint in \Gamma, comparing nicely with the bound of O(k^{d-1}) vertices for the less general and arguably simpler d-Hitting Set problem. Otherwise, any relation in \Gamma that is not mergeable permits us to construct a log-cost selection formula, i.e., an n-ary selection formula with O(log n) true local variables. From this we can construct our lower bound using recent results by Bodlaender et al. as well as Fortnow and Santhanam, proving that there is no polynomial kernelization, unless NP \subseteq coNP/poly and the polynomial hierarchy collapses to the third level.


Automata and Reduced Words in the Free Group

Abstract: We consider some questions about formal languages that arise when inverses of letters, words and languages are defined. The reduced representation of a language over the free monoid is its unique equivalent representation in the free group. We show that the class of regular languages is closed under taking the reduced representation, while the class of context-free languages is not. We also give an upper bound on the state complexity of the reduced representation of a regular language, and prove upper and lower bounds on the length of the shortest reducible string in a regular language. Finally we show that the set of all words which are equivalent to the words in a regular language can be nonregular, and that regular languages are not closed under taking a generalized form of the reduced representation.


Classification with Tarskian system executions (Bakery Algorithms as an example)

Abstract: We argue that predicate languages and their Tarskian structures have an important place for the study of concurrency. The argument in our paper is based on an example: we show that two seemingly dissimilar algorithms have a common set of high-level properties, which reveals their affinity. The algorithms are a variant of Lamport's Bakery Algorithm and the Ricart and Agrawala algorithm. They seem different because one uses shared memory and the other message passing for communication. Yet it is intuitively obvious that they are in some sense very similar, and they belong to the same "family of Bakery Algorithms". The aim of this paper is to express in a formal way this intuition that classifies the two algorithms together. For this aim of expressing the abstract high level properties that are shared by the two algorithms we use predicate languages and their Taskian structures. We find a set of properties expressed in quantification language which are satisfied by every Tarskian system execution that models a run by either one of the protocols, and which is strong enough to ensure that the mutual exclusion property holds in these runs.


SPECI, a simulation tool exploring cloud-scale data centres

Abstract: There is a rapid increase in the size of data centres (DCs) used to provide cloud computing services. It is commonly agreed that not all properties in the middleware that manages DCs will scale linearly with the number of components. Further, "normal failure" complicates the assessment of the per-formance of a DC. However, unlike in other engineering domains, there are no well established tools that allow the prediction of the performance and behav-iour of future generations of DCs. SPECI, Simulation Program for Elastic Cloud Infrastructures, is a simulation tool which allows exploration of aspects of scaling as well as performance properties of future DCs.


Throughput in Asynchronous Networks

Abstract: We introduce a new, "worst-case" model for an asynchronous communication network and investigate the simplest (yet central) task in this model, namely the feasibility of end-to-end routing. Motivated by the question of how successful a protocol can hope to perform in a network whose reliability is guaranteed by as few assumptions as possible, we combine the main "unreliability" features encountered in network models in the literature, allowing our model to exhibit all of these characteristics simultaneously. In particular, our model captures networks that exhibit the following properties: 1) On-line; 2) Dynamic Topology; 3)Distributed/Local Control 4) Asynchronous Communication; 5) (Polynomially) Bounded Memory; 6) No Minimal Connectivity Assumptions. In the confines of this network, we evaluate throughput performance and prove matching upper and lower bounds. In particular, using competitive analysis (perhaps somewhat surprisingly) we prove that the optimal competitive ratio of any on-line protocol is 1/n (where n is the number of nodes in the network), and then we describe a specific protocol and prove that it is n-competitive. The model we describe in the paper and for which we achieve the above matching upper and lower bounds for throughput represents the "worst-case" network, in that it makes no reliability assumptions. In many practical applications, the optimal competitive ratio of 1/n may be unacceptable, and consequently stronger assumptions must be imposed on the network to improve performance. However, we believe that a fundamental starting point to understanding which assumptions are necessary to impose on a network model, given some desired throughput performance, is to understand what is achievable in the worst case for the simplest task (namely end-to-end routing).


