The Arcade Learning Environment: An Evaluation Platform for General Agents

Abstract: In this article we introduce the Arcade Learning Environment (ALE): both a challenge problem and a platform and methodology for evaluating the development of general, domain-independent AI technology. ALE provides an interface to hundreds of Atari 2600 game environments, each one different, interesting, and designed to be a challenge for human players. ALE presents significant research challenges for reinforcement learning, model learning, model-based planning, imitation learning, transfer learning, and intrinsic motivation. Most importantly, it provides a rigorous testbed for evaluating and comparing approaches to these problems. We illustrate the promise of ALE by developing and benchmarking domain-independent agents designed using well-established AI techniques for both reinforcement learning and planning. In doing so, we also propose an evaluation methodology made possible by ALE, reporting empirical results on over 55 different games. All of the software, including the benchmark agents, is publicly available.


Complexity of Canadian Traveler Problem Variants

Abstract: The Canadian traveler problem (CTP) is the problem of traversing a given graph, where some of the edges may be blocked - a state which is revealed only upon reaching an incident vertex. Originally stated by Papadimitriou and Yannakakis (1991), the adversarial version of CTP was shown to be PSPACE-complete, with the stochastic version shown to be #P-hard. We show that stochastic CTP is also PSPACE-complete: initially proving PSPACE-hardness for the dependent version of stochastic CTP,and proceeding with gadgets that allow us to extend the proof to the independent case. Since for disjoint-path graphs, CTP can be solved in polynomial time, we examine the complexity of the more general remote-sensing CTP, and show that it is NP-hard even for disjoint-path graphs.


"Two betting strategies that predict all compressible sequences" presentation

Abstract: Presentation for a talk "Two betting strategies that predict all compressible sequences" given at Seventh International Conference on Computability, Complexity and Randomness (CCR 2012) http://www.newton.ac.uk/programmes/SAS/seminars/070217001.html


Design and User Satisfaction of Interactive Maps for Visually Impaired People

Abstract: Multimodal interactive maps are a solution for presenting spatial information to visually impaired people. In this paper, we present an interactive multimodal map prototype that is based on a tactile paper map, a multi-touch screen and audio output. We first describe the different steps for designing an interactive map: drawing and printing the tactile paper map, choice of multi-touch technology, interaction technologies and the software architecture. Then we describe the method used to assess user satisfaction. We provide data showing that an interactive map - although based on a unique, elementary, double tap interaction - has been met with a high level of user satisfaction. Interestingly, satisfaction is independent of a user's age, previous visual experience or Braille experience. This prototype will be used as a platform to design advanced interactions for spatial learning.


Testing Permanent Oracles -- Revisited

Abstract: Suppose we are given an oracle that claims to approximate the permanent for most matrices X, where X is chosen from the Gaussian ensemble (the matrix entries are i.i.d. univariate complex Gaussians). Can we test that the oracle satisfies this claim? This paper gives a polynomial-time algorithm for the task. The oracle-testing problem is of interest because a recent paper of Aaronson and Arkhipov showed that if there is a polynomial-time algorithm for simulating boson-boson interactions in quantum mechanics, then an approximation oracle for the permanent (of the type described above) exists in BPP^NP. Since computing the permanent of even 0/1 matrices is #P-complete, this seems to demonstrate more computational power in quantum mechanics than Shor's factoring algorithm does. However, unlike factoring, which is in NP, it was unclear previously how to test the correctness of an approximation oracle for the permanent, and this is the contribution of the paper. The technical difficulty overcome here is that univariate polynomial self-correction, which underlies similar oracle-testing algorithms for permanent over finite fields --- and whose discovery led to a revolution in complexity theory --- does not seem to generalize to complex (or even, real) numbers. We believe that this tester will motivate further progress on understanding the permanent of Gaussian matrices.


Exploring the rationality of some syntactic merging operators (extended version)

Abstract: Most merging operators are defined by semantics methods which have very high computational complexity. In order to have operators with a lower computational complexity, some merging operators defined in a syntactical way have be proposed. In this work we define some syntactical merging operators and exploring its rationality properties. To do that we constrain the belief bases to be sets of formulas very close to logic programs and the underlying logic is defined through forward chaining rule (Modus Ponens). We propose two types of operators: arbitration operators when the inputs are only two bases and fusion with integrity constraints operators. We introduce a set of postulates inspired of postulates LS, proposed by Liberatore and Shaerf and then we analyzed the first class of operators through these postulates. We also introduce a set of postulates inspired of postulates KP, proposed by Konieczny and Pino P\'erez and then we analyzed the second class of operators through these postulates.


