Optimization Approach for Detecting the Critical Data on a Database

Abstract: Through purposeful introduction of malicious transactions (tracking transactions) into randomly select nodes of a (database) graph, soiled and clean segments are identified. Soiled and clean measures corresponding those segments are then computed. These measures are used to repose the problem of critical database elements detection as an optimization problem over the graph. This method is universally applicable over a large class of graphs (including directed, weighted, disconnected, cyclic) that occur in several contexts of databases. A generalization argument is presented which extends the critical data problem to abstract settings.


Electronic Voting: the Devil is in the Details

Abstract: Observing electronic voting from an international point of view gives some perspective about its genesis and evolution. An analysis of the voting process through its cultural, ontological, legal and political dimensions explains the difficulty to normalize this process. It appears that international organizations are not capable to properly defend the fundamental rights of the citizens. The approach that was taken when DRE voting computers appeared seems to have reoccured with VVAT voting computers and the european e-poll project.


A Synthesizer Based on Frequency-Phase Analysis and Square Waves

Abstract: This article introduces an effective generalization of the polar flavor of the Fourier Theorem based on a new method of analysis. Under the premises of the new theory an ample class of functions become viable as bases, with the further advantage of using the same basis for analysis and reconstruction. In fact other tools, like the wavelets, admit specially built nonorthogonal bases but require different bases for analysis and reconstruction (biorthogonal and dual bases) and vectorial coordinates; this renders those systems unintuitive and computing intensive. As an example of the advantages of the new generalization of the Fourier Theorem, this paper introduces a novel method for the synthesis that is based on frequency-phase series of square waves (the equivalent of the polar Fourier Theorem but for nonorthogonal bases). The resulting synthesizer is very efficient needing only few components, frugal in terms of computing needs, and viable for many applications.


Phoneme recognition in TIMIT with BLSTM-CTC

Abstract: We compare the performance of a recurrent neural network with the best results published so far on phoneme recognition in the TIMIT database. These published results have been obtained with a combination of classifiers. However, in this paper we apply a single recurrent neural network to the same task. Our recurrent neural network attains an error rate of 24.6%. This result is not significantly different from that obtained by the other best methods, but they rely on a combination of classifiers for achieving comparable performance.


On the Expressive Power of Multiple Heads in CHR

Abstract: Constraint Handling Rules (CHR) is a committed-choice declarative language which has been originally designed for writing constraint solvers and which is nowadays a general purpose language. CHR programs consist of multi-headed guarded rules which allow to rewrite constraints into simpler ones until a solved form is reached. Many empirical evidences suggest that multiple heads augment the expressive power of the language, however no formal result in this direction has been proved, so far. In the first part of this paper we analyze the Turing completeness of CHR with respect to the underneath constraint theory. We prove that if the constraint theory is powerful enough then restricting to single head rules does not affect the Turing completeness of the language. On the other hand, differently from the case of the multi-headed language, the single head CHR language is not Turing powerful when the underlying signature (for the constraint theory) does not contain function symbols. In the second part we prove that, no matter which constraint theory is considered, under some reasonable assumptions it is not possible to encode the CHR language (with multi-headed rules) into a single headed language while preserving the semantics of the programs. We also show that, under some stronger assumptions, considering an increasing number of atoms in the head of a rule augments the expressive power of the language. These results provide a formal proof for the claim that multiple heads augment the expressive power of the CHR language.


A New Approach to Automated Epileptic Diagnosis Using EEG and Probabilistic Neural Network

Abstract: Epilepsy is one of the most common neurological disorders that greatly impair patient' daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of seizure (ictal) activities. Nowadays, there are many systems helping the neurologists to quickly find interesting segments of the lengthy signal by automatic seizure detection. However, we notice that it is very difficult, if not impossible, to obtain long-term EEG data with seizure activities for epilepsy patients in areas lack of medical resources and trained neurologists. Therefore, we propose to study automated epileptic diagnosis using interictal EEG data that is much easier to collect than ictal data. The authors are not aware of any report on automated EEG diagnostic system that can accurately distinguish patients' interictal EEG from the EEG of normal people. The research presented in this paper, therefore, aims to develop an automated diagnostic system that can use interictal EEG data to diagnose whether the person is epileptic. Such a system should also detect seizure activities for further investigation by doctors and potential patient monitoring. To develop such a system, we extract four classes of features from the EEG data and build a Probabilistic Neural Network (PNN) fed with these features. Leave-one-out cross-validation (LOO-CV) on a widely used epileptic-normal data set reflects an impressive 99.5% accuracy of our system on distinguishing normal people's EEG from patient's interictal EEG. We also find our system can be used in patient monitoring (seizure detection) and seizure focus localization, with 96.7% and 77.5% accuracy respectively on the data set.


Lecture notes on the lambda calculus

Abstract: This is a set of lecture notes that developed out of courses on the lambda calculus that I taught at the University of Ottawa in 2001 and at Dalhousie University in 2007 and 2013. Topics covered in these notes include the untyped lambda calculus, the Church-Rosser theorem, combinatory algebras, the simply-typed lambda calculus, the Curry-Howard isomorphism, weak and strong normalization, polymorphism, type inference, denotational semantics, complete partial orders, and the language PCF.


Stability and Throughput of Buffered Aloha with Backoff

Abstract: This paper studies the buffered Aloha with K-exponential backoff collision resolution algorithms. The buffered Aloha network is modeled as a multi-queue single-server system. We adopt a widely used approach in packet switching systems to decompose the multi-queue system into independent first-in-first-out (FIFO) queues, which are hinged together by the probability of success of head-of-line (HOL) packets. A unified method is devised to tackle the stability and throughput problems of K-exponential backoff with any cutoff phase K. For networks with a finite number of nodes, we show that the K-exponential backoff is stable if the retransmission factor is properly chosen from the stable region. The maximum stable throughput is derived and demonstrated via examples of geometric retransmission (K=1) and exponential backoff (K=infinity). For networks with an infinite number of nodes, we show that geometric retransmission is unstable, and the stable network throughput of exponential backoff can only be achieved at the cost of potential unbounded delay in each input queue. Furthermore, we address the stability issue of the systems at the undesired stable point. All analytical results presented in this paper are verified and confirmed by simulations.


Natural pseudo-distance and optimal matching between reduced size functions

Abstract: This paper studies the properties of a new lower bound for the natural pseudo-distance. The natural pseudo-distance is a dissimilarity measure between shapes, where a shape is viewed as a topological space endowed with a real-valued continuous function. Measuring dissimilarity amounts to minimizing the change in the functions due to the application of homeomorphisms between topological spaces, with respect to the $L_\infty$-norm. In order to obtain the lower bound, a suitable metric between size functions, called matching distance, is introduced. It compares size functions by solving an optimal matching problem between countable point sets. The matching distance is shown to be resistant to perturbations, implying that it is always smaller than the natural pseudo-distance. We also prove that the lower bound so obtained is sharp and cannot be improved by any other distance between size functions.


Isotropic PCA and Affine-Invariant Clustering

Abstract: We present a new algorithm for clustering points in R^n. The key property of the algorithm is that it is affine-invariant, i.e., it produces the same partition for any affine transformation of the input. It has strong guarantees when the input is drawn from a mixture model. For a mixture of two arbitrary Gaussians, the algorithm correctly classifies the sample assuming only that the two components are separable by a hyperplane, i.e., there exists a halfspace that contains most of one Gaussian and almost none of the other in probability mass. This is nearly the best possible, improving known results substantially. For k > 2 components, the algorithm requires only that there be some (k-1)-dimensional subspace in which the emoverlap in every direction is small. Here we define overlap to be the ratio of the following two quantities: 1) the average squared distance between a point and the mean of its component, and 2) the average squared distance between a point and the mean of the mixture. The main result may also be stated in the language of linear discriminant analysis: if the standard Fisher discriminant is small enough, labels are not needed to estimate the optimal subspace for projection. Our main tools are isotropic transformation, spectral projection and a simple reweighting technique. We call this combination isotropic PCA.


Matching Interdiction

Abstract: In the matching interdiction problem, we are given an undirected graph with weights and interdiction costs on the edges and seek to remove a subset of the edges constrained to some budget, such that the weight of a maximum weight matching in the remaining graph is minimized. In this work we introduce the matching interdiction problem and show that it is strongly NP-complete even when the input is restricted to simple, bipartite graphs with unit edge weights and unit interdiction costs. Furthermore, we present a pseudo-polynomial algorithm for solving the matching interdiction problem on graphs with bounded treewidth. The proposed algorithm extends the approach that is typically used for the creation of efficient algorithms on graphs with bounded treewidth to interdiction problems.


Respect My Authority! HITS Without Hyperlinks, Utilizing Cluster-Based Language Models

Abstract: We present an approach to improving the precision of an initial document ranking wherein we utilize cluster information within a graph-based framework. The main idea is to perform re-ranking based on centrality within bipartite graphs of documents (on one side) and clusters (on the other side), on the premise that these are mutually reinforcing entities. Links between entities are created via consideration of language models induced from them. We find that our cluster-document graphs give rise to much better retrieval performance than previously proposed document-only graphs do. For example, authority-based re-ranking of documents via a HITS-style cluster-based approach outperforms a previously-proposed PageRank-inspired algorithm applied to solely-document graphs. Moreover, we also show that computing authority scores for clusters constitutes an effective method for identifying clusters containing a large percentage of relevant documents.


