Mobile Agents for Content-Based WWW Distributed Image Retrieval

Abstract: At present, the de-facto standard for providing contents in the Internet is the World Wide Web. A technology, which is now emerging on the Web, is Content-Based Image Retrieval (CBIR). CBIR applies methods and algorithms from computer science to analyse and index images based on their visual content. Mobile agents push the flexibility of distributed systems to their limits since not only computations are dynamically distributed but also the code that performs them. The current commercial applet-based methodologies for accessing image database systems offer limited flexibility, scalability and robustness. In this paper the author proposes a new framework for content-based WWW distributed image retrieval based on Java-based mobile agents. The implementation of the framework shows that its performance is comparable to, and in some cases outperforms, the current approach.


A compact topology for sand automata

Abstract: In this paper, we exhibit a strong relation between the sand automata configuration space and the cellular automata configuration space. This relation induces a compact topology for sand automata, and a new context in which sand automata are homeomorphic to cellular automata acting on a specific subshift. We show that the existing topological results for sand automata, including the Hedlund-like representation theorem, still hold. In this context, we give a characterization of the cellular automata which are sand automata, and study some dynamical behaviors such as equicontinuity. Furthermore, we deal with the nilpotency. We show that the classical definition is not meaningful for sand automata. Then, we introduce a suitable new notion of nilpotency for sand automata. Finally, we prove that this simple dynamical behavior is undecidable.


On disjoint matchings in cubic graphs

Abstract: For $i=2,3$ and a cubic graph $G$ let $\nu_{i}(G)$ denote the maximum number of edges that can be covered by $i$ matchings. We show that $\nu_{2}(G)\geq {4/5}| V(G)| $ and $\nu_{3}(G)\geq {7/6}| V(G)| $. Moreover, it turns out that $\nu_{2}(G)\leq \frac{|V(G)|+2\nu_{3}(G)}{4}$.


Polynomial time algorithms for bi-criteria, multi-objective and ratio problems in clustering and imaging. Part I: Normalized cut and ratio regions

Abstract: Partitioning and grouping of similar objects plays a fundamental role in image segmentation and in clustering problems. In such problems a typical goal is to group together similar objects, or pixels in the case of image processing. At the same time another goal is to have each group distinctly dissimilar from the rest and possibly to have the group size fairly large. These goals are often combined as a ratio optimization problem. One example of such problem is the normalized cut problem, another is the ratio regions problem. We devise here the first polynomial time algorithms solving these problems optimally. The algorithms are efficient and combinatorial. This contrasts with the heuristic approaches used in the image segmentation literature that formulate those problems as nonlinear optimization problems, which are then relaxed and solved with spectral techniques in real numbers. These approaches not only fail to deliver an optimal solution, but they are also computationally expensive. The algorithms presented here use as a subroutine a minimum $s,t-cut procedure on a related graph which is of polynomial size. The output consists of the optimal solution to the respective ratio problem, as well as a sequence of nested solution with respect to any relative weighting of the objectives of the numerator and denominator. An extension of the results here to bi-criteria and multi-criteria objective functions is presented in part II.


Towards a Spreadsheet Engineering

Abstract: In this paper, we report some on-going focused research, but are further keen to set it in the context of a proposed bigger picture, as follows. There is a certain depressing pattern about the attitude of industry to spreadsheet error research and a certain pattern about conferences highlighting these issues. Is it not high time to move on from measuring spreadsheet errors to developing an armoury of disciplines and controls? In short, we propose the need to rigorously lay the foundations of a spreadsheet engineering discipline. Clearly, multiple research teams would be required to tackle such a big task. This suggests the need for both national and international collaborative research, since any given group can only address a small segment of the whole. There are already a small number of examples of such on-going international collaborative research. Having established the need for a directed research effort, the rest of the paper then attempts to act as an exemplar in demonstrating and applying this focus. With regard to one such of research, in a recent paper, Panko (2005) stated that: "...group development and testing appear to be promising areas to pursue". Of particular interest to us are some gaps in the published research record on techniques to reduce errors. We further report on the topics: techniques for cross-checking, time constraints effects, and some aspects of developer perception.


A Software Development Methodology for Research and Prototyping in Financial Markets

Abstract: The objective of this paper is to develop a standardized methodology for software development in the very unique industry and culture of financial markets. The prototyping process we present allows the development team to deliver for review and comment intermediate-level models based upon clearly defined customer requirements. This spreadsheet development methodology is presented within a larger business context, that of trading system development, the subject of an upcoming book by the authors of this paper.


Rapid Spreadsheet Reshaping with Excelsior: multiple drastic changes to content and layout are easy when you represent enough structure

Abstract: Spreadsheets often need changing in ways made tedious and risky by Excel. For example: simultaneously altering many tables' size, orientation, and position; inserting cross-tabulations; moving data between sheets; splitting and merging sheets. A safer, faster restructuring tool is, we claim, Excelsior. The result of a research project into reducing spreadsheet risk, Excelsior is the first ever tool for modularising spreadsheets; i.e. for building them from components which can be independently created, tested, debugged, and updated. It represents spreadsheets in a way that makes these components explicit, separates them from layout, and allows both components and layout to be changed without breaking dependent formulae. Here, we report experiments to test that this does indeed make such changes easier. In one, we automatically generated a cross-tabulation and added it to a spreadsheet. In the other, we generated new versions of a 10,000-cell housing-finance spreadsheet containing many interconnected 20*40 tables. We varied table sizes from 5*10 to 200*2,000; moved tables between sheets; and flipped table orientations. Each change generated a spreadsheet with different structure but identical outputs; each change took just a few minutes.


Considering Functional Spreadsheet Operator Usage Suggests the Value of Example Driven Modelling for Decision Support Systems

Abstract: Most spreadsheet surveys both for reporting use and error focus on the practical application of the spreadsheet in a particular industry. Typically these studies will illustrate that a particular percentage of spreadsheets are used for optimisation and a further percentage are used for 'What if' analysis. Much less common is examining the classes of function, as defined by the vendor, used by modellers to build their spreadsheet models. This alternative analysis allows further insight into the programming nature of spreadsheets and may assist researchers in targeting particular structures in spreadsheet software for further investigation. Further, understanding the functional make-up of spreadsheets allows effective evaluation of novel approaches from a programming point of view. It allows greater insight into studies that report what spreadsheets are used for since it is explicit which functional structures are in use in spreadsheets. We conclude that a deeper understanding of the use of operators and the operator's relationship to error would provide fresh insight into the spreadsheet error problem. Considering functional spreadsheet operator usage suggests the value of Example Driven Modelling for Decision Support Systems


Documenting Spreadsheets

Abstract: This paper discusses spreadsheets documentation and new means to achieve this end by using Excel's built-in "Comment" function. By structuring comments, they can be used as an essential tool to fully explain spreadsheet. This will greatly facilitate spreadsheet change control, risk management and auditing. It will fill a crucial gap in corporate governance by adding essential information that can be managed in order to satisfy internal controls and accountability standards.


Spreadsheet Validation and Analysis through Content Visualization

Abstract: Visualizing spreadsheet content provides analytic insight and visual validation of large amounts of spreadsheet data. Oculus Excel Visualizer is a point and click data visualization experiment which directly visualizes Excel data and re-uses the layout and formatting already present in the spreadsheet.


Does an awareness of differing types of spreadsheet errors aid end-users in identifying spreadsheets errors?

Abstract: The research presented in this paper establishes a valid, and simplified, revision of previous spreadsheet error classifications. This investigation is concerned with the results of a web survey and two web-based gender and domain-knowledge free spreadsheet error identification exercises. The participants of the survey and exercises were a test group of professionals (all of whom regularly use spreadsheets) and a control group of students from the University of Greenwich (UK). The findings show that over 85% of users are also the spreadsheet's developer, supporting the revised spreadsheet error classification. The findings also show that spreadsheet error identification ability is directly affected both by spreadsheet experience and by error-type awareness. In particular, that spreadsheet error-type awareness significantly improves the user's ability to identify, the more surreptitious, qualitative error.


Comparison of Characteristics and Practices amongst Spreadsheet Users with Different Levels of Experience

Abstract: We developed an internet-based questionnaire on spreadsheet use that we administered to a large number of users in several companies and organizations to document how spreadsheets are currently being developed and used in business. In this paper, we discuss the results drawn from of a comparison of responses from individuals with the most experience and expertise with those from individuals with the least. These results describe two views of spreadsheet design and use in organizations, and reflect gaps between these two groups and between these groups and the entire population of nearly 1600 respondents. Moreover, our results indicate that these gaps have multiple dimensions: they reflect not only the context, skill, and practices of individual users but also the policies of large organizations.