A Game Theoretic Analysis of Incentives in Content Production and Sharing over Peer-to-Peer Networks

Abstract: User-generated content can be distributed at a low cost using peer-to-peer (P2P) networks, but the free-rider problem hinders the utilization of P2P networks. In order to achieve an efficient use of P2P networks, we investigate fundamental issues on incentives in content production and sharing using game theory. We build a basic model to analyze non-cooperative outcomes without an incentive scheme and then use different game formulations derived from the basic model to examine five incentive schemes: cooperative, payment, repeated interaction, intervention, and enforced full sharing. The results of this paper show that 1) cooperative peers share all produced content while non-cooperative peers do not share at all without an incentive scheme; 2) a cooperative scheme allows peers to consume more content than non-cooperative outcomes do; 3) a cooperative outcome can be achieved among non-cooperative peers by introducing an incentive scheme based on payment, repeated interaction, or intervention; and 4) enforced full sharing has ambiguous welfare effects on peers. In addition to describing the solutions of different formulations, we discuss enforcement and informational requirements to implement each solution, aiming to offer a guideline for protocol designers when designing incentive schemes for P2P networks.


Counting Independent Sets and Kernels of Regular Graphs

Abstract: Chandrasekaran, Chertkov, Gamarnik, Shah, and Shin recently proved that the average number of independent sets of random regular graphs of size n and degree 3 approaches w^n for large n, where w is approximately 1.54563, consistent with the Bethe approximation. They also made the surprising conjecture that the fluctuations of the logarithm of the number of independent sets were only O(1) as n grew large, which would mean that the Bethe approximation is amazingly accurate for all 3-regular graphs. Here, I provide numerical evidence supporting this conjecture obtained from exact counts of independent sets using binary decision diagrams. I also provide numerical evidence that supports the novel conjectures that the number of kernels of 3-regular graphs of size n is given by y^n, where y is approximately 1.299, and that the fluctuations in the logarithm of the number of kernels is also only O(1).


Computing modular correspondences for abelian varieties

Abstract: The aim of this paper is to give a higher dimensional equivalent of the classical modular polynomials $\Phi_\ell(X,Y)$. If $j$ is the $j$-invariant associated to an elliptic curve $E_k$ over a field $k$ then the roots of $\Phi_\ell(j,X)$ correspond to the $j$-invariants of the curves which are $\ell$-isogeneous to $E_k$. Denote by $X_0(N)$ the modular curve which parametrizes the set of elliptic curves together with a $N$-torsion subgroup. It is possible to interpret $\Phi_\ell(X,Y)$ as an equation cutting out the image of a certain modular correspondence $X_0(\ell) \to X_0(1) \times X_0(1)$ in the product $X_0(1) \times X_0(1)$. Let $g$ be a positive integer and $\overn \in \N^g$. We are interested in the moduli space that we denote by $\Mn$ of abelian varieties of dimension $g$ over a field $k$ together with an ample symmetric line bundle $\pol$ and a symmetric theta structure of type $\overn$. If $\ell$ is a prime and let $\overl=(\ell, ..., \ell)$, there exists a modular correspondence $\Mln \to \Mn \times \Mn$. We give a system of algebraic equations defining the image of this modular correspondence.


Competing with Gaussian linear experts

Abstract: We study the problem of online regression. We prove a theoretical bound on the square loss of Ridge Regression. We do not make any assumptions about input vectors or outcomes. We also show that Bayesian Ridge Regression can be thought of as an online algorithm competing with all the Gaussian linear experts.