The Architecture of an Autonomic, Resource-Aware, Workstation-Based Distributed Database System

Abstract: Distributed software systems that are designed to run over workstation machines within organisations are termed workstation-based. Workstation-based systems are characterised by dynamically changing sets of machines that are used primarily for other, user-centric tasks. They must be able to adapt to and utilize spare capacity when and where it is available, and ensure that the non-availability of an individual machine does not affect the availability of the system. This thesis focuses on the requirements and design of a workstation-based database system, which is motivated by an analysis of existing database architectures that are typically run over static, specially provisioned sets of machines. A typical clustered database system -- one that is run over a number of specially provisioned machines -- executes queries interactively, returning a synchronous response to applications, with its data made durable and resilient to the failure of machines. There are no existing workstation-based databases. Furthermore, other workstation-based systems do not attempt to achieve the requirements of interactivity and durability, because they are typically used to execute asynchronous batch processing jobs that tolerate data loss -- results can be re-computed. These systems use external servers to store the final results of computations rather than workstation machines. This thesis describes the design and implementation of a workstation-based database system and investigates its viability by evaluating its performance against existing clustered database systems and testing its availability during machine failures.


Intruder deducibility constraints with negation. Decidability and application to secured service compositions

Abstract: The problem of finding a mediator to compose secured services has been reduced in our former work to the problem of solving deducibility constraints similar to those employed for cryptographic protocol analysis. We extend in this paper the mediator synthesis procedure by a construction for expressing that some data is not accessible to the mediator. Then we give a decision procedure for verifying that a mediator satisfying this non-disclosure policy can be effectively synthesized. This procedure has been implemented in CL-AtSe, our protocol analysis tool. The procedure extends constraint solving for cryptographic protocol analysis in a significative way as it is able to handle negative deducibility constraints without restriction. In particular it applies to all subterm convergent theories and therefore covers several interesting theories in formal security analysis including encryption, hashing, signature and pairing.


Kernel Bounds for Structural Parameterizations of Pathwidth

Abstract: Assuming the AND-distillation conjecture, the Pathwidth problem of determining whether a given graph G has pathwidth at most k admits no polynomial kernelization with respect to k. The present work studies the existence of polynomial kernels for Pathwidth with respect to other, structural, parameters. Our main result is that, unless NP is in coNP/poly, Pathwidth admits no polynomial kernelization even when parameterized by the vertex deletion distance to a clique, by giving a cross-composition from Cutwidth. The cross-composition works also for Treewidth, improving over previous lower bounds by the present authors. For Pathwidth, our result rules out polynomial kernels with respect to the distance to various classes of polynomial-time solvable inputs, like interval or cluster graphs. This leads to the question whether there are nontrivial structural parameters for which Pathwidth does admit a polynomial kernelization. To answer this, we give a collection of graph reduction rules that are safe for Pathwidth. We analyze the success of these results and obtain polynomial kernelizations with respect to the following parameters: the size of a vertex cover of the graph, the vertex deletion distance to a graph where each connected component is a star, and the vertex deletion distance to a graph where each connected component has at most c vertices.


Motion Planning Of an Autonomous Mobile Robot Using Artificial Neural Network

Abstract: The paper presents the electronic design and motion planning of a robot based on decision making regarding its straight motion and precise turn using Artificial Neural Network (ANN). The ANN helps in learning of robot so that it performs motion autonomously. The weights calculated are implemented in microcontroller. The performance has been tested to be excellent.


A Methodology to manage victim components using CBO measure

Abstract: The current practices of software industry demands development of a software within time and budget which is highly productive. The traditional approach of developing a software from scratch requires considerable amount of effort. To overcome the drawback a reuse drive software development approach is adopted. However there is a dire need for realizing effective software reuse. This paper presents several measures of reusability and presents a methodology of reconfiguring the victim components. The CBO measure helps in identifying the component to be reconfigured. The proposed strategy is simulated using HR portal domain specific component system.


Ontology for Cellular Communication

Abstract: The lack of interoperability between mobile cellular access networks has long been a challenging obstacle, which telecommunication engineering is trying to overcome. In second generation networks for example, this problem lies in the fact that there are multiple standards. Each of these standards can operate in the same frequency range. However, each utilizes a different Radio Technology and Modulation Scheme, which are characteristics of the standard. Therefore, the lack of interoperability in 2G occurs because of the lack of standardization. Interoperability within 3G networks is limited to a few operating modes using different Radio Transmission Technologies that are not inter-operable. Thus, interoperability remains an issue for 3G. 4G technology even being successful in its various trials cannot guarantee the interoperability. This is within each network generation; meanwhile between heterogeneous network generations the situation seems to be worst. This approach is first to analyze the structure, inputs, and outputs of three different cellular technologies, performing a domain analysis (of this subset of technologies) and producing a feature model of the domain. Finally, we sought to build an ontology capable of providing a common view of the domain, providing an effective representation of relations between representations of corresponding concepts in different cellular technologies.