Combinatorial invariants for graph isomorphism problem

Abstract: Presented approach in polynomial time calculates large number of invariants for each vertex, which won't change with graph isomorphism and should fully determine the graph. For example numbers of closed paths of length k for given starting vertex, what can be though as the diagonal terms of k-th power of the adjacency matrix. For k=2 we would get degree of verities invariant, higher describes local topology deeper. Now if two graphs are isomorphic, they have the same set of such vectors of invariants - we can sort theses vectors lexicographically and compare them. If they agree, permutations from sorting allow to reconstruct the isomorphism. I'm presenting arguments that these invariants should fully determine the graph, but unfortunately I can't prove it in this moment. This approach can give hope, that maybe P=NP - instead of checking all instances, we should make arithmetics on these large numbers.


Constructions for Clumps Statistics

Abstract: We consider a component of the word statistics known as clump; starting from a finite set of words, clumps are maximal overlapping sets of these occurrences. This parameter has first been studied by Schbath with the aim of counting the number of occurrences of words in random texts. Later work with similar probabilistic approach used the Chen-Stein approximation for a compound Poisson distribution, where the number of clumps follows a law close to Poisson. Presently there is no combinatorial counterpart to this approach, and we fill the gap here. We emphasize the fact that, in contrast with the probabilistic approach which only provides asymptotic results, the combinatorial approach provides exact results that are useful when considering short sequences.


The privacy implications of Bluetooth

Abstract: A substantial amount of research, as well as media hype, has surrounded RFID technology and its privacy implications. Currently, researchers and the media focus on the privacy threats posed by RFID, while consumer groups choose to boycott products bearing RFID tags. At the same, however, a very similar technology has quietly become part of our everyday lives: Bluetooth. In this paper we highlight the fact that Bluetooth is a widespread technology that has real privacy implications. Furthermore, we explore the applicability of RFID-based solutions to address these privacy implications.


From formal proofs to mathematical proofs: a safe, incremental way for building in first-order decision procedures

Abstract: We investigate here a new version of the Calculus of Inductive Constructions (CIC) on which the proof assistant Coq is based: the Calculus of Congruent Inductive Constructions, which truly extends CIC by building in arbitrary first-order decision procedures: deduction is still in charge of the CIC kernel, while computation is outsourced to dedicated first-order decision procedures that can be taken from the shelves provided they deliver a proof certificate. The soundness of the whole system becomes an incremental property following from the soundness of the certificate checkers and that of the kernel. A detailed example shows that the resulting style of proofs becomes closer to that of the working mathematician.


On the metric distortion of nearest-neighbour graphs on random point sets

Abstract: We study the graph constructed on a Poisson point process in $d$ dimensions by connecting each point to the $k$ points nearest to it. This graph a.s. has an infinite cluster if $k > k_c(d)$ where $k_c(d)$, known as the critical value, depends only on the dimension $d$. This paper presents an improved upper bound of 188 on the value of $k_c(2)$. We also show that if $k \geq 188$ the infinite cluster of $\NN(2,k)$ has an infinite subset of points with the property that the distance along the edges of the graphs between these points is at most a constant multiplicative factor larger than their Euclidean distance. Finally we discuss in detail the relevance of our results to the study of multi-hop wireless sensor networks.


Towards Usage-based Impact Metrics: - First Results from the MESUR Project

Abstract: Scholarly usage data holds the potential to be used as a tool to study the dynamics of scholarship in real time, and to form the basis for the definition of novel metrics of scholarly impact. However, the formal groundwork to reliably and validly exploit usage data is lacking, and the exact nature, meaning and applicability of usage-based metrics is poorly understood. The MESUR project funded by the Andrew W. Mellon Foundation constitutes a systematic effort to define, validate and cross-validate a range of usage-based metrics of scholarly impact. MESUR has collected nearly 1 billion usage events as well as all associated bibliographic and citation data from significant publishers, aggregators and institutional consortia to construct a large-scale usage data reference set. This paper describes some major challenges related to aggregating and processing usage data, and discusses preliminary results obtained from analyzing the MESUR reference data set. The results confirm the intrinsic value of scholarly usage data, and support the feasibility of reliable and valid usage-based metrics of scholarly impact.


Service Cloaking and Authentication at Data Link Layer

Abstract: This paper discusses that there is significant benefit in providing stronger security at lower layers of the network stack for hosts connected to a network. It claims to reduce the attack vulnerability of a networked host by providing security mechanisms in a programmable Network Interface Card (NIC). Dynamic access control mechanisms are implemented in hardware to restrict access to the services provided, only to authenticated hosts. This reduces server vulnerability to various layer 2 attacks. Also the services will be immune to zero-day vulnerabilities due to the minimal code execution paths. To this end, it presents architecture and implementation details of a programmable network interface card equipped with these measures. It works alongside, and augments, existing security protocols making deployment practical.


Link Enhancer for Vehicular Wireless ATM Communications

Abstract: Majority of the applications used in defense are voice, video and data oriented and has strict QoS requirements. One of the technologies that enabled this is Asynchronous Transfer Mode (ATM) networking. Traditional ATM networks are wired networks. But Tactical networks are meant to be mobile and this necessitates the use of radio relays for Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communications. ATM networks assume a physical link layer BER of 10^-9 or better because of the availability of reliable media like optical fiber links. But this assumption is no longer valid when ATM switches are connected through radio relay where error rates are in the rage of 10^-3. This paper presents the architecture of a Link Enhancer meant to improve the Bit Error Rate of the Wireless links used for V2I and V2V communications from 1 in 10^4 to 1 in 10^8


Multiple Random Oracles Are Better Than One

Abstract: We study the problem of learning k-juntas given access to examples drawn from a number of different product distributions. Thus we wish to learn a function f : {-1,1}^n -> {-1,1} that depends on k (unknown) coordinates. While the best known algorithms for the general problem of learning a k-junta require running time of n^k * poly(n,2^k), we show that given access to k different product distributions with biases separated by \gamma>0, the functions may be learned in time poly(n,2^k,\gamma^{-k}). More generally, given access to t <= k different product distributions, the functions may be learned in time n^{k/t} * poly(n,2^k,\gamma^{-k}). Our techniques involve novel results in Fourier analysis relating Fourier expansions with respect to different biases and a generalization of Russo's formula.


An $\tilde{O}(n^{2.5})$-Time Algorithm for Online Topological Ordering

Abstract: We present an $\tilde{O}(n^{2.5})$-time algorithm for maintaining the topological order of a directed acyclic graph with $n$ vertices while inserting $m$ edges.


Image Processing in Optical Guidance for Autonomous Landing of Lunar Probe

Abstract: Because of the communication delay between earth and moon, the GNC technology of lunar probe is becoming more important than ever. Current navigation technology is not able to provide precise motion estimation for probe landing control system Computer vision offers a new approach to solve this problem. In this paper, author introduces an image process algorithm of computer vision navigation for autonomous landing of lunar probe. The purpose of the algorithm is to detect and track feature points which are factors of navigation. Firstly, fixation areas are detected as sub-images and matched. Secondly, feature points are extracted from sub-images and tracked. Computer simulation demonstrates the result of algorithm takes less computation and fulfils requests of navigation algorithm.


Hardware In The Loop Simulator in UAV Rapid Development Life Cycle

Abstract: Field trial is very critical and high risk in autonomous UAV development life cycle. Hardware in the loop (HIL) simulation is a computer simulation that has the ability to simulate UAV flight characteristic, sensor modeling and actuator modeling while communicating in real time with the UAV autopilot hardware. HIL simulation can be used to test the UAV autopilot hardware reliability, test the closed loop performance of the overall system and tuning the control parameter. By rigorous testing in the HIL simulator, the risk in the field trial can be minimized.


Effects of Leaders Position and Shape on Aerodynamic Performances of V Flight Formation

Abstract: The influences of the leader in a group of V flight formation are dealt with. The investigation is focused on the effect of its position and shape on aerodynamics performances of a given V flight formation. Vortices generated the wing tip of the leader moves downstream forming a pair of opposite rotating line vortices. These vortices are generally undesirable because they create a downwash that increases the induced drag on leaders wing. However, this downwash is also accompanied by an upwash that can beneficial to the followers wing flying behind the leaders one, namely a favorable lift for the followers wing. How much contributions of the leaders wing to the followers wing in the V formation flight is determined by the strength of tip vortices generated by the leaders wing which is influenced by its position and shape including incidence angle, dihedral angle, aspect ratio and taper ratio. The prediction of aerodynamic performances of the V flight formation including lift, drag and moment coefficients is numerically performed by solving Navier Stokes equations with k e turbulence model. The computational domain is defined with multiblock topology to capture the complex geometry arrangement of the V flight formation.


Automated Flight Test and System Identification for Rotary Wing Small Aerial Platform using Frequency Responses Analysis

Abstract: This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency swept is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency swept is guaranteed to produce high quality data for system identification. Beside that we can set the safety parameter during the flight test (maximum roll or pitch value, minimum altitude, etc) so the safety of the whole flight test is guaranteed. This autopilot for automated flight test will be tested using hardware in the loop simulator for hover flight condition.


Virtual Reality Simulation of Fire Fighting Robot Dynamic and Motion

Abstract: This paper presents one approach in designing a Fire Fighting Robot which has been contested annually in a robotic student competition in many countries following the rules initiated at the Trinity College. The approach makes use of computer simulation and animation in a virtual reality environment. In the simulation, the amount of time, starting from home until the flame is destroyed, can be confirmed. The efficacy of algorithms and parameter values employed can be easily evaluated. Rather than spending time building the real robot in a trial and error fashion, now students can explore more variation of algorithm, parameter and sensor-actuator configuration in the early stage of design. Besides providing additional excitement during learning process and enhancing students understanding to the engineering aspects of the design, this approach could become a useful tool to increase the chance of winning the contest.


