Planning with Partial Preference Models

Abstract: Current work in planning with preferences assume that the user's preference models are completely specified and aim to search for a single solution plan. In many real-world planning scenarios, however, the user probably cannot provide any information about her desired plans, or in some cases can only express partial preferences. In such situations, the planner has to present not only one but a set of plans to the user, with the hope that some of them are similar to the plan she prefers. We first propose the usage of different measures to capture quality of plan sets that are suitable for such scenarios: domain-independent distance measures defined based on plan elements (actions, states, causal links) if no knowledge of the user's preferences is given, and the Integrated Convex Preference measure in case the user's partial preference is provided. We then investigate various heuristic approaches to find set of plans according to these measures, and present empirical results demonstrating the promise of our approach.


A Factorial Experiment on Scalability of Search Based Software Testing

Abstract: Software testing is an expensive process, which is vital in the industry. Construction of the test-data in software testing requires the major cost and to decide which method to use in order to generate the test data is important. This paper discusses the efficiency of search-based algorithms (preferably genetic algorithm) versus random testing, in soft- ware test-data generation. This study differs from all previous studies due to sample programs (SUTs) which are used. Since we want to in- crease the complexity of SUTs gradually, and the program generation is automatic as well, Grammatical Evolution is used to guide the program generation. SUTs are generated according to the grammar we provide, with different levels of complexity. SUTs will first undergo genetic al- gorithm and then random testing. Based on the test results, this paper recommends one method to use for automation of software testing.


Automatic segmentation of HeLa cell images

Abstract: In this work, the possibilities for segmentation of cells from their background and each other in digital image were tested, combined and improoved. Lot of images with young, adult and mixture cells were able to prove the quality of described algorithms. Proper segmentation is one of the main task of image analysis and steps order differ from work to work, depending on input images. Reply for biologicaly given question was looking for in this work, including filtration, details emphasizing, segmentation and sphericity computing. Order of algorithms and way to searching for them was also described. Some questions and ideas for further work were mentioned in the conclusion part.


Review and Evaluation of Feature Selection Algorithms in Synthetic Problems

Abstract: The main purpose of Feature Subset Selection is to find a reduced subset of attributes from a data set described by a feature set. The task of a feature selection algorithm (FSA) is to provide with a computational solution motivated by a certain definition of relevance or by a reliable evaluation measure. In this paper several fundamental algorithms are studied to assess their performance in a controlled experimental scenario. A measure to evaluate FSAs is devised that computes the degree of matching between the output given by a FSA and the known optimal solutions. An extensive experimental study on synthetic problems is carried out to assess the behaviour of the algorithms in terms of solution accuracy and size as a function of the relevance, irrelevance, redundancy and size of the data samples. The controlled experimental conditions facilitate the derivation of better-supported and meaningful conclusions.


Minimum Covering with Travel Cost

Abstract: Given a polygon and a visibility range, the Myopic Watchman Problem with Discrete Vision (MWPDV) asks for a closed path P and a set of scan points S, such that (i) every point of the polygon is within visibility range of a scan point; and (ii) path length plus weighted sum of scan number along the tour is minimized. Alternatively, the bicriteria problem (ii') aims at minimizing both scan number and tour length. We consider both lawn mowing (in which tour and scan points may leave P) and milling (in which tour, scan points and visibility must stay within P) variants for the MWPDV; even for simple special cases, these problems are NP-hard. We show that this problem is NP-hard, even for the special cases of rectilinear polygons and L_\infty scan range 1, and negligible small travel cost or negligible travel cost. For rectilinear MWPDV milling in grid polygons we present a 2.5-approximation with unit scan range; this holds for the bicriteria version, thus for any linear combination of travel cost and scan cost. For grid polygons and circular unit scan range, we describe a bicriteria 4-approximation. These results serve as stepping stones for the general case of circular scans with scan radius r and arbitrary polygons of feature size a, for which we extend the underlying ideas to a pi(r/a}+(r+1)/2) bicriteria approximation algorithm. Finally, we describe approximation schemes for MWPDV lawn mowing and milling of grid polygons, for fixed ratio between scan cost and travel cost.


Extracting Features from Ratings: The Role of Factor Models

Abstract: Performing effective preference-based data retrieval requires detailed and preferentially meaningful structurized information about the current user as well as the items under consideration. A common problem is that representations of items often only consist of mere technical attributes, which do not resemble human perception. This is particularly true for integral items such as movies or songs. It is often claimed that meaningful item features could be extracted from collaborative rating data, which is becoming available through social networking services. However, there is only anecdotal evidence supporting this claim; but if it is true, the extracted information could very valuable for preference-based data retrieval. In this paper, we propose a methodology to systematically check this common claim. We performed a preliminary investigation on a large collection of movie ratings and present initial evidence.


Domain decomposition schemes for evolutionary equations of first order with not self-adjoint operators

Abstract: Domain decomposition methods are essential in solving applied problems on parallel computer systems. For boundary value problems for evolutionary equations the implicit schemes are in common use to solve problems at a new time level employing iterative methods of domain decomposition. An alternative approach is based on constructing iteration-free methods based on special schemes of splitting into subdomains. Such regionally-additive schemes are constructed using the general theory of additive operator-difference schemes. There are employed the analogues of classical schemes of alternating direction method, locally one-dimensional schemes, factorization methods, vector and regularized additive schemes. The main results were obtained here for time-dependent problems with self-adjoint elliptic operators of second order. The paper discusses the Cauchy problem for the first order evolutionary equations with a nonnegative not self-adjoint operator in a finite-dimensional Hilbert space. Based on the partition of unit, we have constructed the operators of decomposition which preserve nonnegativity for the individual operator terms of splitting. Unconditionally stable additive schemes of domain decomposition were constructed using the regularization principle for operator-difference schemes. Vector additive schemes were considered, too. The results of our work are illustrated by a model problem for the two-dimensional parabolic equation.


Content-Based Filtering for Video Sharing Social Networks

Abstract: In this paper we compare the use of several features in the task of content filtering for video social networks, a very challenging task, not only because the unwanted content is related to very high-level semantic concepts (e.g., pornography, violence, etc.) but also because videos from social networks are extremely assorted, preventing the use of constrained a priori information. We propose a simple method, able to combine diverse evidence, coming from different features and various video elements (entire video, shots, frames, keyframes, etc.). We evaluate our method in three social network applications, related to the detection of unwanted content - pornographic videos, violent videos, and videos posted to artificially manipulate popularity scores. Using challenging test databases, we show that this simple scheme is able to obtain good results, provided that adequate features are chosen. Moreover, we establish a representation using codebooks of spatiotemporal local descriptors as critical to the success of the method in all three contexts. This is consequential, since the state-of-the-art still relies heavily on static features for the tasks addressed.


A Review of Research on Devnagari Character Recognition

Abstract: English Character Recognition (CR) has been extensively studied in the last half century and progressed to a level, sufficient to produce technology driven applications. But same is not the case for Indian languages which are complicated in terms of structure and computations. Rapidly growing computational power may enable the implementation of Indic CR methodologies. Digital document processing is gaining popularity for application to office and library automation, bank and postal services, publishing houses and communication technology. Devnagari being the national language of India, spoken by more than 500 million people, should be given special attention so that document retrieval and analysis of rich ancient and modern Indian literature can be effectively done. This article is intended to serve as a guide and update for the readers, working in the Devnagari Optical Character Recognition (DOCR) area. An overview of DOCR systems is presented and the available DOCR techniques are reviewed. The current status of DOCR is discussed and directions for future research are suggested.


Analysis of Biometric Authentication Protocols in the Blackbox Model

Abstract: In this paper we analyze different biometric authentication protocols considering an internal adversary. Our contribution takes place at two levels. On the one hand, we introduce a new comprehensive framework that encompasses the various schemes we want to look at. On the other hand, we exhibit actual attacks on recent schemes such as those introduced at ACISP 2007, ACISP 2008, and SPIE 2010, and some others. We follow a blackbox approach in which we consider components that perform operations on the biometric data they contain and where only the input/output behavior of these components is analyzed.


An Overview of Portable Distributed Techniques

Abstract: In this paper, we reviewed of several portable parallel programming paradigms for use in a distributed programming environment. The Techniques reviewed here are portable. These are mainly distributing computing using MPI pure java based, MPI native java based (JNI) and PVM. We will discuss architecture and utilities of each technique based on our literature review. We explored these portable distributed techniques in four important characteristics scalability, fault tolerance, load balancing and performance. We have identified the various factors and issues for improving these four important characteristics.


On Sampling, Anonymization, and Differential Privacy: Or, k-Anonymization Meets Differential Privacy

Abstract: This paper aims at answering the following two questions in privacy-preserving data analysis and publishing: What formal privacy guarantee (if any) does $k$-anonymization provide? How to benefit from the adversary's uncertainty about the data? We have found that random sampling provides a connection that helps answer these two questions, as sampling can create uncertainty. The main result of the paper is that $k$-anonymization, when done "safely", and when preceded with a random sampling step, satisfies $(\epsilon,\delta)$-differential privacy with reasonable parameters. This result illustrates that "hiding in a crowd of $k$" indeed offers some privacy guarantees. This result also suggests an alternative approach to output perturbation for satisfying differential privacy: namely, adding a random sampling step in the beginning and pruning results that are too sensitive to change of a single tuple. Regarding the second question, we provide both positive and negative results. On the positive side, we show that adding a random-sampling pre-processing step to a differentially-private algorithm can greatly amplify the level of privacy protection. Hence, when given a dataset resulted from sampling, one can utilize a much large privacy budget. On the negative side, any privacy notion that takes advantage of the adversary's uncertainty likely does not compose. We discuss what these results imply in practice.