An Investigation of the Incidence and Effect of Spreadsheet Errors Caused by the Hard Coding of Input Data Values into Formulas

Abstract: The hard coding of input data or constants into spreadsheet formulas is widely recognised as poor spreadsheet model design. However, the importance of avoiding such practice appears to be underestimated perhaps in light of the lack of quantitative error at the time of occurrence and the recognition that this design defect may never result in a bottom-line error. The paper examines both the academic and practitioner view of such hard coding design flaws. The practitioner or industry viewpoint is gained indirectly through a review of commercial spreadsheet auditing software. The development of an automated (electronic) means for detecting such hard coding is described together with a discussion of some results obtained through analysis of a number of student and practitioner spreadsheet models.


Quiescence of Self-stabilizing Gossiping among Mobile Agents in Graphs

Abstract: This paper considers gossiping among mobile agents in graphs: agents move on the graph and have to disseminate their initial information to every other agent. We focus on self-stabilizing solutions for the gossip problem, where agents may start from arbitrary locations in arbitrary states. Self-stabilization requires (some of the) participating agents to keep moving forever, hinting at maximizing the number of agents that could be allowed to stop moving eventually. This paper formalizes the self-stabilizing agent gossip problem, introduces the quiescence number (i.e., the maximum number of eventually stopping agents) of self-stabilizing solutions and investigates the quiescence number with respect to several assumptions related to agent anonymity, synchrony, link duplex capacity, and whiteboard capacity.


Acquisition Accuracy Evaluation in Visual Inspection Systems - a Practical Approach

Abstract: This paper draws a proposal of a set of parameters and methods for accuracy evaluation of visual inspection systems. The case of a monochrome board is treated, but practically all conclusions and methods may be extended for colour acquisition. Basically, the proposed parameters are grouped in five sets as follows:Internal noise;Video ADC cuantisation parameters;Analogue processing section parameters;Dominant frequencies;Synchronisation (lock-in) accuracy. On basis of this set of parameters was developed a software environment, in conjunction with a test signal generator that allows the "test" images. The paper also presents conclusions of evaluation for two types of video acquisition boards


DSP Based System for Real time Voice Synthesis Applications Development

Abstract: This paper describes an experimental system designed for development of real time voice synthesis applications. The system is composed from a DSP coprocessor card, equipped with an TMS320C25 or TMS320C50 chip, voice acquisition module (ADDA2),host computer (IBM-PC compatible), software specific tools.


Random hypergraphs and algorithmics

Abstract: Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of hypergraph component is bounded, as a generalisation of Wright inequalities for graphs: the proof is a combinatorial understanding of the structure by inclusion exclusion. Asymptotic results are obtained, thanks to generating functions proofs are at the end very easy to read, through complex analysis by saddle point method. By this way, we characterized: - the components with a given number of vertices and of hyperedges by the expected size of a random hypermatching in these structures. - the random hypergraphs (evolving hyperedge by hyperedge) according to the expected number of hyperedges when the first cycle appears in the evolving structure. This work is an open road to further works on random hypergraphs such as threshold phenomenon, tools used here seem to be sufficient at first sight.


Self-Stabilizing Pulse Synchronization Inspired by Biological Pacemaker Networks

Abstract: We define the ``Pulse Synchronization'' problem that requires nodes to achieve tight synchronization of regular pulse events, in the settings of distributed computing systems. Pulse-coupled synchronization is a phenomenon displayed by a large variety of biological systems, typically overcoming a high level of noise. Inspired by such biological models, a robust and self-stabilizing Byzantine pulse synchronization algorithm for distributed computer systems is presented. The algorithm attains near optimal synchronization tightness while tolerating up to a third of the nodes exhibiting Byzantine behavior concurrently. Pulse synchronization has been previously shown to be a powerful building block for designing algorithms in this severe fault model. We have previously shown how to stabilize general Byzantine algorithms, using pulse synchronization. To the best of our knowledge there is no other scheme to do this without the use of synchronized pulses.


Networks become navigable as nodes move and forget

Abstract: We propose a dynamical process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of individuals are linked by a short chain of acquaintances computable by a simple decentralized routing algorithm, known as greedy routing. Previously proposed dynamical processes enabled to demonstrate experimentally (by simulations) that the small world phenomenon can emerge from local dynamics. However, the analysis of greedy routing using the probability distributions arising from these dynamics is quite complex because of mutual dependencies. In contrast, our process enables complete formal analysis. It is based on the combination of two simple processes: a random walk process, and an harmonic forgetting process. Both processes reflect natural behaviors of the individuals, viewed as nodes in the network of inter-individual acquaintances. We prove that, in k-dimensional lattices, the combination of these two processes generates long-range links mutually independently distributed as a k-harmonic distribution. We analyze the performances of greedy routing at the stationary regime of our process, and prove that the expected number of steps for routing from any source to any target in any multidimensional lattice is a polylogarithmic function of the distance between the two nodes in the lattice. Up to our knowledge, these results are the first formal proof that navigability in small worlds can emerge from a dynamical process for network evolution. Our dynamical process can find practical applications to the design of spatial gossip and resource location protocols.


Staged Self-Assembly:Nanomanufacture of Arbitrary Shapes with O(1) Glues

Abstract: We introduce staged self-assembly of Wang tiles, where tiles can be added dynamically in sequence and where intermediate constructions can be stored for later mixing. This model and its various constraints and performance measures are motivated by a practical nanofabrication scenario through protein-based bioengineering. Staging allows us to break through the traditional lower bounds in tile self-assembly by encoding the shape in the staging algorithm instead of the tiles. All of our results are based on the practical assumption that only a constant number of glues, and thus only a constant number of tiles, can be engineered, as each new glue type requires significant biochemical research and experiments. Under this assumption, traditional tile self-assembly cannot even manufacture an n*n square; in contrast, we show how staged assembly enables manufacture of arbitrary orthogonal shapes in a variety of precise formulations of the model.


Thread algebra for poly-threading

Abstract: Threads as considered in basic thread algebra are primarily looked upon as behaviours exhibited by sequential programs on execution. It is a fact of life that sequential programs are often fragmented. Consequently, fragmented program behaviours are frequently found. In this paper, we consider this phenomenon. We extend basic thread algebra with the barest mechanism for sequencing of threads that are taken for fragments. This mechanism, called poly-threading, supports both autonomous and non-autonomous thread selection in sequencing. We relate the resulting theory to the algebraic theory of processes known as ACP and use it to describe analytic execution architectures suited for fragmented programs. We also consider the case where the steps of fragmented program behaviours are interleaved in the ways of non-distributed and distributed multi-threading.


The Complexity of Testing Properties of Simple Games

Abstract: Simple games cover voting systems in which a single alternative, such as a bill or an amendment, is pitted against the status quo. A simple game or a yes-no voting system is a set of rules that specifies exactly which collections of ``yea'' votes yield passage of the issue at hand. A collection of ``yea'' voters forms a winning coalition. We are interested on performing a complexity analysis of problems on such games depending on the game representation. We consider four natural explicit representations, winning, loosing, minimal winning, and maximal loosing. We first analyze the computational complexity of obtaining a particular representation of a simple game from a different one. We show that some cases this transformation can be done in polynomial time while the others require exponential time. The second question is classifying the complexity for testing whether a game is simple or weighted. We show that for the four types of representation both problem can be solved in polynomial time. Finally, we provide results on the complexity of testing whether a simple game or a weighted game is of a special type. In this way, we analyze strongness, properness, decisiveness and homogeneity, which are desirable properties to be fulfilled for a simple game.


Multi-dimensional sparse time series: feature extraction

Abstract: We show an analysis of multi-dimensional time series via entropy and statistical linguistic techniques. We define three markers encoding the behavior of the series, after it has been translated into a multi-dimensional symbolic sequence. The leading component and the trend of the series with respect to a mobile window analysis result from the entropy analysis and label the dynamical evolution of the series. The diversification formalizes the differentiation in the use of recurrent patterns, from a Zipf law point of view. These markers are the starting point of further analysis such as classification or clustering of large database of multi-dimensional time series, prediction of future behavior and attribution of new data. We also present an application to economic data. We deal with measurements of money investments of some business companies in advertising market for different media sources.


Optimizing polynomials for floating-point implementation

Abstract: The floating-point implementation of a function on an interval often reduces to polynomial approximation, the polynomial being typically provided by Remez algorithm. However, the floating-point evaluation of a Remez polynomial sometimes leads to catastrophic cancellations. This happens when some of the polynomial coefficients are very small in magnitude with respects to others. In this case, it is better to force these coefficients to zero, which also reduces the operation count. This technique, classically used for odd or even functions, may be generalized to a much larger class of functions. An algorithm is presented that forces to zero the smaller coefficients of the initial polynomial thanks to a modified Remez algorithm targeting an incomplete monomial basis. One advantage of this technique is that it is purely numerical, the function being used as a numerical black box. This algorithm is implemented within a larger polynomial implementation tool that is demonstrated on a range of examples, resulting in polynomials with less coefficients than those obtained the usual way.


