Beamsteering on Mobile Devices: Network Capacity and Client Efficiency

Abstract: Current and emerging mobile devices are omni directional in wireless communication. Such omni directionality not only limits device energy efficiency but also poses a significant challenge toward the capacity of wireless networks through inter-link interference. In this work, we seek to make mobile clients directional with beamsteering. We first demonstrate that beamsteering is already feasible to mobile devices such as Netbooks and eBook readers in terms of form factor, power efficiency, and device mobility. We further reveal that beamsteering mobile clients face a unique challenge to balance client efficiency and network capacity. There is an optimal operating point for a beamsteering mobile client in terms of the number of antennas and transmit power that achieve the required capacity with lowest power. Finally, we provide a distributed algorithm called BeamAdapt that allows each client to closely approach its optimal point iteratively without central coordination. We also offer a cellular system realization of BeamAdapt. Using Qualnet-based simulation, we show that BeamAdapt with four antennas can reduce client power consumption by 55% while maintaining a required network throughput for a large-scale network, compared to the same network with omni directional mobile clients.


Sesame: Self-Constructive System Energy Modeling for Battery-Powered Mobile Systems

Abstract: System energy models are important for energy optimization and management in mobile systems. However, existing system energy models are built in lab with the help from a second computer. Not only are they labor-intensive; but also they will not adequately account for the great diversity in the hardware and usage of mobile systems. Moreover, existing system energy models are intended for energy estimation for time intervals of one second or longer; they do not provide the required rate for fine-grain use such as per-application energy accounting. In this work, we study a self-modeling paradigm in which a mobile system automatically generates its energy model without any external assistance. Our solution, Se-same, leverages the possibility of self power measurement through the smart battery interface and employs a suite of novel techniques to achieve accuracy and rate much higher than that of the smart battery interface. We report the implementation and evaluation of Se-same on a laptop and a smartphone. The experiment results show that Sesame generates system energy models of 95% accuracy at one estimation per second and 88% accuracy at one estimation per 10ms, without any external assistance. A five-day field studies with four laptop and four smartphones users further demonstrate the effectiveness, efficiency, and noninvasiveness of Sesame.


A Longitudinal Study of Non-Voice Mobile Phone Usage by Teens from an Underserved Urban Community

Abstract: We report a user study of over four months on the non-voice usage of mobile phones by teens from an underserved urban community in the USA where a community-wide, open-access Wi-Fi network exists. We instrumented the phones to record quantitative information regarding their usage and location in a privacy-respecting manner. We conducted focus group meetings and interviewed participants regularly for qualitative data. We present our findings on what applications our participants used and how their usage changed over time. The findings highlight the challenges to evaluating the usability of mobile systems and the value of long-term methodologies. Based on our findings, we analyze the unique values of mobile phones, as a platform technology. Our study shows that the usage is highly mobile, location-dependent, and serves multiple social purposes for the participants. Furthermore, we present concrete findings on how to perform and analyze similar user studies on mobile phones, including four contributing factors to usage evolution, and provide guidelines for their design and evaluation.


Relational transducers for declarative networking

Abstract: Motivated by a recent conjecture concerning the expressiveness of declarative networking, we propose a formal computation model for "eventually consistent" distributed querying, based on relational transducers. A tight link has been conjectured between coordination-freeness of computations, and monotonicity of the queries expressed by such computations. Indeed, we propose a formal definition of coordination-freeness and confirm that the class of monotone queries is captured by coordination-free transducer networks. Coordination-freeness is a semantic property, but the syntactic class that we define of "oblivious" transducers also captures the same class of monotone queries. Transducer networks that are not coordination-free are much more powerful.


Towards Refactoring the DMF to Support Jini and JMS DMS in GIPSY

Abstract: In this paper we report on our re-engineering effort to refactor and unify two somewhat disjoint Java distributed middleware technologies -- Jini and JMS -- used in the implementation of the Demand Migration System (DMS). In doing so, we refactor their parent Demand Migration Framework (DMF), within the General Intensional Programming System (GIPSY). The complex Java-based GIPSY project is used to investigate on the intensional and hybrid programming paradigms.


Digital watermarking : An approach based on Hilbert transform

Abstract: Most of the well known algorithms for watermarking of digital images involve transformation of the image data to Fourier or singular vector space. In this paper, we introduce watermarking in Hilbert transform domain for digital media. Generally, if the image is a matrix of order $m$ by $n$, then the transformed space is also an image of the same order. However, with Hilbert transforms, the transformed space is of order $2m$ by $2n$. This allows for more latitude in storing the watermark in the host image. Based on this idea, we propose an algorithm for embedding and extracting watermark in a host image and analytically obtain a parameter related to this procedure. Using extensive simulations, we show that the algorithm performs well even if the host image is corrupted by various attacks.


A Study on Recent Approaches in Handling DDoS Attacks

Abstract: In this paper, we present a study on the recent approaches in handling Distributed Denial of Service (DDoS) attacks. DDoS attack is a fairly new type of attack to cripple the availability of Internet services and resources. A DDos attack can originate from anywhere in the network and typically overwhelms the victim server by sending a huge number of packets. Several remedial measures have been proposed by various researchers. This paper attempts to discuss the recent offerings to handle the DDoS attacks.


A Proof Carrying Code Framework for Inlined Reference Monitors in Java Bytecode

Abstract: We propose a light-weight approach for certification of monitor inlining for sequential Java bytecode using proof-carrying code. The goal is to enable the use of monitoring for quality assurance at development time, while minimizing the need for post-shipping code rewrites as well as changes to the end-host TCB. Standard automaton-based security policies express constraints on allowed API call/return sequences. Proofs are represented as JML-style program annotations. This is adequate in our case as all proofs generated in our framework are recognized in time polynomial in the size of the program. Policy adherence is proved by comparing the transitions of an inlined monitor with those of a trusted "ghost" monitor represented using JML-style annotations. At time of receiving a program with proof annotations, it is sufficient for the receiver to plug in its own trusted ghost monitor and check the resulting verification conditions, to verify that inlining has been performed correctly, of the correct policy. We have proved correctness of the approach at the Java bytecode level and formalized the proof of soundness in Coq. An implementation, including an application loader running on a mobile device, is available, and we conclude by giving benchmarks for two sample applications.


On Probabilistic Parallel Programs with Process Creation and Synchronisation

Abstract: We initiate the study of probabilistic parallel programs with dynamic process creation and synchronisation. To this end, we introduce probabilistic split-join systems (pSJSs), a model for parallel programs, generalising both probabilistic pushdown systems (a model for sequential probabilistic procedural programs which is equivalent to recursive Markov chains) and stochastic branching processes (a classical mathematical model with applications in various areas such as biology, physics, and language processing). Our pSJS model allows for a possibly recursive spawning of parallel processes; the spawned processes can synchronise and return values. We study the basic performance measures of pSJSs, especially the distribution and expectation of space, work and time. Our results extend and improve previously known results on the subsumed models. We also show how to do performance analysis in practice, and present two case studies illustrating the modelling power of pSJSs.


Random Generation and Approximate Counting of Combinatorial Structures

Abstract: The aim of this thesis is to determine classes of NP relations for which random generation and approximate counting problems admit an efficient solution. Since efficient rank implies efficient random generation, we first investigate some classes of NP relations admitting efficient ranking. On the other hand, there are situations in which efficient random generation is possible even when ranking is computationally infeasible. We introduce the notion of ambiguous description as a tool for random generation and approximate counting in such cases and show, in particular, some applications to the case of formal languages. Finally, we discuss a limit of an heuristic for combinatorial optimization problems based on the random initialization of local search algorithms showing that derandomizing such heuristic can be, in some cases, #P-hard.


An Improved Algorithm for Bipartite Correlation Clustering

Abstract: Bipartite Correlation clustering is the problem of generating a set of disjoint bi-cliques on a set of nodes while minimizing the symmetric difference to a bipartite input graph. The number or size of the output clusters is not constrained in any way. The best known approximation algorithm for this problem gives a factor of 11. This result and all previous ones involve solving large linear or semi-definite programs which become prohibitive even for modestly sized tasks. In this paper we present an improved factor 4 approximation algorithm to this problem using a simple combinatorial algorithm which does not require solving large convex programs. The analysis extends a method developed by Ailon, Charikar and Alantha in 2008, where a randomized pivoting algorithm was analyzed for obtaining a 3-approximation algorithm for Correlation Clustering, which is the same problem on graphs (not bipartite). The analysis for Correlation Clustering there required defining events for structures containing 3 vertices and using the probability of these events to produce a feasible solution to a dual of a certain natural LP bounding the optimal cost. It is tempting here to use sets of 4 vertices, which are the smallest structures for which contradictions arise for Bipartite Correlation Clustering. This simple idea, however, appears to be evasive. We show that, by modifying the LP, we can analyze algorithms which take into consideration subgraph structures of unbounded size. We believe our techniques are interesting in their own right, and may be used for other problems as well.