Sum of Us: Strategyproof Selection from the Selectors

Abstract: We consider directed graphs over a set of n agents, where an edge (i,j) is taken to mean that agent i supports or trusts agent j. Given such a graph and an integer k\leq n, we wish to select a subset of k agents that maximizes the sum of indegrees, i.e., a subset of k most popular or most trusted agents. At the same time we assume that each individual agent is only interested in being selected, and may misreport its outgoing edges to this end. This problem formulation captures realistic scenarios where agents choose among themselves, which can be found in the context of Internet search, social networks like Twitter, or reputation systems like Epinions. Our goal is to design mechanisms without payments that map each graph to a k-subset of agents to be selected and satisfy the following two constraints: strategyproofness, i.e., agents cannot benefit from misreporting their outgoing edges, and approximate optimality, i.e., the sum of indegrees of the selected subset of agents is always close to optimal. Our first main result is a surprising impossibility: for k \in {1,...,n-1}, no deterministic strategyproof mechanism can provide a finite approximation ratio. Our second main result is a randomized strategyproof mechanism with an approximation ratio that is bounded from above by four for any value of k, and approaches one as k grows.


Performance of Joint Spectrum Sensing and MAC Algorithms for Multichannel Opportunistic Spectrum Access Ad Hoc Networks

Abstract: We present an analytical framework to assess the link layer throughput of multichannel Opportunistic Spectrum Access (OSA) ad hoc networks. Specifically, we focus on analyzing various combinations of collaborative spectrum sensing and Medium Access Control (MAC) protocol abstractions. We decompose collaborative spectrum sensing into layers, parametrize each layer, classify existing solutions, and propose a new protocol called Truncated Time Division Multiple Access (TTDMA) that supports efficient distribution of sensing results in "k out of N" fusion rule. In case of multichannel MAC protocols we evaluate two main approaches of control channel design with (i) dedicated and (ii) hopping channel. We propose to augment these protocols with options of handling secondary user (SU) connections preempted by primary user (PU) by (i) connection buffering until PU departure and (ii) connection switching to a vacant PU channel. By comparing and optimizing different design combinations we show that (i) it is generally better to buffer preempted SU connections than to switch them to PU vacant channels and (ii) TTDMA is a promising design option for collaborative spectrum sensing process when k does not change over time.


Parallelization of the LBG Vector Quantization Algorithm for Shared Memory Systems

Abstract: This paper proposes a parallel approach for the Vector Quantization (VQ) problem in image processing. VQ deals with codebook generation from the input training data set and replacement of any arbitrary data with the nearest codevector. Most of the efforts in VQ have been directed towards designing parallel search algorithms for the codebook, and little has hitherto been done in evolving a parallelized procedure to obtain an optimum codebook. This parallel algorithm addresses the problem of designing an optimum codebook using the traditional LBG type of vector quantization algorithm for shared memory systems and for the efficient usage of parallel processors. Using the codebook formed from a training set, any arbitrary input data is replaced with the nearest codevector from the codebook. The effectiveness of the proposed algorithm is indicated.


Correctness Kernels of Abstract Interpretations

Abstract: In abstract interpretation-based static analysis, approximation is encoded by abstract domains. They provide systematic guidelines for designing abstract semantic functions that approximate some concrete system behaviors under analysis. It may happen that an abstract domain contains redundant information for the specific purpose of approximating a given concrete semantic function. This paper introduces the notion of correctness kernel of abstract interpretations, a methodology for simplifying abstract domains, i.e. removing abstract values from them, in a maximal way while retaining exactly the same approximate behavior of the system under analysis. We show that in abstract model checking correctness kernels provide a simplification paradigm of the abstract state space that is guided by examples, meaning that this simplification preserves spuriousness of examples (i.e., abstract paths). In particular, we show how correctness kernels can be integrated with the well-known CEGAR (CounterExample-Guided Abstraction Refinement) methodology.