Stream sampling for variance-optimal estimation of subset sums

Abstract: From a high volume stream of weighted items, we want to maintain a generic sample of a certain limited size $k$ that we can later use to estimate the total weight of arbitrary subsets. This is the classic context of on-line reservoir sampling, thinking of the generic sample as a reservoir. We present an efficient reservoir sampling scheme, $\varoptk$, that dominates all previous schemes in terms of estimation quality. $\varoptk$ provides {\em variance optimal unbiased estimation of subset sums}. More precisely, if we have seen $n$ items of the stream, then for {\em any} subset size $m$, our scheme based on $k$ samples minimizes the average variance over all subsets of size $m$. In fact, the optimality is against any off-line scheme with $k$ samples tailored for the concrete set of items seen. In addition to optimal average variance, our scheme provides tighter worst-case bounds on the variance of {\em particular} subsets than previously possible. It is efficient, handling each new item of the stream in $O(\log k)$ time. Finally, it is particularly well suited for combination of samples from different streams in a distributed setting.


Intuitive Source Code Visualization Tools for Improving Student Comprehension: BRICS

Abstract: Even relatively simple code analysis can be a daunting task for many first year students. Perceived complexity, coupled with foreign and harsh syntax, often outstrips the ability for students to take in what they are seeing in terms of their verbal memory. That is, first year students often lack the experience to encode critical building blocks in source code, and their interrelationships, into their own words. We believe this argues for the need for IDEs to provide additional support for representations that would appeal directly to visual memory. In this paper, we examine this need for intuitive source code visualization tools that are easily accessible to novice programmers, discuss the requirements for such a tool, and suggest a novel idea that takes advantage of human peripheral vision to achieve stronger overall code structure awareness.


Une approche modulaire probabiliste pour le routage \`a Qualit\'e de Service int\'egr\'ee

Abstract: Due to emerging real-time and multimedia applications, efficient routing of information packets in dynamically changing communication network requires that as the load levels, traffic patterns and topology of the network change, the routing policy also adapts. We focused in this paper on QoS based routing by developing a neuro-dynamic programming to construct dynamic state dependent routing policies. We propose an approach based on adaptive algorithm for packet routing using reinforcement learning which optimizes two criteria: cumulative cost path and end-to-end delay. Numerical results obtained with OPNET simulator for different packet interarrival times statistical distributions with different levels of traffic's load show that the proposed approach gives better results compared to standard optimal path routing algorithms.


Evaluation and exploitation of knowledge robustness in knowledge-based systems

Abstract: Industrial knowledge is complex, difficult to formalize and very dynamic in reason of the continuous development of techniques and technologies. The verification of the validity of the knowledge base at the time of its elaboration is not sufficient. To be exploitable, this knowledge must then be able to be used under conditions (slightly) different from the conditions in which it was formalized. So, it becomes vital for the company to permanently evaluate the quality of the industrial knowledge implemented in the system. This evaluation is founded on the concept of robustness of the knowledge formalized by conceptual graphs. The evaluation method is supported by a computerized tool.


Aggregating and Deploying Network Access Control Policies

Abstract: The existence of errors or inconsistencies in the configuration of security components, such as filtering routers and/or firewalls, may lead to weak access control policies -- potentially easy to be evaded by unauthorized parties. We present in this paper a proposal to create, manage, and deploy consistent policies in those components in an efficient way. To do so, we combine two main approaches. The first approach is the use of an aggregation mechanism that yields consistent configurations or signals inconsistencies. Through this mechanism we can fold existing policies of a given system and create a consistent and global set of access control rules -- easy to maintain and manage by using a single syntax. The second approach is the use of a refinement mechanism that guarantees the proper deployment of such a global set of rules into the system, yet free of inconsistencies.


Towards an Optimal Separation of Space and Length in Resolution

Abstract: Most state-of-the-art satisfiability algorithms today are variants of the DPLL procedure augmented with clause learning. The main bottleneck for such algorithms, other than the obvious one of time, is the amount of memory used. In the field of proof complexity, the resources of time and memory correspond to the length and space of resolution proofs. There has been a long line of research trying to understand these proof complexity measures, but while strong results have been proven on length our understanding of space is still quite poor. For instance, it remains open whether the fact that a formula is provable in short length implies that it is also provable in small space or whether on the contrary these measures are unrelated in the sense that short proofs can be arbitrarily complex with respect to space. In this paper, we present some evidence that the true answer should be that the latter case holds. We do this by proving a tight bound of Theta(sqrt(n)) on the space needed for so-called pebbling contradictions over pyramid graphs of size n. This yields the first polynomial lower bound on space that is not a consequence of a corresponding lower bound on width, another well-studied measure in resolution, as well as an improvement of the weak separation in (Nordstrom 2006) of space and width from logarithmic to polynomial. Also, continuing the line of research initiated by (Ben-Sasson 2002) into trade-offs between different proof complexity measures, we present a simplified proof of the recent length-space trade-off result in (Hertel and Pitassi 2007), and show how our ideas can be used to prove a couple of other exponential trade-offs in resolution.


An approach to control collaborative processes in PLM systems

Abstract: Companies that collaborate within the product development processes need to implement an effective management of their collaborative activities. Despite the implementation of a PLM system, the collaborative activities are not efficient as it might be expected. This paper presents an analysis of the problems related to the collaborative work using a PLM system. From this analysis, we propose an approach for improving collaborative processes within a PLM system, based on monitoring indicators. This approach leads to identify and therefore to mitigate the brakes of the collaborative work.


Spanning directed trees with many leaves

Abstract: The {\sc Directed Maximum Leaf Out-Branching} problem is to find an out-branching (i.e. a rooted oriented spanning tree) in a given digraph with the maximum number of leaves. In this paper, we obtain two combinatorial results on the number of leaves in out-branchings. We show that - every strongly connected $n$-vertex digraph $D$ with minimum in-degree at least 3 has an out-branching with at least $(n/4)^{1/3}-1$ leaves; - if a strongly connected digraph $D$ does not contain an out-branching with $k$ leaves, then the pathwidth of its underlying graph UG($D$) is $O(k\log k)$. Moreover, if the digraph is acyclic, the pathwidth is at most $4k$. The last result implies that it can be decided in time $2^{O(k\log^2 k)}\cdot n^{O(1)}$ whether a strongly connected digraph on $n$ vertices has an out-branching with at least $k$ leaves. On acyclic digraphs the running time of our algorithm is $2^{O(k\log k)}\cdot n^{O(1)}$.


A quadratic algorithm for road coloring

Abstract: The Road Coloring Theorem states that every aperiodic directed graph with constant out-degree has a synchronized coloring. This theorem had been conjectured during many years as the Road Coloring Problem before being settled by A. Trahtman. Trahtman's proof leads to an algorithm that finds a synchronized labeling with a cubic worst-case time complexity. We show a variant of his construction with a worst-case complexity which is quadratic in time and linear in space. We also extend the Road Coloring Theorem to the periodic case.


Incremental Topological Ordering and Strong Component Maintenance

Abstract: We present an on-line algorithm for maintaining a topological order of a directed acyclic graph as arcs are added, and detecting a cycle when one is created. Our algorithm takes O(m^{1/2}) amortized time per arc, where m is the total number of arcs. For sparse graphs, this bound improves the best previous bound by a logarithmic factor and is tight to within a constant factor for a natural class of algorithms that includes all the existing ones. Our main insight is that the bidirectional search method of previous algorithms does not require an ordered search, but can be more general. This allows us to avoid the use of heaps (priority queues) entirely. Instead, the deterministic version of our algorithm uses (approximate) median-finding. The randomized version of our algorithm avoids this complication, making it very simple. We extend our topological ordering algorithm to give the first detailed algorithm for maintaining the strong components of a directed graph, and a topological order of these components, as arcs are added. This extension also has an amortized time bound of O(m^{1/2}) per arc.


Un Algorithme de Gestion des Adjacences bas\'e sur la Puissance du Signal

Abstract: In this proposition, we present a link management technique for pro-active routing protocols for ad-hoc networks. This new mechanism is based on signal strength hence cross layer approach is used. The hysteresis mechanism provided by OLSR is improved upon by using signal strength in combination with the hello loss based hysteresis. The signal power is used to determine if the link-quality is improving or deteriorating while packet losses are handled through the hysteresis mechanism specified in OLSR RFC. This not only makes the link management more robust but also helps in anticipating link breakages thereby greatly improving the performance.


Website Optimization through Mining User Navigational Pattern

Abstract: With the World Wide Web's ubiquity increase and the rapid development of various online businesses, the complexity of web sites grow. The analysis of web user's navigational pattern within a web site can provide useful information for server performance enhancements, restructuring a website and direct marketing in e-commerce etc. In this paper, an algorithm is proposed for mining such navigation patterns. The key insight is that users access information of interest and follow a certain path while navigating a web site. If they don't find it, they would backtrack and choose among the alternate paths till they reach the destination. The point they backtrack is the Intermediate Reference Location. Identifying such Intermediate locations and destinations out of the pattern will be the main endeavor in the rest of this report.