Heading Lock Maneuver Testing of Autonomous Underwater Vehicle

Abstract: In recent years, Autonomous Underwater Vehicle (UAV) research and development at Bandung Institute of Technology in Indonesia has achieved the testing stage in the field. This testing was still being classified as the early testing, since some of the preliminary tests were carried out in the scale of the laboratory. The paper would discuss the laboratory test and several tests that were done in the field. Discussions were stressed in the procedure and the aim that will be achieved, along with several early results. The testing was carried out in the lake with the area around 8300 Ha and the maximum depth of 50 meters. The location of the testing was chosen with consideration of minimizing the effect of the current and the wave, as well as the location that was not too far from the Laboratory. The type of testing that will be discussed in paper was Heading Lock Maneuver Testing. The vehicle was tested to move with a certain cruising speed, afterwards it was commanded by an arbitrarily selected heading direction. The response and the behavior of the vehicle were recorded as the data produced by the testing.


Development of Architectures for Internet Telerobotics Systems

Abstract: This paper presents our experience in developing and implementing Internet telerobotics system. Internet telerobotics system refers to a robot system controlled and monitored remotely through the Internet. A robot manipulator with five degrees of freedom, called Mentor, is employed. Client-server architecture is chosen as a platform for our Internet telerobotics system. Three generations of telerobotics systems have evolved in this research. The first generation was based on CGI and two tiered architecture, where a client presents a Graphical User Interface to the user, and utilizes the user's data entry and actions to perform requests to robot server running on a different machine. The second generation was developed using Java. We also employ Java 3D for creating and manipulating 3D geometry of manipulator links and for constructing the structures used in rendering that geometry, resulting in 3D robot movement simulation presented to the users(clients) through their web browser. Recent development in our Internet telerobotics includes object recognition through image captured by a camera, which poses challenging problem, given the undeterministic latency of the Internet. The third generation is centered around the use of CORBA for development platform of distributed internet telerobotics system, aimed at distributing task of telerobotics system.


Unmanned Aerial Vehicle Instrumentation for Rapid Aerial Photo System

Abstract: This research will proposed a new kind of relatively low cost autonomous UAV that will enable farmers to make just in time mosaics of aerial photo of their crop. These mosaics of aerial photo should be able to be produced with relatively low cost and within the 24 hours of acquisition constraint. The autonomous UAV will be equipped with payload management system specifically developed for rapid aerial mapping. As mentioned before turn around time is the key factor, so accuracy is not the main focus (not orthorectified aerial mapping). This system will also be equipped with special software to post process the aerial photos to produce the mosaic aerial photo map


First Principle Approach to Modeling of Small Scale Helicopter

Abstract: The establishment of global helicopter linear model is very precious and useful for the design of the linear control laws, since it is never afforded in the published literatures. In the first principle approach, the mathematical model was developed using basic helicopter theory accounting for particular characteristic of the miniature helicopter. No formal system identification procedures are required for the proposed model structure. The relevant published literatures however did not present the linear models required for the design of linear control laws. The paper presents a step by step development of linear model for small scale helicopter based on first-principle approach. Beyond the previous work in literatures, the calculation of the stability derivatives is presented in detail. A computer program is used to solve the equilibrium conditions and then calculate the change in aerodynamics forces and moments due to the change in each degree of freedom and control input. The detail derivation allows the comprehensive analysis of relative dominance of vehicle states and input variables to force and moment components. Hence it facilitates the development of minimum complexity small scale helicopter dynamics model.


Optimal Tracking Controller Design for a Small Scale Helicopter

Abstract: A model helicopter is more difficult to control than its full scale counterparts. This is due to its greater sensitivity to control inputs and disturbances as well as higher bandwidth of dynamics. This works is focused on designing practical tracking controller for a small scale helicopter following predefined trajectories. A tracking controller based on optimal control theory is synthesized as part of the development of an autonomous helicopter. Some issues in regards to control constraints are addressed. The weighting between state tracking performance and control power expenditure is analyzed. Overall performance of the control design is evaluated based on its time domain histories of trajectories as well as control inputs.


Minimum-energy broadcast in random-grid ad-hoc networks: approximation and distributed algorithms

Abstract: The Min Energy broadcast problem consists in assigning transmission ranges to the nodes of an ad-hoc network in order to guarantee a directed spanning tree from a given source node and, at the same time, to minimize the energy consumption (i.e. the energy cost) yielded by the range assignment. Min energy broadcast is known to be NP-hard. We consider random-grid networks where nodes are chosen independently at random from the $n$ points of a $\sqrt n \times \sqrt n$ square grid in the plane. The probability of the existence of a node at a given point of the grid does depend on that point, that is, the probability distribution can be non-uniform. By using information-theoretic arguments, we prove a lower bound $(1-\epsilon) \frac n{\pi}$ on the energy cost of any feasible solution for this problem. Then, we provide an efficient solution of energy cost not larger than $1.1204 \frac n{\pi}$. Finally, we present a fully-distributed protocol that constructs a broadcast range assignment of energy cost not larger than $8n$,thus still yielding constant approximation. The energy load is well balanced and, at the same time, the work complexity (i.e. the energy due to all message transmissions of the protocol) is asymptotically optimal. The completion time of the protocol is only an $O(\log n)$ factor slower than the optimum. The approximation quality of our distributed solution is also experimentally evaluated. All bounds hold with probability at least $1-1/n^{\Theta(1)}$.


Reasoning in Abella about Structural Operational Semantics Specifications

Abstract: The approach to reasoning about structural operational semantics style specifications supported by the Abella system is discussed. This approach uses lambda tree syntax to treat object language binding and encodes binding related properties in generic judgments. Further, object language specifications are embedded directly into the reasoning framework through recursive definitions. The treatment of binding via generic judgments implicitly enforces distinctness and atomicity in the names used for bound variables. These properties must, however, be made explicit in reasoning tasks. This objective can be achieved by allowing recursive definitions to also specify generic properties of atomic predicates. The utility of these various logical features in the Abella system is demonstrated through actual reasoning tasks. Brief comparisons with a few other logic based approaches are also made.


Time Dependent Contraction Hierarchies -- Basic Algorithmic Ideas

Abstract: Contraction hierarchies are a simple hierarchical routing technique that has proved extremely efficient for static road networks. We explain how to generalize them to networks with time-dependent edge weights. This is the first hierarchical speedup technique for time-dependent routing that allows bidirectional query algorithms.


Energy and Time Efficient Scheduling of Tasks with Dependencies on Asymmetric Multiprocessors

Abstract: In this work we study the problem of scheduling tasks with dependencies in multiprocessor architectures where processors have different speeds. We present the preemptive algorithm "Save-Energy" that given a schedule of tasks it post processes it to improve the energy efficiency without any deterioration of the makespan. In terms of time efficiency, we show that preemptive scheduling in an asymmetric system can achieve the same or better optimal makespan than in a symmetric system. Motivited by real multiprocessor systems, we investigate architectures that exhibit limited asymmetry: there are two essentially different speeds. Interestingly, this special case has not been studied in the field of parallel computing and scheduling theory; only the general case was studied where processors have $K$ essentially different speeds. We present the non-preemptive algorithm ``Remnants'' that achieves almost optimal makespan. We provide a refined analysis of a recent scheduling method. Based on this analysis, we specialize the scheduling policy and provide an algorithm of $(3 + o(1))$ expected approximation factor. Note that this improves the previous best factor (6 for two speeds). We believe that our work will convince researchers to revisit this well studied scheduling problem for these simple, yet realistic, asymmetric multiprocessor architectures.


Logic Mining Using Neural Networks

Abstract: Knowledge could be gained from experts, specialists in the area of interest, or it can be gained by induction from sets of data. Automatic induction of knowledge from data sets, usually stored in large databases, is called data mining. Data mining methods are important in the management of complex systems. There are many technologies available to data mining practitioners, including Artificial Neural Networks, Regression, and Decision Trees. Neural networks have been successfully applied in wide range of supervised and unsupervised learning applications. Neural network methods are not commonly used for data mining tasks, because they often produce incomprehensible models, and require long training times. One way in which the collective properties of a neural network may be used to implement a computational task is by way of the concept of energy minimization. The Hopfield network is well-known example of such an approach. The Hopfield network is useful as content addressable memory or an analog computer for solving combinatorial-type optimization problems. Wan Abdullah [1] proposed a method of doing logic programming on a Hopfield neural network. Optimization of logical inconsistency is carried out by the network after the connection strengths are defined from the logic program; the network relaxes to neural states corresponding to a valid interpretation. In this article, we describe how Hopfield network is able to induce logical rules from large database by using reverse analysis method: given the values of the connections of a network, we can hope to know what logical rules are entrenched in the database.


Grainy Numbers

Abstract: Grainy numbers are defined as tuples of bits. They form a lattice where the meet and the join operations are an addition and a multiplication. They may be substituted for the real numbers in the definition of fuzzy sets. The aim is to propose an alternative negation for the complement that we'll call supplement.


Logic Learning in Hopfield Networks

Abstract: Synaptic weights for neurons in logic programming can be calculated either by using Hebbian learning or by Wan Abdullah's method. In other words, Hebbian learning for governing events corresponding to some respective program clauses is equivalent with learning using Wan Abdullah's method for the same respective program clauses. In this paper we will evaluate experimentally the equivalence between these two types of learning through computer simulations.