On the size of data structures used in symbolic model checking

Abstract: Temporal Logic Model Checking is a verification method in which we describe a system, the model, and then we verify whether some properties, expressed in a temporal logic formula, hold in the system. It has many industrial applications. In order to improve performance, some tools allow preprocessing of the model, verifying on-line a set of properties reusing the same compiled model; we prove that the complexity of the Model Checking problem, without any preprocessing or preprocessing the model or the formula in a polynomial data structure, is the same. As a result preprocessing does not always exponentially improve performance. Symbolic Model Checking algorithms work by manipulating sets of states, and these sets are often represented by BDDs. It has been observed that the size of BDDs may grow exponentially as the model and formula increase in size. As a side result, we formally prove that a superpolynomial increase of the size of these BDDs is unavoidable in the worst case. While this exponential growth has been empirically observed, to the best of our knowledge it has never been proved so far in general terms. This result not only holds for all types of BDDs regardless of the variable ordering, but also for more powerful data structures, such as BEDs, RBCs, MTBDDs, and ADDs.


E = I + T: The internal extent formula for compacted tries

Abstract: It is well known that in a binary tree the external path length minus the internal path length is exactly 2n-2, where n is the number of external nodes. We show that a generalization of the formula holds for compacted tries, replacing the role of paths with the notion of extent, and the value 2n-2 with the trie measure, an estimation of the number of bits that are necessary to describe the trie.


Numerically Representing A Stochastic Process Algebra

Abstract: The syntactic nature and compositionality characteristic of stochastic process algebras make models to be easily understood by human beings, but not convenient for machines as well as people to directly carry out mathematical analysis and stochastic simulation. This paper presents a numerical representation schema for the stochastic process algebra PEPA, which can provide a platform to directly and conveniently employ a variety of computational approaches to both qualitatively and quantitatively analyse the models. Moreover, these approaches developed on the basis of the schema are demonstrated and discussed. In particular, algorithms for automatically deriving the schema from a general PEPA model and simulating the model based on the derived schema to derive performance measures are presented.


Speeding Up the 3D Surface Generator VESTA

Abstract: The very recent volume-enclosing surface extraction algorithm, VESTA, is revisited. VESTA is used to determine implicit surfaces that are potentially contained in 3D data sets, such as 3D image data and/or 3D simulation data. VESTA surfaces are non-degenerate, i.e., they always enclose a volume that is larger than zero and they never self-intersect, prior to a further processing, e.g., towards isosurfaces. In addition to its ability to deal with local cell ambiguities consistently - and thereby avoiding the accidental generation of holes in the final surfaces - the information of the interior and/or exterior of enclosed 3D volumes is propagated correctly to each of the final surface tiles. Particular emphasis is put here on the speed up of the original formulation of VESTA, while applying the algorithm to 2x2x2 voxel neighborhoods.


Seamless Flow Migration on Smartphones without Network Support

Abstract: This paper addresses the following question: Is it possible to migrate TCP/IP flows between different networks on modern mobile devices, without infrastructure support or protocol changes? To answer this question, we make three research contributions. (i) We report a comprehensive characterization of IP traffic on smartphones using traces collected from 27 iPhone 3GS users for three months. (ii) Driven by the findings from the characterization, we devise two novel system mechanisms for mobile devices to sup-port seamless flow migration without network support, and extensively evaluate their effectiveness using our field collected traces of real-life usage. Wait-n-Migrate leverages the fact that most flows are short lived. It establishes new flows on newly available networks but allows pre-existing flows on the old network to terminate naturally, effectively decreasing, or even eliminating, connectivity gaps during network switches. Resumption Agent takes advantage of the functionality integrated into many modern protocols to securely resume flows without application intervention. When combined, Wait-n-Migrate and Resumption Agent provide an unprecedented opportunity to immediately deploy performance and efficiency-enhancing policies that leverage multiple networks to improve the performance, efficiency, and connectivity of mobile devices. (iii) Finally, we report an iPhone 3GS based implementation of these two system mechanisms and show that their overhead is negligible. Furthermore, we employ an example network switching policy, called AutoSwitch, to demonstrate their performance. AutoSwitch improves the Wi-Fi user experience by intelligently migrating TCP flows between Wi-Fi and cellular networks. Through traces and field measurements, we show that AutoSwitch reduces the number of user disruptions by an order of magnitude.


Secure Information Flow by Model Checking Pushdown System

Abstract: We propose an approach on model checking information flow for imperative language with procedures. We characterize our model with pushdown system, which has a stack of unbounded length that naturally models the execution of procedural programs. Because the type-based static analysis is sometimes too conservative and rejects safe program as ill-typed, we take a semantic-based approach by self-composing symbolic pushdown system and specifying noninterference with LTL formula. Then we verify this LTL-expressed property via model checker Moped. Except for overcoming the conservative characteristic of type-based approach, our motivation also includes the insufficient state of arts on precise information flow analysis under inter-procedural setting. To remedy the inefficiency of model checking compared with type system, we propose both compact form and contracted form of self-composition. According to our experimental results, they can greatly increase the efficiency of realistic verification. Our method provides flexibility on separating program abstraction from noninterference verification, thus could be expected to use on different programming languages.


How to Catch L_2-Heavy-Hitters on Sliding Windows

Abstract: Finding heavy-elements (heavy-hitters) in streaming data is one of the central, and well-understood tasks. Despite the importance of this problem, when considering the sliding windows model of streaming (where elements eventually expire) the problem of finding L_2-heavy elements has remained completely open despite multiple papers and considerable success in finding L_1-heavy elements. In this paper, we develop the first poly-logarithmic-memory algorithm for finding L_2-heavy elements in sliding window model. Since L_2 heavy elements play a central role for many fundamental streaming problems (such as frequency moments), we believe our method would be extremely useful for many sliding-windows algorithms and applications. For example, our technique allows us not only to find L_2-heavy elements, but also heavy elements with respect to any L_p for 0<p<2 on sliding windows. Thus, our paper completely resolves the question of finding L_p-heavy elements for sliding windows with poly-logarithmic memory for all values of p since it is well known that for p>2 this task is impossible. Our method may have other applications as well. We demonstrate a broader applicability of our novel yet simple method on two additional examples: we show how to obtain a sliding window approximation of other properties such as the similarity of two streams, or the fraction of elements that appear exactly a specified number of times within the window (the rarity problem). In these two illustrative examples of our method, we replace the current expected memory bounds with worst case bounds.


To study the phenomenon of the Moravec's Paradox

Abstract: "Encoded in the large, highly evolved sensory and motor portions of the human brain is a billion years of experience about the nature of the world and how to survive in it. The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because it is supported by this much older and much powerful, though usually unconscious, sensor motor knowledge. We are all prodigious Olympians in perceptual and motor areas, so good that we make the difficult look easy. Abstract thought, though, is a new trick, perhaps less than 100 thousand years old. We have not yet mastered it. It is not all that intrinsically difficult; it just seems so when we do it."- Hans Moravec Moravec's paradox is involved with the fact that it is the seemingly easier day to day problems that are harder to implement in a machine, than the seemingly complicated logic based problems of today. The results prove that most artificially intelligent machines are as adept if not more than us at under-taking long calculations or even play chess, but their logic brings them nowhere when it comes to carrying out everyday tasks like walking, facial gesture recognition or speech recognition.


Maximizing Expected Utility for Stochastic Combinatorial Optimization Problems

Abstract: We study the stochastic versions of a broad class of combinatorial problems where the weights of the elements in the input dataset are uncertain. The class of problems that we study includes shortest paths, minimum weight spanning trees, and minimum weight matchings, and other combinatorial problems like knapsack. We observe that the expected value is inadequate in capturing different types of {\em risk-averse} or {\em risk-prone} behaviors, and instead we consider a more general objective which is to maximize the {\em expected utility} of the solution for some given utility function, rather than the expected weight (expected weight becomes a special case). Under the assumption that there is a pseudopolynomial time algorithm for the {\em exact} version of the problem (This is true for the problems mentioned above), we can obtain the following approximation results for several important classes of utility functions: (1) If the utility function $\uti$ is continuous, upper-bounded by a constant and $\lim_{x\rightarrow+\infty}\uti(x)=0$, we show that we can obtain a polynomial time approximation algorithm with an {\em additive error} $\epsilon$ for any constant $\epsilon>0$. (2) If the utility function $\uti$ is a concave increasing function, we can obtain a polynomial time approximation scheme (PTAS). (3) If the utility function $\uti$ is increasing and has a bounded derivative, we can obtain a polynomial time approximation scheme. Our results recover or generalize several prior results on stochastic shortest path, stochastic spanning tree, and stochastic knapsack. Our algorithm for utility maximization makes use of the separability of exponential utility and a technique to decompose a general utility function into exponential utility functions, which may be useful in other stochastic optimization problems.


TILT: Transform Invariant Low-rank Textures

Abstract: In this paper, we show how to efficiently and effectively extract a class of "low-rank textures" in a 3D scene from 2D images despite significant corruptions and warping. The low-rank textures capture geometrically meaningful structures in an image, which encompass conventional local features such as edges and corners as well as all kinds of regular, symmetric patterns ubiquitous in urban environments and man-made objects. Our approach to finding these low-rank textures leverages the recent breakthroughs in convex optimization that enable robust recovery of a high-dimensional low-rank matrix despite gross sparse errors. In the case of planar regions with significant affine or projective deformation, our method can accurately recover both the intrinsic low-rank texture and the precise domain transformation, and hence the 3D geometry and appearance of the planar regions. Extensive experimental results demonstrate that this new technique works effectively for many regular and near-regular patterns or objects that are approximately low-rank, such as symmetrical patterns, building facades, printed texts, and human faces.


