OpenRaiser/Intern-Atlas huggingface dataset:
Content Based Image Retrieval Using Exact Legendre Moments and Support Vector Machine
Venue: arXiv cs.CV 2010
Year: 2010

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based CBIR system is needed. Legendre Moments (LM) are orthogonal, computationally faster, and can represent image shape features compactly. CBIR system using Exact Legendre Moments (ELM) for gray scale images is proposed in this work. Superiority of the proposed CBIR system is observed over other moment based methods, viz., MI and ZM in terms of retrieval efficiency and retrieval time. Further, the classification efficiency is improved by employing Support Vector Machine (SVM) classifier. Improved retrieval results are obtained over existing CBIR algorithm based on Stacked Euler Vector (SERVE) combined with Modified Moment Invariants (MMI).
An Algebraic Approach for Computing Equilibria of a Subclass of Finite Normal Form Games
Venue: arXiv cs.GT 2010
Year: 2010

A Nash equilibrium has become important solution concept for analyzing the decision making in Game theory. In this paper, we consider the problem of computing Nash equilibria of a subclass of generic finite normal form games. We define "rational payoff irrational equilibria games" to be the games with all rational payoffs and all irrational equilibria. We present a purely algebraic method for computing all Nash equilibria of these games that uses knowledge of Galois groups. Some results, showing properties of the class of games, and an example to show working of the method concludes the paper.
On the Fly Query Entity Decomposition Using Snippets
Venue: arXiv cs.IR 2010
Year: 2010

One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, can be one of such tools. Such techniques usually rely on a prior training phase involving large datasets. That training is costly, specially in environments which are increasingly moving towards real time scenarios where latency to retrieve fresh informacion should be minimal. In this paper an `on-the-fly' query decomposition method is proposed. It uses snippets which are mined by means of a naïve statistical algorithm. An initial evaluation of such a method is provided, in addition to a discussion on its applicability to different scenarios.
Empirical learning aided by weak domain knowledge in the form of feature importance
Venue: arXiv cs.LG 2010
Year: 2010

Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowledge while being cost effective. Weak knowledge in the form of feature relative importance (FRI) is presented and explained. Feature relative importance is a real valued approximation of a feature's importance provided by experts. Advantage of using this knowledge is demonstrated by IANN, a modified multilayer neural network algorithm. IANN is a very simple modification of standard neural network algorithm but attains significant performance gains. Experimental results in the field of molecular biology show higher performance over other empirical learning algorithms including standard backpropagation and support vector machines. IANN performance is even comparable to a theory refinement system KBANN that uses stronger domain knowledge. This shows Feature relative importance can improve performance of existing empirical learning algorithms significantly with minimal effort.
An Implicit Characterization of PSPACE
Venue: arXiv cs.LO 2010
Year: 2010

We present a type system for an extension of lambda calculus with a conditional construction, named STAB, that characterizes the PSPACE class. This system is obtained by extending STA, a type assignment for lambda-calculus inspired by Lafont's Soft Linear Logic and characterizing the PTIME class. We extend STA by means of a ground type and terms for booleans and conditional. The key issue in the design of the type system is to manage the contexts in the rule for conditional in an additive way. Thanks to this rule, we are able to program polynomial time Alternating Turing Machines. From the well-known result APTIME = PSPACE, it follows that STAB is complete for PSPACE. Conversely, inspired by the simulation of Alternating Turing machines by means of Deterministic Turing machine, we introduce a call-by-name evaluation machine with two memory devices in order to evaluate programs in polynomial space. As far as we know, this is the first characterization of PSPACE that is based on lambda calculus and light logics.
Balancing congestion for unsplittable routing on a bidirected ring
Venue: arXiv cs.NI 2010
Year: 2010

Given a bidirected ring with capacities and a demand graph, we present an approximation algorithm to the problem of finding the minimum $α$ such that there exists a feasible unsplittable routing of the demands after multiplying each capacity by $α$. We also give an approximation scheme to the problem.
Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges
Venue: arXiv cs.DC 2010
Year: 2010

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.
Soft-Output Sphere Decoder for Multiple-Symbol Differential Detection of Impulse-Radio Ultra-Wideband
Venue: arXiv cs.IT 2010
Year: 2010