Design and Implementation of a Tracer Driver: Easy and Efficient Dynamic Analyses of Constraint Logic Programs

Abstract: Tracers provide users with useful information about program executions. In this article, we propose a ``tracer driver''. From a single tracer, it provides a powerful front-end enabling multiple dynamic analysis tools to be easily implemented, while limiting the overhead of the trace generation. The relevant execution events are specified by flexible event patterns and a large variety of trace data can be given either systematically or ``on demand''. The proposed tracer driver has been designed in the context of constraint logic programming; experiments have been made within GNU-Prolog. Execution views provided by existing tools have been easily emulated with a negligible overhead. Experimental measures show that the flexibility and power of the described architecture lead to good performance. The tracer driver overhead is inversely proportional to the average time between two traced events. Whereas the principles of the tracer driver are independent of the traced programming language, it is best suited for high-level languages, such as constraint logic programming, where each traced execution event encompasses numerous low-level execution steps. Furthermore, constraint logic programming is especially hard to debug. The current environments do not provide all the useful dynamic analysis tools. They can significantly benefit from our tracer driver which enables dynamic analyses to be integrated at a very low cost.


Sketching and Streaming Entropy via Approximation Theory

Abstract: We conclude a sequence of work by giving near-optimal sketching and streaming algorithms for estimating Shannon entropy in the most general streaming model, with arbitrary insertions and deletions. This improves on prior results that obtain suboptimal space bounds in the general model, and near-optimal bounds in the insertion-only model without sketching. Our high-level approach is simple: we give algorithms to estimate Renyi and Tsallis entropy, and use them to extrapolate an estimate of Shannon entropy. The accuracy of our estimates is proven using approximation theory arguments and extremal properties of Chebyshev polynomials, a technique which may be useful for other problems. Our work also yields the best-known and near-optimal additive approximations for entropy, and hence also for conditional entropy and mutual information.


On Computing the Shadows and Slices of Polytopes

Abstract: We study the complexity of computing the projection of an arbitrary $d$-polytope along $k$ orthogonal vectors for various input and output forms. We show that if $d$ and $k$ are part of the input (i.e. not a constant) and we are interested in output-sensitive algorithms, then in most forms the problem is equivalent to enumerating vertices of polytopes, except in two where it is NP-hard. In two other forms the problem is trivial. We also review the complexity of computing projections when the projection directions are in some sense non-degenerate. For full-dimensional polytopes containing origin in the interior, projection is an operation dual to intersecting the polytope with a suitable linear subspace and so the results in this paper can be dualized by interchanging vertices with facets and projection with intersection. To compare the complexity of projection and vertex enumeration, we define new complexity classes based on the complexity of Vertex Enumeration.


Practical Automated Partial Verification of Multi-Paradigm Real-Time Models

Abstract: This article introduces a fully automated verification technique that permits to analyze real-time systems described using a continuous notion of time and a mixture of operational (i.e., automata-based) and descriptive (i.e., logic-based) formalisms. The technique relies on the reduction, under reasonable assumptions, of the continuous-time verification problem to its discrete-time counterpart. This reconciles in a viable and effective way the dense/discrete and operational/descriptive dichotomies that are often encountered in practice when it comes to specifying and analyzing complex critical systems. The article investigates the applicability of the technique through a significant example centered on a communication protocol. More precisely, concurrent runs of the protocol are formalized by parallel instances of a Timed Automaton, while the synchronization rules between these instances are specified through Metric Temporal Logic formulas, thus creating a multi-paradigm model. Verification tests run on this model using a bounded validity checker implementing the technique show consistent results and interesting performances.


Development of a peristaltic micropump for bio-medical applications based on mini LIPCA

Abstract: This paper presents the design, fabrication, and experimental characterization of a peristaltic micropump. The micropump is composed of two layers fabricated from polydimethylsiloxane (PDMS) material. The first layer has a rectangular channel and two valve seals. Three rectangular mini lightweight piezo-composite actuators are integrated in the second layer, and used as actuation parts. Two layers are bonded, and covered by two polymethyl methacrylate (PMMA) plates, which help increase the stiffness of the micropump. A maximum flow rate of 900 mokroliter per min and a maximum backpressure of 1.8 kPa are recorded when water is used as pump liquid. We measured the power consumption of the micropump. The micropump is found to be a promising candidate for bio-medical application due to its bio-compatibility, portability, bidirectionality, and simple effective design.


Eppstein's bound on intersecting triangles revisited

Abstract: Let S be a set of n points in the plane, and let T be a set of m triangles with vertices in S. Then there exists a point in the plane contained in Omega(m^3 / (n^6 log^2 n)) triangles of T. Eppstein (1993) gave a proof of this claim, but there is a problem with his proof. Here we provide a correct proof by slightly modifying Eppstein's argument.


Approximate Equilibria in Games with Few Players

Abstract: We study the problem of computing approximate Nash equilibria (epsilon-Nash equilibria) in normal form games, where the number of players is a small constant. We consider the approach of looking for solutions with constant support size. It is known from recent work that in the 2-player case, a 1/2-Nash equilibrium can be easily found, but in general one cannot achieve a smaller value of epsilon than 1/2. In this paper we extend those results to the k-player case, and find that epsilon = 1-1/k is feasible, but cannot be improved upon. We show how stronger results for the 2-player case may be used in order to slightly improve upon the epsilon = 1-1/k obtained in the k-player case.


The Complexity of Coverage

Abstract: We study the problem of generating a test sequence that achieves maximal coverage for a reactive system under test. We formulate the problem as a repeated game between the tester and the system, where the system state space is partitioned according to some coverage criterion and the objective of the tester is to maximize the set of partitions (or coverage goals) visited during the game. We show the complexity of the maximal coverage problem for non-deterministic systems is PSPACE-complete, but is NP-complete for deterministic systems. For the special case of non-deterministic systems with a re-initializing ``reset'' action, which represent running a new test input on a re-initialized system, we show that the complexity is again co-NP-complete. Our proof technique for reset games uses randomized testing strategies that circumvent the exponentially large memory requirement in the deterministic case.


Strategy Improvement for Concurrent Safety Games

Abstract: We consider concurrent games played on graphs. At every round of the game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety objective: ``stay forever in a set F of states'', and its dual, the reachability objective, ``reach a set R of states''. We present in this paper a strategy improvement algorithm for computing the value of a concurrent safety game, that is, the maximal probability with which player 1 can enforce the safety objective. The algorithm yields a sequence of player-1 strategies which ensure probabilities of winning that converge monotonically to the value of the safety game. The significance of the result is twofold. First, while strategy improvement algorithms were known for Markov decision processes and turn-based games, as well as for concurrent reachability games, this is the first strategy improvement algorithm for concurrent safety games. Second, and most importantly, the improvement algorithm provides a way to approximate the value of a concurrent safety game from below (the known value-iteration algorithms approximate the value from above). Thus, when used together with value-iteration algorithms, or with strategy improvement algorithms for reachability games, our algorithm leads to the first practical algorithm for computing converging upper and lower bounds for the value of reachability and safety games.


Data linkage algebra, data linkage dynamics, and priority rewriting

Abstract: We introduce an algebra of data linkages. Data linkages are intended for modelling the states of computations in which dynamic data structures are involved. We present a simple model of computation in which states of computations are modelled as data linkages and state changes take place by means of certain actions. We describe the state changes and replies that result from performing those actions by means of a term rewriting system with rule priorities. The model in question is an upgrade of molecular dynamics. The upgrading is mainly concerned with the features to deal with values and the features to reclaim garbage.


Feature Unification in TAG Derivation Trees

Abstract: The derivation trees of a tree adjoining grammar provide a first insight into the sentence semantics, and are thus prime targets for generation systems. We define a formalism, feature-based regular tree grammars, and a translation from feature based tree adjoining grammars into this new formalism. The translation preserves the derivation structures of the original grammar, and accounts for feature unification.


\'Etude de performance des syst\`emes de d\'ecouverte de ressources

Abstract: The Desktop Grid offers solutions to overcome several challenges and to answer increasingly needs of scientific computing. This technology consists mainly in exploiting PC resources, geographically dispersed, to treat time consuming applications and/or important storage capacity requiring applications. However, as resources number increases, the need for scalability, self-organisation, dynamic reconfiguration, decentralization and performance becomes more and more essential. In this context, this paper evaluates the scalability and performance of P2P tools for registering and discovering services (Publish/Subscribe systems). Three protocols are used in this purpose: Bonjour, Avahi and Pastry. We have studied the behaviour of these protocols related to two criteria: the elapsed time for registrations services and the needed time to discover new services.


Fast Density Codes for Image Data

Abstract: Recently, a new method for encoding data sets in the form of "Density Codes" was proposed in the literature (Courrieu, 2006). This method allows to compare sets of points belonging to every multidimensional space, and to build shape spaces invariant to a wide variety of affine and non-affine transformations. However, this general method does not take advantage of the special properties of image data, resulting in a quite slow encoding process that makes this tool practically unusable for processing large image databases with conventional computers. This paper proposes a very simple variant of the density code method that directly works on the image function, which is thousands times faster than the original Parzen window based method, without loss of its useful properties.


Comment - Practical Data Protection

Abstract: Recently, Rawat and Saxena proposed a method for protecting data using ``Disclaimer Statement''. This paper presents some issues and several flaws in their proposal.


