On Modeling Dependency between MapReduce Configuration Parameters and Total Execution Time

Abstract: In this paper, we propose an analytical method to model the dependency between configuration parameters and total execution time of Map-Reduce applications. Our approach has three key phases: profiling, modeling, and prediction. In profiling, an application is run several times with different sets of MapReduce configuration parameters to profile the execution time of the application on a given platform. Then in modeling, the relation between these parameters and total execution time is modeled by multivariate linear regression. Among the possible configuration parameters, two main parameters have been used in this study: the number of Mappers, and the number of Reducers. For evaluation, two standard applications (WordCount, and Exim Mainlog parsing) are utilized to evaluate our technique on a 4-node MapReduce platform.


Contribution of Case Based Reasoning (CBR) in the Exploitation of Return of Experience. Application to Accident Scenarii in Railroad Transport

Abstract: The study is from a base of accident scenarii in rail transport (feedback) in order to develop a tool to share build and sustain knowledge and safety and secondly to exploit the knowledge stored to prevent the reproduction of accidents / incidents. This tool should ultimately lead to the proposal of prevention and protection measures to minimize the risk level of a new transport system and thus to improve safety. The approach to achieving this goal largely depends on the use of artificial intelligence techniques and rarely the use of a method of automatic learning in order to develop a feasibility model of a software tool based on case based reasoning (CBR) to exploit stored knowledge in order to create know-how that can help stimulate domain experts in the task of analysis, evaluation and certification of a new system.


On the Role of Vehicular Mobility in Cooperative Content Caching

Abstract: In this paper, we analyze the performance of cooperative content caching in vehicular ad hoc networks (VANETs). In particular, we characterize, using analysis and simulations, the behavior of the probability of outage (i.e. not finding a requested data chunk at a neighbor) under freeway vehicular mobility. First, we introduce a formal definition for the probability of outage in the context of cooperative content caching. Second, we characterize, analytically, the outage probability under vehicular and random mobility scenarios. Next, we verify the analytical results using simulations and compare the performance under a number of plausible mobility scenarios. This provides key insights into the problem and the involved trade-offs and enable us to assess the potential opportunity offered by the, somewhat structured, vehicular mobility that can be exploited by cooperative content caching schemes. The presented numerical results exhibit complete agreement between the analytical and simulation studies. Finally, we observe that vehicular mobility creates opportunities for enhanced outage performance under practically relevant scenarios.


Verification and Diagnosis Infrastructure of SoC HDL-model

Abstract: This article describes technology for diagnosing SoC HDL-models, based on transactional graph. Diagnosis method is focused to considerable decrease the time of fault detection and memory for storage of diagnosis matrix by means of forming ternary relations in the form of test, monitor, and functional component. The following problems are solved: creation of digital system model in the form of transaction graph and multi-tree of fault detection tables, as well as ternary matrices for activating functional components in tests, relative to the selected set of monitors; development of a method for analyzing the activation matrix to detect the faults with given depth and synthesizing logic functions for subsequent embedded hardware fault diagnosing.


Target set selection problem for honeycomb networks

Abstract: Let $G$ be a graph with a threshold function $\theta:V(G)\rightarrow \mathbb{N}$ such that $1\leq \theta(v)\leq d_G(v)$ for every vertex $v$ of $G$, where $d_G(v)$ is the degree of $v$ in $G$. Suppose we are given a target set $S\subseteq V(G)$. The paper considers the following repetitive process on $G$. At time step 0 the vertices of $S$ are colored black and the other vertices are colored white. After that, at each time step $t>0$, the colors of white vertices (if any) are updated according to the following rule. All white vertices $v$ that have at least $\theta(v)$ black neighbors at the time step $t-1$ are colored black, and the colors of the other vertices do not change. The process runs until no more white vertices can update colors from white to black. The following optimization problem is called Target Set Selection: Finding a target set $S$ of smallest possible size such that all vertices in $G$ are black at the end of the process. Such an $S$ is called an {\em optimal target set} for $G$ under the threshold function $\theta$. We are interested in finding an optimal target set for the well-known class of honeycomb networks under an important threshold function called {\em strict majority threshold}, where $\theta(v)=\lceil (d_G(v)+1)/2\rceil$ for each vertex $v$ in $G$. In a graph $G$, a {\em feedback vertex set} is a subset $S\subseteq V(G)$ such that the subgraph induced by $V(G)\setminus S$ is cycle-free. In this paper we give exact value on the size of the optimal target set for various kinds of honeycomb networks under strict majority threshold, and as a by-product we also provide a minimum feedback vertex set for different kinds regular graphs in the class of honeycomb networks


Preservation of Strong Normalisation modulo permutations for the structural lambda-calculus

Abstract: Inspired by a recent graphical formalism for lambda-calculus based on linear logic technology, we introduce an untyped structural lambda-calculus, called lambda j, which combines actions at a distance with exponential rules decomposing the substitution by means of weakening, contraction and derelicition. First, we prove some fundamental properties of lambda j such as confluence and preservation of beta-strong normalisation. Second, we add a strong bisimulation to lambda j by means of an equational theory which captures in particular Regnier's sigma-equivalence. We then complete this bisimulation with two more equations for (de)composition of substitutions and we prove that the resulting calculus still preserves beta-strong normalization. Finally, we discuss some consequences of our results.


Manual and Fast C Code Optimization

Abstract: Developing an application with high performance through the code optimization places a greater responsibility on the programmers. While most of the existing compilers attempt to automatically optimize the program code, manual techniques remain the predominant method for performing optimization. Deciding where to try to optimize code is difficult, especially for large complex applications. For manual optimization, the programmers can use his experiences in writing the code, and then he can use a software profiler in order to collect and analyze the performance data from the code. In this work, we have gathered the most experiences which can be applied to improve the style of writing programs in C language as well as we present an implementation of the manual optimization of the codes using the Intel VTune profiler. The paper includes two case studies to illustrate our optimization on the Heap Sort and Factorial functions.


Ambiguous Language and Differences in Beliefs

Abstract: Standard models of multi-agent modal logic do not capture the fact that information is often ambiguous, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different semantics that capture different assumptions about the agents' beliefs regarding whether or not there is ambiguity. We consider the impact of ambiguity on a seminal result in economics: Aumann's result saying that agents with a common prior cannot agree to disagree. This result is known not to hold if agents do not have a common prior; we show that it also does not hold in the presence of ambiguity. We then consider the tradeoff between assuming a common interpretation (i.e., no ambiguity) and a common prior (i.e., shared initial beliefs).


Towards an intelligence based conceptual framework for e-maintenance

Abstract: Since the time when concept of e-maintenance was introduced, most of the works insisted on the relevance of the underlying Information and Communication Technologies infrastructure. Through a review of current e-maintenance conceptual approaches and realizations, this paper aims to reconsider the predominance of ICT within e-maintenance projects and literature. The review brings to light the importance of intelligence as a fundamental dimension of e-maintenance that is to be led in a holistic predefined manner rather than isolated efforts within ICT driven approaches. As a contribution towards an intelligence based e-maintenance conceptual framework, a proposal is outlined in this paper to model e-maintenance system as an intelligent system. The proposed frame is based on CogAff architecture for intelligent agents. Within the proposed frame, more importance was reserved to the environment that the system is to be continuously aware of: Plant Environment, Internal and External Enterprise Environment and Human Environment. In addition to the abilities required for internal coherent behavior of the system, requirements for maintenance activities support are also mapped within the same frame according to corresponding levels of management. A case study was detailed in this paper sustaining the applicability of the proposal in relation to the classification of existing e-maintenance platforms. However, more work is needed to enhance exhaustiveness of the frame to serve as a comparison tool of existing e-maintenance systems. At the conceptual level, our future work is to use the proposed frame in an e-maintenance project.


Secure and Energy-Efficient Data Aggregation in Wireless Sensor Networks

Abstract: Data aggregation in intermediate nodes (called aggregator nodes) is an effective approach for optimizing consumption of scarce resources like bandwidth and energy in Wireless Sensor Networks (WSNs). However, in-network processing poses a problem for the privacy of the sensor data since individual data of sensor nodes need to be known to the aggregator node before the aggregation process can be carried out. In applications of WSNs, privacy-preserving data aggregation has become an important requirement due to sensitive nature of the sensor data. Researchers have proposed a number of protocols and schemes for this purpose. He et al. (INFOCOM 2007) have proposed a protocol - called CPDA - for carrying out additive data aggregation in a privacy-preserving manner for application in WSNs. The scheme has been quite popular and well-known. In spite of the popularity of this protocol, it has been found that the protocol is vulnerable to attack and it is also not energy-efficient. In this paper, we first present a brief state of the art survey on the current privacy-preserving data aggregation protocols for WSNS. Then we describe the CPDA protocol and identify its security vulnerability. Finally, we demonstrate how the protocol can be made secure and energy efficient.