Power efficiency of noncoherent receivers for impulse-radio ultra-wideband (IR-UWB) transmission systems can significantly be improved, on the one hand, by employing multiple-symbol differential detection (MSDD), and, on the other hand, by providing reliability information to the subsequent channel decoder. In this paper, we combine these two techniques. Incorporating the computation of the soft information into a single-tree-search sphere decoder (SD), the application of this soft-output MSDD in a typical IR-UWB system imposes only a moderate complexity increase at, however, improved performance over hard-output MSDD, and in particular, over conventional symbol-by-symbol noncoherent differential detection.
Computing the speed of convergence of ergodic averages and pseudorandom points in computable dynamical systems
Venue: arXiv cs.NA 2010
Year: 2010

A pseudorandom point in an ergodic dynamical system over a computable metric space is a point which is computable but its dynamics has the same statistical behavior as a typical point of the system. It was proved in [Avigad et al. 2010, Local stability of ergodic averages] that in a system whose dynamics is computable the ergodic averages of computable observables converge effectively. We give an alternative, simpler proof of this result. This implies that if also the invariant measure is computable then the pseudorandom points are a set which is dense (hence nonempty) on the support of the invariant measure.
Computing the Solutions of the Combined Korteweg-de Vries Equation by Turing Machines
Venue: arXiv cs.CC 2010
Year: 2010

In this paper, we study the computability of the initial value problem of the Combined KdV equation. It is shown that, for any integer s>2, the nonlinear solution operator which maps an initial condition data to the solution of the Combined KdV equation can be computed by a Turing machine.
Making big steps in trajectories
Venue: arXiv cs.MS 2010
Year: 2010

We consider the solution of initial value problems within the context of hybrid systems and emphasise the use of high precision approximations (in software for exact real arithmetic). We propose a novel algorithm for the computation of trajectories up to the area where discontinuous jumps appear, applicable for holomorphic flow functions. Examples with a prototypical implementation illustrate that the algorithm might provide results with higher precision than well-known ODE solvers at a similar computation time.
Multicast Capacity Scaling of Wireless Networks with Multicast Outage
Venue: arXiv cs.IT 2010
Year: 2010

Multicast transmission has several distinctive traits as opposed to more commonly studied unicast networks. Specially, these include (i) identical packets must be delivered successfully to several nodes, (ii) outage could simultaneously happen at different receivers, and (iii) the multicast rate is dominated by the receiver with the weakest link in order to minimize outage and retransmission. To capture these key traits, we utilize a Poisson cluster process consisting of a distinct Poisson point process (PPP) for the transmitters and receivers, and then define the multicast transmission capacity (MTC) as the maximum achievable multicast rate times the number of multicast clusters per unit volume, accounting for outages and retransmissions. Our main result shows that if $τ$ transmission attempts are allowed in a multicast cluster, the MTC is $Θ\left(ρk^{x}\log(k)\right)$ where $ρ$ and $x$ are functions of $τ$ depending on the network size and density, and $k$ is the average number of the intended receivers in a cluster. We also show that an appropriate number of retransmissions can significantly enhance the MTC.
Gestion efficace de séries temporelles en P2P: Application à l'analyse technique et l'étude des objets mobiles
Venue: arXiv cs.DB 2010
Year: 2010

In this paper, we propose a simple generic model to manage time series. A time series is composed of a calendar with a typed value for each calendar entry. Although the model could support any kind of XML typed values, in this paper we focus on real numbers, which are the usual application. We define basic vector space operations (plus, minus, scale), and also relational-like and application oriented operators to manage time series. We show the interest of this generic model on two applications: (i) a stock investment helper; (ii) an ecological transport management system. Stock investment requires window-based operations while trip management requires complex queries. The model has been implemented and tested in PHP, Java, and XQuery. We show benchmark results illustrating that the computing of 5000 series of over 100.000 entries in length - common requirements for both applications - is difficult on classical centralized PCs. In order to serve a community of users sharing time series, we propose a P2P implementation of time series by dividing them in segments and providing optimized algorithms for operator expression computation.
Secure Neighbor Position Discovery in VANETs
Venue: arXiv cs.CR 2010
Year: 2010