Combining geometry and combinatorics: A unified approach to sparse signal recovery

Abstract: There are two main algorithmic approaches to sparse signal recovery: geometric and combinatorial. The geometric approach starts with a geometric constraint on the measurement matrix and then uses linear programming to decode information about the signal from its measurements. The combinatorial approach constructs the measurement matrix and a combinatorial decoding algorithm to match. We present a unified approach to these two classes of sparse signal recovery algorithms. The unifying elements are the adjacency matrices of high-quality unbalanced expanders. We generalize the notion of Restricted Isometry Property (RIP), crucial to compressed sensing results for signal recovery, from the Euclidean norm to the l_p norm for p about 1, and then show that unbalanced expanders are essentially equivalent to RIP-p matrices. From known deterministic constructions for such matrices, we obtain new deterministic measurement matrix constructions and algorithms for signal recovery which, compared to previous deterministic algorithms, are superior in either the number of measurements or in noise tolerance.


Introduction to Relational Networks for Classification

Abstract: The use of computational intelligence techniques for classification has been used in numerous applications. This paper compares the use of a Multi Layer Perceptron Neural Network and a new Relational Network on classifying the HIV status of women at ante-natal clinics. The paper discusses the architecture of the relational network and its merits compared to a neural network and most other computational intelligence classifiers. Results gathered from the study indicate comparable classification accuracies as well as revealed relationships between data features in the classification data. Much higher classification accuracies are recommended for future research in the area of HIV classification as well as missing data estimation.


Intelligent Unmanned Explorer for Deep Space Exploration

Abstract: asteroids or comets have received remarkable attention in the world. In small body explorations, especially, detailed in-situ surface exploration by tiny rover is one of effective and fruitful means and is expected to make strong contributions towards scientific studies. JAXA ISAS is promoting MUSES C mission, which is the worlds first sample and return attempt to or from the near earth asteroid. Hayabusa spacecraft in MUSES C mission took the tiny rover, which was expected to perform the in-situ surface exploration by hopping. This paper describes the system design, mobility and intelligence of the developed unmanned explorer. This paper also presents the ground experimental results and the flight results.


An Affine-invariant Time-dependent Triangulation of Spatio-temporal Data

Abstract: In the geometric data model for spatio-temporal data, introduced by Chomicki and Revesz, spatio-temporal data are modelled as a finite collection of triangles that are transformed by time-dependent affinities of the plane. To facilitate querying and animation of spatio-temporal data, we present a normal form for data in the geometric data model. We propose an algorithm for constructing this normal form via a spatio-temporal triangulation of geometric data objects. This triangulation algorithm generates new geometric data objects that partition the given objects both in space and in time. A particular property of the proposed partition is that it is invariant under time-dependent affine transformations, and hence independent of the particular choice of coordinate system used to describe he spatio-temporal data in. We can show that our algorithm works correctly and has a polynomial time complexity (of reasonably low degree in the number of input triangles and the maximal degree of the polynomial functions that describe the transformation functions). We also discuss several possible applications of this spatio-temporal triangulation.


The Effect of Structural Diversity of an Ensemble of Classifiers on Classification Accuracy

Abstract: This paper aims to showcase the measure of structural diversity of an ensemble of 9 classifiers and then map a relationship between this structural diversity and accuracy. The structural diversity was induced by having different architectures or structures of the classifiers The Genetical Algorithms (GA) were used to derive the relationship between diversity and the classification accuracy by evolving the classifiers and then picking 9 classifiers out on an ensemble of 60 classifiers. It was found that as the ensemble became diverse the accuracy improved. However at a certain diversity measure the accuracy began to drop. The Kohavi-Wolpert variance method is used to measure the diversity of the ensemble. A method of voting is used to aggregate the results from each classifier. The lowest error was observed at a diversity measure of 0.16 with a mean square error of 0.274, when taking 0.2024 as maximum diversity measured. The parameters that were varied were: the number of hidden nodes, learning rate and the activation function.


Lattice Problems, Gauge Functions and Parameterized Algorithms

Abstract: Given a k-dimensional subspace M\subseteq \R^n and a full rank integer lattice L\subseteq \R^n, the \emph{subspace avoiding problem} SAP is to find a shortest vector in L\setminus M. Treating k as a parameter, we obtain new parameterized approximation and exact algorithms for SAP based on the AKS sieving technique. More precisely, we give a randomized $(1+\epsilon)$-approximation algorithm for parameterized SAP that runs in time 2^{O(n)}.(1/\epsilon)^k, where the parameter k is the dimension of the subspace M. Thus, we obtain a 2^{O(n)} time algorithm for \epsilon=2^{-O(n/k)}. We also give a 2^{O(n+k\log k)} exact algorithm for the parameterized SAP for any \ell_p norm. Several of our algorithms work for all gauge functions as metric with some natural restrictions, in particular for all \ell_p norms. We also prove an \Omega(2^n) lower bound on the query complexity of AKS sieving based exact algorithms for SVP that accesses the gauge function as oracle.


Study of improving nano-contouring performance by employing cross-coupling controller

Abstract: For the tracking stage path planning, we design a two-axis cross-coupling control system which uses the PI controller to compensate the contour error between axes. In this paper, the stage adoptive is designed by our laboratory (Precision Machine Center of National Formosa University). The cross-coupling controller calculates the actuating signal of each axis by combining multi-axes position error. Hence, the cross-coupling controller improves the stage tracking ability and decreases the contour error. The experiments show excellent stage motion. This finding confirms that the proposed method is a powerful and efficient tool for improving stage tracking ability. Also found were the stages tracking to minimize contour error of two types circular to approximately 25nm.


The Numerical Control Design for a Pair of Dubins Vehicles

Abstract: In this paper, a model of a pair of Dubins vehicles is considered. The vehicles move from an initial position and orientation to final position and orientation. A long the motion, the two vehicles are not allowed to collide however the two vehicles cant to far each other. The optimal control of the vehicle is found using the Pontryagins Maximum Principle (PMP). This PMP leads to a Hamiltonian system consisting of a system of differential equation and its adjoint. The originally differential equation has initial and final condition but the adjoint system doesn't have one. The classical difficulty is solved numerically by the greatest gradient descent method. Some simulation results are presented in this paper.


Simulation of Dynamic Yaw Stability Derivatives of a Bird Using CFD

Abstract: Simulation results on dynamic yaw stability derivatives of a gull bird by means of computational fluid dynamics are presented. Two different kinds of motions are used for determining the dynamic yaw stability derivatives CNr and CNbeta . Concerning the first one, simple lateral translation and yaw rotary motions in yaw are considered. The second one consists of combined motions. To determine dynamic yaw stability derivatives of the bird, the simulation of an unsteady flow with a bird model showing a harmonic motion is performed. The unsteady flow solution for each time step is obtained by solving unsteady Euler equations based on a finite volume approach for a smaller reduced frequency. Then, an evaluation of unsteady forces and moments for one cycle is conducted using harmonic Fourier analysis. The results on the dynamic yaw stability derivatives for both simulations of the model motion show a good agreement.


Wavelet Based Iterative Learning Control with Fuzzy PD Feedback for Position Tracking of A Pneumatic Servo System

Abstract: In this paper, a wavelet-based iterative learning control (WILC) scheme with Fuzzy PD feedback is presented for a pneumatic control system with nonsmooth nonlinearities and uncertain parameters. The wavelet transform is employed to extract the learnable dynamics from measured output signal before it can be used to update the control profile. The wavelet transform is adopted to decompose the original signal into many low-resolution signals that contain the learnable and unlearnable parts. The desired control profile is then compared with the learnable part of the transformed signal. Thus, the effects from unlearnable dynamics on the controlled system can be attenuated by a Fuzzy PD feedback controller. As for the rules of Fuzzy PD controller in the feedback loop, a genetic algorithm (GA) is employed to search for the inference rules of optimization. A proportional-valve controlled pneumatic cylinder actuator system is used as the control target for simulation. Simulation results have shown a much-improved positiontracking performance.


Positive Real Synthesis of Networked Control System An LMI Approach

Abstract: This paper presents the positive real analysis and synthesis for Networked Control Systems (NCS) in discrete time. Based on the definition of passivity, the sufficient condition of NCS is given by stochastic Lyapunov functional. The controller via state feedback is designed to guarantee the stability of NCS and closed-loop positive realness. It is shown that a mode-dependent positive real controller exists if a set of coupled linear matrix inequalities has solutions. The controller can be then constructed in terms of the solutions.


Analysis of Stability, Response and LQR Controller Design of a Small Scale Helicopter Dynamics

Abstract: This paper presents how to use feedback controller with helicopter dynamics state space model. A simplified analysis is presented for controller design using LQR of small scale helicopters for axial and forward flights. Our approach is simple and gives the basic understanding about how to develop controller for solving the stability of linear helicopter flight dynamics.


Design and control of dynamical quantum processes in ortho para H2 conversion on surfaces

Abstract: We present here a novel, cost-effective method for increasing and controlling the ortho para H2 (o p H2) conversion yield. First, we invoke two processes derived from fundamental, surface science insights, based on the effect of molecular orientation on the hydrogen solid surface reaction, i.e., dynamical quantum filtering and steering, and apply them to enhance the o p H2 conversion yield. Second, we find an important factor that can significantly influence the yield i.e., inhomogeneity of spin density distribution. This factor gives us a promising possibility to increase the yield and to find the best catalyst e.g., design of materials that can function as catalysts for the o p H2 conversion.