Enrichissement des contenus par la r\'eindexation des usagers : un \'etat de l'art sur la probl\'ematique

Abstract: Information retrieval (IR) is a user approach to obtain relevant information which meets needs with the help of a IR system (IRS). However, the IRS shows certain differences between user relevance and system relevance. These gaps are essentially related to the imperfection of the indexing process (as approach related to the IR), to problems related to the misunderstanding of the natural language and the non correspondence between the real needs of the user and the results of his query. As idea is to think about an ?intellectual? indexing that takes into account the point of view of the user. By consulting the document, user can build information as added-value on the existing content: new information which grows contents and allows the semantic visibility or facilitates the reading by the annotations, by links to other content, by new descriptors, specific new abstracts of users: it is the reindexing of the contents by the contribution or the vote of the uses


Performance limitations for sparse matrix-vector multiplications on current multicore environments

Abstract: The increasing importance of multicore processors calls for a reevaluation of established numerical algorithms in view of their ability to profit from this new hardware concept. In order to optimize the existent algorithms, a detailed knowledge of the different performance-limiting factors is mandatory. In this contribution we investigate sparse matrix-vector multiplication, which is the dominant operation in many sparse eigenvalue solvers. Two conceptually different storage schemes and computational kernels have been conceived in the past to target cache-based and vector architectures, respectively. Starting from a series of microbenchmarks we apply the gained insight on optimized sparse MVM implementations, whose serial and OpenMP-parallel performance we review on state-of-the-art multicore systems.


A $p$-adic RanSaC algorithm for stereo vision using Hensel lifting

Abstract: A $p$-adic variation of the Ran(dom) Sa(mple) C(onsensus) method for solving the relative pose problem in stereo vision is developped. From two 2-adically encoded images a random sample of five pairs of corresponding points is taken, and the equations for the essential matrix are solved by lifting solutions modulo 2 to the 2-adic integers. A recently devised $p$-adic hierarchical classification algorithm imitating the known LBG quantisation method classifies the solutions for all the samples after having determined the number of clusters using the known intra-inter validity of clusterings. In the successful case, a cluster ranking will determine the cluster containing a 2-adic approximation to the "true" solution of the problem.


Yet Another Pacman 3D Adventures

Abstract: This game is meant to be extension of the overly-beaten pacman-style game (code-named "Yet Another Pacman 3D Adventures", or YAP3DAD) from the proposed ideas and other projects with advance visual and computer graphics features, including a-game-in-a-game approach. The project is an open-source project published on SourceForge.net for possible future development and extension.


Multi-core architectures: Complexities of performance prediction and the impact of cache topology

Abstract: The balance metric is a simple approach to estimate the performance of bandwidth-limited loop kernels. However, applying the method to in-cache situations and modern multi-core architectures yields unsatisfactory results. This paper analyzes the in uence of cache hierarchy design on performance predictions for bandwidth-limited loop kernels on current mainstream processors. We present a diagnostic model with improved predictive power, correcting the limitations of the simple balance metric. The importance of code execution overhead even in bandwidth-bound situations is emphasized. Finally we analyze the impact of synchronization overhead on multi-threaded performance with a special emphasis on the in uence of cache topology.


Artificial Immune Systems

Abstract: The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.


Articulation and Clarification of the Dendritic Cell Algorithm

Abstract: The Dendritic Cell algorithm (DCA) is inspired by recent work in innate immunity. In this paper a formal description of the DCA is given. The DCA is described in detail, and its use as an anomaly detector is illustrated within the context of computer security. A port scan detection task is performed to substantiate the influence of signal selection on the behaviour of the algorithm. Experimental results provide a comparison of differing input signal mappings.


Algorithmic metatheorems for decidable LTL model checking over infinite systems

Abstract: By algorithmic metatheorems for a model checking problem P over infinite-state systems we mean generic results that can be used to infer decidability (possibly complexity) of P not only over a specific class of infinite systems, but over a large family of classes of infinite systems. Such results normally start with a powerful formalism of infinite-state systems, over which P is undecidable, and assert decidability when is restricted by means of an extra "semantic condition" C. We prove various algorithmic metatheorems for the problems of model checking LTL and its two common fragments LTL(Fs,Gs) and LTLdet over the expressive class of word/tree automatic transition systems, which are generated by synchronized finite-state transducers operating on finite words and trees. We present numerous applications, where we derive (in a unified manner) many known and previously unknown decidability and complexity results of model checking LTL and its fragments over specific classes of infinite-state systems including pushdown systems; prefix-recognizable systems; reversal-bounded counter systems with discrete clocks and a free counter; concurrent pushdown systems with a bounded number of context-switches; various subclasses of Petri nets; weakly extended PA-processes; and weakly extended ground-tree rewrite systems. In all cases,we are able to derive optimal (or near optimal) complexity. Finally, we pinpoint the exact locations in the arithmetic and analytic hierarchies of the problem of checking a relevant semantic condition and the LTL model checking problems over all word/tree automatic systems.