Minimally Infrequent Itemset Mining using Pattern-Growth Paradigm and Residual Trees

Abstract: Itemset mining has been an active area of research due to its successful application in various data mining scenarios including finding association rules. Though most of the past work has been on finding frequent itemsets, infrequent itemset mining has demonstrated its utility in web mining, bioinformatics and other fields. In this paper, we propose a new algorithm based on the pattern-growth paradigm to find minimally infrequent itemsets. A minimally infrequent itemset has no subset which is also infrequent. We also introduce the novel concept of residual trees. We further utilize the residual trees to mine multiple level minimum support itemsets where different thresholds are used for finding frequent itemsets for different lengths of the itemset. Finally, we analyze the behavior of our algorithm with respect to different parameters and show through experiments that it outperforms the competing ones.


Service Oriented Architecture A Revolution For Comprehensive Web Based Project Management Software

Abstract: Service Oriented Architecture A Revolution for Project Management Software has changed the way projects today are moving on the fly with the help of web services booming the industry. Service oriented architecture improves performance and the communication between the distributed and remote teams. Web Services to Provide Project Management software the visibility and control of the application development lifecycle-giving a better control over the entire development process, from the management stage through development. The goal of Service Oriented Architecture for Project Management Software is to produce a product that is delivered on time, within the allocated budget, and with the capabilities expected by the customer. Web Services in Project management Project management software is basically a properly managed project and has a clear, communicated, and managed set of goals and objectives, whose progress is quantifiable and controlled. Resources are used effectively and efficiently to produce the desired product. With the help of service oriented architecture we can move into the future without abandoning the past. A project usually has a communicated set of processes that cover the daily activities of the project, forming the project framework. As a result, every team member understands their roles, responsibilities and how they fit into the big picture thus promoting the efficient use of resources.


Control and Synthesis of Non-Interferent Timed Systems

Abstract: In this paper, we focus on the synthesis of secure timed systems which are modelled as timed automata. The security property that the system must satisfy is a non-interference property. Intuitively, non-interference ensures the absence of any causal dependency from a high-level domain to a lower-level domain. Various notions of non-interference have been defined in the literature, and in this paper we focus on Strong Non-deterministic Non-Interference (SNNI) and two (bi)simulation based variants thereof (CSNNI and BSNNI). We consider timed non-interference properties for timed systems specified by timed automata and we study the two following problems: (1) check whether it is possible to find a sub-system so that it is non-interferent; if yes (2) compute a (largest) sub-system which is non-interferent.


Multisegmentation through wavelets: Comparing the efficacy of Daubechies vs Coiflets

Abstract: In this paper, we carry out a comparative study of the efficacy of wavelets belonging to Daubechies and Coiflet family in achieving image segmentation through a fast statistical algorithm.The fact that wavelets belonging to Daubechies family optimally capture the polynomial trends and those of Coiflet family satisfy mini-max condition, makes this comparison interesting. In the context of the present algorithm, it is found that the performance of Coiflet wavelets is better, as compared to Daubechies wavelet.


Checking Satisfiability by Dependency Sequents

Abstract: We introduce a new algorithm for checking satisfiability based on a calculus of Dependency sequents (D-sequents). Given a CNF formula F(X), a D-sequent is a record stating that under a partial assignment a set of variables of X is redundant in formula \exists{X}[F]. The D-sequent calculus is based on operation join that forms a new D-sequent from two existing D-sequents. The new algorithm solves the quantified version of SAT. That is, given a satisfiable formula F, it, in general, does not produce an assignment satisfying F. The new algorithm is called DS-QSAT where DS stands for Dependency Sequent and Q for Quantified. Importantly, a DPLL-like procedure is only a special case of DS-QSAT where a very restricted kind of D-sequents is used. We argue that this restriction a) adversely affects scalability of SAT-solvers and b) is caused by looking for an explicit satisfying assignment rather than just proving satisfiability. We give experimental results substantiating these claims.