Solving Time of Least Square Systems in Sigma-Pi Unit Networks

Abstract: The solving of least square systems is a useful operation in neurocomputational modeling of learning, pattern matching, and pattern recognition. In these last two cases, the solution must be obtained on-line, thus the time required to solve a system in a plausible neural architecture is critical. This paper presents a recurrent network of Sigma-Pi neurons, whose solving time increases at most like the logarithm of the system size, and of its condition number, which provides plausible computation times for biological systems.


Fast Computation of Moore-Penrose Inverse Matrices

Abstract: Many neural learning algorithms require to solve large least square systems in order to obtain synaptic weights. Moore-Penrose inverse matrices allow for solving such systems, even with rank deficiency, and they provide minimum-norm vectors of synaptic weights, which contribute to the regularization of the input-output mapping. It is thus of interest to develop fast and accurate algorithms for computing Moore-Penrose inverse matrices. In this paper, an algorithm based on a full rank Cholesky factorization is proposed. The resulting pseudoinverse matrices are similar to those provided by other algorithms. However the computation time is substantially shorter, particularly for large systems.


Tight local approximation results for max-min linear programs

Abstract: In a bipartite max-min LP, we are given a bipartite graph $\myG = (V \cup I \cup K, E)$, where each agent $v \in V$ is adjacent to exactly one constraint $i \in I$ and exactly one objective $k \in K$. Each agent $v$ controls a variable $x_v$. For each $i \in I$ we have a nonnegative linear constraint on the variables of adjacent agents. For each $k \in K$ we have a nonnegative linear objective function of the variables of adjacent agents. The task is to maximise the minimum of the objective functions. We study local algorithms where each agent $v$ must choose $x_v$ based on input within its constant-radius neighbourhood in $\myG$. We show that for every $\epsilon>0$ there exists a local algorithm achieving the approximation ratio ${\Delta_I (1 - 1/\Delta_K)} + \epsilon$. We also show that this result is the best possible -- no local algorithm can achieve the approximation ratio ${\Delta_I (1 - 1/\Delta_K)}$. Here $\Delta_I$ is the maximum degree of a vertex $i \in I$, and $\Delta_K$ is the maximum degree of a vertex $k \in K$. As a methodological contribution, we introduce the technique of graph unfolding for the design of local approximation algorithms.


The Minimum Backlog Problem

Abstract: We study the minimum backlog problem (MBP). This online problem arises, e.g., in the context of sensor networks. We focus on two main variants of MBP. The discrete MBP is a 2-person game played on a graph $G=(V,E)$. The player is initially located at a vertex of the graph. In each time step, the adversary pours a total of one unit of water into cups that are located on the vertices of the graph, arbitrarily distributing the water among the cups. The player then moves from her current vertex to an adjacent vertex and empties the cup at that vertex. The player's objective is to minimize the backlog, i.e., the maximum amount of water in any cup at any time. The geometric MBP is a continuous-time version of the MBP: the cups are points in the two-dimensional plane, the adversary pours water continuously at a constant rate, and the player moves in the plane with unit speed. Again, the player's objective is to minimize the backlog. We show that the competitive ratio of any algorithm for the MBP has a lower bound of $\Omega(D)$, where $D$ is the diameter of the graph (for the discrete MBP) or the diameter of the point set (for the geometric MBP). Therefore we focus on determining a strategy for the player that guarantees a uniform upper bound on the absolute value of the backlog. For the absolute value of the backlog there is a trivial lower bound of $\Omega(D)$, and the deamortization analysis of Dietz and Sleator gives an upper bound of $O(D\log N)$ for $N$ cups. Our main result is a tight upper bound for the geometric MBP: we show that there is a strategy for the player that guarantees a backlog of $O(D)$, independently of the number of cups.


Characterizing Video Responses in Social Networks

Abstract: Video sharing sites, such as YouTube, use video responses to enhance the social interactions among their users. The video response feature allows users to interact and converse through video, by creating a video sequence that begins with an opening video and followed by video responses from other users. Our characterization is over 3.4 million videos and 400,000 video responses collected from YouTube during a 7-day period. We first analyze the characteristics of the video responses, such as popularity, duration, and geography. We then examine the social networks that emerge from the video response interactions.


Search Space Contraction in Canonical Labeling of Graphs

Abstract: The individualization-refinement paradigm for computing a canonical labeling and the automorphism group of a graph is investigated. A new algorithmic design aimed at reducing the size of the associated search space is introduced, and a new tool, named "Traces", is presented, together with experimental results and comparisons with existing software, such as McKay's "nauty". It is shown that the approach presented here leads to a huge reduction in the search space, thereby making computation feasible for several classes of graphs which are hard for all the main canonical labeling tools in the literature.


SimDialog: A visual game dialog editor

Abstract: SimDialog is a visual editor for dialog in computer games. This paper presents the design of SimDialog, illustrating how script writers and non-programmers can easily create dialog for video games with complex branching structures and dynamic response characteristics. The system creates dialog as a directed graph. This allows for play using the dialog with a state-based cause and effect system that controls selection of non-player character responses and can provide a basic scoring mechanism for games.


Monotony in Service Orchestrations

Abstract: Web Service orchestrations are compositions of different Web Services to form a new service. The services called during the orchestration guarantee a given performance to the orchestrater, usually in the form of contracts. These contracts can be used by the orchestrater to deduce the contract it can offer to its own clients, by performing contract composition. An implicit assumption in contract based QoS management is: "the better the component services perform, the better the orchestration's performance will be". Thus, contract based QoS management for Web services orchestrations implicitly assumes monotony. In some orchestrations, however, monotony can be violated, i.e., the performance of the orchestration improves when the performance of a component service degrades. This is highly undesirable since it can render the process of contract composition inconsistent. In this paper we define monotony for orchestrations modelled by Colored Occurrence Nets (CO-nets) and we characterize the classes of monotonic orchestrations. We show that few orchestrations are indeed monotonic, mostly since latency can be traded for quality of data. We also propose a sound refinement of monotony, called conditional monotony, which forbids this kind of cheating and show that conditional monotony is widely satisfied by orchestrations. This finding leads to reconsidering the way SLAs should be formulated.


A Quadratic Loss Multi-Class SVM

Abstract: Using a support vector machine requires to set two types of hyperparameters: the soft margin parameter C and the parameters of the kernel. To perform this model selection task, the method of choice is cross-validation. Its leave-one-out variant is known to produce an estimator of the generalization error which is almost unbiased. Its major drawback rests in its time requirement. To overcome this difficulty, several upper bounds on the leave-one-out error of the pattern recognition SVM have been derived. Among those bounds, the most popular one is probably the radius-margin bound. It applies to the hard margin pattern recognition SVM, and by extension to the 2-norm SVM. In this report, we introduce a quadratic loss M-SVM, the M-SVM^2, as a direct extension of the 2-norm SVM to the multi-class case. For this machine, a generalized radius-margin bound is then established.


Straight Skeletons of Three-Dimensional Polyhedra

Abstract: This paper studies the straight skeleton of polyhedra in three dimensions. We first address voxel-based polyhedra (polycubes), formed as the union of a collection of cubical (axis-aligned) voxels. We analyze the ways in which the skeleton may intersect each voxel of the polyhedron, and show that the skeleton may be constructed by a simple voxel-sweeping algorithm taking constant time per voxel. In addition, we describe a more complex algorithm for straight skeletons of voxel-based polyhedra, which takes time proportional to the area of the surfaces of the straight skeleton rather than the volume of the polyhedron. We also consider more general polyhedra with axis-parallel edges and faces, and show that any n-vertex polyhedron of this type has a straight skeleton with O(n^2) features. We provide algorithms for constructing the straight skeleton, with running time O(min(n^2 log n, k log^{O(1)} n)) where k is the output complexity. Next, we discuss the straight skeleton of a general nonconvex polyhedron. We show that it has an ambiguity issue, and suggest a consistent method to resolve it. We prove that the straight skeleton of a general polyhedron has a superquadratic complexity in the worst case. Finally, we report on an implementation of a simple algorithm for the general case.


Universe Detectors for Sybil Defense in Ad Hoc Wireless Networks

Abstract: The Sybil attack in unknown port networks such as wireless is not considered tractable. A wireless node is not capable of independently differentiating the universe of real nodes from the universe of arbitrary non-existent fictitious nodes created by the attacker. Similar to failure detectors, we propose to use universe detectors to help nodes determine which universe is real. In this paper, we (i) define several variants of the neighborhood discovery problem under Sybil attack (ii) propose a set of matching universe detectors (iii) demonstrate the necessity of additional topological constraints for the problems to be solvable: node density and communication range; (iv) present SAND -- an algorithm that solves these problems with the help of appropriate universe detectors, this solution demonstrates that the proposed universe detectors are the weakest detectors possible for each problem.


Nonnegative Matrix Factorization via Rank-One Downdate

Abstract: Nonnegative matrix factorization (NMF) was popularized as a tool for data mining by Lee and Seung in 1999. NMF attempts to approximate a matrix with nonnegative entries by a product of two low-rank matrices, also with nonnegative entries. We propose an algorithm called rank-one downdate (R1D) for computing a NMF that is partly motivated by singular value decomposition. This algorithm computes the dominant singular values and vectors of adaptively determined submatrices of a matrix. On each iteration, R1D extracts a rank-one submatrix from the dataset according to an objective function. We establish a theoretical result that maximizing this objective function corresponds to correctly classifying articles in a nearly separable corpus. We also provide computational experiments showing the success of this method in identifying features in realistic datasets.