Many significant functionalities of vehicular ad hoc networks (VANETs) require that nodes have knowledge of the positions of other vehicles, and notably of those within communication range. However, adversarial nodes could provide false position information or disrupt the acquisition of such information. Thus, in VANETs, the discovery of neighbor positions should be performed in a secure manner. In spite of a multitude of security protocols in the literature, there is no secure discovery protocol for neighbors positions. We address this problem in our paper: we design a distributed protocol that relies solely on information exchange among one-hop neighbors, we analyze its security properties in presence of one or multiple (independent or colluding) adversaries, and we evaluate its performance in a VANET environment using realistic mobility traces. We show that our protocol can be highly effective in detecting falsified position information, while maintaining a low rate of false positive detections.
Analysis of Beaulieu Pulse Shaping Family Based FIR Filter for WCDMA
Venue: arXiv cs.NI 2010
Year: 2010

The analysis and simulation of transmit and receive pulse shaping filter is an important aspect of digital wireless communication since it has a direct effect on error probabilities. Pulse shaping for wireless communication over time as well as frequency selective channels is the need of hour for 3G and 4G systems. The pulse shaping filter is a useful means to shape the signal spectrum and avoid interferences. Basically digital filters are used to modify the characteristics of signal in time and frequency domain and have been recognized as primary digital signal processing operations.
An Interactive Zoo Guide: A Case Study of Collaborative Learning
Venue: arXiv cs.CY 2010
Year: 2010

Real Industry Projects and team work can have a great impact on student learning but providing these activities requires significant commitment from academics. It requires several years planning implementing to create a collaborative learning environment that mimics the real world ICT (Information and Communication Technology) industry workplace. In this project, staff from all the three faculties, namely the Faculty of Health, Engineering and Science, Faculty of Arts, Education and Human Development, and Faculty of Business and Law in higher education work together to establish a detailed project management plan and to develop the unit guidelines for participating students. The proposed project brings together students from business, multimedia and computer science degrees studying their three project-based units within each faculty to work on a relatively large IT project with our industry partner, Melbourne Zoo. This paper presents one multimedia software project accomplished by one of the multi-discipline student project teams. The project was called 'Interactive ZooOz Guide' and developed on a GPS-enabled PDA device in 2007. The developed program allows its users to navigate through the Zoo via an interactive map and provides multimedia information of animals on hotspots at the 'Big Cats' section of the Zoo so that it enriches user experience at the Zoo. A recent development in zoo applications is also reviewed. This paper is also intended to encourage academia to break boundaries to enhance students' learning beyond classroom.
Building a Data Warehouse for National Social Security Fund of the Republic of Tunisia
Venue: arXiv cs.DB 2010
Year: 2010

The amounts of data available to decision makers are increasingly important, given the network availability, low cost storage and diversity of applications. To maximize the potential of these data within the National Social Security Fund (NSSF) in Tunisia, we have built a data warehouse as a multidimensional database, cleaned, homogenized, historicized and consolidated. We used Oracle Warehouse Builder to extract, transform and load the source data into the Data Warehouse, by applying the KDD process. We have implemented the Data Warehouse as an Oracle OLAP. The knowledge extraction has been performed using the Oracle Discoverer tool. This allowed users to take maximum advantage of knowledge as a regular report or as ad hoc queries. We started by implementing the main topic for this public institution, accounting for the movements of insured persons. The great success that has followed the completion of this work has encouraged the NSSF to complete the achievement of other topics of interest within the NSSF. We suggest in the near future to use Multidimensional Data Mining to extract hidden knowledge and that are not predictable by the OLAP.
Developing E-Learning Materials for Software Development Course
Venue: arXiv cs.CY 2010
Year: 2010

Software Development is a core second-year course currently offered to undergraduate students at Victoria University at its five local and international campuses. The project aims to redesign the existing course curriculum to support student-centred teaching and learning. It is intended to provide a learning context in which learners can reflect on new material, discuss their tentative understandings with others, actively search for new information, develop skills in communication and collaboration, and build conceptual connections to their existing knowledge base. The key feature of the cross-campus curriculum innovation is the use of Blackboard, short for Blackboard Learning System, to assist in course content organization and online delivery. A well-defined and integrated case study is used throughout the course to provide realistic practical experience of software development. It allows students to take control of their own learning while at the same time providing support to those students who have particular learning difficulties. In this paper, the developed curriculum and the learning outcome are described. The e-Learning material and various Blackboard tools used for teaching and learning activities are presented. Finally, conclusion is drawn from classroom experience.
On cycles through two arcs in strong multipartite tournaments
Venue: arXiv cs.DM 2010
Year: 2010