A Dialogue Concerning Two World Systems: Info-Computational vs. Mechanistic

Abstract: The dialogue develops arguments for and against adopting a new world system, info-computationalist naturalism, that is poised to replace the traditional mechanistic world system. We try to figure out what the info-computational paradigm would mean, in particular its pancomputationalism. We make some steps towards developing the notion of computing that is necessary here, especially in relation to traditional notions. We investigate whether pancomputationalism can possibly provide the basic causal structure to the world, whether the overall research programme appears productive and whether it can revigorate computationalism in the philosophy of mind.


An Iterative Shrinkage Approach to Total-Variation Image Restoration

Abstract: The problem of restoration of digital images from their degraded measurements plays a central role in a multitude of practically important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modeled by an ill-conditioned operator. In such a case, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some a priori information about its properties. Such a priori information is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used in this case is defined by the Rudin-Osher-Fatemi model, which results in total variation (TV) based image restoration. The current arsenal of algorithms for TV-based image restoration is vast. In the present paper, a different approach to the solution of the problem is proposed based on the method of iterative shrinkage (aka iterated thresholding). In the proposed method, the TV-based image restoration is performed through a recursive application of two simple procedures, viz. linear filtering and soft thresholding. Therefore, the method can be identified as belonging to the group of first-order algorithms which are efficient in dealing with images of relatively large sizes. Another valuable feature of the proposed method consists in its working directly with the TV functional, rather then with its smoothed versions. Moreover, the method provides a single solution for both isotropic and anisotropic definitions of the TV functional, thereby establishing a useful connection between the two formulae.


Temporal Debugging using URDB

Abstract: A new style of temporal debugging is proposed. The new URDB debugger can employ such techniques as temporal search for finding an underlying fault that is causing a bug. This improves on the standard iterative debugging style, which iteratively re-executes a program under debugger control in the search for the underlying fault. URDB acts as a meta-debugger, with current support for four widely used debuggers: gdb, MATLAB, python, and perl. Support for a new debugger can be added in a few hours. Among its points of novelty are: (i) the first reversible debuggers for MATLAB, python, and perl; (ii) support for today's multi-core architectures; (iii) reversible debugging of multi-process and distributed computations; and (iv) temporal search on changes in program expressions. URDB gains its reversibility and temporal abilities through the fast checkpoint-restart capability of DMTCP (Distributed MultiThreaded CheckPointing). The recently enhanced DMTCP also adds ptrace support, enabling one to freeze, migrate, and replicate debugging sessions.


Compiling and securing cryptographic protocols

Abstract: Protocol narrations are widely used in security as semi-formal notations to specify conversations between roles. We define a translation from a protocol narration to the sequences of operations to be performed by each role. Unlike previous works, we reduce this compilation process to well-known decision problems in formal protocol analysis. This allows one to define a natural notion of prudent translation and to reuse many known results from the literature in order to cover more crypto-primitives. In particular this work is the first one to show how to compile protocols parameterised by the properties of the available operations.


The Complexity of Iterated Strategy Elimination

Abstract: We consider the computational complexity of the question whether a certain strategy can be removed from a game by means of iterated elimination of dominated strategies. In particular, we study the influence of different definitions of domination and of the number of different payoff values. In addition, the consequence of restriction to constant-sum games is shown.