Iterative Beam Search for Simple Assembly Line Balancing with a Fixed Number of Work Stations

Abstract: The simple assembly line balancing problem (SALBP) concerns the assignment of tasks with pre-defined processing times to work stations that are arranged in a line. Hereby, precedence constraints between the tasks must be respected. The optimization goal of the SALBP-2 version of the problem concerns the minimization of the so-called cycle time, that is, the time in which the tasks of each work station must be completed. In this work we propose to tackle this problem with an iterative search method based on beam search. The proposed algorithm is able to obtain optimal, respectively best-known, solutions in 283 out of 302 test cases. Moreover, for 9 further test cases the algorithm is able to produce new best-known solutions. These numbers indicate that the proposed iterative beam search algorithm is currently a state-of-the-art method for the SALBP-2.


Collaborative Knowledge Creation and Management in Information Retrieval

Abstract: The final goal of Information Retrieval (IR) is knowledge production. However, it has been argued that knowledge production is not an individual effort but a collaborative effort. Collaboration in information retrieval is geared towards knowledge sharing and creation of new knowledge by users. This paper discusses Collaborative Information Retrieval (CIR) and how it culminates to knowledge creation. It explains how created knowledge is organized and structured. It describes a functional architecture for the development of a CIR prototype called MECOCIR. Some of the features of the prototype are presented as well as how they facilitate collaborative knowledge exploitation. Knowledge creation is explained through the knowledge conversion/transformation processes proposed by Nonaka and CIR activities that facilitate these processes are high-lighted and discussed


A new Recommender system based on target tracking: a Kalman Filter approach

Abstract: In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the multidimensional space of the categories of the resources. Knowing this space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation space.


Incentive Games and Mechanisms for Risk Management

Abstract: Incentives play an important role in (security and IT) risk management of a large-scale organization with multiple autonomous divisions. This paper presents an incentive mechanism design framework for risk management based on a game-theoretic approach. The risk manager acts as a mechanism designer providing rules and incentive factors such as assistance or subsidies to divisions or units, which are modeled as selfish players of a strategic (noncooperative) game. Based on this model, incentive mechanisms with various objectives are developed that satisfy efficiency, preference-compatibility, and strategy-proofness criteria. In addition, iterative and distributed algorithms are presented, which can be implemented under information limitations such as the risk manager not knowing the individual units' preferences. An example scenario illustrates the framework and results numerically. The incentive mechanism design approach presented is useful for not only deriving guidelines but also developing computer-assistance systems for large-scale risk management.


Set Covering with Ordered Replacement -- Additive and Multiplicative Gaps

Abstract: We consider set covering problems where the underlying set system satisfies a particular replacement property w.r.t. a given partial order on the elements: Whenever a set is in the set system then a set stemming from it via the replacement of an element by a smaller element is also in the set system. Many variants of BIN PACKING that have appeared in the literature are such set covering problems with ordered replacement. We provide a rigorous account on the additive and multiplicative integrality gap and approximability of set covering with replacement. In particular we provide a polylogarithmic upper bound on the additive integrality gap that also yields a polynomial time additive approximation algorithm if the linear programming relaxation can be efficiently solved. We furthermore present an extensive list of covering problems that fall into our framework and consequently have polylogarithmic additive gaps as well.


Validating XML Documents in the Streaming Model with External Memory

Abstract: We study the problem of validating XML documents of size $N$ against general DTDs in the context of streaming algorithms. The starting point of this work is a well-known space lower bound. There are XML documents and DTDs for which $p$-pass streaming algorithms require $\Omega(N/p)$ space. We show that when allowing access to external memory, there is a deterministic streaming algorithm that solves this problem with memory space $O(\log^2 N)$, a constant number of auxiliary read/write streams, and $O(\log N)$ total number of passes on the XML document and auxiliary streams. An important intermediate step of this algorithm is the computation of the First-Child-Next-Sibling (FCNS) encoding of the initial XML document in a streaming fashion. We study this problem independently, and we also provide memory efficient streaming algorithms for decoding an XML document given in its FCNS encoding. Furthermore, validating XML documents encoding binary trees in the usual streaming model without external memory can be done with sublinear memory. There is a one-pass algorithm using $O(\sqrt{N \log N})$ space, and a bidirectional two-pass algorithm using $O(\log^2 N)$ space performing this task.


Dynamic Capitalization and Visualization Strategy in Collaborative Knowledge Management System for EI Process

Abstract: Knowledge is attributed to human whose problem-solving behavior is subjective and complex. In today's knowledge economy, the need to manage knowledge produced by a community of actors cannot be overemphasized. This is due to the fact that actors possess some level of tacit knowledge which is generally difficult to articulate. Problem-solving requires searching and sharing of knowledge among a group of actors in a particular context. Knowledge expressed within the context of a problem resolution must be capitalized for future reuse. In this paper, an approach that permits dynamic capitalization of relevant and reliable actors' knowledge in solving decision problem following Economic Intelligence process is proposed. Knowledge annotation method and temporal attributes are used for handling the complexity in the communication among actors and in contextualizing expressed knowledge. A prototype is built to demonstrate the functionalities of a collaborative Knowledge Management system based on this approach. It is tested with sample cases and the result showed that dynamic capitalization leads to knowledge validation hence increasing reliability of captured knowledge for reuse. The system can be adapted to various domains


Data Conflict Resolution Using Trust Mappings

Abstract: In massively collaborative projects such as scientific or community databases, users often need to agree or disagree on the content of individual data items. On the other hand, trust relationships often exist between users, allowing them to accept or reject other users' beliefs by default. As those trust relationships become complex, however, it becomes difficult to define and compute a consistent snapshot of the conflicting information. Previous solutions to a related problem, the update reconciliation problem, are dependent on the order in which the updates are processed and, therefore, do not guarantee a globally consistent snapshot. This paper proposes the first principled solution to the automatic conflict resolution problem in a community database. Our semantics is based on the certain tuples of all stable models of a logic program. While evaluating stable models in general is well known to be hard, even for very simple logic programs, we show that the conflict resolution problem admits a PTIME solution. To the best of our knowledge, ours is the first PTIME algorithm that allows conflict resolution in a principled way. We further discuss extensions to negative beliefs and prove that some of these extensions are hard. This work is done in the context of the BeliefDB project at the University of Washington, which focuses on the efficient management of conflicts in community databases.


Dynamic Knowledge Capitalization through Annotation among Economic Intelligence Actors in a Collaborative Environment

Abstract: The shift from industrial economy to knowledge economy in today's world has revolutionalized strategic planning in organizations as well as their problem solving approaches. The point of focus today is knowledge and service production with more emphasis been laid on knowledge capital. Many organizations are investing on tools that facilitate knowledge sharing among their employees and they are as well promoting and encouraging collaboration among their staff in order to build the organization's knowledge capital with the ultimate goal of creating a lasting competitive advantage for their organizations. One of the current leading approaches used for solving organization's decision problem is the Economic Intelligence (EI) approach which involves interactions among various actors called EI actors. These actors collaborate to ensure the overall success of the decision problem solving process. In the course of the collaboration, the actors express knowledge which could be capitalized for future reuse. In this paper, we propose in the first place, an annotation model for knowledge elicitation among EI actors. Because of the need to build a knowledge capital, we also propose a dynamic knowledge capitalisation approach for managing knowledge produced by the actors. Finally, the need to manage the interactions and the interdependencies among collaborating EI actors, led to our third proposition which constitute an awareness mechanism for group work management.


Short collusion-secure fingerprint codes against three pirates

Abstract: In this article, we propose a new construction of probabilistic collusion-secure fingerprint codes against up to three pirates and give a theoretical security evaluation. Our pirate tracing algorithm combines a scoring method analogous to Tardos codes (J. ACM, 2008) with an extension of parent search techniques of some preceding 2-secure codes. Numerical examples show that our code lengths are significantly shorter than (about 30% to 40% of) the shortest known c-secure codes by Nuida et al. (Des. Codes Cryptogr., 2009) with c = 3. Some preliminary proposal for improving efficiency of our tracing algorithm is also given.


An Architectural Design for Brokered Collaborative Content Delivery System

Abstract: Advances in web technologies have driven massive content uploads and requests that can be identified by the increased usage of multimedia web and social web services. This situation enforces the content providers to scale their infrastructure in order to cope with the extra provisioning of network traffic, storage and other resources. Since the complexity and cost factors in scaling the infrastructure exist, we propose a novel solution for providing and delivering contents to clients by introducing a brokered collaborative content delivery system. The architectural design of this system leverages content redundancy and content distribution mechanisms in other content providers to deliver contents to the clients. With the recent emergence of cloud computing, we show that this system can also be adopted to run on the cloud. In this paper, we focus on a brokering scheme to mediate user requests to the most appropriate content provider based on a ranking system. The architecture provides a novel Global Rank Value (GRV) concept in estimating content provider capability and transforming the QoS requirement of a content request. A fairness model that will bring this design to be attractive to the current content delivery regime is also introduced. Through simulation, we show that using fair provider selection, contents can be provisioned by a better pool of qualified providers thus leveraging the collaboration and preventing potential QoS violation that may occur when the size of pool is smaller.