Knapsack cryptosystems built on NP-hard instance

Abstract: We construct three public key knapsack cryptosystems. Standard knapsack cryptosystems hide easy instances of the knapsack problem and have been broken. The systems considered in the article face this problem: They hide a random (possibly hard) instance of the knapsack problem. We provide both complexity results (size of the key, time needed to encypher/decypher...) and experimental results. Security results are given for the second cryptosystem (the fastest one and the one with the shortest key). Probabilistic polynomial reductions show that finding the private key is as difficult as factorizing a product of two primes. We also consider heuristic attacks. First, the density of the cryptosystem can be chosen arbitrarily close to one, discarding low density attacks. Finally, we consider explicit heuristic attacks based on the LLL algorithm and we prove that with respect to these attacks, the public key is as secure as a random key.


Untangling planar graphs from a specified vertex position - Hard cases

Abstract: Given a planar graph $G$, we consider drawings of $G$ in the plane where edges are represented by straight line segments (which possibly intersect). Such a drawing is specified by an injective embedding $\pi$ of the vertex set of $G$ into the plane. We prove that a wheel graph $W_n$ admits a drawing $\pi$ such that, if one wants to eliminate edge crossings by shifting vertices to new positions in the plane, then at most $(2+o(1))\sqrt n$ of all $n$ vertices can stay fixed. Moreover, such a drawing $\pi$ exists even if it is presupposed that the vertices occupy any prescribed set of points in the plane. Similar questions are discussed for other families of planar graphs.


A Method for Solving Cyclic Block Penta-diagonal Systems of Linear Equations

Abstract: A method for solving cyclic block three-diagonal systems of equations is generalized for solving a block cyclic penta-diagonal system of equations. Introducing a special form of two new variables the original system is split into three block pentagonal systems, which can be solved by the known methods. As such method belongs to class of direct methods without pivoting. Implementation of the algorithm is discussed in some details and the numerical examples are present.


What Can We Learn Privately?

Abstract: Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output does not depend too heavily on any one input or specific training example? More precisely, we investigate learning algorithms that satisfy differential privacy, a notion that provides strong confidentiality guarantees in contexts where aggregate information is released about a database containing sensitive information about individuals. We demonstrate that, ignoring computational constraints, it is possible to privately agnostically learn any concept class using a sample size approximately logarithmic in the cardinality of the concept class. Therefore, almost anything learnable is learnable privately: specifically, if a concept class is learnable by a (non-private) algorithm with polynomial sample complexity and output size, then it can be learned privately using a polynomial number of samples. We also present a computationally efficient private PAC learner for the class of parity functions. Local (or randomized response) algorithms are a practical class of private algorithms that have received extensive investigation. We provide a precise characterization of local private learning algorithms. We show that a concept class is learnable by a local algorithm if and only if it is learnable in the statistical query (SQ) model. Finally, we present a separation between the power of interactive and noninteractive local learning algorithms.


Graph Sparsification by Effective Resistances

Abstract: We present a nearly-linear time algorithm that produces high-quality sparsifiers of weighted graphs. Given as input a weighted graph $G=(V,E,w)$ and a parameter $\epsilon>0$, we produce a weighted subgraph $H=(V,\tilde{E},\tilde{w})$ of $G$ such that $|\tilde{E}|=O(n\log n/\epsilon^2)$ and for all vectors $x\in\R^V$ $(1-\epsilon)\sum_{uv\in E}(x(u)-x(v))^2w_{uv}\le \sum_{uv\in\tilde{E}}(x(u)-x(v))^2\tilde{w}_{uv} \le (1+\epsilon)\sum_{uv\in E}(x(u)-x(v))^2w_{uv}. (*)$ This improves upon the sparsifiers constructed by Spielman and Teng, which had $O(n\log^c n)$ edges for some large constant $c$, and upon those of Bencz\'ur and Karger, which only satisfied (*) for $x\in\{0,1\}^V$. A key ingredient in our algorithm is a subroutine of independent interest: a nearly-linear time algorithm that builds a data structure from which we can query the approximate effective resistance between any two vertices in a graph in $O(\log n)$ time.


Femtocell Networks: A Survey

Abstract: The surest way to increase the system capacity of a wireless link is by getting the transmitter and receiver closer to each other, which creates the dual benefits of higher quality links and more spatial reuse. In a network with nomadic users, this inevitably involves deploying more infrastructure, typically in the form of microcells, hotspots, distributed antennas, or relays. A less expensive alternative is the recent concept of femtocells, also called home base-stations, which are data access points installed by home users get better indoor voice and data coverage. In this article, we overview the technical and business arguments for femtocells, and describe the state-of-the-art on each front. We also describe the technical challenges facing femtocell networks, and give some preliminary ideas for how to overcome them.


Selective association rule generation

Abstract: Mining association rules is a popular and well researched method for discovering interesting relations between variables in large databases. A practical problem is that at medium to low support values often a large number of frequent itemsets and an even larger number of association rules are found in a database. A widely used approach is to gradually increase minimum support and minimum confidence or to filter the found rules using increasingly strict constraints on additional measures of interestingness until the set of rules found is reduced to a manageable size. In this paper we describe a different approach which is based on the idea to first define a set of ``interesting'' itemsets (e.g., by a mixture of mining and expert knowledge) and then, in a second step to selectively generate rules for only these itemsets. The main advantage of this approach over increasing thresholds or filtering rules is that the number of rules found is significantly reduced while at the same time it is not necessary to increase the support and confidence thresholds which might lead to missing important information in the database.


Characterizing path graphs by forbidden induced subgraphs

Abstract: A graph is a path graph if it is the intersection graph of a family of subpaths of a tree. In 1970, Renz asked for a characterizaton of path graphs by forbidden induced subgraphs. Here we answer this question by listing all graphs that are not path graphs and are minimal with this property.


Faster Approximate Lossy Generalized Flow via Interior Point Algorithms

Abstract: We present faster approximation algorithms for generalized network flow problems. A generalized flow is one in which the flow out of an edge differs from the flow into the edge by a constant factor. We limit ourselves to the lossy case, when these factors are at most 1. Our algorithm uses a standard interior-point algorithm to solve a linear program formulation of the network flow problem. The system of linear equations that arises at each step of the interior-point algorithm takes the form of a symmetric M-matrix. We present an algorithm for solving such systems in nearly linear time. The algorithm relies on the Spielman-Teng nearly linear time algorithm for solving linear systems in diagonally-dominant matrices. For a graph with m edges, our algorithm obtains an additive epsilon approximation of the maximum generalized flow and minimum cost generalized flow in time tildeO(m^(3/2) * log(1/epsilon)). In many parameter ranges, this improves over previous algorithms by a factor of approximately m^(1/2). We also obtain a similar improvement for exactly solving the standard min-cost flow problem.


Robust Stochastic Chemical Reaction Networks and Bounded Tau-Leaping

Abstract: The behavior of some stochastic chemical reaction networks is largely unaffected by slight inaccuracies in reaction rates. We formalize the robustness of state probabilities to reaction rate deviations, and describe a formal connection between robustness and efficiency of simulation. Without robustness guarantees, stochastic simulation seems to require computational time proportional to the total number of reaction events. Even if the concentration (molecular count per volume) stays bounded, the number of reaction events can be linear in the duration of simulated time and total molecular count. We show that the behavior of robust systems can be predicted such that the computational work scales linearly with the duration of simulated time and concentration, and only polylogarithmically in the total molecular count. Thus our asymptotic analysis captures the dramatic speedup when molecular counts are large, and shows that for bounded concentrations the computation time is essentially invariant with molecular count. Finally, by noticing that even robust stochastic chemical reaction networks are capable of embedding complex computational problems, we argue that the linear dependence on simulated time and concentration is likely optimal.


The Future of Scientific Simulations: from Artificial Life to Artificial Cosmogenesis

Abstract: This philosophical paper explores the relation between modern scientific simulations and the future of the universe. We argue that a simulation of an entire universe will result from future scientific activity. This requires us to tackle the challenge of simulating open-ended evolution at all levels in a single simulation. The simulation should encompass not only biological evolution, but also physical evolution (a level below) and cultural evolution (a level above). The simulation would allow us to probe what would happen if we would "replay the tape of the universe" with the same or different laws and initial conditions. We also distinguish between real-world and artificial-world modelling. Assuming that intelligent life could indeed simulate an entire universe, this leads to two tentative hypotheses. Some authors have argued that we may already be in a simulation run by an intelligent entity. Or, if such a simulation could be made real, this would lead to the production of a new universe. This last direction is argued with a careful speculative philosophical approach, emphasizing the imperative to find a solution to the heat death problem in cosmology. The reader is invited to consult Annex 1 for an overview of the logical structure of this paper. -- Keywords: far future, future of science, ALife, simulation, realization, cosmology, heat death, fine-tuning, physical eschatology, cosmological natural selection, cosmological artificial selection, artificial cosmogenesis, selfish biocosm hypothesis, meduso-anthropic principle, developmental singularity hypothesis, role of intelligent life.