Resource Availability-Aware Advance Reservation for Parallel Jobs with Deadlines

Abstract: Advance reservation is important to guarantee the quality of services of jobs by allowing exclusive access to resources over a defined time interval on resources. It is a challenge for the scheduler to organize available resources efficiently and to allocate them for parallel AR jobs with deadline constraint appropriately. This paper provides a slot-based data structure to organize available resources of multiprocessor systems in a way that enables efficient search and update operations, and formulates a suite of scheduling policies to allocate resources for dynamically arriving AR requests. The performance of the scheduling algorithms were investigated by simulations with different job sizes and durations, system loads and scheduling flexibilities. Simulation results show that job sizes and durations, system load and the flexibility of scheduling will impact the performance metrics of all the scheduling algorithms, and the PE-Worst-Fit algorithm becomes the best algorithm for the scheduler with the highest acceptance rate of AR requests, and the jobs with the First-Fit algorithm experience the lowest average slowdown. The data structure and scheduling policies can be used to organize and allocate resources for parallel AR jobs with deadline constraint in large-scale computing systems.


A Report on Multilinear PCA Plus Multilinear LDA to Deal with Tensorial Data: Visual Classification as An Example

Abstract: In practical applications, we often have to deal with high order data, such as a grayscale image and a video sequence are intrinsically 2nd-order tensor and 3rd-order tensor, respectively. For doing clustering or classification of these high order data, it is a conventional way to vectorize these data before hand, as PCA or FDA does, which often induce the curse of dimensionality problem. For this reason, experts have developed many methods to deal with the tensorial data, such as multilinear PCA, multilinear LDA, and so on. In this paper, we still address the problem of high order data representation and recognition, and propose to study the result of merging multilinear PCA and multilinear LDA into one scenario, we name it \textbf{GDA} for the abbreviation of Generalized Discriminant Analysis. To evaluate GDA, we perform a series of experiments, and the experimental results demonstrate our GDA outperforms a selection of competing methods such (2D)$^2$PCA, (2D)$^2$LDA, and MDA.


A review of EO image information mining

Abstract: We analyze the state of the art of content-based retrieval in Earth observation image archives focusing on complete systems showing promise for operational implementation. The different paradigms at the basis of the main system families are introduced. The approaches taken are analyzed, focusing in particular on the phases after primitive feature extraction. The solutions envisaged for the issues related to feature simplification and synthesis, indexing, semantic labeling are reviewed. The methodologies for query specification and execution are analyzed.


On Global Types and Multi-Party Session

Abstract: Global types are formal specifications that describe communication protocols in terms of their global interactions. We present a new, streamlined language of global types equipped with a trace-based semantics and whose features and restrictions are semantically justified. The multi-party sessions obtained projecting our global types enjoy a liveness property in addition to the traditional progress and are shown to be sound and complete with respect to the set of traces of the originating global type. Our notion of completeness is less demanding than the classical ones, allowing a multi-party session to leave out redundant traces from an underspecified global type. In addition to the technical content, we discuss some limitations of our language of global types and provide an extensive comparison with related specification languages adopted in different communities.


Posterior Mean Super-Resolution with a Compound Gaussian Markov Random Field Prior

Abstract: This manuscript proposes a posterior mean (PM) super-resolution (SR) method with a compound Gaussian Markov random field (MRF) prior. SR is a technique to estimate a spatially high-resolution image from observed multiple low-resolution images. A compound Gaussian MRF model provides a preferable prior for natural images that preserves edges. PM is the optimal estimator for the objective function of peak signal-to-noise ratio (PSNR). This estimator is numerically determined by using variational Bayes (VB). We then solve the conjugate prior problem on VB and the exponential-order calculation cost problem of a compound Gaussian MRF prior with simple Taylor approximations. In experiments, the proposed method roughly overcomes existing methods.


A handy systematic method for data hazards detection in an instruction set of a pipelined microprocessor

Abstract: It is intended in this document to introduce a handy systematic method for enumerating all possible data dependency cases that could occur between any two instructions that might happen to be processed at the same time at different stages of the pipeline. Given instructions of the instruction set, specific information about operands of each instruction and when an instruction reads or writes data, the method could be used to enumerate all possible data hazard cases and to determine whether forwarding or stalling is suitable for resolving each case.


Faster Parameterized Algorithms using Linear Programming

Abstract: We investigate the parameterized complexity of Vertex Cover parameterized by the difference between the size of the optimal solution and the value of the linear programming (LP) relaxation of the problem. By carefully analyzing the change in the LP value in the branching steps, we argue that combining previously known preprocessing rules with the most straightforward branching algorithm yields an $O^*((2.618)^k)$ algorithm for the problem. Here $k$ is the excess of the vertex cover size over the LP optimum, and we write $O^*(f(k))$ for a time complexity of the form $O(f(k)n^{O(1)})$, where $f (k)$ grows exponentially with $k$. We proceed to show that a more sophisticated branching algorithm achieves a runtime of $O^*(2.3146^k)$. Following this, using known and new reductions, we give $O^*(2.3146^k)$ algorithms for the parameterized versions of Above Guarantee Vertex Cover, Odd Cycle Transversal, Split Vertex Deletion and Almost 2-SAT, and an $O^*(1.5214^k)$ algorithm for Ko\"nig Vertex Deletion, Vertex Cover Param by OCT and Vertex Cover Param by KVD. These algorithms significantly improve the best known bounds for these problems. The most notable improvement is the new bound for Odd Cycle Transversal - this is the first algorithm which beats the dependence on $k$ of the seminal $O^*(3^k)$ algorithm of Reed, Smith and Vetta. Finally, using our algorithm, we obtain a kernel for the standard parameterization of Vertex Cover with at most $2k - c \log k$ vertices. Our kernel is simpler than previously known kernels achieving the same size bound.


Functional Logic Programming with Generalized Circular Coinduction

Abstract: We propose a method to adapt functional logic programming to deal with reasoning on coinductively interpreted programs as well as on inductively interpreted programs. In order to do so, we consider a class of objects interesting for this coinductive interpretation, namely regular terms. We show how the usual data structures can be adapted to capture these objects. We adapt the operational semantics of Curry to interpret programs coinductively. We illustrate this method with several examples that show the working of our method and several cases in which it could be useful. Finally, we suggest how the declarative semantics can be adapted suitably.


How much could we cover a set by c.e sets?

Abstract: "How much c.e. sets could cover a given set?" in this paper we are going to answer this question. Also, in this approach some old concepts come into a new arrangement. The major goal of this article is to introduce an appropriate definition for this purpose. Introduction In Computability Theory (Recursion Theory) in the first step we wish to recognize the sets which could be enumerated by Turing machines (equivalently, algorithms) and in the next step we will compare these sets by some reasonable order (Like Turing degree). Also sometimes with some extra information (Oracles) a class of non c.e. sets show the same behavior as c.e. sets (Post hierarchy and related theorems). Here we try another approach: "Let A be an arbitrary set and we wish to recognize how much this set might be covered by a c.e. set?" Although in some sense this approach could be seen in some definitions of Recursion Theory, but at the best of our knowledge it didn't considered as an approach yet, even though it is able to shed a light on some subjects of Computability of sets. Defining this approach is not quite straightforward and there are some obstacles to define them. To overcome these difficulties we modify the definitions. We have an alternative problem here when we consider recursive sets and not c.e. sets. In this case, the problem would be: "Let A be an arbitrary set and we wish to know that how much this set might be covered by a recursive Set?" Here, we try the first definition and the first problem.


Online Discriminative Dictionary Learning for Image Classification Based on Block-Coordinate Descent Method

Abstract: Previous researches have demonstrated that the framework of dictionary learning with sparse coding, in which signals are decomposed as linear combinations of a few atoms of a learned dictionary, is well adept to reconstruction issues. This framework has also been used for discrimination tasks such as image classification. To achieve better performances of classification, experts develop several methods to learn a discriminative dictionary in a supervised manner. However, another issue is that when the data become extremely large in scale, these methods will be no longer effective as they are all batch-oriented approaches. For this reason, we propose a novel online algorithm for discriminative dictionary learning, dubbed \textbf{ODDL} in this paper. First, we introduce a linear classifier into the conventional dictionary learning formulation and derive a discriminative dictionary learning problem. Then, we exploit an online algorithm to solve the derived problem. Unlike the most existing approaches which update dictionary and classifier alternately via iteratively solving sub-problems, our approach directly explores them jointly. Meanwhile, it can largely shorten the runtime for training and is also particularly suitable for large-scale classification issues. To evaluate the performance of the proposed ODDL approach in image recognition, we conduct some experiments on three well-known benchmarks, and the experimental results demonstrate ODDL is fairly promising for image classification tasks.


An MLP based Approach for Recognition of Handwritten `Bangla' Numerals

Abstract: The work presented here involves the design of a Multi Layer Perceptron (MLP) based pattern classifier for recognition of handwritten Bangla digits using a 76 element feature vector. Bangla is the second most popular script and language in the Indian subcontinent and the fifth most popular language in the world. The feature set developed for representing handwritten Bangla numerals here includes 24 shadow features, 16 centroid features and 36 longest-run features. On experimentation with a database of 6000 samples, the technique yields an average recognition rate of 96.67% evaluated after three-fold cross validation of results. It is useful for applications related to OCR of handwritten Bangla Digit and can also be extended to include OCR of handwritten characters of Bangla alphabet.