A Novel Probabilistic Pruning Approach to Speed Up Similarity Queries in Uncertain Databases

Abstract: In this paper, we propose a novel, effective and efficient probabilistic pruning criterion for probabilistic similarity queries on uncertain data. Our approach supports a general uncertainty model using continuous probabilistic density functions to describe the (possibly correlated) uncertain attributes of objects. In a nutshell, the problem to be solved is to compute the PDF of the random variable denoted by the probabilistic domination count: Given an uncertain database object B, an uncertain reference object R and a set D of uncertain database objects in a multi-dimensional space, the probabilistic domination count denotes the number of uncertain objects in D that are closer to R than B. This domination count can be used to answer a wide range of probabilistic similarity queries. Specifically, we propose a novel geometric pruning filter and introduce an iterative filter-refinement strategy for conservatively and progressively estimating the probabilistic domination count in an efficient way while keeping correctness according to the possible world semantics. In an experimental evaluation, we show that our proposed technique allows to acquire tight probability bounds for the probabilistic domination count quickly, even for large uncertain databases.


Planarity Testing Revisited

Abstract: Planarity Testing is the problem of determining whether a given graph is planar while planar embedding is the corresponding construction problem. The bounded space complexity of these problems has been determined to be exactly Logspace by Allender and Mahajan with the aid of Reingold's result. Unfortunately, the algorithm is quite daunting and generalizing it to say, the bounded genus case seems a tall order. In this work, we present a simple planar embedding algorithm running in logspace. We hope this algorithm will be more amenable to generalization. The algorithm is based on the fact that 3-connected planar graphs have a unique embedding, a variant of Tutte's criterion on conflict graphs of cycles and an explicit change of cycle basis.% for planar graphs. We also present a logspace algorithm to find obstacles to planarity, viz. a Kuratowski minor, if the graph is non-planar. To the best of our knowledge this is the first logspace algorithm for this problem.


Parallelization Strategies for Ant Colony Optimisation on GPUs

Abstract: Ant Colony Optimisation (ACO) is an effective population-based meta-heuristic for the solution of a wide variety of problems. As a population-based algorithm, its computation is intrinsically massively parallel, and it is there- fore theoretically well-suited for implementation on Graphics Processing Units (GPUs). The ACO algorithm comprises two main stages: Tour construction and Pheromone update. The former has been previously implemented on the GPU, using a task-based parallelism approach. However, up until now, the latter has always been implemented on the CPU. In this paper, we discuss several parallelisation strategies for both stages of the ACO algorithm on the GPU. We propose an alternative data-based parallelism scheme for Tour construction, which fits better on the GPU architecture. We also describe novel GPU programming strategies for the Pheromone update stage. Our results show a total speed-up exceeding 28x for the Tour construction stage, and 20x for Pheromone update, and suggest that ACO is a potentially fruitful area for future research in the GPU domain.


Lower bound for deterministic semantic-incremental branching programs solving GEN

Abstract: We answer a problem posed in (G\'al, Kouck\'y, McKenzie 2008) regarding a restricted model of small-space computation, tailored for solving the GEN problem. They define two variants of "incremental branching programs", the syntactic variant defined by a restriction on the graph-theoretic paths in the program, and the more-general semantic variant in which the same restriction is enforced only on the consistent paths - those that are followed by at least one input. They show that exponential size is required for the syntactic variant, but leave open the problem of superpolynomial lower bounds for the semantic variant. Here we give an exponential lower bound for the semantic variant by generalizing lower bound arguments, from earlier work, for a similar restricted model tailored for solving a special case of GEN called Tree Evaluation.


A Proposal to Classify Latinamerican Scientific Journals using Citation Indicators: Case Study in Colombia

Abstract: Colombian scientific journals are poorly represented in international digital libraries; however, through Google Scholar (GS) it is possible to determine their use by the community. Between the years of 2003 and 2007 a classification of 185 Colombian journals indexed in the Colombian National Bibliographical Index (IBNP) was performed using the information provided by GS, basing categorization on size indicators, indexation and citation. The indicators were analyzed by grouping the journals in two general areas: sciences and social sciences. In each area, the indicators provided by the digital libraries Scopus, Redalyc and Scielo were compared. Additionally, the indicators provided by IBNP journals categories (A1, A2, B and C) were also compared. The sciences and social sciences had a similar pattern in their indicators. The existence of positive correlations was established between some indicators and they predicted that the number of citations per journal in GS and the h index depends on its visibility in GS and Scopus. We put forward that the current IBNP categories (A1, A2, B or C) faintly reflect the use of journals by the community and we propose a classification based on the h index as an infometric indicator, which reflects not only its visibility in Google Scholar, but also its inclusion in certain international digital libraries, particularly Scopus. Our results may be applied to the creation of public policies regarding science and technology in Colombia and in developing countries.


A Novel Mechanism for Detection of Distributed Denial of Service Attacks

Abstract: The increasing popularity of web-based applications has led to several critical services being provided over the Internet. This has made it imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper has presented a mechanism for protecting a web-server against a distributed denial of service (DDoS) attack. Incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. While the detection process is on, the sessions from the legitimate sources are not disrupted and the load on the server is restored to the normal level by blocking the traffic from the attacking sources. To cater to different scenarios, the detection algorithm has various modules with varying level of computational and memory overheads for their execution. While the approximate modules are fast in detection and involve less overhead, they have lower detection accuracy. The accurate modules involve complex detection logic and hence involve more overhead for their execution, but they have very high detection accuracy. Simulations carried out on the proposed mechanism have produced results that demonstrate effectiveness of the scheme.


Energy-Efficient Design and Optimization of Wireline Access Networks

Abstract: Access networks, in particular, Digital Subscriber Line (DSL) equipment, are a significant source of energy consumption for wireline operators. Replacing large monolithic DSLAMs with smaller remote DSLAM units closer to customers can reduce the energy consumption as well as increase the reach of the access network. This paper attempts to formalize the design and optimization of the "last mile" wireline access network with energy as one of the costs to be minimized. In particular, the placement of remote DSLAM units needs to be optimized. We propose solutions for two scenarios. For the scenario where an existing all-copper network from the central office to the customers is to be transformed into a fiber-copper network with remote DSLAM units, we present optimal polynomial-time solutions. In the green-field scenario, both the access network layout and the placement of remote DSLAM units must be determined. We show that this problem is NP-complete. We present an optimal ILP formulation and also design an efficient heuristic-based approach to build a power-and-cost-optimized access network. Our heuristic-based approach yields results that are very close to optimal. We show how the power consumption of the access network can be reduced by carefully laying the access network and introducing remote DSLAM units.


An Efficient and User Privacy-Preserving Routing Protocol for Wireless Mesh Networks

Abstract: Wireless mesh networks (WMNs) have emerged as a key technology for next generation wireless broadband networks showing rapid progress and inspiring numerous compelling applications. A WMN comprises of a set of mesh routers (MRs) and mesh clients (MCs), where MRs are connected to the Internet backbone through the Internet gateways (IGWs). The MCs are wireless devices and communicate among themselves over possibly multi-hop paths with or without the involvement of MRs. User privacy and security have been primary concerns in WMNs due to their peer-to-peer network topology, shared wireless medium, stringent resource constraints, and highly dynamic environment. Moreover, to support real-time applications, WMNs must also be equipped with robust, reliable and efficient routing protocols so as to minimize the end-to-end latency. Design of a secure and efficient routing protocol for WMNs, therefore, is of paramount importance. In this paper, we propose an efficient and reliable routing protocol that also provides user anonymity in WMNs. The protocol is based on an accurate estimation of the available bandwidth in the wireless links and a robust estimation of the end-to-end delay in a routing path, and minimization of control message overhead. The user anonymity, authentication and data privacy is achieved by application of a novel protocol that is based on Rivest's ring signature scheme. Simulations carried out on the proposed protocol demonstrate that it is more efficient than some of the existing routing protocols.


Routing Security Issues in Wireless Sensor Networks: Attacks and Defenses

Abstract: Wireless Sensor Networks (WSNs) are rapidly emerging as an important new area in wireless and mobile computing research. Applications of WSNs are numerous and growing, and range from indoor deployment scenarios in the home and office to outdoor deployment scenarios in adversary's territory in a tactical battleground (Akyildiz et al., 2002). For military environment, dispersal of WSNs into an adversary's territory enables the detection and tracking of enemy soldiers and vehicles. For home/office environments, indoor sensor networks offer the ability to monitor the health of the elderly and to detect intruders via a wireless home security system. In each of these scenarios, lives and livelihoods may depend on the timeliness and correctness of the sensor data obtained from dispersed sensor nodes. As a result, such WSNs must be secured to prevent an intruder from obstructing the delivery of correct sensor data and from forging sensor data. To address the latter problem, end-to-end data integrity checksums and post-processing of senor data can be used to identify forged sensor data (Estrin et al., 1999; Hu et al., 2003a; Ye et al., 2004). The focus of this chapter is on routing security in WSNs. Most of the currently existing routing protocols for WSNs make an optimization on the limited capabilities of the nodes and the application-specific nature of the network, but do not any the security aspects of the protocols. Although these protocols have not been designed with security as a goal, it is extremely important to analyze their security properties. When the defender has the liabilities of insecure wireless communication, limited node capabilities, and possible insider threats, and the adversaries can use powerful laptops with high energy and long range communication to attack the network, designing a secure routing protocol for WSNs is obviously a non-trivial task.