Optimizing Web Sites for Customer Retention

Abstract: With customer relationship management (CRM) companies move away from a mainly product-centered view to a customer-centered view. Resulting from this change, the effective management of how to keep contact with customers throughout different channels is one of the key success factors in today's business world. Company Web sites have evolved in many industries into an extremely important channel through which customers can be attracted and retained. To analyze and optimize this channel, accurate models of how customers browse through the Web site and what information within the site they repeatedly view are crucial. Typically, data mining techniques are used for this purpose. However, there already exist numerous models developed in marketing research for traditional channels which could also prove valuable to understanding this new channel. In this paper we propose the application of an extension of the Logarithmic Series Distribution (LSD) model repeat-usage of Web-based information and thus to analyze and optimize a Web Site's capability to support one goal of CRM, to retain customers. As an example, we use the university's blended learning web portal with over a thousand learning resources to demonstrate how the model can be used to evaluate and improve the Web site's effectiveness.


Hierarchical Grid-Based Pairwise Key Pre-distribution in Wireless Sensor Networks

Abstract: The security of wireless sensor networks is an active topic of research where both symmetric and asymmetric key cryptography issues have been studied. Due to their computational feasibility on typical sensor nodes, symmetric key algorithms that use the same key to encrypt and decrypt messages have been intensively studied and perfectly deployed in such environment. Because of the wireless sensor's limited infrastructure, the bottleneck challenge for deploying these algorithms is the key distribution. For the same reason of resources restriction, key distribution mechanisms which are used in traditional wireless networks are not efficient for sensor networks. To overcome the key distribution problem, several key pre-distribution algorithms and techniques that assign keys or keying material for the networks nodes in an offline phase have been introduced recently. In this paper, we introduce a supplemental distribution technique based on the communication pattern and deployment knowledge modeling. Our technique is based on the hierarchical grid deployment. For granting a proportional security level with number of dependent sensors, we use different polynomials in different orders with different weights. In seek of our proposed work's value, we provide a detailed analysis on the used resources, resulting security, resiliency, and connectivity compared with other related works.


Serious Flaws in Korf et al.'s Analysis on Time Complexity of A*

Abstract: This paper has been withdrawn.


Hsiao-Code Check Matrices and Recursively Balanced Matrices

Abstract: The key step of generating the well-known Hsiao code is to construct a {0,1}-check-matrix in which each column contains the same odd-number of 1's and each row contains the same number of 1's or differs at most by one for the number of 1's. We also require that no two columns are identical in the matrix. The author solved this problem in 1986 by introducing a type of recursively balanced matrices. However, since the paper was published in Chinese, the solution for such an important problem was not known by international researchers in coding theory. In this note, we focus on how to practically generate the check matrix of Hsiao codes. We have modified the original algorithm to be more efficient and effective. We have also corrected an error in algorithm analysis presented in the earlier paper. The result shows that the algorithm attained optimum in average cases if a divide-and-conquer technique must be involved in the algorithm.


22-Step Collisions for SHA-2

Abstract: In this note, we provide the first 22-step collisions for SHA-256 and SHA-512. Detailed technique of generating these collisions will be provided in the next revision of this note.


On the Topology of the Restricted Delaunay Triangulation and Witness Complex in Higher Dimensions

Abstract: It is a well-known fact that, under mild sampling conditions, the restricted Delaunay triangulation provides good topological approximations of 1- and 2-manifolds. We show that this is not the case for higher-dimensional manifolds, even under stronger sampling conditions. Specifically, it is not true that, for any compact closed submanifold M of R^n, and any sufficiently dense uniform sampling L of M, the Delaunay triangulation of L restricted to M is homeomorphic to M, or even homotopy equivalent to it. Besides, it is not true either that, for any sufficiently dense set W of witnesses, the witness complex of L relative to M contains or is contained in the restricted Delaunay triangulation of L.


Treewidth computation and extremal combinatorics

Abstract: For a given graph G and integers b,f >= 0, let S be a subset of vertices of G of size b+1 such that the subgraph of G induced by S is connected and S can be separated from other vertices of G by removing f vertices. We prove that every graph on n vertices contains at most n\binom{b+f}{b} such vertex subsets. This result from extremal combinatorics appears to be very useful in the design of several enumeration and exact algorithms. In particular, we use it to provide algorithms that for a given n-vertex graph G - compute the treewidth of G in time O(1.7549^n) by making use of exponential space and in time O(2.6151^n) and polynomial space; - decide in time O(({\frac{2n+k+1}{3})^{k+1}\cdot kn^6}) if the treewidth of G is at most k; - list all minimal separators of G in time O(1.6181^n) and all potential maximal cliques of G in time O(1.7549^n). This significantly improves previous algorithms for these problems.


On the need for a global academic internet platform

Abstract: The article collects arguments for the necessity of a global academic internet platform, which is organized as a kind of ``global scientific parliament''. With such a constitution educational and research institutions will have direct means for communicating scientific results, as well as a platform for representing academia and scientific life in the public.


Hybrid Reasoning and the Future of Iconic Representations

Abstract: We give a brief overview of the main characteristics of diagrammatic reasoning, analyze a case of human reasoning in a mastermind game, and explain why hybrid representation systems (HRS) are particularly attractive and promising for Artificial General Intelligence and Computer Science in general.


NCore: Architecture and Implementation of a Flexible, Collaborative Digital Library

Abstract: NCore is an open source architecture and software platform for creating flexible, collaborative digital libraries. NCore was developed by the National Science Digital Library (NSDL) project, and it serves as the central technical infrastructure for NSDL. NCore consists of a central Fedora-based digital repository, a specific data model, an API, and a set of backend services and frontend tools that create a new model for collaborative, contributory digital libraries. This paper describes NCore, presents and analyzes its architecture, tools and services; and reports on the experience of NSDL in building and operating a major digital library on it over the past year and the experience of the Digital Library for Earth Systems Education in porting their existing digital library and tools to the NCore platform.


Integrity-Enhancing Replica Coordination for Byzantine Fault Tolerant Systems

Abstract: Strong replica consistency is often achieved by writing deterministic applications, or by using a variety of mechanisms to render replicas deterministic. There exists a large body of work on how to render replicas deterministic under the benign fault model. However, when replicas can be subject to malicious faults, most of the previous work is no longer effective. Furthermore, the determinism of the replicas is often considered harmful from the security perspective and for many applications, their integrity strongly depends on the randomness of some of their internal operations. This calls for new approaches towards achieving replica consistency while preserving the replica randomness. In this paper, we present two such approaches. One is based on Byzantine agreement and the other on threshold coin-tossing. Each approach has its strength and weaknesses. We compare the performance of the two approaches and outline their respective best use scenarios.


Proactive Service Migration for Long-Running Byzantine Fault Tolerant Systems

Abstract: In this paper, we describe a novel proactive recovery scheme based on service migration for long-running Byzantine fault tolerant systems. Proactive recovery is an essential method for ensuring long term reliability of fault tolerant systems that are under continuous threats from malicious adversaries. The primary benefit of our proactive recovery scheme is a reduced vulnerability window. This is achieved by removing the time-consuming reboot step from the critical path of proactive recovery. Our migration-based proactive recovery is coordinated among the replicas, therefore, it can automatically adjust to different system loads and avoid the problem of excessive concurrent proactive recoveries that may occur in previous work with fixed watchdog timeouts. Moreover, the fast proactive recovery also significantly improves the system availability in the presence of faults.


Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data

Abstract: We consider privacy preserving decision tree induction via ID3 in the case where the training data is horizontally or vertically distributed. Furthermore, we consider the same problem in the case where the data is both horizontally and vertically distributed, a situation we refer to as grid partitioned data. We give an algorithm for privacy preserving ID3 over horizontally partitioned data involving more than two parties. For grid partitioned data, we discuss two different evaluation methods for preserving privacy ID3, namely, first merging horizontally and developing vertically or first merging vertically and next developing horizontally. Next to introducing privacy preserving data mining over grid-partitioned data, the main contribution of this paper is that we show, by means of a complexity analysis that the former evaluation method is the more efficient.


Dempster-Shafer for Anomaly Detection

Abstract: In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email dataset the algorithm works for email worm detection. Dempster-Shafer can be a promising method for anomaly detection problems with multiple features (data sources), and two or more classes.