Handwritten Bangla Alphabet Recognition using an MLP Based Classifier

Abstract: The work presented here involves the design of a Multi Layer Perceptron (MLP) based classifier for recognition of handwritten Bangla alphabet using a 76 element feature set Bangla is the second most popular script and language in the Indian subcontinent and the fifth most popular language in the world. The feature set developed for representing handwritten characters of Bangla alphabet includes 24 shadow features, 16 centroid features and 36 longest-run features. Recognition performances of the MLP designed to work with this feature set are experimentally observed as 86.46% and 75.05% on the samples of the training and the test sets respectively. The work has useful application in the development of a complete OCR system for handwritten Bangla text.


Data-Driven Execution of Fast Multipole Methods

Abstract: Fast multipole methods have O(N) complexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next-generation supercomputers. Their most common application is to accelerate N-body problems, but they can also be used to solve boundary integral equations. When the particle distribution is irregular and the tree structure is adaptive, load-balancing becomes a non-trivial question. A common strategy for load-balancing FMMs is to use the work load from the previous step as weights to statically repartition the next step. The authors discuss in the paper another approach based on data-driven execution to efficiently tackle this challenging load-balancing problem. The core idea consists of breaking the most time-consuming stages of the FMMs into smaller tasks. The algorithm can then be represented as a Directed Acyclic Graph (DAG) where nodes represent tasks, and edges represent dependencies among them. The execution of the algorithm is performed by asynchronously scheduling the tasks using the QUARK runtime environment, in a way such that data dependencies are not violated for numerical correctness purposes. This asynchronous scheduling results in an out-of-order execution. The performance results of the data-driven FMM execution outperform the previous strategy and show linear speedup on a quad-socket quad-core Intel Xeon system.


Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

Abstract: In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.


Modeling the geographical studies with GeoGebra-software

Abstract: The problem of mathematical modeling in geography is one of the most important strategies in order to establish the evolution and the prevision of geographical phenomena. Models must have a simplified structure, to reflect essential components and must be selective, structured, and suggestive and approximate the reality. Models could be static or dynamic, developed in a theoretical, symbolic, conceptual or mental way, mathematically modeled. The present paper is focused on the virtual model which uses GeoGebra software, free and available at www.geogebra.org, in order to establish new methods of geographical analysis in a dynamic, didactic way.


Fluid Model Checking

Abstract: In this paper we investigate a potential use of fluid approximation techniques in the context of stochastic model checking of CSL formulae. We focus on properties describing the behaviour of a single agent in a (large) population of agents, exploiting a limit result known also as fast simulation. In particular, we will approximate the behaviour of a single agent with a time-inhomogeneous CTMC which depends on the environment and on the other agents only through the solution of the fluid differential equation. We will prove the asymptotic correctness of our approach in terms of satisfiability of CSL formulae and of reachability probabilities. We will also present a procedure to model check time-inhomogeneous CTMC against CSL formulae.


The cloud paradigm: Are you tuned for the lyrics?

Abstract: Major players, business angels and opinion-makers are broadcasting beguiled lyrics on the most recent IT hype: your software should ascend to the clouds. There are many clouds and the stake is high. Distractedly, many of us became assiduous users of the cloud, but perhaps due to the legacy systems and legacy knowledge, IT professionals, mainly those many that work in business information systems for the long tail, are not as much plunged into producing cloud-based systems for their clients. This keynote will delve into several aspects of this cloud paradigm, from more generic concerns regarding security and value for money, to more specific worries that reach software engineers in general. Do we need a different software development process? Are development techniques and tools mature enough? What about the role of open-source in the cloud? How do we assess the quality in cloud-based development? Please stay tuned for more!


Bibliometric Perspectives on Medical Innovation using the Medical Subject Headings (MeSH) of PubMed

Abstract: Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the Medline database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the Medline database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the Medline database, on the one hand, and the Science Citation Index and Scopus (containing citation information), on the other.


Development of an Ontology to Assist the Modeling of Accident Scenarii "Application on Railroad Transport "

Abstract: In a world where communication and information sharing are at the heart of our business, the terminology needs are most pressing. It has become imperative to identify the terms used and defined in a consensual and coherent way while preserving linguistic diversity. To streamline and strengthen the process of acquisition, representation and exploitation of scenarii of train accidents, it is necessary to harmonize and standardize the terminology used by players in the security field. The research aims to significantly improve analytical activities and operations of the various safety studies, by tracking the error in system, hardware, software and human. This paper presents the contribution of ontology to modeling scenarii for rail accidents through a knowledge model based on a generic ontology and domain ontology. After a detailed presentation of the state of the art material, this article presents the first results of the developed model.


Can the Eureqa symbolic regression program, computer algebra and numerical analysis help each other?

Abstract: The Eureqa symbolic regression program has recently received extensive press praise. A representative quote is "There are very clever 'thinking machines' in existence today, such as Watson, the IBM computer that conquered Jeopardy! last year. But next to Eureqa, Watson is merely a glorified search engine." The program was designed to work with noisy experimental data. However, if the data is generated from an expression for which there exists more concise equivalent expressions, sometimes some of the Eureqa results are one or more of those more concise equivalents. If not, perhaps one or more of the returned Eureqa results might be a sufficiently accurate approximation that is more concise than the given expression. Moreover, when there is no known closed form expression, the data points can be generated by numerical methods, enabling Eureqa to find expressions that concisely fit those data points with sufficient accuracy. In contrast to typical regression software, the user does not have to explicitly or implicitly provide a specific expression or class of expressions containiing unknown constants for the software to determine. Is Eureqa useful enough in these regards to provide an additional tool for experimental mathematics, computer algebra users and numerical analysis? Yes if used carefully. Can computer algebra and numerical methods help Eureqa? Definitely.


Lower bounds for Arrangement-based Range-Free Localization in Sensor Networks

Abstract: Colander are location aware entities that collaborate to determine approximate location of mobile or static objects when beacons from an object are received by all colanders that are within its distance $R$. This model, referred to as arrangement-based localization, does not require distance estimation between entities, which has been shown to be highly erroneous in practice. Colander are applicable in localization in sensor networks and tracking of mobile objects. A set $S \subset {\mathbb R}^2$ is an $(R,\epsilon)$-colander if by placing receivers at the points of $S$, a wireless device with transmission radius $R$ can be localized to within a circle of radius $\epsilon$. We present tight upper and lower bounds on the size of $(R,\epsilon)$-colanders. We measure the expected size of colanders that will form $(R, \epsilon)$-colanders if they distributed uniformly over the plane.


A Symbolic Approach to the Design of Nonlinear Networked Control Systems

Abstract: Networked control systems (NCS) are spatially distributed systems where communication among plants, sensors, actuators and controllers occurs in a shared communication network. NCS have been studied for the last ten years and important research results have been obtained. These results are in the area of stability and stabilizability. However, while important, these results must be complemented in different areas to be able to design effective NCS. In this paper we approach the control design of NCS using symbolic (finite) models. Symbolic models are abstract descriptions of continuous systems where one symbol corresponds to an "aggregate" of continuous states. We consider a fairly general multiple-loop network architecture where plants communicate with digital controllers through a shared, non-ideal, communication network characterized by variable sampling and transmission intervals, variable communication delays, quantization errors, packet losses and limited bandwidth. We first derive a procedure to obtain symbolic models that are proven to approximate NCS in the sense of alternating approximate bisimulation. We then use these symbolic models to design symbolic controllers that realize specifications expressed in terms of automata on infinite strings. An example is provided where we address the control design of a pair of nonlinear control systems sharing a common communication network. The closed-loop NCS obtained is validated through the OMNeT++ network simulation framework.


Data Structure Lower Bounds on Random Access to Grammar-Compressed Strings

Abstract: In this paper we investigate the problem of building a static data structure that represents a string s using space close to its compressed size, and allows fast access to individual characters of s. This type of structures was investigated by the recent paper of Bille et al. Let n be the size of a context-free grammar that derives a unique string s of length L. (Note that L might be exponential in n.) Bille et al. showed a data structure that uses space O(n) and allows to query for the i-th character of s using running time O(log L). Their data structure works on a word RAM with a word size of logL bits. Here we prove that for such data structures, if the space is poly(n), then the query time must be at least (log L)^{1-\epsilon}/log S where S is the space used, for any constant eps>0. As a function of n, our lower bound is \Omega(n^{1/2-\epsilon}). Our proof holds in the cell-probe model with a word size of log L bits, so in particular it holds in the word RAM model. We show that no lower bound significantly better than n^{1/2-\epsilon} can be achieved in the cell-probe model, since there is a data structure in the cell-probe model that uses O(n) space and achieves O(\sqrt{n log n}) query time. The "bad" setting of parameters occurs roughly when L=2^{\sqrt{n}}. We also prove a lower bound for the case of not-as-compressible strings, where, say, L=n^{1+\epsilon}. For this case, we prove that if the space is n polylog(n), then the query time must be at least \Omega(log n/loglog n). The proof works by reduction to communication complexity, namely to the LSD problem, recently employed by Patrascu and others. We prove lower bounds also for the case of LZ-compression and Burrows-Wheeler (BWT) compression. All of our lower bounds hold even when the strings are over an alphabet of size 2 and hold even for randomized data structures with 2-sided error.