Robust Line Planning in case of Multiple Pools and Disruptions

Abstract: We consider the line planning problem in public transportation, under a robustness perspective. We present a mechanism for robust line planning in the case of multiple line pools, when the line operators have a different utility function per pool. We conduct an experimental study of our mechanism on both synthetic and real-world data that shows fast convergence to the optimum. We also explore a wide range of scenarios, varying from an arbitrary initial state (to be solved) to small disruptions in a previously optimal solution (to be recovered). Our experiments with the latter scenario show that our mechanism can be used as an online recovery scheme causing the system to re-converge to its optimum extremely fast.


Powermonads and Tensors of Unranked Effects

Abstract: In semantics and in programming practice, algebraic concepts such as monads or, essentially equivalently, (large) Lawvere theories are a well-established tool for modelling generic side-effects. An important issue in this context are combination mechanisms for such algebraic effects, which allow for the modular design of programming languages and verification logics. The most basic combination operators are sum and tensor: while the sum of effects is just their non-interacting union, the tensor imposes commutation of effects. However, for effects with unbounded arity, such as continuations or unbounded nondeterminism, it is not a priori clear whether these combinations actually exist in all cases. Here, we introduce the class of uniform effects, which includes unbounded nondeterminism and continuations, and prove that the tensor does always exist if one of the component effects is uniform, thus in particular improving on previous results on tensoring with continuations. We then treat the case of nondeterminism in more detail, and give an order-theoretic characterization of effects for which tensoring with nondeterminism is conservative, thus enabling nondeterministic arguments such as a generic version of the Fischer-Ladner encoding of control operators.


On Logical Extension of Algebraic Division

Abstract: Basic arithmetic is the cornerstone of mathematics and computer sciences. In arithmetic, 'division by zero' is an undefined operation and any attempt at extending logic for algebraic division to incorporate division by zero has resulted in paradoxes and fallacies. However, there is no proven theorem or mathematical logic that suggests that, defining logic for division by zero would result in break-down of theory. Basing on this motivation, in this paper, we attempt at logically defining a solution for 'division by zero' problem.


A Refined Denominator Bounding Algorithm for Multivariate Linear Difference Equations

Abstract: We continue to investigate which polynomials can possibly occur as factors in the denominators of rational solutions of a given partial linear difference equation. In an earlier article we had introduced the distinction between periodic and aperiodic factors in the denominator, and we gave an algorithm for predicting the aperiodic ones. Now we extend this technique towards the periodic case and present a refined algorithm which also finds most of the periodic factors.


Formal Verification of Differential Privacy for Interactive Systems

Abstract: Differential privacy is a promising approach to privacy preserving data analysis with a well-developed theory for functions. Despite recent work on implementing systems that aim to provide differential privacy, the problem of formally verifying that these systems have differential privacy has not been adequately addressed. This paper presents the first results towards automated verification of source code for differentially private interactive systems. We develop a formal probabilistic automaton model of differential privacy for systems by adapting prior work on differential privacy for functions. The main technical result of the paper is a sound proof technique based on a form of probabilistic bisimulation relation for proving that a system modeled as a probabilistic automaton satisfies differential privacy. The novelty lies in the way we track quantitative privacy leakage bounds using a relation family instead of a single relation. We illustrate the proof technique on a representative automaton motivated by PINQ, an implemented system that is intended to provide differential privacy. To make our proof technique easier to apply to realistic systems, we prove a form of refinement theorem and apply it to show that a refinement of the abstract PINQ automaton also satisfies our differential privacy definition. Finally, we begin the process of automating our proof technique by providing an algorithm for mechanically checking a restricted class of relations from the proof technique.


Subjective Collaborative Filtering

Abstract: We present an item-based approach for collaborative filtering. We determine a list of recommended items for a user by considering their previous purchases. Additionally other features of the users could be considered such as page views, search queries, etc... In particular we address the problem of efficiently comparing items. Our algorithm can efficiently approximate an estimate of the similarity between two items. As measure of similarity we use an approximation of the Jaccard similarity that can be computed by constant time operations and one bitwise OR. Moreover we improve the accuracy of the similarity by introducing the concept of user preference for a given product, which both takes into account multiple purchases and purchases of related items. The product of the user preference and the Jaccard measure (or its approximation) is used as a score for deciding whether a given product has to be recommended.


Dueling Algorithms

Abstract: We revisit classic algorithmic search and optimization problems from the perspective of competition. Rather than a single optimizer minimizing expected cost, we consider a zero-sum game in which an optimization problem is presented to two players, whose only goal is to outperform the opponent. Such games are typically exponentially large zero-sum games, but they often have a rich combinatorial structure. We provide general techniques by which such structure can be leveraged to find minmax-optimal and approximate minmax-optimal strategies. We give examples of ranking, hiring, compression, and binary search duels, among others. We give bounds on how often one can beat the classic optimization algorithms in such duels.


Hypercontractivity and its applications

Abstract: Hypercontractive inequalities are a useful tool in dealing with extremal questions in the geometry of high-dimensional discrete and continuous spaces. In this survey we trace a few connections between different manifestations of hypercontractivity, and also present some relatively recent applications of these techniques in computer science.


Approximations for Monotone and Non-monotone Submodular Maximization with Knapsack Constraints

Abstract: Submodular maximization generalizes many fundamental problems in discrete optimization, including Max-Cut in directed/undirected graphs, maximum coverage, maximum facility location and marketing over social networks. In this paper we consider the problem of maximizing any submodular function subject to $d$ knapsack constraints, where $d$ is a fixed constant. We establish a strong relation between the discrete problem and its continuous relaxation, obtained through {\em extension by expectation} of the submodular function. Formally, we show that, for any non-negative submodular function, an $\alpha$-approximation algorithm for the continuous relaxation implies a randomized $(\alpha - \eps)$-approximation algorithm for the discrete problem. We use this relation to improve the best known approximation ratio for the problem to $1/4- \eps$, for any $\eps > 0$, and to obtain a nearly optimal $(1-e^{-1}-\eps)-$approximation ratio for the monotone case, for any $\eps>0$. We further show that the probabilistic domain defined by a continuous solution can be reduced to yield a polynomial size domain, given an oracle for the extension by expectation. This leads to a deterministic version of our technique.


Binary trees and number of states in buddy systems

Abstract: In the paper are computed: the number of binary trees with n nodes and k leaves; the number of leaves in the set of all binary trees with n nodes. These are used to compute the number of states in the buddy system.


Maximizing Non-monotone Submodular Set Functions Subject to Different Constraints: Combined Algorithms

Abstract: We study the problem of maximizing constrained non-monotone submodular functions and provide approximation algorithms that improve existing algorithms in terms of either the approximation factor or simplicity. Our algorithms combine existing local search and greedy based algorithms. Different constraints that we study are exact cardinality and multiple knapsack constraints. For the multiple-knapsack constraints we achieve a $(0.25-2\epsilon)$-factor algorithm. We also show, as our main contribution, how to use the continuous greedy process for non-monotone functions and, as a result, obtain a $0.13$-factor approximation algorithm for maximization over any solvable down-monotone polytope. The continuous greedy process has been previously used for maximizing smooth monotone submodular function over a down-monotone polytope \cite{CCPV08}. This implies a 0.13-approximation for several discrete problems, such as maximizing a non-negative submodular function subject to a matroid constraint and/or multiple knapsack constraints.


Resequencing: A Method for Conforming to Conventions for Sharing Credits Among Multiple Authors

Abstract: Devising an appropriate scheme that assigns the weights to share credits among multiple authors of a paper is a challenging task. This challenge comes from the fact that different types of conventions might be followed among different research discipline or research groups. In this paper, we discuss that for the purpose of evaluating the quality of research produced by authors, one can resequence either authors or weights and can apply a weight assignment policy which the evaluator deems fit for the particular research discipline or research group.


Support vector machines/relevance vector machine for remote sensing classification: A review

Abstract: Kernel-based machine learning algorithms are based on mapping data from the original input feature space to a kernel feature space of higher dimensionality to solve a linear problem in that space. Over the last decade, kernel based classification and regression approaches such as support vector machines have widely been used in remote sensing as well as in various civil engineering applications. In spite of their better performance with different datasets, support vector machines still suffer from shortcomings such as visualization/interpretation of model, choice of kernel and kernel specific parameter as well as the regularization parameter. Relevance vector machines are another kernel based approach being explored for classification and regression with in last few years. The advantages of the relevance vector machines over the support vector machines is the availability of probabilistic predictions, using arbitrary kernel functions and not requiring setting of the regularization parameter. This paper presents a state-of-the-art review of SVM and RVM in remote sensing and provides some details of their use in other civil engineering application also.