A Quantifier Elimination Algorithm for Linear Real Arithmetic

Abstract: We propose a new quantifier elimination algorithm for the theory of linear real arithmetic. This algorithm uses as subroutine satisfiability modulo this theory, a problem for which there are several implementations available. The quantifier elimination algorithm presented in the paper is compared, on examples arising from program analysis problems, to several other implementations, all of which cannot solve some of the examples that our algorithm solves easily.


Simulation Optimization of the Crossdock Door Assignment Problem

Abstract: The purpose of this report is to present the Crossdock Door Assignment Problem, which involves assigning destinations to outbound dock doors of Crossdock centres such that travel distance by material handling equipment is minimized. We propose a two fold solution; simulation and optimization of the simulation model simulation optimization. The novel aspect of our solution approach is that we intend to use simulation to derive a more realistic objective function and use Memetic algorithms to find an optimal solution. The main advantage of using Memetic algorithms is that it combines a local search with Genetic Algorithms. The Crossdock Door Assignment Problem is a new domain application to Memetic Algorithms and it is yet unknown how it will perform.


Spatio-activity based object detection

Abstract: We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.


Using Intelligent Agents to understand organisational behaviour

Abstract: This paper introduces two ongoing research projects which seek to apply computer modelling techniques in order to simulate human behaviour within organisations. Previous research in other disciplines has suggested that complex social behaviours are governed by relatively simple rules which, when identified, can be used to accurately model such processes using computer technology. The broad objective of our research is to develop a similar capability within organisational psychology.


A Multi-Agent Simulation of Retail Management Practices

Abstract: We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents do offer potential for developing organizational capabilities in the future. Our multi-disciplinary research team has worked with a UK department store to collect data and capture perceptions about operations from actors within departments. Based on this case study work, we have built a simulator that we present in this paper. We then use the simulator to gather empirical evidence regarding two specific management practices: empowerment and employee development.


Understanding Retail Productivity by Simulating Management Practise

Abstract: Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. Our research so far has led us to conduct case study work with a top ten UK retailer, collecting data in four departments in two stores. Based on our case study data we have built and tested a first version of a department store simulator. In this paper we will report on the current development of our simulator which includes new features concerning more realistic data on the pattern of footfall during the day and the week, a more differentiated view of customers, and the evolution of customers over time. This allows us to investigate more complex scenarios and to analyze the impact of various management practices.


Using Intelligent Agents to Understand Management Practices and Retail Productivity

Abstract: Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.


A Queueing System for Modeling a File Sharing Principle

Abstract: We investigate in this paper the performance of a simple file sharing principle. For this purpose, we consider a system composed of N peers becoming active at exponential random times; the system is initiated with only one server offering the desired file and the other peers after becoming active try to download it. Once the file has been downloaded by a peer, this one immediately becomes a server. To investigate the transient behavior of this file sharing system, we study the instant when the system shifts from a congested state where all servers available are saturated by incoming demands to a state where a growing number of servers are idle. In spite of its apparent simplicity, this queueing model (with a random number of servers) turns out to be quite difficult to analyze. A formulation in terms of an urn and ball model is proposed and corresponding scaling results are derived. These asymptotic results are then compared against simulations.


An Agent-Based Simulation of In-Store Customer Experiences

Abstract: Agent-based modelling and simulation offers a new and exciting way of understanding the world of work. In this paper we describe the development of an agent-based simulation model, designed to help to understand the relationship between human resource management practices and retail productivity. We report on the current development of our simulation model which includes new features concerning the evolution of customers over time. To test some of these features we have conducted a series of experiments dealing with customer pool sizes, standard and noise reduction modes, and the spread of the word of mouth. Our multi-disciplinary research team draws upon expertise from work psychologists and computer scientists. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents offer potential for fostering sustainable organisational capabilities in the future.


Genetic-Algorithm Seeding Of Idiotypic Networks For Mobile-Robot Navigation

Abstract: Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jernes idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, pre-engineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.


Self-Assembly of Discrete Self-Similar Fractals

Abstract: In this paper, we search for {\it absolute} limitations of the Tile Assembly Model (TAM), along with techniques to work around such limitations. Specifically, we investigate the self-assembly of fractal shapes in the TAM. We prove that no self-similar fractal fully weakly self-assembles at temperature 1, and that certain kinds of self-similar fractals do not strictly self-assemble at any temperature. Additionally, we extend the fiber construction from Lathrop et. al. (2007) to show that any self-similar fractal belonging to a particular class of "nice" self-similar fractals has a fibered version that strictly self-assembles in the TAM.


Citation Counting, Citation Ranking, and h-Index of Human-Computer Interaction Researchers: A Comparison between Scopus and Web of Science

Abstract: This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR--a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially if citations in conference proceedings are sought and that h scores should be manually calculated instead of relying on system calculations.


Estimation of available bandwidth and measurement infrastructure for Russian segment of Internet

Abstract: In paper the method for estimation of available bandwidth is supposed which does not demand the advanced utilities. Our method is based on the measurement of network delay $D$ for packets of different sizes $W$. The simple expression for available bandwidth $B_{av} =(W_2-W_1)/(D_2-D_1)$ is substantiated. For the experimental testing the measurement infrastructure for Russian segment of Internet was installed in framework of RFBR grant 06-07-89074.


Investigating a Hybrid Metaheuristic For Job Shop Rescheduling

Abstract: Previous research has shown that artificial immune systems can be used to produce robust schedules in a manufacturing environment. The main goal is to develop building blocks (antibodies) of partial schedules that can be used to construct backup solutions (antigens) when disturbances occur during production. The building blocks are created based upon underpinning ideas from artificial immune systems and evolved using a genetic algorithm (Phase I). Each partial schedule (antibody) is assigned a fitness value and the best partial schedules are selected to be converted into complete schedules (antigens). We further investigate whether simulated annealing and the great deluge algorithm can improve the results when hybridised with our artificial immune system (Phase II). We use ten fixed solutions as our target and measure how well we cover these specific scenarios.


A Computational Framework for the Near Elimination of Spreadsheet Risk

Abstract: We present Risk Integrated's Enterprise Spreadsheet Platform (ESP), a technical approach to the near-elimination of spreadsheet risk in the enterprise computing environment, whilst maintaining the full flexibility of spreadsheets for modelling complex financial structures and processes. In its Basic Mode of use, the system comprises a secure and robust centralised spreadsheet management framework. In Advanced Mode, the system can be viewed as a robust computational framework whereby users can "submit jobs" to the spreadsheet, and retrieve the results from the computations, but with no direct access to the underlying spreadsheet. An example application, Monte Carlo simulation, is presented to highlight the benefits of this approach with regard to mitigating spreadsheet risk in complex, mission-critical, financial calculations.


TellTable Spreadsheet Audit: from Technical Possibility to Operating Prototype

Abstract: At the 2003 EuSpRIG meeting, we presented a framework and software infrastructure to generate and analyse an audit trail for a spreadsheet file. This report describes the results of a pilot implementation of this software (now called TellTable; see www.telltable.com), along with developments in the server infrastructure and availability, extensions to other "Office Suite" files, integration of the audit tool into the server interface, and related developments, licensing and reports. We continue to seek collaborators and partners in what is primarily an open-source project with some shared-source components.


A Novel Approach to Formulae Production and Overconfidence Measurement to Reduce Risk in Spreadsheet Modelling

Abstract: Research on formulae production in spreadsheets has established the practice as high risk yet unrecognised as such by industry. There are numerous software applications that are designed to audit formulae and find errors. However these are all post creation, designed to catch errors before the spreadsheet is deployed. As a general conclusion from EuSpRIG 2003 conference it was decided that the time has come to attempt novel solutions based on an understanding of human factors. Hence in this paper we examine one such possibility namely a novel example driven modelling approach. We discuss a control experiment that compares example driven modelling against traditional approaches over several progressively more difficult tests. The results are very interesting and certainly point to the value of further investigation of the example driven potential. Lastly we propose a method for statistically analysing the problem of overconfidence in spreadsheet modellers.


WiFly: experimenting with Wireless Sensor Networks and Virtual coordinates

Abstract: Experimentation is important when designing communication protocols for Wireless Sensor Networks. Lower-layers have a major impact on upper-layer performance, and the complexity of the phenomena can not be entirely captured by analysis or simulation. In this report, we go through the complete process, from designing an energy-efficient self-organizing communication architecture (MAC, routing and application layers) to real-life experimentation roll-outs. The presented communication architecture includes a MAC protocol which avoids building and maintaining neighborhood tables, and a geographically-inspired routing protocol over virtual coordinates. The application consists of a mobile sink interrogating a wireless sensor network based on the requests issued by a disconnected base station. After the design process of this architecture, we verify it functions correctly by simulation, and we perform a temporal verification. This study is needed to calculate the maximum speed the mobile sink can take. We detail the implementation, and the results of the off-site experimentation (energy consumption at PHY layer, collision probability at MAC layer, and routing). Finally, we report on the real-world deployment where we have mounted the mobile sink node on a radio-controlled airplane.