A Focused Sequent Calculus Framework for Proof Search in Pure Type Systems

Abstract: Basic proof-search tactics in logic and type theory can be seen as the root-first applications of rules in an appropriate sequent calculus, preferably without the redundancies generated by permutation of rules. This paper addresses the issues of defining such sequent calculi for Pure Type Systems (PTS, which were originally presented in natural deduction style) and then organizing their rules for effective proof-search. We introduce the idea of Pure Type Sequent Calculus with meta-variables (PTSCalpha), by enriching the syntax of a permutation-free sequent calculus for propositional logic due to Herbelin, which is strongly related to natural deduction and already well adapted to proof-search. The operational semantics is adapted from Herbelin's and is defined by a system of local rewrite rules as in cut-elimination, using explicit substitutions. We prove confluence for this system. Restricting our attention to PTSC, a type system for the ground terms of this system, we obtain the Subject Reduction property and show that each PTSC is logically equivalent to its corresponding PTS, and the former is strongly normalising iff the latter is. We show how to make the logical rules of PTSC into a syntax-directed system PS for proof-search, by incorporating the conversion rules as in syntax-directed presentations of the PTS rules for type-checking. Finally, we consider how to use the explicitly scoped meta-variables of PTSCalpha to represent partial proof-terms, and use them to analyse interactive proof construction. This sets up a framework PE in which we are able to study proof-search strategies, type inhabitant enumeration and (higher-order) unification.


Descriptive-complexity based distance for fuzzy sets

Abstract: A new distance function dist(A,B) for fuzzy sets A and B is introduced. It is based on the descriptive complexity, i.e., the number of bits (on average) that are needed to describe an element in the symmetric difference of the two sets. The distance gives the amount of additional information needed to describe any one of the two sets given the other. We prove its mathematical properties and perform pattern clustering on data based on this distance.


Th\'eorie de Galois effective : aide m\'emoire

Abstract: This paper collects many results on galoisian ideals and Galois theory.


Customer Appeasement Scheduling

Abstract: Almost all of the current process scheduling algorithms which are used in modern operating systems (OS) have their roots in the classical scheduling paradigms which were developed during the 1970's. But modern computers have different types of software loads and user demands. We think it is important to run what the user wants at the current moment. A user can be a human, sitting in front of a desktop machine, or it can be another machine sending a request to a server through a network connection. We think that OS should become intelligent to distinguish between different processes and allocate resources, including CPU, to those processes which need them most. In this work, as a first step to make the OS aware of the current state of the system, we consider process dependencies and interprocess communications. We are developing a model, which considers the need to satisfy interactive users and other possible remote users or customers, by making scheduling decisions based on process dependencies and interprocess communications. Our simple proof of concept implementation and experiments show the effectiveness of this approach in the real world applications. Our implementation does not require any change in the software applications nor any special kind of configuration in the system, Moreover, it does not require any additional information about CPU needs of applications nor other resource requirements. Our experiments show significant performance improvement for real world applications. For example, almost constant average response time for Mysql data base server and constant frame rate for mplayer under different simulated load values.


Instantaneous, non-squeezed, noise-based logic

Abstract: Noise-based logic, by utilizing its multidimensional logic hyperspace, has significant potential for low-power parallel operations in beyond-Moore-chips. However universal gates for Boolean logic thus far had to rely on either time averaging to distinguish signals from each other or, alternatively, on squeezed logic signals, where the logic-high was represented by a random process and the logic-low was a zero signal. A major setback is that squeezed logic variables are unable to work in the hyperspace, because the logic-low zero value sets the hyperspace product vector to zero. This paper proposes Boolean universal logic gates that alleviate such shortcomings. They are able to work with non-squeezed logic values where both the high and low values are encoded into nonzero, bipolar, independent random telegraph waves. Non-squeezed universal Boolean logic gates for spike-based brain logic are also shown. The advantages vs. disadvantages of the two logic types are compared.


On the polynomial depth of various sets of random strings

Abstract: This paper proposes new notions of polynomial depth (called monotone poly depth), based on a polynomial version of monotone Kolmogorov complexity. We show that monotone poly depth satisfies all desirable properties of depth notions i.e., both trivial and random sequences are not monotone poly deep, monotone poly depth satisfies the slow growth law i.e., no simple process can transform a non deep sequence into a deep one, and monotone poly deep sequences exist (unconditionally). We give two natural examples of deep sets, by showing that both the set of Levin-random strings and the set of Kolmogorov random strings are monotone poly deep.


Fast and Power Efficient Sensor Arbitration: Physical Layer Collision Recovery of Passive RFID Tags

Abstract: This work concerns physical layer collision recovery for cheap sensors with allowed variations in frequency and delay of their communications. The work is presented as a generic, communication theoretic framework and demonstrated using UHF RFID tag technology. Previous work in this area has not provided recovery for more than two tags, which is shown to be possible in this work. Also presented is a novel mathematical model of the tag signal, incorporating the allowed variations in frequency and delay. The main motivation is seen in the observation that random variations in frequency and delay make the collided signals of different tags separable. The collision recovery is done by estimating the sensor specific variation in frequency and delay and using these estimates in a successive interference cancellation algorithm and a maximum likelihood sequence decoder, to iteratively reconstruct a sensor signal and remove it from the received signal. Numerical simulations show that the estimates and proposed algorithm are effective in recovering collisions. The proposed algorithm is then incorporated into a numerical simulation of the Qprotocol for UHF RFID tags and is shown to be effective in providing fast and power efficient sensor arbitration.


Adaptive Cluster Expansion (ACE): A Multilayer Network for Estimating Probability Density Functions

Abstract: We derive an adaptive hierarchical method of estimating high dimensional probability density functions. We call this method of density estimation the "adaptive cluster expansion" or ACE for short. We present an application of this approach, based on a multilayer topographic mapping network, that adaptively estimates the joint probability density function of the pixel values of an image, and presents this result as a "probability image". We apply this to the problem of identifying statistically anomalous regions in otherwise statistically homogeneous images.


Analysis of Agglomerative Clustering

Abstract: The diameter $k$-clustering problem is the problem of partitioning a finite subset of $\mathbb{R}^d$ into $k$ subsets called clusters such that the maximum diameter of the clusters is minimized. One early clustering algorithm that computes a hierarchy of approximate solutions to this problem (for all values of $k$) is the agglomerative clustering algorithm with the complete linkage strategy. For decades, this algorithm has been widely used by practitioners. However, it is not well studied theoretically. In this paper, we analyze the agglomerative complete linkage clustering algorithm. Assuming that the dimension $d$ is a constant, we show that for any $k$ the solution computed by this algorithm is an $O(\log k)$-approximation to the diameter $k$-clustering problem. Our analysis does not only hold for the Euclidean distance but for any metric that is based on a norm. Furthermore, we analyze the closely related $k$-center and discrete $k$-center problem. For the corresponding agglomerative algorithms, we deduce an approximation factor of $O(\log k)$ as well.


A Decidable Timeout based Extension of Propositional Linear Temporal Logic

Abstract: We develop a timeout based extension of propositional linear temporal logic (which we call TLTL) to specify timing properties of timeout based models of real time systems. TLTL formulas explicitly refer to a running global clock together with static timing variables as well as a dynamic variable abstracting the timeout behavior. We extend LTL with the capability to express timeout constraints. From the expressiveness view point, TLTL is not comparable with important known clock based real-time logics including TPTL, XCTL, and MTL, i.e., TLTL can specify certain properties, which cannot be specified in these logics (also vice-versa). We define a corresponding timeout tableau for satisfiability checking of the TLTL formulas. Also a model checking algorithm over timeout Kripke structure is presented. Further we prove that the validity checking for such an extended logic remains PSPACE-complete even in the presence of timeout constraints and infinite state models. Under discrete time semantics, with bounded timeout increments, the model-checking problem that if a TLTL-formula holds in a timeout Kripke structure is also PSPACE complete. We further prove that when TLTL is interpreted over discrete time, it can be embedded in the monadic second order logic with time, and when TLTL is interpreted over dense time without the condition of non-zenoness, the resulting logic becomes $\Sigma_1^1$-complete.


Stochastic Vector Quantisers

Abstract: In this paper a stochastic generalisation of the standard Linde-Buzo-Gray (LBG) approach to vector quantiser (VQ) design is presented, in which the encoder is implemented as the sampling of a vector of code indices from a probability distribution derived from the input vector, and the decoder is implemented as a superposition of reconstruction vectors, and the stochastic VQ is optimised using a minimum mean Euclidean reconstruction distortion criterion, as in the LBG case. Numerical simulations are used to demonstrate how this leads to self-organisation of the stochastic VQ, where different stochastically sampled code indices become associated with different input subspaces. This property may be used to automate the process of splitting high-dimensional input vectors into low-dimensional blocks before encoding them.


The Development of Dominance Stripes and Orientation Maps in a Self-Organising Visual Cortex Network (VICON)

Abstract: A self-organising neural network is presented that is based on a rigorous Bayesian analysis of the information contained in individual neural firing events. This leads to a visual cortex network (VICON) that has many of the properties emerge when a mammalian visual cortex is exposed to data arriving from two imaging sensors (i.e. the two retinae), such as dominance stripes and orientation maps.


Detecting Image Forgeries using Geometric Cues

Abstract: This chapter presents a framework for detecting fake regions by using various methods including watermarking technique and blind approaches. In particular, we describe current categories on blind approaches which can be divided into five: pixel-based techniques, format-based techniques, camera-based techniques, physically-based techniques and geometric-based techniques. Then we take a second look on the geometric-based techniques and further categorize them in detail. In the following section, the state-of-the-art methods involved in the geometric technique are elaborated.