Generalizing Topology via Chu Spaces

Abstract: By using the representational power of Chu spaces we define the notion of a generalized topological space (or GTS, for short), i.e., a mathematical structure that generalizes the notion of a topological space. We demonstrate that these topological spaces have as special cases known topological spaces. Furthermore, we develop the various topological notions and concepts for GTS. Moreover, since the logic of Chu spaces is linear logic, we give an interpretation of most linear logic connectives as operators that yield topological spaces.


The Theory of Intervention Games for Resource Sharing in Wireless Communications

Abstract: This paper develops a game-theoretic framework for the design and analysis of a new class of incentive schemes called intervention schemes. We formulate intervention games, propose a solution concept of intervention equilibrium, and prove its existence in a finite intervention game. We apply our framework to resource sharing scenarios in wireless communications, whose non-cooperative outcomes without intervention yield suboptimal performance. We derive analytical results and analyze illustrative examples in the cases of imperfect and perfect monitoring. In the case of imperfect monitoring, intervention schemes can improve the suboptimal performance of non-cooperative equilibrium when the intervention device has a sufficiently accurate monitoring technology, although it may not be possible to achieve the best feasible performance. In the case of perfect monitoring, the best feasible performance can be obtained with an intervention scheme when the intervention device has a sufficiently strong intervention capability.


Wiselib: A Generic Algorithm Library for Heterogeneous Sensor Networks

Abstract: One unfortunate consequence of the success story of wireless sensor networks (WSNs) in separate research communities is an ever-growing gap between theory and practice. Even though there is a increasing number of algorithmic methods for WSNs, the vast majority has never been tried in practice; conversely, many practical challenges are still awaiting efficient algorithmic solutions. The main cause for this discrepancy is the fact that programming sensor nodes still happens at a very technical level. We remedy the situation by introducing Wiselib, our algorithm library that allows for simple implementations of algorithms onto a large variety of hardware and software. This is achieved by employing advanced C++ techniques such as templates and inline functions, allowing to write generic code that is resolved and bound at compile time, resulting in virtually no memory or computation overhead at run time. The Wiselib runs on different host operating systems, such as Contiki, iSense OS, and ScatterWeb. Furthermore, it runs on virtual nodes simulated by Shawn. For any algorithm, the Wiselib provides data structures that suit the specific properties of the target platform. Algorithm code does not contain any platform-specific specializations, allowing a single implementation to run natively on heterogeneous networks. In this paper, we describe the building blocks of the Wiselib, and analyze the overhead. We demonstrate the effectiveness of our approach by showing how routing algorithms can be implemented. We also report on results from experiments with real sensor-node hardware.


A Robust and Secure Aggregation Protocol for Wireless Sensor Networks

Abstract: The purpose of a wireless sensor network (WSN) is to provide the users with access to the information of interest from data gathered by spatially distributed sensors. Generally the users require only certain aggregate functions of this distributed data. Computation of this aggregate data under the end-to-end information flow paradigm by communicating all the relevant data to a central collector node is a highly inefficient solution for this purpose. An alternative proposition is to perform in-network computation. This, however, raises questions such as: what is the optimal way to compute an aggregate function from a set of statistically correlated values stored in different nodes; what is the security of such aggregation as the results sent by a compromised or faulty node in the network can adversely affect the accuracy of the computed result. In this paper, we have presented an energy-efficient aggregation algorithm for WSNs that is secure and robust against malicious insider attack by any compromised or faulty node in the network. In contrast to the traditional snapshot aggregation approach in WSNs, a node in the proposed algorithm instead of unicasting its sensed information to its parent node, broadcasts its estimate to all its neighbors. This makes the system more fault-tolerant and increase the information availability in the network. The simulations conducted on the proposed algorithm have produced results that demonstrate its effectiveness.


Experimental Performance Evaluation of Location Distinction for MIMO Channels

Abstract: Location distinction is defined as determining whether or not the position of a device has changed. We introduce methods and metrics for performing location distinction in multiple-input multiple-output (MIMO) wireless networks. Using MIMO channel measurements from two different testbeds, we evaluate the performance of temporal signature-based location distinction with varying system parameters, and show that it can be applied to MIMO channels with favorable results. In particular, a 2x2 MIMO channel with a bandwidth of 80 MHz allows a 64-fold reduction in miss rate over the SISO channel for a fixed false alarm rate, achieving as small as 4 x 10^-4 probability of false alarm for a 2.4 x 10^-4 probability of missed detection. The very high reliability of MIMO location distinction enables location distinction systems to detect the change in position of a transmitter even when using a single receiver.


SafeVchat: Detecting Obscene Content and Misbehaving Users in Online Video Chat Services

Abstract: Online video chat services such as Chatroulette, Omegle, and vChatter that randomly match pairs of users in video chat sessions are fast becoming very popular, with over a million users per month in the case of Chatroulette. A key problem encountered in such systems is the presence of flashers and obscene content. This problem is especially acute given the presence of underage minors in such systems. This paper presents SafeVchat, a novel solution to the problem of flasher detection that employs an array of image detection algorithms. A key contribution of the paper concerns how the results of the individual detectors are fused together into an overall decision classifying the user as misbehaving or not, based on Dempster-Shafer Theory. The paper introduces a novel, motion-based skin detection method that achieves significantly higher recall and better precision. The proposed methods have been evaluated over real world data and image traces obtained from Chatroulette.com.


Reactive Valuations

Abstract: In sequential logic there is an order in which the atomic propositions in an expression are evaluated. This order allows the same atomic proposition to have different values depending on which atomic propositions have already been evaluated. In the sequential propositional logic discussed in this thesis, such valuations are called "reactive" valuations, in contrast to "static" valuations as are common in e.g. ordinary propositional logic. There are many classes of these reactive valuations e.g., we can define a class of reactive valuations such that the value for each atomic proposition remains the same until another atomic proposition is evaluated. This Master of Logic thesis consists of a study of some of the properties of this logic. We take a closer look at some of the classes of reactive valuations. We particularly focus on the relation between the axiomatization and the semantics. Consequently, the main part of this thesis focuses on proving soundness and completeness. Furthermore, we show that the axioms in the provided axiomatizations are independent i.e., there are no redundant axioms present. Finally, we show {\omega}-completeness for two classes of reactive valuations.


Deflation and Certified Isolation of Singular Zeros of Polynomial Systems

Abstract: We develop a new symbolic-numeric algorithm for the certification of singular isolated points, using their associated local ring structure and certified numerical computations. An improvement of an existing method to compute inverse systems is presented, which avoids redundant computation and reduces the size of the intermediate linear systems to solve. We derive a one-step deflation technique, from the description of the multiplicity structure in terms of differentials. The deflated system can be used in Newton-based iterative schemes with quadratic convergence. Starting from a polynomial system and a small-enough neighborhood, we obtain a criterion for the existence and uniqueness of a singular root of a given multiplicity structure, applying a well-chosen symbolic perturbation. Standard verification methods, based eg. on interval arithmetic and a fixed point theorem, are employed to certify that there exists a unique perturbed system with a singular root in the domain. Applications to topological degree computation and to the analysis of real branches of an implicit curve illustrate the method.


Ensuring Correctness at the Application Level: a Software Framework Approach

Abstract: As scientific applications extend to the simulation of more and more complex systems, they involve an increasing number of abstraction levels, at each of which errors can emerge and across which they can propagate; tools for correctness evaluation and enforcement at every level (from the code level to the application level) are therefore necessary. Whilst code-level debugging tools are already a well established standard, application-level tools are lagging behind, possibly due to their stronger dependence on the application's details. In this paper, we describe the programming model introduced by the Cactus framework, review the High Performance Computing (HPC) challenges that Cactus is designed to address, and illustrate the correctness strategies that are currently available in Cactus at the code, component, and application level.


Multi-Stage Improved Route Planning Approach: theoretical foundations

Abstract: A new approach to the static route planning problem, based on a multi-staging concept and a \emph{scope} notion, is presented. The main goal (besides implied efficiency of planning) of our approach is to address---with a solid theoretical foundation---the following two practically motivated aspects: a \emph{route comfort} and a very \emph{limited storage} space of a small navigation device, which both do not seem to be among the chief objectives of many other studies. We show how our novel idea can tackle both these seemingly unrelated aspects at once, and may also contribute to other established route planning approaches with which ours can be naturally combined. We provide a theoretical proof that our approach efficiently computes exact optimal routes within this concept, as well as we demonstrate with experimental results on publicly available road networks of the US the good practical performance of the solution.


A note on triangle-free graphs

Abstract: We show that if $G$ is a simple triangle-free graph with $n\geq 3$ vertices, without a perfect matching, and having a minimum degree at least $\frac{n-1}{2}$, then $G$ is isomorphic either to $C_5$ or to $K_{\frac{n-1}{2},\frac{n+1}{2}}$.


A Symbolic Transformation Language and its Application to a Multiscale Method

Abstract: The context of this work is the design of a software, called MEMSALab, dedicated to the automatic derivation of multiscale models of arrays of micro- and nanosystems. In this domain a model is a partial differential equation. Multiscale methods approximate it by another partial differential equation which can be numerically simulated in a reasonable time. The challenge consists in taking into account a wide range of geometries combining thin and periodic structures with the possibility of multiple nested scales. In this paper we present a transformation language that will make the development of MEMSALab more feasible. It is proposed as a Maple package for rule-based programming, rewriting strategies and their combination with standard Maple code. We illustrate the practical interest of this language by using it to encode two examples of multiscale derivations, namely the two-scale limit of the derivative operator and the two-scale model of the stationary heat equation.