On Recovery of Sparse Signals via $\ell_1$ Minimization

Abstract: This article considers constrained $\ell_1$ minimization methods for the recovery of high dimensional sparse signals in three settings: noiseless, bounded error and Gaussian noise. A unified and elementary treatment is given in these noise settings for two $\ell_1$ minimization methods: the Dantzig selector and $\ell_1$ minimization with an $\ell_2$ constraint. The results of this paper improve the existing results in the literature by weakening the conditions and tightening the error bounds. The improvement on the conditions shows that signals with larger support can be recovered accurately. This paper also establishes connections between restricted isometry property and the mutual incoherence property. Some results of Candes, Romberg and Tao (2006) and Donoho, Elad, and Temlyakov (2006) are extended.


Morphing of Triangular Meshes in Shape Space

Abstract: We present a novel approach to morph between two isometric poses of the same non-rigid object given as triangular meshes. We model the morphs as linear interpolations in a suitable shape space $\mathcal{S}$. For triangulated 3D polygons, we prove that interpolating linearly in this shape space corresponds to the most isometric morph in $\mathbb{R}^3$. We then extend this shape space to arbitrary triangulations in 3D using a heuristic approach and show the practical use of the approach using experiments. Furthermore, we discuss a modified shape space that is useful for isometric skeleton morphing. All of the newly presented approaches solve the morphing problem without the need to solve a minimization problem.


(m,k)-firm constraints and DBP scheduling: impact of the initial k-sequence and exact schedulability test

Abstract: In this paper we study the scheduling of (m,k)-firm synchronous periodic task systems using the Distance Based Priority (DBP) scheduler. We first show three phenomena: (i) choosing, for each task, the initial k-sequence 1^k is not optimal, (ii) we can even start the scheduling from a (fictive) error state (in regard to the initial k-sequence) and (iii) the period of feasible DBP-schedules is not necessarily the task hyper-period. We then show that any feasible DBP-schedule is periodic and we upper-bound the length of that period. Lastly, based on our periodicity result we provide an exact schedulability test.


A Pseudo-Boolean Solution to the Maximum Quartet Consistency Problem

Abstract: Determining the evolutionary history of a given biological data is an important task in biological sciences. Given a set of quartet topologies over a set of taxa, the Maximum Quartet Consistency (MQC) problem consists of computing a global phylogeny that satisfies the maximum number of quartets. A number of solutions have been proposed for the MQC problem, including Dynamic Programming, Constraint Programming, and more recently Answer Set Programming (ASP). ASP is currently the most efficient approach for optimally solving the MQC problem. This paper proposes encoding the MQC problem with pseudo-Boolean (PB) constraints. The use of PB allows solving the MQC problem with efficient PB solvers, and also allows considering different modeling approaches for the MQC problem. Initial results are promising, and suggest that PB can be an effective alternative for solving the MQC problem.


CMA-ES with Two-Point Step-Size Adaptation

Abstract: We combine a refined version of two-point step-size adaptation with the covariance matrix adaptation evolution strategy (CMA-ES). Additionally, we suggest polished formulae for the learning rate of the covariance matrix and the recombination weights. In contrast to cumulative step-size adaptation or to the 1/5-th success rule, the refined two-point adaptation (TPA) does not rely on any internal model of optimality. In contrast to conventional self-adaptation, the TPA will achieve a better target step-size in particular with large populations. The disadvantage of TPA is that it relies on two additional objective function


Alternating Automata on Data Trees and XPath Satisfiability

Abstract: A data tree is an unranked ordered tree whose every node is labelled by a letter from a finite alphabet and an element ("datum") from an infinite set, where the latter can only be compared for equality. The article considers alternating automata on data trees that can move downward and rightward, and have one register for storing data. The main results are that nonemptiness over finite data trees is decidable but not primitive recursive, and that nonemptiness of safety automata is decidable but not elementary. The proofs use nondeterministic tree automata with faulty counters. Allowing upward moves, leftward moves, or two registers, each causes undecidability. As corollaries, decidability is obtained for two data-sensitive fragments of the XPath query language.


Prediction and Mitigation of Crush Conditions in Emergency Evacuations

Abstract: Several simulation environments exist for the simulation of large-scale evacuations of buildings, ships, or other enclosed spaces. These offer sophisticated tools for the study of human behaviour, the recreation of environmental factors such as fire or smoke, and the inclusion of architectural or structural features, such as elevators, pillars and exits. Although such simulation environments can provide insights into crowd behaviour, they lack the ability to examine potentially dangerous forces building up within a crowd. These are commonly referred to as crush conditions, and are a common cause of death in emergency evacuations. In this paper, we describe a methodology for the prediction and mitigation of crush conditions. The paper is organised as follows. We first establish the need for such a model, defining the main factors that lead to crush conditions, and describing several exemplar case studies. We then examine current methods for studying crush, and describe their limitations. From this, we develop a three-stage hybrid approach, using a combination of techniques. We conclude with a brief discussion of the potential benefits of our approach.


Algorithms for Probabilistically-Constrained Models of Risk-Averse Stochastic Optimization with Black-Box Distributions

Abstract: We consider various stochastic models that incorporate the notion of risk-averseness into the standard 2-stage recourse model, and develop novel techniques for solving the algorithmic problems arising in these models. A key notable feature of our work that distinguishes it from work in some other related models, such as the (standard) budget model and the (demand-) robust model, is that we obtain results in the black-box setting, that is, where one is given only sampling access to the underlying distribution. Our first model, which we call the risk-averse budget model, incorporates the notion of risk-averseness via a probabilistic constraint that restricts the probability (according to the underlying distribution) with which the second-stage cost may exceed a given budget B to at most a given input threshold \rho. We also a consider a closely-related model that we call the risk-averse robust model, where we seek to minimize the first-stage cost and the (1-\rho)-quantile of the second-stage cost. We obtain approximation algorithms for a variety of combinatorial optimization problems including the set cover, vertex cover, multicut on trees, min cut, and facility location problems, in the risk-averse budget and robust models with black-box distributions. We obtain near-optimal solutions that preserve the budget approximately and incur a small blow-up of the probability threshold (both of which are unavoidable). To the best of our knowledge, these are the first approximation results for problems involving probabilistic constraints and black-box distributions. A major component of our results is a fully polynomial approximation scheme for solving the LP-relaxation of the risk-averse problem.


Two-enqueuer queue in Common2

Abstract: The question of whether all shared objects with consensus number 2 belong to Common2, the set of objects that can be implemented in a wait-free manner by any type of consensus number 2, was first posed by Herlihy. In the absence of general results, several researchers have obtained implementations for restricted-concurrency versions of FIFO queues. We present the first Common2 algorithm for a queue with two enqueuers and any number of dequeuers.


From a set of parts to an indivisible whole. Part II: Operations in an open comparative mode

Abstract: This paper describes a new method, HGV2C, for pattern analysis. The HGV2C method involves the construction of a computer ego (CE) based on an individual object that can be either a part of the system under analysis or a newly created object based on a certain hypothesis. The CE provides a capability to analyze data from a specific standpoint, e.g. from a viewpoint of a certain object. The CE is constructed from two identical copies of a query object, and its functioning mechanism involves: a hypothesis-parameter (HP) and infothyristor (IT). HP is a parameter that is introduced into an existing set of parameters. The HP value for one of the clones of a query object is set to equal 1, whereas for another clone it is greater than 1. The IT is based on the previously described algorithm of iterative averaging and performs three functions: 1) computation of a similarity matrix for the group of three objects including two clones of a query object and a target object; 2) division of the group into two alternative subgroups; and 3) a successive increase of the HP weight in the totality of all the parameters. Initially, both clones of the query object appear together in one of the subgroups as all of their parameter values, except the HP, are identical. At a certain point of the HP multiplication, one of the clones moves to the group of the target object. A respective number of the HP multiplications represents the dissimilarity (D) between the query and target objects. The product of D multiplied by the difference in HP values of the clones is strictly constant and linearly increases as the difference in HP values of the clones decreases. This new approach to knowledge representation is demonstrated on the example of population pyramids of 220 countries.


Phase transition in SONFIS&SORST

Abstract: In this study, we introduce general frame of MAny Connected Intelligent Particles Systems (MACIPS). Connections and interconnections between particles get a complex behavior of such merely simple system (system in system).Contribution of natural computing, under information granulation theory, are the main topics of this spacious skeleton. Upon this clue, we organize two algorithms involved a few prominent intelligent computing and approximate reasoning methods: self organizing feature map (SOM), Neuro- Fuzzy Inference System and Rough Set Theory (RST). Over this, we show how our algorithms can be taken as a linkage of government-society interaction, where government catches various fashions of behavior: solid (absolute) or flexible. So, transition of such society, by changing of connectivity parameters (noise) from order to disorder is inferred. Add to this, one may find an indirect mapping among financial systems and eventual market fluctuations with MACIPS. Keywords: phase transition, SONFIS, SORST, many connected intelligent particles system, society-government interaction


The Tractability of Model-Checking for LTL: The Good, the Bad, and the Ugly Fragments

Abstract: In a seminal paper from 1985, Sistla and Clarke showed that the model-checking problem for Linear Temporal Logic (LTL) is either NP-complete or PSPACE-complete, depending on the set of temporal operators used. If, in contrast, the set of propositional operators is restricted, the complexity may decrease. This paper systematically studies the model-checking problem for LTL formulae over restricted sets of propositional and temporal operators. For almost all combinations of temporal and propositional operators, we determine whether the model-checking problem is tractable (in P) or intractable (NP-hard). We then focus on the tractable cases, showing that they all are NL-complete or even logspace solvable. This leads to a surprising gap in complexity between tractable and intractable cases. It is worth noting that our analysis covers an infinite set of problems, since there are infinitely many sets of propositional operators.