Element Retrieval using Namespace Based on keyword search over XML Documents

Abstract: Querying over XML elements using keyword search is steadily gaining popularity. The traditional similarity measure is widely employed in order to effectively retrieve various XML documents. A number of authors have already proposed different similarity-measure methods that take advantage of the structure and content of XML documents. They do not, however, consider the similarity between latent semantic information of element texts and that of keywords in a query. Although many algorithms on XML element search are available, some of them have the high computational complexity due to searching a huge number of elements. In this paper, we propose a new algorithm that makes use of the semantic similarity between elements instead of between entire XML documents, considering not only the structure and content of an XML document, but also semantic information of namespaces in elements. We compare our algorithm with the three other algorithms by testing on the real datasets. The experiments have demonstrated that our proposed method is able to improve the query accuracy, as well as to reduce the running time.


The model checking problem for intuitionistic propositional logic with one variable is AC1-complete

Abstract: We show that the model checking problem for intuitionistic propositional logic with one variable is complete for logspace-uniform AC1. As basic tool we use the connection between intuitionistic logic and Heyting algebra, and investigate its complexity theoretical aspects. For superintuitionistic logics with one variable, we obtain NC1-completeness for the model checking problem.


On the CNF encoding of cardinality constraints and beyond

Abstract: In this report, we propose a quick survey of the currently known techniques for encoding a Boolean cardinality constraint into a CNF formula, and we discuss about the relevance of these encodings. We also propose models to facilitate analysis and design of CNF encodings for Boolean constraints.


Queue-Aware Dynamic Clustering and Power Allocation for Network MIMO Systems via Distributive Stochastic Learning

Abstract: In this paper, we propose a two-timescale delay-optimal dynamic clustering and power allocation design for downlink network MIMO systems. The dynamic clustering control is adaptive to the global queue state information (GQSI) only and computed at the base station controller (BSC) over a longer time scale. On the other hand, the power allocations of all the BSs in one cluster are adaptive to both intra-cluster channel state information (CCSI) and intra-cluster queue state information (CQSI), and computed at the cluster manager (CM) over a shorter time scale. We show that the two-timescale delay-optimal control can be formulated as an infinite-horizon average cost Constrained Partially Observed Markov Decision Process (CPOMDP). By exploiting the special problem structure, we shall derive an equivalent Bellman equation in terms of Pattern Selection Q-factor to solve the CPOMDP. To address the distributive requirement and the issue of exponential memory requirement and computational complexity, we approximate the Pattern Selection Q-factor by the sum of Per-cluster Potential functions and propose a novel distributive online learning algorithm to estimate the Per-cluster Potential functions (at each CM) as well as the Lagrange multipliers (LM) (at each BS). We show that the proposed distributive online learning algorithm converges almost surely (with probability 1). By exploiting the birth-death structure of the queue dynamics, we further decompose the Per-cluster Potential function into sum of Per-cluster Per-user Potential functions and formulate the instantaneous power allocation as a Per-stage QSI-aware Interference Game played among all the CMs. We also propose a QSI-aware Simultaneous Iterative Water-filling Algorithm (QSIWFA) and show that it can achieve the Nash Equilibrium (NE).


Minimum regulation of uncoordinated matchings

Abstract: Due to the lack of coordination, it is unlikely that the selfish players of a strategic game reach a socially good state. A possible way to cope with selfishness is to compute a desired outcome (if it is tractable) and impose it. However this answer is often inappropriate because compelling an agent can be costly, unpopular or just hard to implement. Since both situations (no coordination and full coordination) show opposite advantages and drawbacks, it is natural to study possible tradeoffs. In this paper we study a strategic game where the nodes of a simple graph G are independent agents who try to form pairs: e.g. jobs and applicants, tennis players for a match, etc. In many instances of the game, a Nash equilibrium significantly deviates from a social optimum. We analyze a scenario where we fix the strategy of some players; the other players are free to make their choice. The goal is to compel a minimum number of players and guarantee that any possible equilibrium of the modified game is a social optimum, i.e. created pairs must form a maximum matching of G. We mainly show that this intriguing problem is NP-hard and propose an approximation algorithm with a constant ratio.


Balanced Interval Coloring

Abstract: We consider the discrepancy problem of coloring $n$ intervals with $k$ colors such that at each point on the line, the maximal difference between the number of intervals of any two colors is minimal. Somewhat surprisingly, a coloring with maximal difference at most one always exists. Furthermore, we give an algorithm with running time $O(n \log n + kn \log k)$ for its construction. This is in particular interesting because many known results for discrepancy problems are non-constructive. This problem naturally models a load balancing scenario, where $n$ tasks with given start- and endtimes have to be distributed among $k$ servers. Our results imply that this can be done ideally balanced. When generalizing to $d$-dimensional boxes (instead of intervals), a solution with difference at most one is not always possible. We show that for any $d \ge 2$ and any $k \ge 2$ it is NP-complete to decide if such a solution exists, which implies also NP-hardness of the respective minimization problem. In an online scenario, where intervals arrive over time and the color has to be decided upon arrival, the maximal difference in the size of color classes can become arbitrarily high for any online algorithm.


Interpolation in Equilibrium Logic and Answer Set Programming: the Propositional Case

Abstract: Interpolation is an important property of classical and many non classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the propositional version of the non-monotonic system of equilibrium logic, establishing weaker or stronger forms of interpolation depending on the precise interpretation of the inference relation. These results also yield a form of interpolation for ground logic programs under the answer sets semantics. For disjunctive logic programs we also study the property of uniform interpolation that is closely related to the concept of variable forgetting.


Diffusion-geometric maximally stable component detection in deformable shapes

Abstract: Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D world. In this paper, we formulate a diffusion-geometric framework for stable component detection in non-rigid 3D shapes, which can be used for geometric feature detection and description. A quantitative evaluation of our method on the SHREC'10 feature detection benchmark shows its potential as a source of high-quality features.


Quotient Complexity of Star-Free Languages

Abstract: The quotient complexity, also known as state complexity, of a regular language is the number of distinct left quotients of the language. The quotient complexity of an operation is the maximal quotient complexity of the language resulting from the operation, as a function of the quotient complexities of the operands. The class of star-free languages is the smallest class containing the finite languages and closed under boolean operations and concatenation. We prove that the tight bounds on the quotient complexities of union, intersection, difference, symmetric difference, concatenation, and star for star-free languages are the same as those for regular languages, with some small exceptions, whereas the bound for reversal is 2^n-1.


A Note on Solid Coloring of Pure Simplicial Complexes

Abstract: We establish a simple generalization of a known result in the plane. The simplices in any pure simplicial complex in R^d may be colored with d+1 colors so that no two simplices that share a (d-1)-facet have the same color. In R^2 this says that any planar map all of whose faces are triangles may be 3-colored, and in R^3 it says that tetrahedra in a collection may be "solid 4-colored" so that no two glued face-to-face receive the same color.


A Type System for the Vectorial Aspect of the Linear-Algebraic Lambda-Calculus

Abstract: We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms resulting from the reduction of programs. This gives rise to an original type theory where types, in the same way as terms, can be superposed into linear combinations. We show that the resulting typed lambda-calculus is strongly normalizing and features a weak subject-reduction.


Application of Global and One-Dimensional Local Optimization to Operating System Scheduler Tuning

Abstract: This paper describes a study of comparison of global and one-dimensional local optimization methods to operating system scheduler tuning. The operating system scheduler we use is the Linux 2.6.23 Completely Fair Scheduler (CFS) running in simulator (LinSched). We have ported the Hackbench scheduler benchmark to this simulator and use this as the workload. The global optimization approach we use is Particle Swarm Optimization (PSO). We make use of Response Surface Methodology (RSM) to specify optimal parameters for our PSO implementation. The one-dimensional local optimization approach we use is the Golden Section method. In order to use this approach, we convert the scheduler tuning problem from one involving setting of three parameters to one involving the manipulation of one parameter. Our results show that the global optimization approach yields better response but the one- dimensional optimization approach converges to a solution faster than the global optimization approach.


Artificial Intelligence in Reverse Supply Chain Management: The State of the Art

Abstract: Product take-back legislation forces manufacturers to bear the costs of collection and disposal of products that have reached the end of their useful lives. In order to reduce these costs, manufacturers can consider reuse, remanufacturing and/or recycling of components as an alternative to disposal. The implementation of such alternatives usually requires an appropriate reverse supply chain management. With the concepts of reverse supply chain are gaining popularity in practice, the use of artificial intelligence approaches in these areas is also becoming popular. As a result, the purpose of this paper is to give an overview of the recent publications concerning the application of artificial intelligence techniques to reverse supply chain with emphasis on certain types of product returns.


Survey & Experiment: Towards the Learning Accuracy

Abstract: To attain the best learning accuracy, people move on with difficulties and frustrations. Though one can optimize the empirical objective using a given set of samples, its generalization ability to the entire sample distribution remains questionable. Even if a fair generalization guarantee is offered, one still wants to know what is to happen if the regularizer is removed, and/or how well the artificial loss (like the hinge loss) relates to the accuracy. For such reason, this report surveys four different trials towards the learning accuracy, embracing the major advances in supervised learning theory in the past four years. Starting from the generic setting of learning, the first two trials introduce the best optimization and generalization bounds for convex learning, and the third trial gets rid of the regularizer. As an innovative attempt, the fourth trial studies the optimization when the objective is exactly the accuracy, in the special case of binary classification. This report also analyzes the last trial through experiments.