Psi-calculi: a framework for mobile processes with nominal data and logic

Abstract: The framework of psi-calculi extends the pi-calculus with nominal datatypes for data structures and for logical assertions and conditions. These can be transmitted between processes and their names can be statically scoped as in the standard pi-calculus. Psi-calculi can capture the same phenomena as other proposed extensions of the pi-calculus such as the applied pi-calculus, the spi-calculus, the fusion calculus, the concurrent constraint pi-calculus, and calculi with polyadic communication channels or pattern matching. Psi-calculi can be even more general, for example by allowing structured channels, higher-order formalisms such as the lambda calculus for data structures, and predicate logic for assertions. We provide ample comparisons to related calculi and discuss a few significant applications. Our labelled operational semantics and definition of bisimulation is straightforward, without a structural congruence. We establish minimal requirements on the nominal data and logic in order to prove general algebraic properties of psi-calculi, all of which have been checked in the interactive theorem prover Isabelle. Expressiveness of psi-calculi significantly exceeds that of other formalisms, while the purity of the semantics is on par with the original pi-calculus.


Fast Vertex Guarding for Polygons

Abstract: For a polygon P with n vertices, the vertex guarding problem asks for the minimum subset G of P's vertices such that every point in P is seen by at least one point in G. This problem is NP-complete and APX-hard. The first approximation algorithm (Ghosh, 1987) involves decomposing P into O(n^4) cells that are equivalence classes for visibility from the vertices of P. This discretized problem can then be treated as an instance of set cover and solved in O(n^5) time with a greedy O(log n)-approximation algorithm. Ghosh (2010) recently revisited the algorithm, noting that minimum visibility decompositions for simple polygons (Bose et al., 2000) have only O(n^3) cells, improving the running time of the algorithm to O(n^4) for simple polygons. In this paper we show that, since minimum visibility decompositions for simple polygons have only O(n^2) cells of minimal visibility (Bose et al., 2000), the running time of the algorithm can be further improved to O(n^3). This result was obtained independently by Jang and Kwon (2011). We extend the result of Bose et al. to polygons with holes, showing that a minimum visibility decomposition of a polygon with h holes has only O((h+1)n^3) cells and only O((h+1)^2 n^2) cells of minimal visibility. We exploit this result to obtain a faster algorithm for vertex guarding polygons with holes. We then show that, in the same time complexity, we can attain approximation factors of O(log log(opt)) for simple polygons and O((1+\log((h+1))) log(opt)) for polygons with holes.


Collaborative Filtering without Explicit Feedbacks for Digital Recorders

Abstract: Recommendation is usually reduced to a prediction problem over the function $r(u_a, e_i)$ that returns the expected rating of element $e_i$ for user $u_a$. In the IPTV domain, we deal with an environment where the definitions of all the parameters involved in this function (i.e., user profiles, feedback ratings and elements) are controversial. To our knowledge, this paper represents the first attempt to run collaborative filtering algorithms without inner assumptions: we start our analysis from an unstructured set of recordings, before performing a data pre-processing phase in order to extract useful information. Hence, we experiment with a real Digital Video Recorder system where EPG have not been provided to the user for selecting event timings and where explicit feedbacks were not collected.


Introduction to the Bag of Features Paradigm for Image Classification and Retrieval

Abstract: The past decade has seen the growing popularity of Bag of Features (BoF) approaches to many computer vision tasks, including image classification, video search, robot localization, and texture recognition. Part of the appeal is simplicity. BoF methods are based on orderless collections of quantized local image descriptors; they discard spatial information and are therefore conceptually and computationally simpler than many alternative methods. Despite this, or perhaps because of this, BoF-based systems have set new performance standards on popular image classification benchmarks and have achieved scalability breakthroughs in image retrieval. This paper presents an introduction to BoF image representations, describes critical design choices, and surveys the BoF literature. Emphasis is placed on recent techniques that mitigate quantization errors, improve feature detection, and speed up image retrieval. At the same time, unresolved issues and fundamental challenges are raised. Among the unresolved issues are determining the best techniques for sampling images, describing local image features, and evaluating system performance. Among the more fundamental challenges are how and whether BoF methods can contribute to localizing objects in complex images, or to associating high-level semantics with natural images. This survey should be useful both for introducing new investigators to the field and for providing existing researchers with a consolidated reference to related work.


CAL: A Language for Aggregating Functional and Extrafunctional Constraints in Streaming Networks

Abstract: In this article we present the {\em Constraint Aggregation Language} (CAL), a declarative language for describing properties of stateless program components that interact by exchanging messages. CAL allows one to describe functional as well as extra-functional behaviours, such as computation latency. The CAL language intention is to be able to describe the behaviour of so-called boxes in the context of S-Net. However, the language would find application in other coordination models based on stateless components.


Efficient Independence-Based MAP Approach for Robust Markov Networks Structure Discovery

Abstract: This work introduces the IB-score, a family of independence-based score functions for robust learning of Markov networks independence structures. Markov networks are a widely used graphical representation of probability distributions, with many applications in several fields of science. The main advantage of the IB-score is the possibility of computing it without the need of estimation of the numerical parameters, an NP-hard problem, usually solved through an approximate, data-intensive, iterative optimization. We derive a formal expression for the IB-score from first principles, mainly maximum a posteriori and conditional independence properties, and exemplify several instantiations of it, resulting in two novel algorithms for structure learning: IBMAP-HC and IBMAP-TS. Experimental results over both artificial and real world data show these algorithms achieve important error reductions in the learnt structures when compared with the state-of-the-art independence-based structure learning algorithm GSMN, achieving increments of more than 50% in the amount of independencies they encode correctly, and in some cases, learning correctly over 90% of the edges that GSMN learnt incorrectly. Theoretical analysis shows IBMAP-HC proceeds efficiently, achieving these improvements in a time polynomial to the number of random variables in the domain.


A Generalized Criterion for Signature Related Gr\"obner Basis Algorithms

Abstract: A generalized criterion for signature related algorithms to compute Gr\"obner basis is proposed in this paper. Signature related algorithms are a popular kind of algorithms for computing Gr\"obner basis, including the famous F5 algorithm, the extended F5 algorithm and the GVW algorithm. The main purpose of current paper is to study in theory what kind of criteria is correct in signature related algorithms and provide a generalized method to develop new criteria. For this purpose, a generalized criterion is proposed. The generalized criterion only relies on a general partial order defined on a set of polynomials. When specializing the partial order to appropriate specific orders, the generalized criterion can specialize to almost all existing criteria of signature related algorithms. For {\em admissible} partial orders, a complete proof of the correctness of the algorithm based on this generalized criterion is also presented. This proof has no extra requirements on the computing order of critical pairs, and is also valid for non-homogeneous polynomial systems. More importantly, the partial orders implied by existing criteria are admissible. Besides, one can also check whether a new criterion is correct in signature related algorithms or even develop new criteria by using other admissible partial orders in the generalized criterion.


Multi-objective Optimization For The Dynamic Multi-Pickup and Delivery Problem with Time Windows

Abstract: The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for multi-objective optimization of a dynamic multi pickup and delivery problem with time windows (Dynamic m-PDPTW). We propose a brief literature review of the PDPTW, present our approach based on Pareto dominance method and lower bounds, to give a satisfying solution to the Dynamic m-PDPTW minimizing the compromise between total travel cost and total tardiness time. Computational results indicate that the proposed algorithm gives good results with a total tardiness equal to zero with a tolerable cost.


Behavioral On-Line Advertising

Abstract: We present a new algorithm for behavioral targeting of banner advertisements. We record different user's actions such as clicks, search queries and page views. We use the collected information on the user to estimate in real time the probability of a click on a banner. A banner is displayed if it either has the highest probability of being clicked or if it is the one that generates the highest average profit.


Categorical Abstract Rewriting Systems and Functoriality of Graph Transformation

Abstract: Rewriting systems are often defined as binary relations over a given set of objects. This simple definition is used to describe various properties of rewriting such as termination, confluence, normal forms etc. In this paper, we introduce a new notion of abstract rewriting in the framework of categories. Then, we define the functoriality property of rewriting systems. This property is sometimes called vertical composition. We show that most of graph transformation systems are functorial and provide a counter-example of graph transformation systems which is not functorial.


Inducing the LCP-Array

Abstract: We show how to modify the linear-time construction algorithm for suffix arrays based on induced sorting (Nong et al., DCC'09) such that it computes the array of longest common prefixes (LCP-array) as well. Practical tests show that this outperforms recent LCP-array construction algorithms (Gog and Ohlebusch, ALENEX'11).


The "psychological map of the brain", as a personal information card (file), - a project for the student of the 21st century

Abstract: We suggest a procedure that is relevant both to electronic performance and human psychology, so that the creative logic and the respect for human nature appear in a good agreement. The idea is to create an electronic card containing basic information about a person's psychological behavior in order to make it possible to quickly decide about the suitability of one for another. This "psychological electronics" approach could be tested via student projects.