Analysis of the Deterministic Polynomial Time Solvability of the 0-1-Knapsack Problem

Abstract: Previously the author has demonstrated that a representative polynomial search partition is required to solve a NP-complete problem in deterministic polynomial time. It has also been demonstrated that finding such a partition can only be done in deterministic polynomial time if the form of the problem provides a simple method for producing the partition. It is the purpose of this article to demonstrate that no deterministic polynomial time method exists to produce a representative polynomial search partition for the Knapsack problem.


Climate modification directed by control theory

Abstract: Climate modification measures to counteract global warming receive some more new attentions in these years. Most current researches only discuss the impact of these measures to climate, but how to design such a climate regulator is still unknown. This paper shows the control theory could give the systematic direction for climate modification. But the control analyzing also reveals that climate modifications should only be regarded as a last-ditch measure.


An Approach to Learning Research with a Wireless Sensor Network in an Outdoor Setting

Abstract: Automated collection of environmental data may be accomplished with wireless sensor networks (WSNs). In this paper, a general discussion of WSNs is given for the gathering of data for educational research. WSNs have the capability to enhance the scope of a researcher to include multiple streams of data: environmental, location, cyberdata, video, and RFID. The location of data stored in a database can allow reconstruction of the learning activity for the evaluation of significance at a later time. A brief overview of the technology forms the basis of an exploration of a setting used for outdoor learning.


Discrete Mathematics for Computer Science, Some Notes

Abstract: These are notes on discrete mathematics for computer scientists. The presentation is somewhat unconventional. Indeed I begin with a discussion of the basic rules of mathematical reasoning and of the notion of proof formalized in a natural deduction system ``a la Prawitz''. The rest of the material is more or less traditional but I emphasize partial functions more than usual (after all, programs may not terminate for all input) and I provide a fairly complete account of the basic concepts of graph theory.


3D Building Model Fitting Using A New Kinetic Framework

Abstract: We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variational optimization. This new kinetic framework allows the manipulation of a bounded polyhedron with simple faces by specifying the target plane equations of each of its faces. It proceeds by evolving continuously from the polyhedron defined by its initial topology and its initial plane equations to a polyhedron that is as topologically close as possible to the initial polyhedron but with the new plane equations. This kinetic framework handles internally the necessary topological changes that may be required to keep the faces simple and the polyhedron bounded. For each intermediate configurations where the polyhedron looses the simplicity of its faces or its boundedness, the simplest topological modification that is able to reestablish the simplicity and the boundedness is performed.


Plat_Forms -- a contest: The web development platform comparison

Abstract: "Plat_Forms" is a competition in which top-class teams of three programmers compete to implement the same requirements for a web-based system within 30 hours, each team using a different technology platform (Java EE, .NET, PHP, Perl, Python, or Ruby on Rails). The results will provide new insights into the real (rather than purported) pros, cons, and emergent properties of each platform. The evaluation will analyze many aspects of each solution, both external (usability, functionality, reliability, performance, etc.) and internal (structure, understandability, flexibility, etc.).


Stochastic Optimization Approaches for Solving Sudoku

Abstract: In this paper the Sudoku problem is solved using stochastic search techniques and these are: Cultural Genetic Algorithm (CGA), Repulsive Particle Swarm Optimization (RPSO), Quantum Simulated Annealing (QSA) and the Hybrid method that combines Genetic Algorithm with Simulated Annealing (HGASA). The results obtained show that the CGA, QSA and HGASA are able to solve the Sudoku puzzle with CGA finding a solution in 28 seconds, while QSA finding a solution in 65 seconds and HGASA in 1.447 seconds. This is mainly because HGASA combines the parallel searching of GA with the flexibility of SA. The RPSO was found to be unable to solve the puzzle.


Pruning Attribute Values From Data Cubes with Diamond Dicing

Abstract: Data stored in a data warehouse are inherently multidimensional, but most data-pruning techniques (such as iceberg and top-k queries) are unidimensional. However, analysts need to issue multidimensional queries. For example, an analyst may need to select not just the most profitable stores or--separately--the most profitable products, but simultaneous sets of stores and products fulfilling some profitability constraints. To fill this need, we propose a new operator, the diamond dice. Because of the interaction between dimensions, the computation of diamonds is challenging. We present the first diamond-dicing experiments on large data sets. Experiments show that we can compute diamond cubes over fact tables containing 100 million facts in less than 35 minutes using a standard PC.


Sponsored Search Auctions with Markovian Users

Abstract: Sponsored search involves running an auction among advertisers who bid in order to have their ad shown next to search results for specific keywords. Currently, the most popular auction for sponsored search is the "Generalized Second Price" (GSP) auction in which advertisers are assigned to slots in the decreasing order of their "score," which is defined as the product of their bid and click-through rate. In the past few years, there has been significant research on the game-theoretic issues that arise in an advertiser's interaction with the mechanism as well as possible redesigns of the mechanism, but this ranking order has remained standard. From a search engine's perspective, the fundamental question is: what is the best assignment of advertisers to slots? Here "best" could mean "maximizing user satisfaction," "most efficient," "revenue-maximizing," "simplest to interact with," or a combination of these. To answer this question we need to understand the behavior of a search engine user when she sees the displayed ads, since that defines the commodity the advertisers are bidding on, and its value. Most prior work has assumed that the probability of a user clicking on an ad is independent of the other ads shown on the page. We propose a simple Markovian user model that does not make this assumption. We then present an algorithm to determine the most efficient assignment under this model, which turns out to be different than that of GSP. A truthful auction then follows from an application of the Vickrey-Clarke-Groves (VCG) mechanism. Further, we show that our assignment has many of the desirable properties of GSP that makes bidding intuitive. At the technical core of our result are a number of insights about the structure of the optimal assignment.


A new queueing strategy for the Adversarial Queueing Theory

Abstract: In the today's Internet and TCP/IP-networks, the queueing of packets is commonly implemented using the protocol FIFO (First In First Out). Unfortunately, FIFO performs poorly in the Adversarial Queueing Theory. Other queueing strategies are researched in this model and better results are performed by alternative queueing strategies, e.g. LIS (Longest In System). This article introduces a new queueing protocol called interval-strategy that is concerned with the reduction from dynamic to static routing. We discuss the maximum system time for a packet and estimate with up-to-date results how this can be achieved. We figure out the maximum amount of time where a packet can spend in the network (i.e. worst case system time), and argue that the universal instability of the presented interval-strategy can be reached through these results. When a large group of queueing strategies is used for queueing, we prove that the interval-strategy will be universally unstable. Finally, we calculate the maximum time of the static routing to reach an universal stable and polynomial - in detail linear - bounded interval-strategy. Afterwards we close - in order to check this upper bound - with up-to-date results about the delivery times in static routing.


Relational Parametricity and Separation Logic

Abstract: Separation logic is a recent extension of Hoare logic for reasoning about programs with references to shared mutable data structures. In this paper, we provide a new interpretation of the logic for a programming language with higher types. Our interpretation is based on Reynolds's relational parametricity, and it provides a formal connection between separation logic and data abstraction.


AGNOSCO - Identification of Infected Nodes with artificial Ant Colonies

Abstract: If a computer node is infected by a virus, worm or a backdoor, then this is a security risk for the complete network structure where the node is associated. Existing Network Intrusion Detection Systems (NIDS) provide a certain amount of support for the identification of such infected nodes but suffer from the need of plenty of communication and computational power. In this article, we present a novel approach called AGNOSCO to support the identification of infected nodes through the usage of artificial ant colonies. It is shown that AGNOSCO overcomes the communication and computational power problem while identifying infected nodes properly.


SANA - Network Protection through artificial Immunity

Abstract: Current network protection systems use a collection of intelligent components - e.g. classifiers or rule-based firewall systems to detect intrusions and anomalies and to secure a network against viruses, worms, or trojans. However, these network systems rely on individuality and support an architecture with less collaborative work of the protection components. They give less administration support for maintenance, but offer a large number of individual single points of failures - an ideal situation for network attacks to succeed. In this work, we discuss the required features, the performance, and the problems of a distributed protection system called SANA. It consists of a cooperative architecture, it is motivated by the human immune system, where the components correspond to artificial immune cells that are connected for their collaborative work. SANA promises a better protection against intruders than common known protection systems through an adaptive self-management while keeping the resources efficiently by an intelligent reduction of redundant tasks. We introduce a library of several novel and common used protection components and evaluate the performance of SANA by a proof-of-concept implementation.


Service Oriented Architecture in Network Security - a novel Organisation in Security Systems

Abstract: Current network security systems are a collection of various security components, which are directly installed in the operating system. These check the whole node for suspicious behaviour. Armouring intrusions e.g. have the ability to hide themselves from being checked. We present in this paper an alternative organisation of security systems. The node is completely virtualized with current virtualization systems so that the operating system with applications and the security system is distinguished. The security system then checks the node from outside and the right security components are provided through a service oriented architecture. Due to the running in a virtual machine, the infected nodes can be halted, duplicated, and moved to other nodes for further analysis and legal aspects. This organisation is in this article analysed and a preliminary implementation showing promising results are discussed.