Generalized and Resource-Efficient VNet Embeddings with Migrations

Abstract: This paper attends to the problem of embedding flexibly specified CloudNets, virtual networks connecting cloud resources (such as storage or computation). We attend to a scenario where customers can request CloudNets at short notice, and an infrastructure provider (or a potential itermediate broker or reseller) first embeds the CloudNet fast (e.g., using a simple heuristic). Later, however, long-lived CloudNets embeddings are optimized by migrating them to more suitable locations, whose precise definition depends on a given objective function. For instance, such migrations can be useful to reduce the peak resource loads in the network by spreading CloudNets across the infrastructure, to save energy by moving CloudNets together and switching off unused components, or for maintenance purposes. We present a very generic algorithm to compute optimal embeddings of CloudNets: It allows for different objective functions (such as load minimization or energy conservation), supports cost-aware migration, and can deal with all link types that arise in practice (e.g., full-duplex or even wireless or wired broadcast links with multiple endpoints). Our evaluation shows that such a rigorous optimization is even feasible in order to optimize a moderate-size CloudNet of full flexibility (e.g., a router site, a small physical infrastructure or virtual provider network).


A fast divide-and-conquer algorithm for indexing human genome sequences

Abstract: Since the release of human genome sequences, one of the most important research issues is about indexing the genome sequences, and the suffix tree is most widely adopted for that purpose. The traditional suffix tree construction algorithms have severe performance degradation due to the memory bottleneck problem. The recent disk-based algorithms also have limited performance improvement due to random disk accesses. Moreover, they do not fully utilize the recent CPUs with multiple cores. In this paper, we propose a fast algorithm based on 'divide-and-conquer' strategy for indexing the human genome sequences. Our algorithm almost eliminates random disk accesses by accessing the disk in the unit of contiguous chunks. In addition, our algorithm fully utilizes the multi-core CPUs by dividing the genome sequences into multiple partitions and then assigning each partition to a different core for parallel processing. Experimental results show that our algorithm outperforms the previous fastest DIGEST algorithm by up to 3.5 times.


Performance Study of IEEE802.11e QoS in EDCF-Contention-based Static and Dynamic Scenarios

Abstract: In this paper, we carry-out a study of the Quality of Service (QoS) mechanism in IEEE802.11e Enhanced Distribution Coordination Function (EDCF) and how it is achieved by providing traffics with different priorities. It can perform the access to the radio channel or just simply it can considerably be declined subsequently to a variation of network dynamicity. The results of the proposed analysis show that the EDCF scheduler looses the ability of the traffic differentiation and becomes insensitive to the QoS priority requirements. Consequently, it goes away from the region of stability and EDCF doesn't offer better performance than the conventional DCF scheme. Therefore, traffic specifications are weakly applied only for the channel occupation time distribution. During the handoff between the Base Stations (BS's), the response time of the data rate application within the roaming process grows to the initial throughput level. Performance metrics at the MAC layer, like throughput, End-2-End delay, and packet loss have been evaluated.


Self-Organising Stochastic Encoders

Abstract: The processing of mega-dimensional data, such as images, scales linearly with image size only if fixed size processing windows are used. It would be very useful to be able to automate the process of sizing and interconnecting the processing windows. A stochastic encoder that is an extension of the standard Linde-Buzo-Gray vector quantiser, called a stochastic vector quantiser (SVQ), includes this required behaviour amongst its emergent properties, because it automatically splits the input space into statistically independent subspaces, which it then separately encodes. Various optimal SVQs have been obtained, both analytically and numerically. Analytic solutions which demonstrate how the input space is split into independent subspaces may be obtained when an SVQ is used to encode data that lives on a 2-torus (e.g. the superposition of a pair of uncorrelated sinusoids). Many numerical solutions have also been obtained, using both SVQs and chains of linked SVQs: (1) images of multiple independent targets (encoders for single targets emerge), (2) images of multiple correlated targets (various types of encoder for single and multiple targets emerge), (3) superpositions of various waveforms (encoders for the separate waveforms emerge - this is a type of independent component analysis (ICA)), (4) maternal and foetal ECGs (another example of ICA), (5) images of textures (orientation maps and dominance stripes emerge). Overall, SVQs exhibit a rich variety of self-organising behaviour, which effectively discovers the internal structure of the training data. This should have an immediate impact on "intelligent" computation, because it reduces the need for expert human intervention in the design of data processing algorithms.


Employing Coded Relay in Multi-hop Wireless Networks

Abstract: In this paper, we study Coded relay (Crelay) in multi-hop wireless networks. Crelay exploits both partial packets and overhearing capabilities of the wireless nodes, and uses Forward Error Correction code in packet forwarding. When a node overhears a partial packet from an upstream node, it informs the upstream node about the number of parity bytes needed to correct the errors, such that the upstream node need only send a small amount of parity bytes instead of the complete packet, hence improving the network efficiency. Our main contributions include the following. First, we propose an efficient network protocol that can exploit partial packets and overhearing. Second, we study the routing problem in networks with Crelay and propose a greedy algorithm for finding the paths. Third, we propose an error ratio estimator, called AMPS, that can estimate the number of byte errors in a received frame with good accuracy at a low overhead of only 8 bytes per frame, where the estimator is needed for a node to find the number of needed parity bytes. Fourth, we implement the proposed protocol and algorithm within the Click modular router, and our experiments show that Crelay can significantly improve the performance of wireless networks.


Removing Barriers to Interdisciplinary Research

Abstract: A significant amount of high-impact contemporary scientific research occurs where biology, computer science, engineering and chemistry converge. Although programmes have been put in place to support such work, the complex dynamics of interdisciplinarity are still poorly understood. In this paper we interrogate the nature of interdisciplinary research and how we might measure its "success", identify potential barriers to its implementation, and suggest possible mechanisms for removing these impediments.


A Self-Organising Neural Network for Processing Data from Multiple Sensors

Abstract: This paper shows how a folded Markov chain network can be applied to the problem of processing data from multiple sensors, with an emphasis on the special case of 2 sensors. It is necessary to design the network so that it can transform a high dimensional input vector into a posterior probability, for which purpose the partitioned mixture distribution network is ideally suited. The underlying theory is presented in detail, and a simple numerical simulation is given that shows the emergence of ocular dominance stripes.


Compliance of POLYAS with the Common Criteria Protection Profile

Abstract: In 2008, the German Federal Office for Information Security issued the common criteria protection profile for Online Voting Products (PP-0037). Accord- ingly, we evaluated the Polyas electronic voting system, which is used for legally binding elections in several international organizations (German Gesellschaft for Informatik, GI, among others), for compliance with the common criteria protection profile and worked toward fulfilling the given requirements. In this article we pre- sent the findings of the process of creating a compliant security target, necessary restrictions and assumptions to the system design as well as the workings of the committee, and architectural and procedural changes made necessary.


Computation in Large-Scale Scientific and Internet Data Applications is a Focus of MMDS 2010

Abstract: The 2010 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2010) was held at Stanford University, June 15--18. The goals of MMDS 2010 were (1) to explore novel techniques for modeling and analyzing massive, high-dimensional, and nonlinearly-structured scientific and Internet data sets; and (2) to bring together computer scientists, statisticians, applied mathematicians, and data analysis practitioners to promote cross-fertilization of ideas. MMDS 2010 followed on the heels of two previous MMDS workshops. The first, MMDS 2006, addressed the complementary perspectives brought by the numerical linear algebra and theoretical computer science communities to matrix algorithms in modern informatics applications; and the second, MMDS 2008, explored more generally fundamental algorithmic and statistical challenges in modern large-scale data analysis.


ECLiPSe - from LP to CLP

Abstract: ECLiPSe is a Prolog-based programming system, aimed at the development and deployment of constraint programming applications. It is also used for teaching most aspects of combinatorial problem solving, e.g. problem modelling, constraint programming, mathematical programming, and search techniques. It uses an extended Prolog as its high-level modelling and control language, complemented by several constraint solver libraries, interfaces to third-party solvers, an integrated development environment and interfaces for embedding into host environments. This paper discusses language extensions, implementation aspects, components and tools that we consider relevant on the way from Logic Programming to Constraint Logic Programming.


Travel Time Estimation Using Floating Car Data

Abstract: This report explores the use of machine learning techniques to accurately predict travel times in city streets and highways using floating car data (location information of user vehicles on a road network). The aim of this report is twofold, first we present a general architecture of solving this problem, then present and evaluate few techniques on real floating car data gathered over a month on a 5 Km highway in New Delhi.


Lightweight LCP-Array Construction in Linear Time

Abstract: The suffix tree is a very important data structure in string processing, but it suffers from a huge space consumption. In large-scale applications, compressed suffix trees (CSTs) are therefore used instead. A CST consists of three (compressed) components: the suffix array, the LCP-array, and data structures for simulating navigational operations on the suffix tree. The LCP-array stores the lengths of the longest common prefixes of lexicographically adjacent suffixes, and it can be computed in linear time. In this paper, we present new LCP-array construction algorithms that are fast and very space efficient. In practice, our algorithms outperform the currently best algorithms.