A multipartite tournament is an orientation of a complete $c$-partite graph. In [L. Volkmann, A remark on cycles through an arc in strongly connected multipartite tournaments, Appl. Math. Lett. 20 (2007) 1148--1150], Volkmann proved that a strongly connected $c$-partite tournament with $c \ge 3$ contains an arc that belongs to a directed cycle of length $m$ for every $m \in \{3, 4, \ldots, c\}$. He also conjectured the existence of three arcs with this property. In this note, we prove the existence of two such arcs.
Shannon Revisited: Considering a More Tractable Expression to Measure and Manage Intractability, Uncertainty, Risk, Ignorance, and Entropy
Venue: arXiv cs.IT 2010
Year: 2010

Building on Shannon's lead, let's consider a more malleable expression for tracking uncertainty, and states of "knowledge available" vs. "knowledge missing," to better practice innovation, improve risk management, and successfully measure progress of intractable undertakings. Shannon's formula, and its common replacements (Renyi, Tsallis) compute to increased knowledge whenever two competing choices, however marginal, exchange probability measures. Such and other distortions are corrected by anchoring knowledge to a reference challenge. Entropy then expresses progress towards meeting that challenge. We introduce an 'interval of interest' outside which all probability changes should be ignored. The resultant formula for Missing Acquirable Relevant Knowledge (MARK) serves as a means to optimize intractable activities involving knowledge acquisition, such as research, development, risk management, and opportunity exploitation.
Body-and-cad Geometric Constraint Systems
Venue: arXiv cs.CG 2010
Year: 2010

Motivated by constraint-based CAD software, we develop the foundation for the rigidity theory of a very general model: the body-and-cad structure, composed of rigid bodies in 3D constrained by pairwise coincidence, angular and distance constraints. We identify 21 relevant geometric constraints and develop the corresponding infinitesimal rigidity theory for these structures. The classical body-and-bar rigidity model can be viewed as a body-and-cad structure that uses only one constraint from this new class. As a consequence, we identify a new, necessary, but not sufficient, counting condition for minimal rigidity of body-and-cad structures: nested sparsity. This is a slight generalization of the well-known sparsity condition of Maxwell.
Hybrid Scenario Based Performance Analysis of DSDV and DSR
Venue: arXiv cs.NI 2010
Year: 2010

The area of mobile ad hoc networking has received considerable attention of the research community in recent years. These networks have gained immense popularity primarily due to their infrastructure-less mode of operation which makes them a suitable candidate for deployment in emergency scenarios like relief operation, battlefield etc., where either the pre-existing infrastructure is totally damaged or it is not possible to establish a new infrastructure quickly. However, MANETs are constrained due to the limited transmission range of the mobile nodes which reduces the total coverage area. Sometimes the infrastructure-less ad hoc network may be combined with a fixed network to form a hybrid network which can cover a wider area with the advantage of having less fixed infrastructure. In such a combined network, for transferring data, we need base stations which act as gateways between the wired and wireless domains. Due to the hybrid nature of these networks, routing is considered a challenging task. Several routing protocols have been proposed and tested under various traffic conditions. However, the simulations of such routing protocols usually do not consider the hybrid network scenario. In this work we have carried out a systematic performance study of the two prominent routing protocols: Destination Sequenced Distance Vector Routing (DSDV) and Dynamic Source Routing (DSR) protocols in the hybrid networking environment. We have analyzed the performance differentials on the basis of three metrics - packet delivery fraction, average end-to-end delay and normalized routing load under varying pause time with different number of sources using NS2 based simulation.
Secret Sharing and Proactive Renewal of Shares in Hierarchical Groups
Venue: arXiv cs.CR 2010
Year: 2010

Secret sharing in user hierarchy represents a challenging area for research. Although a lot of work has already been done in this direc- tion, this paper presents a novel approach to share a secret among a hierarchy of users while overcoming the limitations of the already exist- ing mechanisms. Our work is based on traditional (k +1; n)-threshold secret sharing, which is secure as long as an adversary can compromise not more than k secret shares. But in real life it is often feasible for an adversary to obtain more than k shares over a long period of time. So, in our work we also present a way to overcome this vulnerability, while implementing our hierarchical secret sharing scheme. The use of Elliptic Curve Cryptography makes the computations easier and faster in our work.