Approximation Algorithms for Link Scheduling with Physical Interference Model in Wireless Multi-hop Networks

Abstract: The link scheduling in wireless multi-hop networks is addressed. Different from most of work that adopt the protocol interference model which merely take consideration of packet collisions, our proposed algorithms use the physical interference model to reflect the aggregated signal to interference and noise ratio (SINR), which is a more accurate abstraction of the real scenario. We first propose a centralized scheduling method based on the Integer Linear Programming (ILP) and resolve it by an approximate solution based on the randomized rounding method. The probability bound of getting a guaranteed approximate factor is given. We then extend the centralized algorithm to a distributed solution, which is favorable in wireless networks. It is proven that with the distributed scheduling method, all links can transmit without interference, and the approximate ratio of the algorithm is also given.


A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion

Abstract: We consider the problem of reconstructing a low-rank matrix from a small subset of its entries. In this paper, we describe the implementation of an efficient algorithm called OptSpace, based on singular value decomposition followed by local manifold optimization, for solving the low-rank matrix completion problem. It has been shown that if the number of revealed entries is large enough, the output of singular value decomposition gives a good estimate for the original matrix, so that local optimization reconstructs the correct matrix with high probability. We present numerical results which show that this algorithm can reconstruct the low rank matrix exactly from a very small subset of its entries. We further study the robustness of the algorithm with respect to noise, and its performance on actual collaborative filtering datasets.


Isogenies of Elliptic Curves: A Computational Approach

Abstract: Isogenies, the mappings of elliptic curves, have become a useful tool in cryptology. These mathematical objects have been proposed for use in computing pairings, constructing hash functions and random number generators, and analyzing the reducibility of the elliptic curve discrete logarithm problem. With such diverse uses, understanding these objects is important for anyone interested in the field of elliptic curve cryptography. This paper, targeted at an audience with a knowledge of the basic theory of elliptic curves, provides an introduction to the necessary theoretical background for understanding what isogenies are and their basic properties. This theoretical background is used to explain some of the basic computational tasks associated with isogenies. Herein, algorithms for computing isogenies are collected and presented with proofs of correctness and complexity analyses. As opposed to the complex analytic approach provided in most texts on the subject, the proofs in this paper are primarily algebraic in nature. This provides alternate explanations that some with a more concrete or computational bias may find more clear.


A theoretical foundation for building Knowledge-work Support Systems

Abstract: In this paper we propose a novel approach aimed at building a new class of information system platforms which we call the "Knowledge-work Support Systems" or KwSS. KwSS can play a significant role in enhancing the IS support for knowledge management processes, including those customarily identified as less amenable to IS support. In our approach we try to enhance basic functionalities provided by the computer-based information systems, namely, that of improving the efficiency of the knowledge workers in accessing, processing and creating useful information. The improvement, along with proper focus on cultural, social and other aspects of the knowledge management processes, can enhance the workers' efficiency significantly in performing high quality knowledge works. In order to build the proposed approach, we develop several new concepts. The approach analyzes the information availability and usage from the knowledge workers and their works' perspectives and consequently brings forth more transparency in various aspects of information life-cycle with respect to knowledge management. KsSSes are technology platforms, which can be implemented independently as well as in conjunction with other knowledge management and data management technology platforms, to provide significant boost in the knowledge capabilities of organizations.


A Graph Model for Imperative Computation

Abstract: Scott's graph model is a lambda-algebra based on the observation that continuous endofunctions on the lattice of sets of natural numbers can be represented via their graphs. A graph is a relation mapping finite sets of input values to output values. We consider a similar model based on relations whose input values are finite sequences rather than sets. This alteration means that we are taking into account the order in which observations are made. This new notion of graph gives rise to a model of affine lambda-calculus that admits an interpretation of imperative constructs including variable assignment, dereferencing and allocation. Extending this untyped model, we construct a category that provides a model of typed higher-order imperative computation with an affine type system. An appropriate language of this kind is Reynolds's Syntactic Control of Interference. Our model turns out to be fully abstract for this language. At a concrete level, it is the same as Reddy's object spaces model, which was the first "state-free" model of a higher-order imperative programming language and an important precursor of games models. The graph model can therefore be seen as a universal domain for Reddy's model.