Search Combinators

Abstract: The ability to model search in a constraint solver can be an essential asset for solving combinatorial problems. However, existing infrastructure for defining search heuristics is often inadequate. Either modeling capabilities are extremely limited or users are faced with a general-purpose programming language whose features are not tailored towards writing search heuristics. As a result, major improvements in performance may remain unexplored. This article introduces search combinators, a lightweight and solver-independent method that bridges the gap between a conceptually simple modeling language for search (high-level, functional and naturally compositional) and an efficient implementation (low-level, imperative and highly non-modular). By allowing the user to define application-tailored search strategies from a small set of primitives, search combinators effectively provide a rich domain-specific language (DSL) for modeling search to the user. Remarkably, this DSL comes at a low implementation cost to the developer of a constraint solver. The article discusses two modular implementation approaches and shows, by empirical evaluation, that search combinators can be implemented without overhead compared to a native, direct implementation in a constraint solver.


Opportunistic Routing with Congestion Diversity in Wireless Ad-hoc Networks

Abstract: We consider the problem of routing packets across a multi-hop network consisting of multiple sources of traffic and wireless links while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes among which the next relay is selected opportunistically. The main challenge in the design of minimum-delay routing policies is balancing the trade-off between routing the packets along the shortest paths to the destination and distributing traffic according to the maximum backpressure. Combining important aspects of shortest path and backpressure routing, this paper provides a systematic development of a distributed opportunistic routing policy with congestion diversity ({D-ORCD}). {D-ORCD} uses a measure of draining time to opportunistically identify and route packets along the paths with an expected low overall congestion. {D-ORCD} is proved to ensure a bounded expected delay for all networks and under any admissible traffic. Furthermore, this paper proposes a practical implementation which empirically optimizes critical algorithm parameters and their effects on delay as well as protocol overhead. Realistic Qualnet simulations for 802.11-based networks demonstrate a significant improvement in the average delay over comparative solutions in the literature. %Finally, various practical modifications to {D-ORCD} are proposed and their performance are evaluated.


The Evolution of Cooperation in Business

Abstract: The development of cooperative relations within and between firms plays an important role in the successful implementation of business strategy. How to produce such relations is less well understood. We build on work in relational contract theory and the evolution of cooperation to examine the conditions under which group based incentives outperform individual based incentives and how they produce more cooperative behavior. Group interactions are modeled as iterated games in which individuals learn optimal strategies under individual and group based reward mechanisms. The space of possible games is examined and it is found that, when individual and group interests are not aligned, group evaluation and reward systems lead to higher group performance and, counter-intuitively, higher individual performance. Such groups include individuals who, quite differently to free-riders, sacrifice their own performance for the good of the group. We discuss the implications of these results for the design of incentive systems.


Secure and Privacy-Preserving Data Aggregation Protocols for Wireless Sensor Networks

Abstract: This chapter discusses the need of security and privacy protection mechanisms in aggregation protocols used in wireless sensor networks (WSN). It presents a comprehensive state of the art discussion on the various privacy protection mechanisms used in WSNs and particularly focuses on the CPDA protocols proposed by He et al. (INFOCOM 2007). It identifies a security vulnerability in the CPDA protocol and proposes a mechanism to plug that vulnerability. To demonstrate the need of security in aggregation process, the chapter further presents various threats in WSN aggregation mechanisms. A large number of existing protocols for secure aggregation in WSN are discussed briefly and a protocol is proposed for secure aggregation which can detect false data injected by malicious nodes in a WSN. The performance of the protocol is also presented. The chapter concludes while highlighting some future directions of research in secure data aggregation in WSNs.


Control of Probabilistic Systems under Dynamic, Partially Known Environments with Temporal Logic Specifications

Abstract: We consider the synthesis of control policies for probabilistic systems, modeled by Markov decision processes, operating in partially known environments with temporal logic specifications. The environment is modeled by a set of Markov chains. Each Markov chain describes the behavior of the environment in each mode. The mode of the environment, however, is not known to the system. Two control objectives are considered: maximizing the expected probability and maximizing the worst-case probability that the system satisfies a given specification.


Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents

Abstract: We consider the synthesis of control policies from temporal logic specifications for robots that interact with multiple dynamic environment agents. Each environment agent is modeled by a Markov chain whereas the robot is modeled by a finite transition system (in the deterministic case) or Markov decision process (in the stochastic case). Existing results in probabilistic verification are adapted to solve the synthesis problem. To partially address the state explosion issue, we propose an incremental approach where only a small subset of environment agents is incorporated in the synthesis procedure initially and more agents are successively added until we hit the constraints on computational resources. Our algorithm runs in an anytime fashion where the probability that the robot satisfies its specification increases as the algorithm progresses.


A Self-Organization Framework for Wireless Ad Hoc Networks as Small Worlds

Abstract: Motivated by the benefits of small world networks, we propose a self-organization framework for wireless ad hoc networks. We investigate the use of directional beamforming for creating long-range short cuts between nodes. Using simulation results for randomized beamforming as a guideline, we identify crucial design issues for algorithm design. Our results show that, while significant path length reduction is achievable, this is accompanied by the problem of asymmetric paths between nodes. Subsequently, we propose a distributed algorithm for small world creation that achieves path length reduction while maintaining connectivity. We define a new centrality measure that estimates the structural importance of nodes based on traffic flow in the network, which is used to identify the optimum nodes for beamforming. We show, using simulations, that this leads to significant reduction in path length while maintaining connectivity.


Dynamic Packet Scheduling in Wireless Networks

Abstract: We consider protocols that serve communication requests arising over time in a wireless network that is subject to interference. Unlike previous approaches, we take the geometry of the network and power control into account, both allowing to increase the network's performance significantly. We introduce a stochastic and an adversarial model to bound the packet injection. Although taken as the primary motivation, this approach is not only suitable for models based on the signal-to-interference-plus-noise ratio (SINR). It also covers virtually all other common interference models, for example the multiple-access channel, the radio-network model, the protocol model, and distance-2 matching. Packet-routing networks allowing each edge or each node to transmit or receive one packet at a time can be modeled as well. Starting from algorithms for the respective scheduling problem with static transmission requests, we build distributed stable protocols. This is more involved than in previous, similar approaches because the algorithms we consider do not necessarily scale linearly when scaling the input instance. We can guarantee a throughput that is as large as the one of the original static algorithm. In particular, for SINR models the competitive ratios of the protocol in comparison to optimal ones in the respective model are between constant and O(log^2 m) for a network of size m.


An Exploratory Study of Critical Factors Affecting the Efficiency of Sorting Techniques (Shell, Heap and Treap)

Abstract: The efficiency of sorting techniques has a significant impact on the overall efficiency of a program. The efficiency of Shell, Heap and Treap sorting techniques in terms of both running time and memory usage was studied, experiments conducted and results subjected to factor analysis by SPSS. The study revealed the main factor affecting these sorting techniques was time taken to sort.


Subtotal ordering -- a pedagogically advantageous algorithm for computing total degree reverse lexicographic order

Abstract: Total degree reverse lexicographic order is currently generally regarded as most often fastest for computing Groebner bases. This article describes an alternate less mysterious algorithm for computing this order using exponent subtotals and describes why it should be very nearly the same speed the traditional algorithm, all other things being equal. However, experimental evidence suggests that subtotal order is actually slightly faster for the Mathematica Groebner basis implementation more often than not. This is probably because the weight vectors associated with the natural subtotal weight matrix and with the usual total degree reverse lexicographic weight matrix are different, and Mathematica also uses those the corresponding weight vectors to help select successive S polynomials and divisor polynomials: Those selection heuristics appear to work slightly better more often with subtotal weight vectors. However, the most important advantage of exponent subtotals is pedagogical. It is easier to understand than the total degree reverse lexicographic algorithm, and it is more evident why the resulting order is often the fastest known order for computing Groebner bases. Keywords: Term order, Total degree reverse lexicographic, tdeg, grevlex, Groebner basis


Model based Software Develeopment: Issues & Challenges

Abstract: One of the goals of software design is to model a system in such a way that it is easily understandable. Nowadays the tendency for software development is changing from manual coding to automatic code generation; it is becoming model-based. This is a response to the software crisis, in which the cost of hardware has decreased and conversely the cost of software development has increased sharply. The methodologies that allowed this change are model-based, thus relieving the human from detailed coding. Still there is a long way to achieve this goal, but work is being done worldwide to achieve this objective. This paper presents the drastic changes related to modeling and important challenging issues and techniques that recur in MBSD.


Performance Analysis of HR Portal Domain Components Extraction

Abstract: Extraction of components pertaining to a particular domain not only reduces the cost but also helps in delivering a quality product. However, the advantages of the Component Level Interaction's (CLI's) are not clearly presented. In the first part of the paper the design of HR Portal application is described. Later the results are simulated using the Netbeans Profiler tool which exposes and highlights the performance characteristics of component based system pertaining to HR domain.


A Turing Machine Resisting Isolated Bursts Of Faults

Abstract: We consider computations of a Turing machine under noise that causes consecutive violations of the machine's transition function. Given a constant upper bound B on the size of bursts of faults, we construct a Turing machine M(B) subject to faults that can simulate any fault-free machine under the condition that bursts are not closer to each other than V for an appropriate V = O(B^2).