Exploring Human Factors in Spreadsheet Development

Abstract: In this paper we consider human factors and their impact on spreadsheet development in strategic decision-making. This paper brings forward research from many disciplines both directly related to spreadsheets and a broader spectrum from psychology to industrial processing. We investigate how human factors affect a simplified development cycle and what the potential consequences are.


Risk Management for Complex Calculations: EuSpRIG Best Practices in Hybrid Applications

Abstract: As the need for advanced, interactive mathematical models has increased, user/programmers are increasingly choosing the MatLab scripting language over spreadsheets. However, applications developed in these tools have high error risk, and no best practices exist. We recommend that advanced, highly mathematical applications incorporate these tools with spreadsheets into hybrid applications, where developers can apply EuSpRIG best practices. Development of hybrid applications can reduce the potential for errors, shorten development time, and enable higher level operations. We believe that hybrid applications are the future and over the course of this paper, we apply and extend spreadsheet best practices to reduce or prevent risks in hybrid Excel/MatLab applications.


Breaking Out of the Cell: On The Benefits of a New Spreadsheet User-Interaction Paradigm

Abstract: Contemporary spreadsheets are plagued by a profusion of errors, auditing difficulties, lack of uniform development methodologies, and barriers to easy comprehension of the underlying business models they represent. This paper presents a case that most of these difficulties stem from the fact that the standard spreadsheet user-interaction paradigm - the 'cell-matrix' approach - is appropriate for spreadsheet data presentation but has significant drawbacks with respect to spreadsheet creation, maintenance and comprehension when workbooks pass a minimal threshold of complexity. An alternative paradigm for the automated generation of spreadsheets directly from plain-language business model descriptions is presented along with its potential benefits. Sunsight Modeller (TM), a working software system implementing the suggested paradigm, is briefly described.


On the Throughput Allocation for Proportional Fairness in Multirate IEEE 802.11 DCF under General Load Conditions

Abstract: This paper presents a modified proportional fairness (PF) criterion suitable for mitigating the \textit{rate anomaly} problem of multirate IEEE 802.11 Wireless LANs employing the mandatory Distributed Coordination Function (DCF) option. Compared to the widely adopted assumption of saturated network, the proposed criterion can be applied to general networks whereby the contending stations are characterized by specific packet arrival rates, $\lambda_s$, and transmission rates $R_d^{s}$. The throughput allocation resulting from the proposed algorithm is able to greatly increase the aggregate throughput of the DCF while ensuring fairness levels among the stations of the same order of the ones available with the classical PF criterion. Put simply, each station is allocated a throughput that depends on a suitable normalization of its packet rate, which, to some extent, measures the frequency by which the station tries to gain access to the channel. Simulation results are presented for some sample scenarios, confirming the effectiveness of the proposed criterion.


Improved evolutionary generation of XSLT stylesheets

Abstract: This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented functional language, generally used to transform XML documents (or, in general, solve any problem that can be coded as an XML document). The proposed solution uses a tree representation for the stylesheets as well as diverse specific operators in order to obtain, in the studied cases and a reasonable time, a XSLT stylesheet that performs the transformation. Several types of representation have been compared, resulting in different performance and degree of success.


Early Experiences in Traffic Engineering Exploiting Path Diversity: A Practical Approach

Abstract: Recent literature has proved that stable dynamic routing algorithms have solid theoretical foundation that makes them suitable to be implemented in a real protocol, and used in practice in many different operational network contexts. Such algorithms inherit much of the properties of congestion controllers implementing one of the possible combination of AQM/ECN schemes at nodes and flow control at sources. In this paper we propose a linear program formulation of the multi-commodity flow problem with congestion control, under max-min fairness, comprising demands with or without exogenous peak rates. Our evaluations of the gain, using path diversity, in scenarios as intra-domain traffic engineering and wireless mesh networks encourages real implementations, especially in presence of hot spots demands and non uniform traffic matrices. We propose a flow aware perspective of the subject by using a natural multi-path extension to current congestion controllers and show its performance with respect to current proposals. Since flow aware architectures exploiting path diversity are feasible, scalable, robust and nearly optimal in presence of flows with exogenous peak rates, we claim that our solution rethinked in the context of realistic traffic assumptions performs as better as an optimal approach with all the additional benefits of the flow aware paradigm.


Compressed Modular Matrix Multiplication

Abstract: We propose to store several integers modulo a small prime into a single machine word. Modular addition is performed by addition and possibly subtraction of a word containing several times the modulo. Modular Multiplication is not directly accessible but modular dot product can be performed by an integer multiplication by the reverse integer. Modular multiplication by a word containing a single residue is a also possible. Therefore matrix multiplication can be performed on such a compressed storage. We here give bounds on the sizes of primes and matrices for which such a compression is possible. We also explicit the details of the required compressed arithmetic routines.


An Investigation of the Sequential Sampling Method for Crossdocking Simulation Output Variance Reduction

Abstract: This paper investigates the reduction of variance associated with a simulation output performance measure, using the Sequential Sampling method while applying minimum simulation replications, for a class of JIT (Just in Time) warehousing system called crossdocking. We initially used the Sequential Sampling method to attain a desired 95% confidence interval half width of plus/minus 0.5 for our chosen performance measure (Total usage cost, given the mean maximum level of 157,000 pounds and a mean minimum level of 149,000 pounds). From our results, we achieved a 95% confidence interval half width of plus/minus 2.8 for our chosen performance measure (Total usage cost, with an average mean value of 115,000 pounds). However, the Sequential Sampling method requires a huge number of simulation replications to reduce variance for our simulation output value to the target level. Arena (version 11) simulation software was used to conduct this study.


Improved Squeaky Wheel Optimisation for Driver Scheduling

Abstract: This paper presents a technique called Improved Squeaky Wheel Optimisation for driver scheduling problems. It improves the original Squeaky Wheel Optimisations effectiveness and execution speed by incorporating two additional steps of Selection and Mutation which implement evolution within a single solution. In the ISWO, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The Analysis step first computes the fitness of a current solution to identify troublesome components. The Selection step then discards these troublesome components probabilistically by using the fitness measure, and the Mutation step follows to further discard a small number of components at random. After the above steps, an input solution becomes partial and thus the resulting partial solution needs to be repaired. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, the optimisation in the ISWO is achieved by solution disruption, iterative improvement and an iterative constructive repair process performed. Encouraging experimental results are reported.


The Application of Bayesian Optimization and Classifier Systems in Nurse Scheduling

Abstract: Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each persons assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems.


Danger Theory: The Link between AIS and IDS?

Abstract: We present ideas about creating a next generation Intrusion Detection System based on the latest immunological theories. The central challenge with computer security is determining the difference between normal and potentially harmful activity. For half a century, developers have protected their systems by coding rules that identify and block specific events. However, the nature of current and future threats in conjunction with ever larger IT systems urgently requires the development of automated and adaptive defensive tools. A promising solution is emerging in the form of Artificial Immune Systems. The Human Immune System can detect and defend against harmful and previously unseen invaders, so can we not build a similar Intrusion Detection System for our computers.


Excelsior: Bringing the Benefits of Modularisation to Excel

Abstract: Excel lacks features for modular design. Had it such features, as do most programming languages, they would save time, avoid unneeded programming, make mistakes less likely, make code-control easier, help organisations adopt a uniform house style, and open business opportunities in buying and selling spreadsheet modules. I present Excelsior, a system for bringing these benefits to Excel.


GraphStream: A Tool for bridging the gap between Complex Systems and Dynamic Graphs

Abstract: The notion of complex systems is common to many domains, from Biology to Economy, Computer Science, Physics, etc. Often, these systems are made of sets of entities moving in an evolving environment. One of their major characteristics is the emergence of some global properties stemmed from local interactions between the entities themselves and between the entities and the environment. The structure of these systems as sets of interacting entities leads researchers to model them as graphs. However, their understanding requires most often to consider the dynamics of their evolution. It is indeed not relevant to study some properties out of any temporal consideration. Thus, dynamic graphs seem to be a very suitable model for investigating the emergence and the conservation of some properties. GraphStream is a Java-based library whose main purpose is to help researchers and developers in their daily tasks of dynamic problem modeling and of classical graph management tasks: creation, processing, display, etc. It may also be used, and is indeed already used, for teaching purpose. GraphStream relies on an event-based engine allowing several event sources. Events may be included in the core of the application, read from a file or received from an event handler.