Computation for Supremal Simulation-Based Controllable and Strong Observable Subautomata

Abstract: Bisimulation relation has been successfully applied to computer science and control theory. In our previous work, simulation-based controllability and simulation-based observability are proposed, under which the existence of bisimilarity supervisor is guaranteed. However, a given specification automaton may not satisfy these conditions, and a natural question is how to compute a maximum permissive subspecification. This paper aims to answer this question and investigate the computation of the supremal simulation-based controllable and strong observable subautomata with respect to given specifications by the lattice theory. In order to achieve the supremal solution, three monotone operators, namely simulation operator, controllable operator and strong observable operator, are proposed upon the established complete lattice. Then, inequalities based on these operators are formulated, whose solution is the simulation-based controllable and strong observable set. In particular, a sufficient condition is presented to guarantee the existence of the supremal simulation-based controllable and strong observable subautomata. Furthermore, an algorithm is proposed to compute such subautomata.


Error-Free Multi-Valued Consensus with Byzantine Failures

Abstract: In this paper, we present an efficient deterministic algorithm for consensus in presence of Byzantine failures. Our algorithm achieves consensus on an $L$-bit value with communication complexity $O(nL + n^4 L^{0.5} + n^6)$ bits, in a network consisting of $n$ processors with up to $t$ Byzantine failures, such that $t<n/3$. For large enough $L$, communication complexity of the proposed algorithm approaches $O(nL)$ bits. In other words, for large $L$, the communication complexity is linear in the number of processors in the network. This is an improvement over the work of Fitzi and Hirt (from PODC 2006), who proposed a probabilistically correct multi-valued Byzantine consensus algorithm with a similar complexity for large $L$. In contrast to the algorithm by Fitzi and Hirt, our algorithm is guaranteed to be always error-free. Our algorithm require no cryptographic technique, such as authentication, nor any secret sharing mechanism. To the best of our knowledge, we are the first to show that, for large $L$, error-free multi-valued Byzantine consensus on an $L$-bit value is achievable with $O(nL)$ bits of communication.


Multiplicity Preserving Triangular Set Decomposition of Two Polynomials

Abstract: In this paper, a multiplicity preserving triangular set decomposition algorithm is proposed for a system of two polynomials. The algorithm decomposes the variety defined by the polynomial system into unmixed components represented by triangular sets, which may have negative multiplicities. In the bivariate case, we give a complete algorithm to decompose the system into multiplicity preserving triangular sets with positive multiplicities. We also analyze the complexity of the algorithm in the bivariate case. We implement our algorithm and show the effectiveness of the method with extensive experiments.


Clustering Protein Sequences Given the Approximation Stability of the Min-Sum Objective Function

Abstract: We study the problem of efficiently clustering protein sequences in a limited information setting. We assume that we do not know the distances between the sequences in advance, and must query them during the execution of the algorithm. Our goal is to find an accurate clustering using few queries. We model the problem as a point set $S$ with an unknown metric $d$ on $S$, and assume that we have access to \emph{one versus all} distance queries that given a point $s \in S$ return the distances between $s$ and all other points. Our one versus all query represents an efficient sequence database search program such as BLAST, which compares an input sequence to an entire data set. Given a natural assumption about the approximation stability of the \emph{min-sum} objective function for clustering, we design a provably accurate clustering algorithm that uses few one versus all queries. In our empirical study we show that our method compares favorably to well-established clustering algorithms when we compare computationally derived clusterings to gold-standard manual classifications.


Diversification improves interpolation

Abstract: We consider the problem of interpolating an unknown multivariate polynomial with coefficients taken from a finite field or as numerical approximations of complex numbers. Building on the recent work of Garg and Schost, we improve on the best-known algorithm for interpolation over large finite fields by presenting a Las Vegas randomized algorithm that uses fewer black box evaluations. Using related techniques, we also address numerical interpolation of sparse polynomials with complex coefficients, and provide the first provably stable algorithm (in the sense of relative error) for this problem, at the cost of modestly more evaluations. A key new technique is a randomization which makes all coefficients of the unknown polynomial distinguishable, producing what we call a diverse polynomial. Another departure from most previous approaches is that our algorithms do not rely on root finding as a subroutine. We show how these improvements affect the practical performance with trial implementations.


Model Checking of Continuous-Time Markov Chains Against Timed Automata Specifications

Abstract: We study the verification of a finite continuous-time Markov chain (CTMC) C against a linear real-time specification given as a deterministic timed automaton (DTA) A with finite or Muller acceptance conditions. The central question that we address is: what is the probability of the set of paths of C that are accepted by A, i.e., the likelihood that C satisfies A? It is shown that under finite acceptance criteria this equals the reachability probability in a finite piecewise deterministic Markov process (PDP), whereas for Muller acceptance criteria it coincides with the reachability probability of terminal strongly connected components in such a PDP. Qualitative verification is shown to amount to a graph analysis of the PDP. Reachability probabilities in our PDPs are then characterized as the least solution of a system of Volterra integral equations of the second type and are shown to be approximated by the solution of a system of partial differential equations. For single-clock DTA, this integral equation system can be transformed into a system of linear equations where the coefficients are solutions of ordinary differential equations. As the coefficients are in fact transient probabilities in CTMCs, this result implies that standard algorithms for CTMC analysis suffice to verify single-clock DTA specifications.


Systolic Arrays for Lattice-Reduction-Aided MIMO Detection

Abstract: Multiple-input, multiple-output (MIMO) technology provides high data rate and enhanced QoS for wireless com- munications. Since the benefits from MIMO result in a heavy computational load in detectors, the design of low-complexity sub-optimum receivers is currently an active area of research. Lattice-reduction-aided detection (LRAD) has been shown to be an effective low-complexity method with near-ML performance. In this paper we advocate the use of systolic array architectures for MIMO receivers, and in particular we exhibit one of them based on LRAD. The "LLL lattice reduction algorithm" and the ensuing linear detections or successive spatial-interference cancellations can be located in the same array, which is con- siderably hardware-efficient. Since the conventional form of the LLL algorithm is not immediately suitable for parallel processing, two modified LLL algorithms are considered here for the systolic array. LLL algorithm with full-size reduction (FSR-LLL) is one of the versions more suitable for parallel processing. Another variant is the all-swap lattice-reduction (ASLR) algorithm for complex-valued lattices, which processes all lattice basis vectors simultaneously within one iteration. Our novel systolic array can operate both algorithms with different external logic controls. In order to simplify the systolic array design, we replace the Lov\'asz condition in the definition of LLL-reduced lattice with the looser Siegel condition. Simulation results show that for LR- aided linear detections, the bit-error-rate performance is still maintained with this relaxation. Comparisons between the two algorithms in terms of bit-error-rate performance, and average FPGA processing time in the systolic array are made, which shows that ASLR is a better choice for a systolic architecture, especially for systems with a large number of antennas.


Transductive-Inductive Cluster Approximation Via Multivariate Chebyshev Inequality

Abstract: Approximating adequate number of clusters in multidimensional data is an open area of research, given a level of compromise made on the quality of acceptable results. The manuscript addresses the issue by formulating a transductive inductive learning algorithm which uses multivariate Chebyshev inequality. Considering clustering problem in imaging, theoretical proofs for a particular level of compromise are derived to show the convergence of the reconstruction error to a finite value with increasing (a) number of unseen examples and (b) the number of clusters, respectively. Upper bounds for these error rates are also proved. Non-parametric estimates of these error from a random sample of sequences empirically point to a stable number of clusters. Lastly, the generalization of algorithm can be applied to multidimensional data sets from different fields.


Tagging with DHARMA, a DHT-based Approach for Resource Mapping through Approximation

Abstract: We introduce collaborative tagging and faceted search on structured P2P systems. Since a trivial and brute force mapping of an entire folksonomy over a DHT-based system may reduce scalability, we propose an approximated graph maintenance approach. Evaluations on real data coming from Last.fm prove that such strategies reduce vocabulary noise (i.e., representation's overfitting phenomena) and hotspots issues.


Relay Selection with Partial Information in Wireless Sensor Networks

Abstract: Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. When a node (referred to as the source) gets a packet to forward, either by detecting an event or from an upstream node, it has to wait for its neighbors in a forwarding set (referred to as relays) to wake-up. Each of the relays is associated with a random reward (e.g., the progress made towards the sink) that is iid. To begin with, the source is uncertain about the number of relays, their wake-up times and the reward values, but knows their distributions. At each relay wake-up instant, when a relay reveals its reward value, the source's problem is to forward the packet or to wait for further relays to wake-up. In this setting, we seek to minimize the expected waiting time at the source subject to a lower bound on the average reward. In terms of the operations research literature, our work can be considered as a variant of the asset selling problem. We formulate the relay selection problem as a partially observable Markov decision process (POMDP), where the unknown state is the number of relays. We begin by considering the case where the source knows the number of relays. For the general case, where the source only knows a pmf on the number of relays, it has to maintain a posterior pmf on the number of relays and forward the packet iff the pmf is in an optimum stopping set. We show that the optimum stopping set is convex and obtain inner and outer bounds to this set. The computational complexity of the above policies motivates us to formulate an alternative simplified model, the optimal policy for which is a simple threshold rule. We provide simulation results to compare the performance of the various one-hop and end-to-end forwarding policies.