A preconditioned iterative solver for the scattering solutions of the Schr\"odinger equation

Abstract: The Schr\"odinger equation defines the dynamics of quantum particles which has been an area of unabated interest in physics. We demonstrate how simple transformations of the Schr\"odinger equation leads to a coupled linear system, whereby each diagonal block is a high frequency Helmholtz problem. Based on this model, we derive indefinite Helmholtz model problems with strongly varying wavenumbers. We employ the iterative approach for their solution. In particular, we develop a preconditioner that has its spectrum restricted to a quadrant (of the complex plane) thereby making it easily invertible by multigrid methods with standard components. This multigrid preconditioner is used in conjuction with suitable Krylov-subspace methods for solving the indefinite Helmholtz model problems. The aim of this study is to report the feasbility of this preconditioner for the model problems. We compare this idea with the other prevalent preconditioning ideas, and discuss its merits. Results of numerical experiments are presented, which complement the proposed ideas, and show that this preconditioner may be used in an automatic setting.


Using virtual human for an interactive customer-oriented constrained environment design

Abstract: For industrial product design, it is very important to take into account assembly/disassembly and maintenance operations during the conceptual and prototype design stage. For these operations or other similar operations in a constrained environment, trajectory planning is always a critical and difficult issue for evaluating the design or for the users' convenience. In this paper, a customer-oriented approach is proposed to partially solve ergonomic issues encountered during the design stage of a constrained environment. A single objective optimization based method is taken from the literature to generate the trajectory in a constrained environment automatically. A motion capture based method assists to guide the trajectory planning interactively if a local minimum is encountered within the single objective optimization. At last, a multi-objective evaluation method is proposed to evaluate the operations generated by the algorithm


A Progressive Network Management Architecture Enabled By Java Technology

Abstract: This paper proposes a framework based completely on Java technology. The advantages brought about by the use of Java in network management answer some critical problems existing in current systems. With this work we address several factors concerning interoperability and security in heterogeneous network environments. Specifically, we present a manager application and a multithreaded agent engine that make use of a lightweight communication mechanism for message exchange. A MIB parser is introduced to accelerate handling of incoming management requests, and the RSA public-key cryptosystem is implemented to provide both encryption and authentication features. Results, measured in terms of response time, compare favourably with other published work and standard management frameworks.


R\'egularisation et optimisation pour l'imagerie sismique des fondations de pyl\^ones

Abstract: This research report summarizes the progress of work carried out jointly by the IRCCyN and the \'Ecole Polytechnique de Montr\'eal about the resolution of the inverse problem for the seismic imaging of transmission overhead line structure foundations. Several methods aimed at mapping the underground medium are considered. More particularly, we focus on methods based on a bilinear formulation of the forward problem on one hand (CSI, modified gradient, etc.) and on methods based on a "primal" formulation on the other hand. The performances of these methods are compared using synthetic data. This work was partially funded by RTE (R\'eseau de Transport d'\'Electricit\'e), which has initiated the project, and was carried out in collaboration with EDF R&D (\'Electricit\'e de France - Recherche et D\'eveloppement).


Multicolored Dynamos on Toroidal Meshes

Abstract: Detecting on a graph the presence of the minimum number of nodes (target set) that will be able to "activate" a prescribed number of vertices in the graph is called the target set selection problem (TSS) proposed by Kempe, Kleinberg, and Tardos. In TSS's settings, nodes have two possible states (active or non-active) and the threshold triggering the activation of a node is given by the number of its active neighbors. Dealing with fault tolerance in a majority based system the two possible states are used to denote faulty or non-faulty nodes, and the threshold is given by the state of the majority of neighbors. Here, the major effort was in determining the distribution of initial faults leading the entire system to a faulty behavior. Such an activation pattern, also known as dynamic monopoly (or shortly dynamo), was introduced by Peleg in 1996. In this paper we extend the TSS problem's settings by representing nodes' states with a "multicolored" set. The extended version of the problem can be described as follows: let G be a simple connected graph where every node is assigned a color from a finite ordered set C = {1, . . ., k} of colors. At each local time step, each node can recolor itself, depending on the local configurations, with the color held by the majority of its neighbors. Given G, we study the initial distributions of colors leading the system to a k monochromatic configuration in toroidal meshes, focusing on the minimum number of initial k-colored nodes. We find upper and lower bounds to the size of a dynamo, and then special classes of dynamos, outlined by means of a new approach based on recoloring patterns, are characterized.


Encryption of Binary and Non-Binary Data Using Chained Hadamard Transforms

Abstract: This paper presents a new chaining technique for the use of Hadamard transforms for encryption of both binary and non-binary data. The lengths of the input and output sequence need not be identical. The method may be used also for hashing.


An Experimental Approach for Optimising Mobile Agent Migrations

Abstract: The field of mobile agent (MA) technology has been intensively researched during the past few years, resulting in the phenomenal proliferation of available MA platforms, all sharing several common design characteristics. Research projects have mainly focused on identifying applications where the employment of MAs is preferable compared to centralised or alternative distributed computing models. Very little work has been made on examining how MA platforms design can be optimised so as the network traffic and latency associated with MA transfers are minimised. The work presented in this paper addresses these issues by investigating the effect of several optimisation ideas applied on our MA platform prototype. Furthermore, we discuss the results of a set of timing experiments that offers a better understanding of the agent migration process and recommend new techniques for reducing MA transfers delay.


Selling Culture: Implementation of e-Commerce and WAP-based Prototypes

Abstract: Museum stores represent integral parts of the museums that have also a lot to benefit from a successful presence on the web arena. In addition to traditional web sites, carefully designed electronic commerce (e-commerce) sites may increase the potential of museum stores offering possibilities for on-line shopping and other commercial functions. In parallel, the recent convergence of the traditionally separate technologies of the Internet and mobile telephony has brought the concept of 'wireless Internet' into the spotlight. Within this context, 'mobile commerce' (m-commerce) is a relatively new trend that represents a natural extension of e-commerce into the wireless world. M-commerce refers to electronic business transactions and differentiates from e-commerce since it involves the use of mobile devices and wireless medium rather than wired. The unique characteristics of mobile computing bring forward new challenges and opportunities for museum stores. This article presents the design and implementation of an e-commerce and an m-commerce museum shop application. The aim is to evaluate and compare the two applications in terms of several parameters, such as available technologies, strengths and limitations, design requirements, usability, interaction speed, usage cost, etc and also to identify ways for enhancing the potential of such applications and designing successful and profitable business models.


Proceedings 24th International Workshop on Unification

Abstract: This volume contains selected papers presented at the 24th International Workshop on Unification, UNIF2010, which was held in Edinburgh on the 14th July 2010, as part of FLoC 2010 (Federated Logic Conferences).


Proceedings Workshop on Partiality and Recursion in Interactive Theorem Provers

Abstract: This volume contains the proceedings of the Workshop on Partiality and Recursion in Interactive Theorem Provers (PAR 2010) which took place on July 15 in Edinburgh, UK. This workshop was held as a satellite workshop of the International Conference on Interactive Theorem Proving (ITP 2010), itself part of the Federated Logic Conference 2010 (FLoC 2010). This workshop is a venue for researchers working on new approaches to cope with partial functions and terminating general (co)recursion in theorem provers.


Selective Multipath Interference Canceller with Linear Equalization for DS-UWB Systems with Low Spreading Factor

Abstract: In high rate DS-UWB systems with low spreading factor, the selective multipath interference canceller with linear equalization (SMPIC-LE) is developed to alleviate severe multipath interferences induced by the poor orthogonality of spreading codes. The SMPIC iteratively mitigates the strongest inter-path interference, inter-chip interference and inter-symbol interference, while the former two are unresolvable in conventional RAKE-decision feedback equalizer (DFE) receivers. The numerical results and complexity analysis demonstrate that SMPIC-LE with proper parameters provides an attractive overall advantage in performance and computational complexity compared with RAKE-DFE. In addition, it approaches the matched filter bound well as the RAKE finger in SMPIC increases.


A Force-Directed Method for Large Crossing Angle Graph Drawing

Abstract: Recent empirical research has indicated that human graph reading performance improves when crossing angles increase. However, crossing angle has not been used as an aesthetic criterion for graph drawing algorithms so far. In this paper, we introduce a force-directed method that aims to construct graph drawings with large crossing angles. Experiments indicate that our method significantly increases crossing angles. Surprisingly, the experimental results further demonstrate that the resulting drawings produced by our method have fewer edge crossings, a shorter total edge length and more uniform edge lengths, compared to classical spring algorithms.


Non-redundant random generation from weighted context-free languages

Abstract: We address the non-redundant random generation of k words of length n from a context-free language. Additionally, we want to avoid a predefined set of words. We study the limits of a rejection-based approach, whose time complexity is shown to grow exponentially in k in some cases. We propose an alternative recursive algorithm, whose careful implementation allows for a non-redundant generation of k words of size n in O(kn log n) arithmetic operations after the precomputation of O(n) numbers. The overall complexity is therefore dominated by the generation of k words, and the non-redundancy comes at a negligible cost.