Simplifying products of fractional powers of powers

Abstract: Most computer algebra systems incorrectly simplify (z - z)/(sqrt(w^2)/w^3 - 1/(w*sqrt(w^2))) to 0 rather than to 0/0. The reasons for this are: 1. The default simplification doesn't succeed in simplifying the denominator to 0. 2. There is a rule that 0 is the result of 0 divided by anything that doesn't simplify to either 0 or 0/0. Try it on your computer algebra systems! This article describes how to simplify products of the form w^a*(w^b1)^g1 ... (w^bn)^gn correctly and well, where w is any real or complex expression and the exponents are rational numbers. It might seem that correct good simplification of such a restrictive expression class must already be published and/or built into at least one widely used computer-algebra system, but apparently this issue has been overlooked. Default and relevant optional simplification was tested with 86 examples for n=1 on Derive, Maple, Mathematica, Maxima and TI-CAS. Totaled over all five systems, 11% of the results were not equivalent to the input everywhere, 50% of the results did not simplify to 0 a result that was equivalent to 0, and at least 16% of the results exhibited one or more of four additional flaw types. There was substantial room for improvement in all five systems, including the two for which I was a co-author. The good news is: These flaws are easy to fix.


Series misdemeanors

Abstract: Puiseux series are power series in which the exponents can be fractional and/or negative rational numbers. Several computer algebra systems have one or more built-in or loadable functions for computing truncated Puiseux series -- perhaps generalized to allow coefficients containing functions of the series variable that are dominated by any power of that variable, such as logarithms and nested logarithms of the series variable. Some computer-algebra systems also offer functions that can compute more-general truncated recursive hierarchical series. However, for all of these kinds of truncated series there are important implementation details that haven't been addressed before in the published literature and in current implementations. For implementers this article contains ideas for designing more convenient, correct, and efficient implementations or improving existing ones. For users, this article is a warning about some of these limitations. Many of the ideas in this article have been implemented in the computer-algebra within the TI-Nspire calculator, Windows and Macintosh products.


Multi-Flow Attacks Against Network Flow Watermarks: Analysis and Countermeasures

Abstract: In this paper, we analyze several recent schemes for watermarking network flows that are based on splitting the flow into timing intervals. We show that this approach creates time-dependent correlations that enable an attack that combines multiple watermarked flows. Such an attack can easily be mounted in nearly all applications of network flow watermarking, both in anonymous communication and stepping stone detection. The attack can be used to detect the presence of a watermark, recover the secret parameters, and remove the watermark from a flow. The attack can be effective even if different flows are marked with different values of a watermark. We analyze the efficacy of our attack using a probabilistic model and a Markov-Modulated Poisson Process (MMPP) model of interactive traffic. We also implement our attack and test it using both synthetic and real-world traces, showing that our attack is effective with as few as 10 watermarked flows. Finally, we propose possible countermeasures to defeat the multi-flow attack.


Region-based memory management for Mercury programs

Abstract: Region-based memory management (RBMM) is a form of compile time memory management, well-known from the functional programming world. In this paper we describe our work on implementing RBMM for the logic programming language Mercury. One interesting point about Mercury is that it is designed with strong type, mode, and determinism systems. These systems not only provide Mercury programmers with several direct software engineering benefits, such as self-documenting code and clear program logic, but also give language implementors a large amount of information that is useful for program analyses. In this work, we make use of this information to develop program analyses that determine the distribution of data into regions and transform Mercury programs by inserting into them the necessary region operations. We prove the correctness of our program analyses and transformation. To execute the annotated programs, we have implemented runtime support that tackles the two main challenges posed by backtracking. First, backtracking can require regions removed during forward execution to be "resurrected"; and second, any memory allocated during a computation that has been backtracked over must be recovered promptly and without waiting for the regions involved to come to the end of their life. We describe in detail our solution of both these problems. We study in detail how our RBMM system performs on a selection of benchmark programs, including some well-known difficult cases for RBMM. Even with these difficult cases, our RBMM-enabled Mercury system obtains clearly faster runtimes for 15 out of 18 benchmarks compared to the base Mercury system with its Boehm runtime garbage collector, with an average runtime speedup of 24%, and an average reduction in memory requirements of 95%. In fact, our system achieves optimal memory consumption in some programs.


Swarm Behavior of Intelligent Cloud

Abstract: In this paper, the main aim is to exhibit swarm intelligence power in cloud based scenario. Heterogeneous environment has been configured at server-side network of the whole cloud network. In the proposed system, different types of servers are being used to manage useful assorted atmosphere. Swarm intelligence has been adopted for enhancing the performance of overall system network. Specific location at server-side of the network is going to be selected by the swarm intelligence concept for accessing desired elements. Flexibility, robustness and self-organization, which are to be considered at the time of designing the system environment, are the main features of swarm intelligence.


AD in Fortran, Part 1: Design

Abstract: We propose extensions to Fortran which integrate forward and reverse Automatic Differentiation (AD) directly into the programming model. Irrespective of implementation technology, embedding AD constructs directly into the language extends the reach and convenience of AD while allowing abstraction of concepts of interest to scientific-computing practice, such as root finding, optimization, and finding equilibria of continuous games. Multiple different subprograms for these tasks can share common interfaces, regardless of whether and how they use AD internally. A programmer can maximize a function F by calling a library maximizer, XSTAR=ARGMAX(F,X0), which internally constructs derivatives of F by AD, without having to learn how to use any particular AD tool. We illustrate the utility of these extensions by example: programs become much more concise and closer to traditional mathematical notation. A companion paper describes how these extensions can be implemented by a program that generates input to existing Fortran-based AD tools.


AD in Fortran, Part 2: Implementation via Prepreprocessor

Abstract: We describe an implementation of the Farfel Fortran AD extensions. These extensions integrate forward and reverse AD directly into the programming model, with attendant benefits to flexibility, modularity, and ease of use. The implementation we describe is a "prepreprocessor" that generates input to existing Fortran-based AD tools. In essence, blocks of code which are targeted for AD by Farfel constructs are put into subprograms which capture their lexical variable context, and these are closure-converted into top-level subprograms and specialized to eliminate EXTERNAL arguments, rendering them amenable to existing AD preprocessors, which are then invoked, possibly repeatedly if the AD is nested.


A New Look at Composition of Authenticated Byzantine Generals

Abstract: The problem of Authenticated Byzantine Generals (ABG) aims to simulate a virtual reliable broadcast channel from the General to all the players via a protocol over a real (point-to-point) network in the presence of faults. We propose a new model to study the self-composition of ABG protocols. The central dogma of our approach can be phrased as follows: Consider a player who diligently executes (only) the delegated protocol but the adversary steals some private information from him. Should such a player be considered faulty? With respect to ABG protocols, we argue that the answer has to be no. In the new model we show that in spite of using unique session identifiers, if $n < 2t$, there cannot exist any ABG protocol that composes in parallel even twice. Further, for $n \geq 2t$, we design ABG protocols that compose for any number of parallel executions. Besides investigating the composition of ABG under a new light, our work also brings out several new insights into Canetti's Universal Composability framework. Specifically, we show that there are several undesirable effects if one deviates from our dogma. This provides further evidence as to why our dogma is the right framework to study the composition of ABG protocols.


Batch-oriented software appliances

Abstract: This paper presents AppPot, a system for creating Linux software appliances. AppPot can be run as a regular batch or grid job and executed in user space, and requires no special virtualization support in the infrastructure. The main design goal of AppPot is to bring the benefits of a virtualization-based IaaS cloud to existing batch-oriented computing infrastructures. In particular, AppPot addresses the application deployment and configuration on large heterogeneous computing infrastructures: users are enabled to prepare their own customized virtual appliance for providing a safe execution environment for their applications. These appliances can then be executed on virtually any computing infrastructure being in a private or public cloud as well as any batch-controlled computing clusters the user may have access to. We give an overview of AppPot and its features, the technology that makes it possible, and report on experiences running it in production use within the Swiss National Grid infrastructure SMSCG.


Crowdsourcing for Usability Testing

Abstract: While usability evaluation is critical to designing usable websites, traditional usability testing can be both expensive and time consuming. The advent of crowdsourcing platforms such as Amazon Mechanical Turk and CrowdFlower offer an intriguing new avenue for performing remote usability testing with potentially many users, quick turn-around, and significant cost savings. To investigate the potential of such crowdsourced usability testing, we conducted two similar (though not completely parallel) usability studies which evaluated a graduate school's website: one via a traditional usability lab setting, and the other using crowdsourcing. While we find crowdsourcing exhibits some notable limitations in comparison to the traditional lab environment, its applicability and value for usability testing is clearly evidenced. We discuss both methodological differences for crowdsourced usability testing, as well as empirical contrasts to results from more traditional, face-to-face usability testing.