U-Learning Within A Context-Aware Multiagent Environment

Abstract: New technological developments have made it possible to interact with computer systems and applications anywhere and anytime. It is vital that these applications are able to adapt to the user, as a person, and to its current situation, whatever that is. Therefore, the premises for evolution towards a learning society and a knowledge economy are present. Hence, there is a stringent demand for new learner-centred frameworks that allow active participation of learners in knowledge creation within communities, organizations, territories and society, at large. This paper presents the multi-agent architecture of our context-aware system and the learning scenarios within ubiquitous learning environments that the system provides support for. This architecture is the outcome of our endeavour to develop ePH, a system for sharing public interest information and knowledge, which is accessible through always-on, context-aware services.


OSPF Weight Setting Optimization for Single Link Failures

Abstract: In operational networks, nodes are connected via multiple links for load sharing and redundancy. This is done to make sure that a failure of a link does not disconnect or isolate some parts of the network. However, link failures have an effect on routing, as the routers find alternate paths for the traffic originally flowing through the link which has failed. This effect is severe in case of failure of a critical link in the network, such as backbone links or the links carrying higher traffic loads. When routing is done using the Open Shortest Path First (OSPF) routing protocol, the original weight selection for the normal state topology may not be as efficient for the failure state. In this paper, we investigate the single link failure issue with an objective to find a weight setting which results in efficient routing in normal and failure states. We engineer Tabu Search Iterative heuristic using two different implementation strategies to solve the OSPF weight setting problem for link failure scenarios. We evaluate these heuristics and show through experimental results that both heuristics efficiently handle weight setting for the failure state. A comparison of both strategies is also presented.


Inter-organizational fault management: Functional and organizational core aspects of management architectures

Abstract: Outsourcing -- successful, and sometimes painful -- has become one of the hottest topics in IT service management discussions over the past decade. IT services are outsourced to external service provider in order to reduce the effort required for and overhead of delivering these services within the own organization. More recently also IT services providers themselves started to either outsource service parts or to deliver those services in a non-hierarchical cooperation with other providers. Splitting a service into several service parts is a non-trivial task as they have to be implemented, operated, and maintained by different providers. One key aspect of such inter-organizational cooperation is fault management, because it is crucial to locate and solve problems, which reduce the quality of service, quickly and reliably. In this article we present the results of a thorough use case based requirements analysis for an architecture for inter-organizational fault management (ioFMA). Furthermore, a concept of the organizational respective functional model of the ioFMA is given.


Integrated monitoring of multi-domain backbone connections -- Operational experience in the LHC optical private network

Abstract: Novel large scale research projects often require cooperation between various different project partners that are spread among the entire world. They do not only need huge computing resources, but also a reliable network to operate on. The Large Hadron Collider (LHC) at CERN is a representative example for such a project. Its experiments result in a vast amount of data, which is interesting for researchers around the world. For transporting the data from CERN to 11 data processing and storage sites, an optical private network (OPN) has been constructed. As the experiment data is highly valuable, LHC defines very high requirements to the underlying network infrastructure. In order to fulfil those requirements, the connections have to be managed and monitored permanently. In this paper, we present the integrated monitoring solution developed for the LHCOPN. We first outline the requirements and show how they are met on the single network layers. After that, we describe, how those single measurements can be combined into an integrated view. We cover design concepts as well as tool implementation highlights.


Two Multivehicle Routing Problems with Unit-Time Windows

Abstract: Two multivehicle routing problems are considered in the framework that a visit to a location must take place during a specific time window in order to be counted and all time windows are the same length. In the first problem, the goal is to visit as many locations as possible using a fixed number of vehicles. In the second, the goal is to visit all locations using the smallest number of vehicles possible. For the first problem, we present an approximation algorithm whose output path collects a reward within a constant factor of optimal for any fixed number of vehicles. For the second problem, our algorithm finds a 6-approximation to the problem on a tree metric, whenever a single vehicle could visit all locations during their time windows.


Speedup in the Traveling Repairman Problem with Constrained Time Windows

Abstract: A bicriteria approximation algorithm is presented for the unrooted traveling repairman problem, realizing increased profit in return for increased speedup of repairman motion. The algorithm generalizes previous results from the case in which all time windows are the same length to the case in which their lengths can range between l and 2. This analysis can extend to any range of time window lengths, following our earlier techniques. This relationship between repairman profit and speedup is applicable over a range of values that is dependent on the cost of putting the input in an especially desirable form, involving what are called "trimmed windows." For time windows with lengths between 1 and 2, the range of values for speedup $s$ for which our analysis holds is $1 \leq s \leq 6$. In this range, we establish an approximation ratio that is constant for any specific value of $s$.


Short Propositional Refutations for Dense Random 3CNF Formulas

Abstract: Random 3CNF formulas constitute an important distribution for measuring the average-case behavior of propositional proof systems. Lower bounds for random 3CNF refutations in many propositional proof systems are known. Most notably are the exponential-size resolution refutation lower bounds for random 3CNF formulas with $\Omega(n^{1.5-\epsilon}) $ clauses [Chvatal and Szemeredi (1988), Ben-Sasson and Wigderson (2001)]. On the other hand, the only known non-trivial upper bound on the size of random 3CNF refutations in a non-abstract propositional proof system is for resolution with $\Omega(n^{2}/\log n) $ clauses, shown by Beame et al. (2002). In this paper we show that already standard propositional proof systems, within the hierarchy of Frege proofs, admit short refutations for random 3CNF formulas, for sufficiently large clause-to-variable ratio. Specifically, we demonstrate polynomial-size propositional refutations whose lines are $TC^0$ formulas (i.e., $TC^0$-Frege proofs) for random 3CNF formulas with $ n $ variables and $ \Omega(n^{1.4}) $ clauses. The idea is based on demonstrating efficient propositional correctness proofs of the random 3CNF unsatisfiability witnesses given by Feige, Kim and Ofek (2006). Since the soundness of these witnesses is verified using spectral techniques, we develop an appropriate way to reason about eigenvectors in propositional systems. To carry out the full argument we work inside weak formal systems of arithmetic and use a general translation scheme to propositional proofs.


A QoS Routing Protocol based on Available Bandwidth Estimation for Wireless Ad Hoc Networks

Abstract: At the same time as the emergence of multimedia in mobile Ad hoc networks, research for the introduction of the quality of service (QoS) has received much attention. However, when designing a QoS solution, the estimation of the available resources still represents one of the main issues. This paper suggests an approach to estimate available resources on a node. This approach is based on the estimation of the busy ratio of the shared canal. We consider in our estimation the several constraints related to the Ad hoc transmission mode such as Interference phenomena. This approach is implemented on the AODV routing protocol. We call AODVwithQOS our new routing protocol. We also performed a performance evaluation by simulations using NS2 simulator. The results confirm that AODVwithQoS provides QoS support in ad hoc wireless networks with good performance and low overhead.


The Impact of Incomplete Information on Games in Parallel Relay Networks

Abstract: We consider the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in maximizing their own profit instead of the social welfare. We consider the practical situation where the channel state on any given relay path is not observable to the source or to the other relays. We examine different bargaining relationships between the source and the relays, and propose a framework for analyzing the efficiency loss induced by incomplete information. We analyze the source of the efficiency loss, and quantify the amount of inefficiency which results.


Self-Index Based on LZ77

Abstract: We introduce the first self-index based on the Lempel-Ziv 1977 compression format (LZ77). It is particularly competitive for highly repetitive text collections such as sequence databases of genomes of related species, software repositories, versioned document collections, and temporal text databases. Such collections are extremely compressible but classical self-indexes fail to capture that source of compressibility. Our self-index takes in practice a few times the space of the text compressed with LZ77 (as little as 2.6 times), extracts 1--2 million characters of the text per second, and finds patterns at a rate of 10--50 microseconds per occurrence. It is smaller (up to one half) than the best current self-index for repetitive collections, and faster in many cases.


Linear-Space Data Structures for Range Mode Query in Arrays

Abstract: A mode of a multiset $S$ is an element $a \in S$ of maximum multiplicity; that is, $a$ occurs at least as frequently as any other element in $S$. Given a list $A[1:n]$ of $n$ items, we consider the problem of constructing a data structure that efficiently answers range mode queries on $A$. Each query consists of an input pair of indices $(i, j)$ for which a mode of $A[i:j]$ must be returned. We present an $O(n^{2-2\epsilon})$-space static data structure that supports range mode queries in $O(n^\epsilon)$ time in the worst case, for any fixed $\epsilon \in [0,1/2]$. When $\epsilon = 1/2$, this corresponds to the first linear-space data structure to guarantee $O(\sqrt{n})$ query time. We then describe three additional linear-space data structures that provide $O(k)$, $O(m)$, and $O(|j-i|)$ query time, respectively, where $k$ denotes the number of distinct elements in $A$ and $m$ denotes the frequency of the mode of $A$. Finally, we examine generalizing our data structures to higher dimensions.