Artificial Immune Tissue using Self-Orgamizing Networks

Abstract: As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some have argued that this concept in the context of AIS brings little novelty to the already saturated field of the immune inspired computational research. This article aims to show that such a component of an AIS has the potential to bring an advantage to a data processing algorithm in terms of data pre-processing, clustering and extraction of features desired by the immune inspired system. The proposed tissue algorithm is based on self-organizing networks, such as self-organizing maps (SOM) developed by Kohonen (1996) and an analogy of the so called Toll-Like Receptors (TLR) affecting the activation function of the clusters developed by the SOM.


The Uned systems at Senseval-2

Abstract: We have participated in the SENSEVAL-2 English tasks (all words and lexical sample) with an unsupervised system based on mutual information measured over a large corpus (277 million words) and some additional heuristics. A supervised extension of the system was also presented to the lexical sample task. Our system scored first among unsupervised systems in both tasks: 56.9% recall in all words, 40.2% in lexical sample. This is slightly worse than the first sense heuristic for all words and 3.6% better for the lexical sample, a strong indication that unsupervised Word Sense Disambiguation remains being a strong challenge.


Word Sense Disambiguation Based on Mutual Information and Syntactic Patterns

Abstract: This paper describes a hybrid system for WSD, presented to the English all-words and lexical-sample tasks, that relies on two different unsupervised approaches. The first one selects the senses according to mutual information proximity between a context word a variant of the sense. The second heuristic analyzes the examples of use in the glosses of the senses so that simple syntactic patterns are inferred. This patterns are matched against the disambiguation contexts. We show that the first heuristic obtains a precision and recall of .58 and .35 respectively in the all words task while the second obtains .80 and .25. The high precision obtained recommends deeper research of the techniques. Results for the lexical sample task are also provided.


Continuum Equilibria and Global Optimization for Routing in Dense Static Ad Hoc Networks

Abstract: We consider massively dense ad hoc networks and study their continuum limits as the node density increases and as the graph providing the available routes becomes a continuous area with location and congestion dependent costs. We study both the global optimal solution as well as the non-cooperative routing problem among a large population of users where each user seeks a path from its origin to its destination so as to minimize its individual cost. Finally, we seek for a (continuum version of the) Wardrop equilibrium. We first show how to derive meaningful cost models as a function of the scaling properties of the capacity of the network and of the density of nodes. We present various solution methodologies for the problem: (1) the viscosity solution of the Hamilton-Jacobi-Bellman equation, for the global optimization problem, (2) a method based on Green's Theorem for the least cost problem of an individual, and (3) a solution of the Wardrop equilibrium problem using a transformation into an equivalent global optimization problem.


An Example of Symmetry Exploitation for Energy-related Eigencomputations

Abstract: One of the most used approaches in simulating materials is the tight-binding approximation. When using this method in a material simulation, it is necessary to compute the eigenvalues and eigenvectors of the Hamiltonian describing the system. In general, the system possesses few explicit symmetries. Due to them, the problem has many degenerate eigenvalues. The ambiguity in choosing a orthonormal basis of the invariant subspaces, associated with degenerate eigenvalues, will result in eigenvectors which are not invariant under the action of the symmetry operators in matrix form. A meaningful computation of the eigenvectors needs to take those symmetries into account. A natural choice is a set of eigenvectors, which simultaneously diagonalizes the Hamiltonian and the symmetry matrices. This is possible because all the matrices commute with each other. The simultaneous eigenvectors and the corresponding eigenvalues will be in a parametrized form in terms of the lattice momentum components. This functional dependence of the eigenvalues is the dispersion relation and describes the band structure of a material. Therefore it is important to find this functional dependence in any numerical computation related to material properties.


Fast algorithms for spherical harmonic expansions, III

Abstract: We accelerate the computation of spherical harmonic transforms, using what is known as the butterfly scheme. This provides a convenient alternative to the approach taken in the second paper from this series on "Fast algorithms for spherical harmonic expansions." The requisite precomputations become manageable when organized as a "depth-first traversal" of the program's control-flow graph, rather than as the perhaps more natural "breadth-first traversal" that processes one-by-one each level of the multilevel procedure. We illustrate the results via several numerical examples.