Learning Random Kernel Approximations for Object Recognition

Abstract: Approximations based on random Fourier features have recently emerged as an efficient and formally consistent methodology to design large-scale kernel machines. By expressing the kernel as a Fourier expansion, features are generated based on a finite set of random basis projections, sampled from the Fourier transform of the kernel, with inner products that are Monte Carlo approximations of the original kernel. Based on the observation that different kernel-induced Fourier sampling distributions correspond to different kernel parameters, we show that an optimization process in the Fourier domain can be used to identify the different frequency bands that are useful for prediction on training data. Moreover, the application of group Lasso to random feature vectors corresponding to a linear combination of multiple kernels, leads to efficient and scalable reformulations of the standard multiple kernel learning model \cite{Varma09}. In this paper we develop the linear Fourier approximation methodology for both single and multiple gradient-based kernel learning and show that it produces fast and accurate predictors on a complex dataset such as the Visual Object Challenge 2011 (VOC2011).


Tree Regular Model Checking for Lattice-Based Automata

Abstract: Tree Regular Model Checking (TRMC) is the name of a family of techniques for analyzing infinite-state systems in which states are represented by terms, and sets of states by Tree Automata (TA). The central problem in TRMC is to decide whether a set of bad states is reachable. The problem of computing a TA representing (an over- approximation of) the set of reachable states is undecidable, but efficient solutions based on completion or iteration of tree transducers exist. Unfortunately, the TRMC framework is unable to efficiently capture both the complex structure of a system and of some of its features. As an example, for JAVA programs, the structure of a term is mainly exploited to capture the structure of a state of the system. On the counter part, integers of the java programs have to be encoded with Peano numbers, which means that any algebraic operation is potentially represented by thousands of applications of rewriting rules. In this paper, we propose Lattice Tree Automata (LTAs), an extended version of tree automata whose leaves are equipped with lattices. LTAs allow us to represent possibly infinite sets of interpreted terms. Such terms are capable to represent complex domains and related operations in an efficient manner. We also extend classical Boolean operations to LTAs. Finally, as a major contribution, we introduce a new completion-based algorithm for computing the possibly infinite set of reachable interpreted terms in a finite amount of time.


Performance Evaluation of Biometric Template Update

Abstract: Template update allows to modify the biometric reference of a user while he uses the biometric system. With such kind of mechanism we expect the biometric system uses always an up to date representation of the user, by capturing his intra-class (temporary or permanent) variability. Although several studies exist in the literature, there is no commonly adopted evaluation scheme. This does not ease the comparison of the different systems of the literature. In this paper, we show that using different evaluation procedures can lead in different, and contradictory, interpretations of the results. We use a keystroke dynamics (which is a modality suffering of template ageing quickly) template update system on a dataset consisting of height different sessions to illustrate this point. Even if we do not answer to this problematic, it shows that it is necessary to normalize the template update evaluation procedures.


Towards Optimal Degree-distributions for Left-perfect Matchings in Random Bipartite Graphs

Abstract: Consider a random bipartite multigraph $G$ with $n$ left nodes and $m \geq n \geq 2$ right nodes. Each left node $x$ has $d_x \geq 1$ random right neighbors. The average left degree $\Delta$ is fixed, $\Delta \geq 2$. We ask whether for the probability that $G$ has a left-perfect matching it is advantageous not to fix $d_x$ for each left node $x$ but rather choose it at random according to some (cleverly chosen) distribution. We show the following, provided that the degrees of the left nodes are independent: If $\Delta$ is an integer then it is optimal to use a fixed degree of $\Delta$ for all left nodes. If $\Delta$ is non-integral then an optimal degree-distribution has the property that each left node $x$ has two possible degrees, $\floor{\Delta}$ and $\ceil{\Delta}$, with probability $p_x$ and $1-p_x$, respectively, where $p_x$ is from the closed interval $[0,1]$ and the average over all $p_x$ equals $\ceil{\Delta}-\Delta$. Furthermore, if $n=c\cdot m$ and $\Delta>2$ is constant, then each distribution of the left degrees that meets the conditions above determines the same threshold $c^*(\Delta)$ that has the following property as $n$ goes to infinity: If $c<c^*(\Delta)$ then there exists a left-perfect matching with high probability. If $c>c^*(\Delta)$ then there exists no left-perfect matching with high probability. The threshold $c^*(\Delta)$ is the same as the known threshold for offline $k$-ary cuckoo hashing for integral or non-integral $k=\Delta$.


Invariant Scattering Convolution Networks

Abstract: A wavelet scattering network computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification. It cascades wavelet transform convolutions with non-linear modulus and averaging operators. The first network layer outputs SIFT-type descriptors whereas the next layers provide complementary invariant information which improves classification. The mathematical analysis of wavelet scattering networks explains important properties of deep convolution networks for classification. A scattering representation of stationary processes incorporates higher order moments and can thus discriminate textures having the same Fourier power spectrum. State of the art classification results are obtained for handwritten digits and texture discrimination, using a Gaussian kernel SVM and a generative PCA classifier.


The Distributed Network Processor: a novel off-chip and on-chip interconnection network architecture

Abstract: One of the most demanding challenges for the designers of parallel computing architectures is to deliver an efficient network infrastructure providing low latency, high bandwidth communications while preserving scalability. Besides off-chip communications between processors, recent multi-tile (i.e. multi-core) architectures face the challenge for an efficient on-chip interconnection network between processor's tiles. In this paper, we present a configurable and scalable architecture, based on our Distributed Network Processor (DNP) IP Library, targeting systems ranging from single MPSoCs to massive HPC platforms. The DNP provides inter-tile services for both on-chip and off-chip communications with a uniform RDMA style API, over a multi-dimensional direct network with a (possibly) hybrid topology.


Programming with Algebraic Effects and Handlers

Abstract: Eff is a programming language based on the algebraic approach to computational effects, in which effects are viewed as algebraic operations and effect handlers as homomorphisms from free algebras. Eff supports first-class effects and handlers through which we may easily define new computational effects, seamlessly combine existing ones, and handle them in novel ways. We give a denotational semantics of eff and discuss a prototype implementation based on it. Through examples we demonstrate how the standard effects are treated in eff, and how eff supports programming techniques that use various forms of delimited continuations, such as backtracking, breadth-first search, selection functionals, cooperative multi-threading, and others.


BotMosaic: Collaborative Network Watermark for Botnet Detection

Abstract: Recent research has made great strides in the field of detecting botnets. However, botnets of all kinds continue to plague the Internet, as many ISPs and organizations do not deploy these techniques. We aim to mitigate this state by creating a very low-cost method of detecting infected bot host. Our approach is to leverage the botnet detection work carried out by some organizations to easily locate collaborating bots elsewhere. We created BotMosaic as a countermeasure to IRC-based botnets. BotMosaic relies on captured bot instances controlled by a watermarker, who inserts a particular pattern into their network traffic. This pattern can then be detected at a very low cost by client organizations and the watermark can be tuned to provide acceptable false-positive rates. A novel feature of the watermark is that it is inserted collaboratively into the flows of multiple captured bots at once, in order to ensure the signal is strong enough to be detected. BotMosaic can also be used to detect stepping stones and to help trace back to the botmaster. It is content agnostic and can operate on encrypted traffic. We evaluate BotMosaic using simulations and a testbed deployment.


SPARQL for a Web of Linked Data: Semantics and Computability (Extended Version)

Abstract: The World Wide Web currently evolves into a Web of Linked Data where content providers publish and link data as they have done with hypertext for the last 20 years. While the declarative query language SPARQL is the de facto for querying a-priory defined sets of data from the Web, no language exists for querying the Web of Linked Data itself. However, it seems natural to ask whether SPARQL is also suitable for such a purpose. In this paper we formally investigate the applicability of SPARQL as a query language for Linked Data on the Web. In particular, we study two query models: 1) a full-Web semantics where the scope of a query is the complete set of Linked Data on the Web and 2) a family of reachability-based semantics which restrict the scope to data that is reachable by traversing certain data links. For both models we discuss properties such as monotonicity and computability as well as the implications of querying a Web that is infinitely large due to data generating servers.


The Complexity of the Puzzles of Final Fantasy XIII-2

Abstract: We analyze the computational complexity of solving the three "temporal rift" puzzles in the recent popular video game Final Fantasy XIII-2. We show that the Tile Trial puzzle is NP-hard and we provide an efficient algorithm for solving the Crystal Bonds puzzle. We also show that slight generalizations of the Crystal Bonds and Hands of Time puzzles are NP-hard.


CensorSpoofer: Asymmetric Communication with IP Spoofing for Censorship-Resistant Web Browsing

Abstract: A key challenge in censorship-resistant web browsing is being able to direct legitimate users to redirection proxies while preventing censors, posing as insiders, from discovering their addresses and blocking them. We propose a new framework for censorship-resistant web browsing called {\it CensorSpoofer} that addresses this challenge by exploiting the asymmetric nature of web browsing traffic and making use of IP spoofing. CensorSpoofer de-couples the upstream and downstream channels, using a low-bandwidth indirect channel for delivering outbound requests (URLs) and a high-bandwidth direct channel for downloading web content. The upstream channel hides the request contents using steganographic encoding within email or instant messages, whereas the downstream channel uses IP address spoofing so that the real address of the proxies is not revealed either to legitimate users or censors. We built a proof-of-concept prototype that uses encrypted VoIP for this downstream channel and demonstrated the feasibility of using the CensorSpoofer framework in a realistic environment.