Context Capture in Software Development

Abstract: The context of a software developer is something hard to define and capture, as it represents a complex network of elements across different dimensions that are not limited to the work developed on an IDE. We propose the definition of a software developer context model that takes into account all the dimensions that characterize the work environment of the developer. We are especially focused on what the software developer context encompasses at the project level and how it can be captured. The experimental work done so far show that useful context information can be extracted from project management tools. The extraction, analysis and availability of this context information can be used to enrich the work environment of the developer with additional knowledge to support her/his work.


Proceedings Fifth Workshop on Intersection Types and Related Systems

Abstract: This volume contains the proceedings of the Fifth International Workshop on Intersection Types and Related Systems (ITRS 2010). The workshop was held in Edinburgh, Scotland, on July 9th 2010, as part of FLoC 2010 and affiliated with LICS 2010. The ITRS workshop series aim at bringing together researchers working on both the theory and practical applications of systems based on intersection types and related approaches (e.g., union types, refinement types, behavioral types).


GridCertLib: a Single Sign-on Solution for Grid Web Applications and Portals

Abstract: This paper describes the design and implementation of GridCertLib, a Java library leveraging a Shibboleth-based authentication infrastructure and the SLCS online certificate signing service, to provide short-lived X.509 certificates and Grid proxies. The main use case envisioned for GridCertLib, is to provide seamless and secure access to Grid/X.509 certificates and proxies in web applications and portals: when a user logs in to the portal using Shibboleth authentication, GridCertLib can automatically obtain a Grid/X.509 certificate from the SLCS service and generate a VOMS proxy from it. We give an overview of the architecture of GridCertLib and briefly describe its programming model. Its application to some deployment scenarios is outlined, as well as a report on practical experience integrating GridCertLib into portals for Bioinformatics and Computational Chemistry applications, based on the popular P-GRADE and Django softwares.


Languages of Dot-depth One over Infinite Words

Abstract: Over finite words, languages of dot-depth one are expressively complete for alternation-free first-order logic. This fragment is also known as the Boolean closure of existential first-order logic. Here, the atomic formulas comprise order, successor, minimum, and maximum predicates. Knast (1983) has shown that it is decidable whether a language has dot-depth one. We extend Knast's result to infinite words. In particular, we describe the class of languages definable in alternation-free first-order logic over infinite words, and we give an effective characterization of this fragment. This characterization has two components. The first component is identical to Knast's algebraic property for finite words and the second component is a topological property, namely being a Boolean combination of Cantor sets. As an intermediate step we consider finite and infinite words simultaneously. We then obtain the results for infinite words as well as for finite words as special cases. In particular, we give a new proof of Knast's Theorem on languages of dot-depth one over finite words.


The Role of Normalization in the Belief Propagation Algorithm

Abstract: An important part of problems in statistical physics and computer science can be expressed as the computation of marginal probabilities over a Markov Random Field. The belief propagation algorithm, which is an exact procedure to compute these marginals when the underlying graph is a tree, has gained its popularity as an efficient way to approximate them in the more general case. In this paper, we focus on an aspect of the algorithm that did not get that much attention in the literature, which is the effect of the normalization of the messages. We show in particular that, for a large class of normalization strategies, it is possible to focus only on belief convergence. Following this, we express the necessary and sufficient conditions for local stability of a fixed point in terms of the graph structure and the beliefs values at the fixed point. We also explicit some connexion between the normalization constants and the underlying Bethe Free Energy.


A Model for Coherent Distributed Memory For Race Condition Detection

Abstract: We present a new model for distributed shared memory systems, based on remote data accesses. Such features are offered by network interface cards that allow one-sided operations, remote direct memory access and OS bypass. This model leads to new interpretations of distributed algorithms allowing us to propose an innovative detection technique of race conditions only based on logical clocks. Indeed, the presence of (data) races in a parallel program makes it hard to reason about and is usually considered as a bug.


Measuring Performance of Continuous-Time Stochastic Processes using Timed Automata

Abstract: We propose deterministic timed automata (DTA) as a model-independent language for specifying performance and dependability measures over continuous-time stochastic processes. Technically, these measures are defined as limit frequencies of locations (control states) of a DTA that observes computations of a given stochastic process. Then, we study the properties of DTA measures over semi-Markov processes in greater detail. We show that DTA measures over semi-Markov processes are well-defined with probability one, and there are only finitely many values that can be assumed by these measures with positive probability. We also give an algorithm which approximates these values and the associated probabilities up to an arbitrarily small given precision. Thus, we obtain a general and effective framework for analysing DTA measures over semi-Markov processes.


Relating coalgebraic notions of bisimulation

Abstract: The theory of coalgebras, for an endofunctor on a category, has been proposed as a general theory of transition systems. We investigate and relate four generalizations of bisimulation to this setting, providing conditions under which the four different generalizations coincide. We study transfinite sequences whose limits are the greatest bisimulations.


Indexing Properties of Primitive Pythagorean Triples for Cryptography Applications

Abstract: This paper presents new properties of Primitive Pythagorean Triples (PPT) that have relevance in applications where events of different probability need to be generated and in cryptography.


Networking

Abstract: This paper discusses an efficient approach to design and implement a highly available peer- to-peer system irrespective of peer timing and churn.


Proceedings Foundations for Interface Technologies

Abstract: FIT stands for Foundations of Interface Technologies. Component-based design is widely considered as a major approach to developing systems in a time and cost effective way. Central in this approach is the notion of an interface. Interfaces summarize the externally visible properties of a component and are seen as a key to achieving component interoperability and to predict global system behavior based on the component behavior. To capture the intricacy of complex software products, rich interfaces have been proposed. These interfaces do not only specify syntactic properties, such as the signatures of methods and operations, but also take into account behavioral and extra-functional properties, such as quality of service, security and dependability. Rich interfaces have been proposed for describing, e.g., the legal sequences of messages or method calls accepted by components, or the resource and timing constraints in embedded software. The development of a rigorous framework for the specification and analysis of rich interfaces is challenging. The aim of this workshop is to bring together researchers who are interested in the formal underpinnings of interface technologies


A Comparative Agglomerative Hierarchical Clustering Method to Cluster Implemented Course

Abstract: There are many clustering methods, such as hierarchical clustering method. Most of the approaches to the clustering of variables encountered in the literature are of hierarchical type. The great majority of hierarchical approaches to the clustering of variables are of agglomerative nature. The agglomerative hierarchical approach to clustering starts with each observation as its own cluster and then continually groups the observations into increasingly larger groups. Higher Learning Institution (HLI) provides training to introduce final-year students to the real working environment. In this research will use Euclidean single linkage and complete linkage. MATLAB and HCE 3.5 software will used to train data and cluster course implemented during industrial training. This study indicates that different method will create a different number of clusters.


Online Verification of Control Parameter Calculations in Communication Based Train Control System

Abstract: Communication Based Train Control (CBTC) system is the state-of-the-art train control system. In a CBTC system, to guarantee the safety of train operation, trains communicate with each other intensively and adjust their control modes autonomously by computing critical control parameters, e.g. velocity range, according to the information they get. As the correctness of the control parameters generated are critical to the safety of the system, a method to verify these parameters is a strong desire in the area of train control system. In this paper, we present our ideas of how to model and verify the control parameter calculations in a CBTC system efficiently. - As the behavior of the system is highly nondeterministic, it is difficult to build and verify the complete behavior space model of the system online in advance. Thus, we propose to model the system according to the ongoing behavior model induced by the control parameters. - As the parameters are generated online and updated very quickly, the verification result will be meaningless if it is given beyond the time bound, since by that time the model will be changed already. Thus, we propose a method to verify the existence of certain dangerous scenarios in the model online quickly. To demonstrate the feasibility of these proposed approaches, we present the composed linear hybrid automata with readable shared variables as a modeling language to model the control parameters calculation and give a path-oriented reachability analysis technique for the scenario-based verification of this model. We demonstrate the model built for the CBTC system, and show the performance of our technique in fast online verification. Last but not least, as CBTC system is a typical CPS system, we also give a short discussion of the potential directions for CPS verification in this paper.


On Making Directed Graphs Eulerian

Abstract: A directed graph is called Eulerian, if it contains a tour that traverses every arc in the graph exactly once. We study the problem of Eulerian extension (EE) where a directed multigraph G and a weight function is given and it is asked whether G can be made Eulerian by adding arcs whose total weight does not exceed a given threshold. This problem is motivated through applications in vehicle routing and flowshop scheduling. However, EE is NP-hard and thus we use the parameterized complexity framework to analyze it. In parameterized complexity, the running time of algorithms is considered not only with respect to input length, but also with respect to other properties of the input - called "parameters". Dorn et. al. proved that EE can be solved in O(4^k n^4) time, where k denotes the parameter "number of arcs that have to be added". In this thesis, we analyze EE with respect to the (smaller) parameters "number c of connected components in the input graph" and "sum b over indeg(v) - outdeg(v) for all vertices v in the input graph where this value is positive". We prove that there is an algorithm for EE whose running time is polynomial except for the term 4^(c log(bc^2)). To obtain this result, we make several observations about the sets of arcs that have to be added to the input graph in order to make it Eulerian. We build upon these observations to restate EE in a matching context. This matching formulation of EE might be an important tool to solve the question of whether EE can be solved within running time whose superpolynomial part depends only on c. We also consider polynomial time preprocessing routines for EE and show that these routines cannot yield instances whose size depends polynomially only on either of the parameters b, c, k unless coNP is contained in NP/poly.