How I won the "Chess Ratings - Elo vs the Rest of the World" Competition

Abstract: This article discusses in detail the rating system that won the kaggle competition "Chess Ratings: Elo vs the rest of the world". The competition provided a historical dataset of outcomes for chess games, and aimed to discover whether novel approaches can predict the outcomes of future games, more accurately than the well-known Elo rating system. The winning rating system, called Elo++ in the rest of the article, builds upon the Elo rating system. Like Elo, Elo++ uses a single rating per player and predicts the outcome of a game, by using a logistic curve over the difference in ratings of the players. The major component of Elo++ is a regularization technique that avoids overfitting these ratings. The dataset of chess games and outcomes is relatively small and one has to be careful not to draw "too many conclusions" out of the limited data. Many approaches tested in the competition showed signs of such an overfitting. The leader-board was dominated by attempts that did a very good job on a small test dataset, but couldn't generalize well on the private hold-out dataset. The Elo++ regularization takes into account the number of games per player, the recency of these games and the ratings of the opponents. Finally, Elo++ employs a stochastic gradient descent scheme for training the ratings, and uses only two global parameters (white's advantage and regularization constant) that are optimized using cross-validation.


Performance Study of ETX based Wireless Routing Metrics

Abstract: Being most popular and IETF standard metric, minimum hop count is appropriately used by Ad hoc Networks, as new paths must rapidly be found in the situations where quality paths could not be found in due time due to high node mobility. There always has been a tradeoff between throughput and energy consumption, but stationary topology of WMNs and high node density of WSN's benefit the algorithms to consider quality-aware routing to choose the best routes. In this paper, we analytically review ongoing research on wireless routing metrics which are based on ETX (Expected Transmission Count) as it performs better than minimum hop count under link availability. Performances over ETX, target platforms and design requirements of these ETX based metrics are high-lighted. Consequences of the criteria being adopted (in addition to expected link layer transmissions & retransmissions) in the form of incremental: (1) performance overheads and computational complexity causing inefficient use of network resources and instability of the routing algorithm, (2) throughput gains achieved with better utilization of wireless medium resources have been elaborated.


Solving a real-life large-scale energy management problem

Abstract: This paper introduces a three-phase heuristic approach for a large-scale energy management and maintenance scheduling problem. The problem is concerned with scheduling maintenance and refueling for nuclear power plants up to five years into the future, while handling a number of scenarios for future demand and prices. The goal is to minimize the expected total production costs. The first phase of the heuristic solves a simplified constraint programming model of the problem, the second performs a local search, and the third handles overproduction in a greedy fashion. This work was initiated in the context of the ROADEF/EURO Challenge 2010, a competition organized jointly by the French Operational Research and Decision Support Society, the European Operational Research Society, and the European utility company Electricite de France. In the concluding phase of the competition our team ranked second in the junior category and sixth overall. After correcting an implementation bug in the program that was submitted for evaluation, our heuristic solves all ten real-life instances, and the solutions obtained are all within 2.45% of the currently best known solutions. The results given here would have ranked first in the original competition.


Vertex Cover Kernelization Revisited: Upper and Lower Bounds for a Refined Parameter

Abstract: An important result in the study of polynomial-time preprocessing shows that there is an algorithm which given an instance (G,k) of Vertex Cover outputs an equivalent instance (G',k') in polynomial time with the guarantee that G' has at most 2k' vertices (and thus O((k')^2) edges) with k' <= k. Using the terminology of parameterized complexity we say that k-Vertex Cover has a kernel with 2k vertices. There is complexity-theoretic evidence that both 2k vertices and Theta(k^2) edges are optimal for the kernel size. In this paper we consider the Vertex Cover problem with a different parameter, the size fvs(G) of a minimum feedback vertex set for G. This refined parameter is structurally smaller than the parameter k associated to the vertex covering number vc(G) since fvs(G) <= vc(G) and the difference can be arbitrarily large. We give a kernel for Vertex Cover with a number of vertices that is cubic in fvs(G): an instance (G,X,k) of Vertex Cover, where X is a feedback vertex set for G, can be transformed in polynomial time into an equivalent instance (G',X',k') such that |V(G')| <= 2k and |V(G')| <= O(|X'|^3). A similar result holds when the feedback vertex set X is not given along with the input. In sharp contrast we show that the Weighted Vertex Cover problem does not have a polynomial kernel when parameterized by the cardinality of a given vertex cover of the graph unless NP is in coNP/poly and the polynomial hierarchy collapses to the third level.


Service-Oriented Simulation Framework: An Overview and Unifying Methodology

Abstract: The prevailing net-centric environment demands and enables modeling and simulation to combine efforts from numerous disciplines. Software techniques and methodology, in particular service-oriented architecture, provide such an opportunity. Service-oriented simulation has been an emerging paradigm following on from object- and process-oriented methods. However, the ad-hoc frameworks proposed so far generally focus on specific domains or systems and each has its pros and cons. They are capable of addressing different issues within service-oriented simulation from different viewpoints. It is increasingly important to describe and evaluate the progress of numerous frameworks. In this paper, we propose a novel three-dimensional reference model for a service-oriented simulation paradigm. The model can be used as a guideline or an analytic means to find the potential and possible future directions of the current simulation frameworks. In particular, the model inspects the crossover between the disciplines of modeling and simulation, service-orientation, and software/systems engineering. Based on the model, we present a comprehensive survey on several classical service-oriented simulation frameworks, including formalism-based, model-driven, interoperability protocol based, eXtensible Modeling and Simulation Framework (XMSF), and Open Grid Services Architecture (OGSA) based frameworks etc. The comparison of these frameworks is also performed. Finally the significance both in academia and practice are presented and future directions are pointed out.


Abstract: This project "Software Oriented Data Monitoring System" deals with real time monitoring of patients' parameters like body temperature, heart rate etc. The parameters are checked at regular intervals and Short Messaging Service (SMS) is sent to concerned doctor regarding the measured values. If the obtained parameters are above or below critical values, an alert SMS is also sent to the concerned doctor. This system is very much useful in hospitals, which saves the valuable time of the doctor who otherwise will have to monitor the patients throughout the day. Here the analog data from the sensors is first converted into digital form and is fed to the parallel port of the computer. This data obtained is converted into useful parameters, which is monitored and checked for safe limits. Appropriate SMS is sent to the doctor depending on whether the request is from an alert or routine signal. This is possible by interfacing a mobile phone (Siemens c35i) to the serial port of the computer. The SMS is sent from the computer using proper AT commands.


Semantic Web: Who is who in the field - A bibliometric analysis

Abstract: The Semantic Web is one of the main efforts aiming to enhance human and machine interaction by representing data in an understandable way for machines to mediate data and services. It is a fast-moving and multidisciplinary field. This study conducts a thorough bibliometric analysis of the field by collecting data from Web of Science (WOS) and Scopus for the period of 1960-2009. It utilizes a total of 44,157 papers with 651,673 citations from Scopus, and 22,951 papers with 571,911 citations from WOS. Based on these papers and citations, it evaluates the research performance of the Semantic Web (SW) by identifying the most productive players, major scholarly communication media, highly cited authors, influential papers and emerging stars.


A simple and practical algorithm for differentially private data release

Abstract: We present new theoretical results on differentially private data release useful with respect to any target class of counting queries, coupled with experimental results on a variety of real world data sets. Specifically, we study a simple combination of the multiplicative weights approach of [Hardt and Rothblum, 2010] with the exponential mechanism of [McSherry and Talwar, 2007]. The multiplicative weights framework allows us to maintain and improve a distribution approximating a given data set with respect to a set of counting queries. We use the exponential mechanism to select those queries most incorrectly tracked by the current distribution. Combing the two, we quickly approach a distribution that agrees with the data set on the given set of queries up to small error. The resulting algorithm and its analysis is simple, but nevertheless improves upon previous work in terms of both error and running time. We also empirically demonstrate the practicality of our approach on several data sets commonly used in the statistical community for contingency table release.


Multiple-source multiple-sink maximum flow in planar graphs

Abstract: In this paper we show an O(n^(3/2) log^2 n) time algorithm for finding a maximum flow in a planar graph with multiple sources and multiple sinks. This is the fastest algorithm whose running time depends only on the number of vertices in the graph. For general (non-planar) graphs the multiple-source multiple-sink version of the maximum flow problem is as difficult as the standard single-source single-sink version. However, the standard reduction does not preserve the planarity of the graph, and it is not known how to generalize existing maximum flow algorithms for planar graphs to the multiple-source multiple-sink maximum flow problem.


Automatic Estimation of the Exposure to Lateral Collision in Signalized Intersections using Video Sensors

Abstract: Intersections constitute one of the most dangerous elements in road systems. Traffic signals remain the most common way to control traffic at high-volume intersections and offer many opportunities to apply intelligent transportation systems to make traffic more efficient and safe. This paper describes an automated method to estimate the temporal exposure of road users crossing the conflict zone to lateral collision with road users originating from a different approach. This component is part of a larger system relying on video sensors to provide queue lengths and spatial occupancy that are used for real time traffic control and monitoring. The method is evaluated on data collected during a real world experiment.


Analytical Modeling of Saturation Throughput in Power Save Mode of an IEEE 802.11 Infrastructure WLAN

Abstract: We consider a single station (STA) in the Power Save Mode (PSM) of an IEEE 802.11 infrastructure WLAN. This STA is assumed to be carrying uplink and downlink traffic via the access point (AP). We assume that the transmission queues of the AP and the STA are saturated, i.e., the AP and the STA always have at least one packet to send. For this scenario, it is observed that uplink and downlink throughputs achieved are different. The reason behind the difference is the long term attempt rates of the STA and the AP due to the PSM protocol. In this paper we first obtain the the long term attempt rates of the STA and the AP and using these, we obtain the saturation throughputs of the AP and the STA. We provide a validation of analytical results using the NS-2 simulator.