Groups from Cyclic Infrastructures and Pohlig-Hellman in Certain Infrastructures

Abstract: In discrete logarithm based cryptography, a method by Pohlig and Hellman allows solving the discrete logarithm problem efficiently if the group order is known and has no large prime factors. The consequence is that such groups are avoided. In the past, there have been proposals for cryptography based on cyclic infrastructures. We will show that the Pohlig-Hellman method can be adapted to certain cyclic infrastructures, which similarly implies that certain infrastructures should not be used for cryptography. This generalizes a result by M\"uller, Vanstone and Zuccherato for infrastructures obtained from hyperelliptic function fields. We recall the Pohlig-Hellman method, define the concept of a cyclic infrastructure and briefly describe how to obtain such infrastructures from certain function fields of unit rank one. Then, we describe how to obtain cyclic groups from discrete cyclic infrastructures and how to apply the Pohlig-Hellman method to compute absolute distances, which is in general a computationally hard problem for cyclic infrastructures. Moreover, we give an algorithm which allows to test whether an infrastructure satisfies certain requirements needed for applying the Pohlig-Hellman method, and discuss whether the Pohlig-Hellman method is applicable in infrastructures obtained from number fields. Finally, we discuss how this influences cryptography based on cyclic infrastructures.


Comparison of the Discriminatory Processor Sharing Policies

Abstract: Discriminatory Processor Sharing policy introduced by Kleinrock is of a great interest in many application areas, including telecommunications, web applications and TCP flow modelling. Under the DPS policy the job priority is controlled by the vector of weights. Verifying the vector of weights it is possible to modify the service rates of the jobs and optimize system characteristics. In the present paper we present the results concerning the comparison of two DPS policies with different weight vectors. We show the monotonicity of the expected sojourn time of the system depending on the weight vector under certain condition on the system. Namely, the system has to consist of classes with means which are quite different from each other. The classes with similar means can be organized together and considered as one class, so the given restriction can be overcame.


On $(P_5,\bar{P_5})$-sparse graphs and other families

Abstract: We extend the notion of $P_4$-sparse graphs previously introduced by {\scshape Ho\`ang} by considering $\mathcal{F}$-sparse graphs were $\mathcal{F}$ denotes a finite set of graphs on $p$ vertices. Thus we obtain some results on $(P_5,\bar{P_5})$-sparse graphs already known on $(P_5,\bar{P_5})$-free graphs. Finally we completely describe the structure of $(P_5,\bar{P_5}, bull$)-sparse graphs, it follows that those graphs have bounded clique-width.


Local Approximation Schemes for Topology Control

Abstract: This paper presents a distributed algorithm on wireless ad-hoc networks that runs in polylogarithmic number of rounds in the size of the network and constructs a linear size, lightweight, (1+\epsilon)-spanner for any given \epsilon > 0. A wireless network is modeled by a d-dimensional \alpha-quasi unit ball graph (\alpha-UBG), which is a higher dimensional generalization of the standard unit disk graph (UDG) model. The d-dimensional \alpha-UBG model goes beyond the unrealistic ``flat world'' assumption of UDGs and also takes into account transmission errors, fading signal strength, and physical obstructions. The main result in the paper is this: for any fixed \epsilon > 0, 0 < \alpha \le 1, and d \ge 2, there is a distributed algorithm running in O(\log n \log^* n) communication rounds on an n-node, d-dimensional \alpha-UBG G that computes a (1+\epsilon)-spanner G' of G with maximum degree \Delta(G') = O(1) and total weight w(G') = O(w(MST(G)). This result is motivated by the topology control problem in wireless ad-hoc networks and improves on existing topology control algorithms along several dimensions. The technical contributions of the paper include a new, sequential, greedy algorithm with relaxed edge ordering and lazy updating, and clustering techniques for filtering out unnecessary edges.


Conditioning Probabilistic Databases

Abstract: Past research on probabilistic databases has studied the problem of answering queries on a static database. Application scenarios of probabilistic databases however often involve the conditioning of a database using additional information in the form of new evidence. The conditioning problem is thus to transform a probabilistic database of priors into a posterior probabilistic database which is materialized for subsequent query processing or further refinement. It turns out that the conditioning problem is closely related to the problem of computing exact tuple confidence values. It is known that exact confidence computation is an NP-hard problem. This has led researchers to consider approximation techniques for confidence computation. However, neither conditioning nor exact confidence computation can be solved using such techniques. In this paper we present efficient techniques for both problems. We study several problem decomposition methods and heuristics that are based on the most successful search techniques from constraint satisfaction, such as the Davis-Putnam algorithm. We complement this with a thorough experimental evaluation of the algorithms proposed. Our experiments show that our exact algorithms scale well to realistic database sizes and can in some scenarios compete with the most efficient previous approximation algorithms.


Lighweight Target Tracking Using Passive Traces in Sensor Networks

Abstract: We study the important problem of tracking moving targets in wireless sensor networks. We try to overcome the limitations of standard state of the art tracking methods based on continuous location tracking, i.e. the high energy dissipation and communication overhead imposed by the active participation of sensors in the tracking process and the low scalability, especially in sparse networks. Instead, our approach uses sensors in a passive way: they just record and judiciously spread information about observed target presence in their vicinity; this information is then used by the (powerful) tracking agent to locate the target by just following the traces left at sensors. Our protocol is greedy, local, distributed, energy efficient and very successful, in the sense that (as shown by extensive simulations) the tracking agent manages to quickly locate and follow the target; also, we achieve good trade-offs between the energy dissipation and latency.


The Anatomy of Mitos Web Search Engine

Abstract: Engineering a Web search engine offering effective and efficient information retrieval is a challenging task. This document presents our experiences from designing and developing a Web search engine offering a wide spectrum of functionalities and we report some interesting experimental results. A rather peculiar design choice of the engine is that its index is based on a DBMS, while some of the distinctive functionalities that are offered include advanced Greek language stemming, real time result clustering, and advanced link analysis techniques (also for spam page detection).


A Practical Attack on the MIFARE Classic

Abstract: The MIFARE Classic is the most widely used contactless smart card in the market. Its design and implementation details are kept secret by its manufacturer. This paper studies the architecture of the card and the communication protocol between card and reader. Then it gives a practical, low-cost, attack that recovers secret information from the memory of the card. Due to a weakness in the pseudo-random generator, we are able to recover the keystream generated by the CRYPTO1 stream cipher. We exploit the malleability of the stream cipher to read all memory blocks of the first sector of the card. Moreover, we are able to read any sector of the memory of the card, provided that we know one memory block within this sector. Finally, and perhaps more damaging, the same holds for modifying memory blocks.


The Abella Interactive Theorem Prover (System Description)

Abstract: Abella is an interactive system for reasoning about aspects of object languages that have been formally presented through recursive rules based on syntactic structure. Abella utilizes a two-level logic approach to specification and reasoning. One level is defined by a specification logic which supports a transparent encoding of structural semantics rules and also enables their execution. The second level, called the reasoning logic, embeds the specification logic and allows the development of proofs of properties about specifications. An important characteristic of both logics is that they exploit the lambda tree syntax approach to treating binding in object languages. Amongst other things, Abella has been used to prove normalizability properties of the lambda calculus, cut admissibility for a sequent calculus and type uniqueness and subject reduction properties. This paper discusses the logical foundations of Abella, outlines the style of theorem proving that it supports and finally describes some of its recent applications.


Tableau-based decision procedures for logics of strategic ability in multi-agent systems

Abstract: We develop an incremental tableau-based decision procedures for the Alternating-time temporal logic ATL and some of its variants. While running within the theoretically established complexity upper bound, we claim that our tableau is practically more efficient in the average case than other decision procedures for ATL known so far. Besides, the ease of its adaptation to variants of ATL demonstrates the flexibility of the proposed procedure.


Problem Solving and Complex Systems

Abstract: The observation and modeling of natural Complex Systems (CSs) like the human nervous system, the evolution or the weather, allows the definition of special abilities and models reusable to solve other problems. For instance, Genetic Algorithms or Ant Colony Optimizations are inspired from natural CSs to solve optimization problems. This paper proposes the use of ant-based systems to solve various problems with a non assessing approach. This means that solutions to some problem are not evaluated. They appear as resultant structures from the activity of the system. Problems are modeled with graphs and such structures are observed directly on these graphs. Problems of Multiple Sequences Alignment and Natural Language Processing are addressed with this approach.


Science mapping with asymmetrical paradigmatic proximity

Abstract: We propose a series of methods to represent the evolution of a field of science at different levels: namely micro, meso and macro levels. We use a previously introduced asymmetric measure of paradigmatic proximity between terms that enables us to extract structure from a large publications database. We apply our set of methods on a case study from the complex systems community through the mapping of more than 400 complex systems science concepts indexed from a database as large as several millions of journal papers. We will first summarize the main properties of our asymmetric proximity measure. Then we show how salient paradigmatic fields can be embedded into a 2-dimensional visualization into which the terms are plotted according to their relative specificity and generality index. This meso-level helps us producing macroscopic maps of the field of science studied featuring the former paradigmatic fields.