Network-Destabilizing Attacks

Abstract: The Border Gateway Protocol (BGP) sets up routes between the smaller networks that make up the Internet. Despite its crucial role, BGP is notoriously vulnerable to serious problems, including (1) propagation of bogus routing information due to attacks or misconfigurations, and (2) network instabilities in the form of persistent routing oscillations. The conditions required to avoid BGP instabilities are quite delicate. How, then, can we explain the observed stability of today's Internet in the face of common configuration errors and attacks? This work explains this phenomenon by first noticing that almost every observed attack and misconfiguration to date shares a common characteristic: even when a router announces egregiously bogus information, it will continue to announce the same bogus information for the duration of its attack/misconfiguration. We call these the "fixed-route attacks", and show that, while even simple fixed-route attacks can destabilize a network, the commercial routing policies used in today's Internet prevent such attacks from creating instabilities.


Statistical Function Tagging and Grammatical Relations of Myanmar Sentences

Abstract: This paper describes a context free grammar (CFG) based grammatical relations for Myanmar sentences which combine corpus-based function tagging system. Part of the challenge of statistical function tagging for Myanmar sentences comes from the fact that Myanmar has free-phrase-order and a complex morphological system. Function tagging is a pre-processing step to show grammatical relations of Myanmar sentences. In the task of function tagging, which tags the function of Myanmar sentences with correct segmentation, POS (part-of-speech) tagging and chunking information, we use Naive Bayesian theory to disambiguate the possible function tags of a word. We apply context free grammar (CFG) to find out the grammatical relations of the function tags. We also create a functional annotated tagged corpus for Myanmar and propose the grammar rules for Myanmar sentences. Experiments show that our analysis achieves a good result with simple sentences and complex sentences.


An Optimized Sparse Approximate Matrix Multiply for Matrices with Decay

Abstract: We present an optimized single-precision implementation of the Sparse Approximate Matrix Multiply (\SpAMM{}) [M. Challacombe and N. Bock, arXiv {\bf 1011.3534} (2010)], a fast algorithm for matrix-matrix multiplication for matrices with decay that achieves an $\mathcal{O} (n \log n)$ computational complexity with respect to matrix dimension $n$. We find that the max norm of the error achieved with a \SpAMM{} tolerance below $2 \times 10^{-8}$ is lower than that of the single-precision {\tt SGEMM} for dense quantum chemical matrices, while outperforming {\tt SGEMM} with a cross-over already for small matrices ($n \sim 1000$). Relative to naive implementations of \SpAMM{} using Intel's Math Kernel Library ({\tt MKL}) or AMD's Core Math Library ({\tt ACML}), our optimized version is found to be significantly faster. Detailed performance comparisons are made for quantum chemical matrices with differently structured sub-blocks. Finally, we discuss the potential of improved hardware prefetch to yield 2--3x speedups.


Requirements Engineering Methods: A Classification Framework and Research Challenges

Abstract: Requirements Engineering Methods (REMs) support Requirements Engineering (RE) tasks, from elicitation, through modeling and analysis, to validation and evolution of requirements. Despite the growing interest to design, validate and teach REMs, it remains unclear what components REMs should have. A classification framework for REMs is proposed. It distinguishes REMs based on the domain-independent properties of their components. The classification framework is intended to facilitate (i) analysis, teaching and extension of existing REMs, (ii) engineering and validation of new REMs, and (iii) identifying research challenges in REM design. The framework should help clarify further the relations between REM and other concepts of interest in and to RE, including Requirements Problem and Solution, Requirements Modeling Language, and Formal Method.


High performance computing network for cloud environment using simulators

Abstract: Cloud computing is the next generation computing. Adopting the cloud computing is like signing up new form of a website. The GUI which controls the cloud computing make is directly control the hardware resource and your application. The difficulty part in cloud computing is to deploy in real environment. Its' difficult to know the exact cost and it's requirement until and unless we buy the service not only that whether it will support the existing application which is available on traditional data center or had to design a new application for the cloud computing environment. The security issue, latency, fault tolerance are some parameter which we need to keen care before deploying, all this we only know after deploying but by using simulation we can do the experiment before deploying it to real environment. By simulation we can understand the real environment of cloud computing and then after it successful result we can start deploying your application in cloud computing environment. By using the simulator it will save us lots of time and money.


Auditing for Distributed Storage Systems

Abstract: Distributed storage codes have recently received a lot of attention in the community. Independently, another body of work has proposed integrity checking schemes for cloud storage, none of which, however, is customized for coding-based storage or can efficiently support repair. In this work, we bridge the gap between these two currently disconnected bodies of work. We propose NC-Audit, a novel cryptography-based remote data integrity checking scheme, designed specifically for network coding-based distributed storage systems. NC-Audit combines, for the first time, the following desired properties: (i) efficient checking of data integrity, (ii) efficient support for repairing failed nodes, and (iii) protection against information leakage when checking is performed by a third party. The key ingredient of the design of NC-Audit is a novel combination of SpaceMac, a homomorphic message authentication code (MAC) scheme for network coding, and NCrypt, a novel chosen-plaintext attack (CPA) secure encryption scheme that is compatible with SpaceMac. Our evaluation of a Java implementation of NC-Audit shows that an audit costs the storage node and the auditor a modest amount computation time and lower bandwidth than prior work.


An Input-Output Simulation Approach to Controlling Multi-AffineSystems for Linear Temporal Logic Specifications

Abstract: This paper presents an input-output simulation approach to controlling multi-affine systems for linear temporal logic (LTL) specifications, which consists of the following steps. First, we partition the state space into rectangles, each of which satisfies atomic LTL propositions. Then, we study the control of multi-affine systems on rectangles including the control of driving all trajectories starting from a rectangle to exit through a facet and the control of stabilizing the system towards a desired point. With the proposed controllers, a finitely abstracted transition system is constructed which is shown to be input-output simulated by the rectangular transition system of the multi-affine system. Since input-output simulation preserves LTL properties, the controller synthesis of the multi-affine system for LTL specifications is achieved by designing a nonblocking supervisor for the abstracted transition system and by continuously implementing the resulting supervisor for the original multi-affine system.


Bisimilarity Enforcing Supervisory Control for Deterministic Specifications

Abstract: This paper investigates the supervisory control of nondeterministic discrete event systems to enforce bisimilarity with respect to deterministic specifications. A notion of synchronous simulation-based controllability is introduced as a necessary and sufficient condition for the existence of a bisimilarity enforcing supervisor, and a polynomial algorithm is developed to verify such a condition. When the existence condition holds, a supervisor achieving bisimulation equivalence is constructed. Furthermore, when the existence condition does not hold, two different methods are provided for synthesizing maximal permissive sub-specifications.


Data Confidentiality in Mobile Ad hoc Networks

Abstract: Mobile ad hoc networks (MANETs) are self-configuring infrastructure-less networks comprised of mobile nodes that communicate over wireless links without any central control on a peer-to-peer basis. These individual nodes act as routers to forward both their own data and also their neighbours' data by sending and receiving packets to and from other nodes in the network. The relatively easy configuration and the quick deployment make ad hoc networks suitable the emergency situations (such as human or natural disasters) and for military units in enemy territory. Securing data dissemination between these nodes in such networks, however, is a very challenging task. Exposing such information to anyone else other than the intended nodes could cause a privacy and confidentiality breach, particularly in military scenarios. In this paper we present a novel framework to enhance the privacy and data confidentiality in mobile ad hoc networks by attaching the originator policies to the messages as they are sent between nodes. We evaluate our framework using the Network Simulator (NS-2) to check whether the privacy and confidentiality of the originator are met. For this we implemented the Policy Enforcement Points (PEPs), as NS-2 agents that manage and enforce the policies attached to packets at every node in the MANET.


Remote Sensing and Control for Establishing and Maintaining Digital Irrigation

Abstract: The remotely sensed data from an unknown location is transmitted in real time through internet and gathered in a PC. The data is collected for a considerable period of time and analyzed in PC as to assess the suitability and fertility of the land for establishing an electronic plantation in that area. The analysis also helps deciding the plantation of appropriate plants in the location identified. The system performing this task with appropriate transducers installed in remote area, the methodologies involved in transmission and data gathering are reported.. The second part of the project deals with data gathering from remote site and issuing control signals to remote appliances in the site; all performed through internet. Therefore, this control scheme is a duplex system monitoring the irrigation activities by collecting data in one direction and issuing commands on the opposite direction. This scheme maintains the digital irrigation systems effectively and efficiently as to utilize the resources optimally for yielding enhanced production. The methodologies involved in extending the two way communication of data are presented.


Known algorithms for EDGE CLIQUE COVER are probably optimal

Abstract: In the EDGE CLIQUE COVER (ECC) problem, given a graph G and an integer k, we ask whether the edges of G can be covered with k complete subgraphs of G or, equivalently, whether G admits an intersection model on k-element universe. Gramm et al. [JEA 2008] have shown a set of simple rules that reduce the number of vertices of G to 2^k, and no algorithm is known with significantly better running time bound than a brute-force search on this reduced instance. In this paper we show that the approach of Gramm et al. is essentially optimal: we present a polynomial time algorithm that reduces an arbitrary 3-CNF-SAT formula with n variables and m clauses to an equivalent ECC instance (G,k) with k = O(log n) and |V(G)| = O(n + m). Consequently, there is no 2^{2^{o(k)}}poly(n) time algorithm for the ECC problem, unless the Exponential Time Hypothesis fails. To the best of our knowledge, these are the first results for a natural, fixed-parameter tractable problem, and proving that a doubly-exponential dependency on the parameter is essentially necessary.


Performance Analysis for Bandwidth Allocation in IEEE 802.16 Broadband Wireless Networks using BMAP Queueing

Abstract: This paper presents a performance analysis for the bandwidth allocation in IEEE 802.16 broadband wireless access (BWA) networks considering the packet-level quality-of-service (QoS) constraints. Adaptive Modulation and Coding (AMC) rate based on IEEE 802.16 standard is used to adjust the transmission rate adaptively in each frame time according to channel quality in order to obtain multiuser diversity gain. To model the arrival process and the traffic source we use the Batch Markov Arrival Process (BMAP), which enables more realistic and more accurate traffic modelling. We determine analytically different performance parameters, such as average queue length, packet dropping probability, queue throughput and average packet delay. Finally, the analytical results are validated numerically.


BPEL-RF: A formal framework for BPEL orchestrations integrating distributed resources

Abstract: Web service compositions are gaining attention to develop complex web systems by combination of existing services. Thus, there are many works that leverage the advantages of this approach. However, there are only few works that use web service compositions to manage distributed resources. In this paper, we then present a formal model that combines orchestrations written in BPEL with distributed resources, by using WSRF.


A comparative evaluation of two algorithms of detection of masses on mammograms

Abstract: In this paper, we implement and carry out the comparison of two methods of computer-aided-detection of masses on mammograms. The two algorithms basically consist of 3 steps each: segmentation, binarization and noise suppression using different techniques for each step. A database of 60 images was used to compare the performance of the two algorithms in terms of general detection efficiency, conservation of size and shape of detected masses.


AMC Model for Denial of Sleep Attack Detection

Abstract: Due to deployment in hostile environment, wireless sensor network is vulnerable to various attacks. Exhausted sensor nodes in sensor network become a challenging issue because it disrupts the normal connectivity of the network. Affected nodes give rise to denial of service that resists to get the objective of sensor network in real life. A mathematical model based on Absorbing Markov Chain (AMC)is proposed for Denial of Sleep attack detection in sensor network. In this mechanism, whether sensor network is affected by denial of sleep attack or not can be decided by considering expected death time of sensor network under normal scenario.


A Comprehensive Study and Performance Comparison of M-ary Modulation Schemes for an Efficient Wireless Mobile Communication System

Abstract: Wireless communications has become one of the fastest growing areas in our modern life and creates enormous impact on nearly every feature of our daily life. In this paper, the performance of M-ary modulations schemes (MPSK, MQAM, MFSK) based wireless communication system on audio signal transmission over Additive Gaussian Noise (AWGN) channel are analyzed in terms of bit error probability as a function of SNR. Based on the results obtained in the present study, MPSK and MQAM are showing better performance for lower modulation order whereas these are inferior with higher M. The BER value is smaller in MFSK for higher M, but it is worse due to the distortion in the reproduce signal at the receiver end. The lossless reproduction of recorded voice signal can be achieved at the receiver end with a lower modulation order.


Calculation of the minimum computational complexity based on information entropy

Abstract: In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on information entropy. The relationship between the minimum computational complexity and information entropy change is illustrated. A few examples are served as evidence of such connection. Meanwhile some basic rules of modeling problems are established. Finally, the nature of solving problems with computer programs is disclosed to support this theory and a redefinition of information entropy in this filed is proposed. This will develop a new field of science.


Using Hausdorff Distance for New Medical Image Annotation

Abstract: Medical images annotation is most of the time a repetitive hard task. Collecting old similar annotations and assigning them to new medical images may not only enhance the annotation process, but also reduce ambiguity caused by repetitive annotations. The goal of this work is to propose an approach based on Hausdorff distance able to compute similarity between a new medical image and old stored images. User has to choose then one of the similar images and annotations related to the selected one are assigned to the new one.


Thermal analysis & optimization of a 3 dimensional heterogeneous structure

Abstract: Besides the lot of advantages offered by the 3D stacking of devices in an integrated circuit there is a chance of device damage due to rise in peak temperature value. Hence, in order to make use of all the potential benefits of the vertical stacking a thermal aware design is very essential. The first step for designing a thermal aware architecture is to analyze the hotspot temperature generated by the devices. In this paper we are presenting the results of our thermal analysis experiments of a 3D heterogeneous structure with three layers. The bottom layer had eight identical processors at 2.4 GHz and the top layer was with four memory units. The intermediate layer was a thermal interface material (TIM). The 2D thermal analysis of the top and bottom layers was also done separately. In the next step simulations were carried out by varying TIM thickness and conductivity to study its affect on hotspot temperature so as to optimize the temperature distribution.


Undominated Groves Mechanisms

Abstract: The family of Groves mechanisms, which includes the well-known VCG mechanism (also known as the Clarke mechanism), is a family of efficient and strategy-proof mechanisms. Unfortunately, the Groves mechanisms are generally not budget balanced. That is, under such mechanisms, payments may flow into or out of the system of the agents, resulting in deficits or reduced utilities for the agents. We consider the following problem: within the family of Groves mechanisms, we want to identify mechanisms that give the agents the highest utilities, under the constraint that these mechanisms must never incur deficits. We adopt a prior-free approach. We introduce two general measures for comparing mechanisms in prior-free settings. We say that a non-deficit Groves mechanism $M$ {\em individually dominates} another non-deficit Groves mechanism $M'$ if for every type profile, every agent's utility under $M$ is no less than that under $M'$, and this holds with strict inequality for at least one type profile and one agent. We say that a non-deficit Groves mechanism $M$ {\em collectively dominates} another non-deficit Groves mechanism $M'$ if for every type profile, the agents' total utility under $M$ is no less than that under $M'$, and this holds with strict inequality for at least one type profile. The above definitions induce two partial orders on non-deficit Groves mechanisms. We study the maximal elements corresponding to these two partial orders, which we call the {\em individually undominated} mechanisms and the {\em collectively undominated} mechanisms, respectively.


Enhancement Techniques for Local Content Preservation and Contrast Improvement in Images

Abstract: There are several images that do not have uniform brightness which pose a challenging problem for image enhancement systems. As histogram equalization has been successfully used to correct for uniform brightness problems, a histogram equalization method that utilizes human visual system based thresholding(human vision thresholding) as well as logarithmic processing techniques were introduced later . But these methods are not good for preserving the local content of the image which is a major factor for various images like medical and aerial images. Therefore new method is proposed here. This method is referred as "Human vision thresholding with enhancement technique for dark blurred images for local content preservation". It uses human vision thresholding together with an existing enhancement method for dark blurred images. Furthermore a comparative study with another method for local content preservation is done which is further extended to make it suitable for contrast improvement. Experimental results shows that the proposed methods outperforms the former existing methods in preserving the local content for standard images, medical and aerial images.


Partition Sort Revisited: Reconfirming the Robustness in Average Case and much more!

Abstract: In our previous work there was some indication that Partition Sort could be having a more robust average case O(nlogn) complexity than the popular Quick Sort. In our first study in this paper, we reconfirm this through computer experiments for inputs from Cauchy distribution for which expectation theoretically does not exist. Additionally, the algorithm is found to be sensitive to parameters of the input probability distribution demanding further investigation on parameterized complexity. The results on this algorithm for Binomial inputs in our second study are very encouraging in that direction.


Distributional Measures of Semantic Distance: A Survey

Abstract: The ability to mimic human notions of semantic distance has widespread applications. Some measures rely only on raw text (distributional measures) and some rely on knowledge sources such as WordNet. Although extensive studies have been performed to compare WordNet-based measures with human judgment, the use of distributional measures as proxies to estimate semantic distance has received little attention. Even though they have traditionally performed poorly when compared to WordNet-based measures, they lay claim to certain uniquely attractive features, such as their applicability in resource-poor languages and their ability to mimic both semantic similarity and semantic relatedness. Therefore, this paper presents a detailed study of distributional measures. Particular attention is paid to flesh out the strengths and limitations of both WordNet-based and distributional measures, and how distributional measures of distance can be brought more in line with human notions of semantic distance. We conclude with a brief discussion of recent work on hybrid measures.


Outlier detection from ETL Execution trace

Abstract: Extract, Transform, Load (ETL) is an integral part of Data Warehousing (DW) implementation. The commercial tools that are used for this purpose captures lot of execution trace in form of various log files with plethora of information. However there has been hardly any initiative where any proactive analyses have been done on the ETL logs to improve their efficiency. In this paper we utilize outlier detection technique to find the processes varying most from the group in terms of execution trace. As our experiment was carried on actual production processes, any outlier we would consider as a signal rather than a noise. To identify the input parameters for the outlier detection algorithm we employ a survey among developer community with varied mix of experience and expertise. We use simple text parsing to extract these features from the logs, as shortlisted from the survey. Subsequently we applied outlier detection technique (Clustering based) on the logs. By this process we reduced our domain of detailed analysis from 500 logs to 44 logs (8 Percentage). Among the 5 outlier cluster, 2 of them are genuine concern, while the other 3 figure out because of the huge number of rows involved.