A Novel Metric Approach Evaluation For The Spatial Enhancement Of Pan-Sharpened Images

Abstract: Various and different methods can be used to produce high-resolution multispectral images from high-resolution panchromatic image (PAN) and low-resolution multispectral images (MS), mostly on the pixel level. The Quality of image fusion is an essential determinant of the value of processing images fusion for many applications. Spatial and spectral qualities are the two important indexes that used to evaluate the quality of any fused image. However, the jury is still out of fused image's benefits if it compared with its original images. In addition, there is a lack of measures for assessing the objective quality of the spatial resolution for the fusion methods. So, an objective quality of the spatial resolution assessment for fusion images is required. Therefore, this paper describes a new approach proposed to estimate the spatial resolution improve by High Past Division Index (HPDI) upon calculating the spatial-frequency of the edge regions of the image and it deals with a comparison of various analytical techniques for evaluating the Spatial quality, and estimating the colour distortion added by image fusion including: MG, SG, FCC, SD, En, SNR, CC and NRMSE. In addition, this paper devotes to concentrate on the comparison of various image fusion techniques based on pixel and feature fusion technique.


Distributed Supervisory Control of Discrete-Event Systems with Communication Delay

Abstract: This paper identifies a property of delay-robustness in distributed supervisory control of discrete-event systems (DES) with communication delays. In previous work a distributed supervisory control problem has been investigated on the assumption that inter-agent communications take place with negligible delay. From an applications viewpoint it is desirable to relax this constraint and identify communicating distributed controllers which are delay-robust, namely logically equivalent to their delay-free counterparts. For this we introduce inter-agent channels modeled as 2-state automata, compute the overall system behavior, and present an effective computational test for delay-robustness. From the test it typically results that the given delay-free distributed control is delay-robust with respect to certain communicated events, but not for all, thus distinguishing events which are not delay-critical from those that are. The approach is illustrated by a workcell model with three communicating agents.


Diamond-Kite Adaptive Quadrilateral Meshing

Abstract: We describe a family of quadrilateral meshes based on diamonds, rhombi with 60 and 120 degree angles, and kites with 60, 90, and 120 degree angles, that can be adapted to a local size function by local subdivision operations. Our meshes use a number of elements that is within a constant factor of the minimum possible for any mesh of bounded aspect ratio elements, graded by the same local size function, and is invariant under Laplacian smoothing. The vertices of our meshes form the centers of the circles in a pair of dual circle packings. The same vertex placement algorithm but a different mesh topology gives a pair of dual well-centered meshes adapted to the given size function.


Assume-Guarantee Abstraction Refinement for Probabilistic Systems

Abstract: We describe an automated technique for assume-guarantee style checking of strong simulation between a system and a specification, both expressed as non-deterministic Labeled Probabilistic Transition Systems (LPTSes). We first characterize counterexamples to strong simulation as "stochastic" trees and show that simpler structures are insufficient. Then, we use these trees in an abstraction refinement algorithm that computes the assumptions for assume-guarantee reasoning as conservative LPTS abstractions of some of the system components. The abstractions are automatically refined based on tree counterexamples obtained from failed simulation checks with the remaining components. We have implemented the algorithms for counterexample generation and assume-guarantee abstraction refinement and report encouraging results.


Learning Probabilistic Systems from Tree Samples

Abstract: We consider the problem of learning a non-deterministic probabilistic system consistent with a given finite set of positive and negative tree samples. Consistency is defined with respect to strong simulation conformance. We propose learning algorithms that use traditional and a new "stochastic" state-space partitioning, the latter resulting in the minimum number of states. We then use them to solve the problem of "active learning", that uses a knowledgeable teacher to generate samples as counterexamples to simulation equivalence queries. We show that the problem is undecidable in general, but that it becomes decidable under a suitable condition on the teacher which comes naturally from the way samples are generated from failed simulation checks. The latter problem is shown to be undecidable if we impose an additional condition on the learner to always conjecture a "minimum state" hypothesis. We therefore propose a semi-algorithm using stochastic partitions. Finally, we apply the proposed (semi-) algorithms to infer intermediate assumptions in an automated assume-guarantee verification framework for probabilistic systems.


Analysis of speech under stress using Linear techniques and Non-Linear techniques for emotion recognition system

Abstract: Analysis of speech for recognition of stress is important for identification of emotional state of person. This can be done using 'Linear Techniques', which has different parameters like pitch, vocal tract spectrum, formant frequencies, Duration, MFCC etc. which are used for extraction of features from speech. TEO-CB-Auto-Env is the method which is non-linear method of features extraction. Analysis is done using TU-Berlin (Technical University of Berlin) German database. Here emotion recognition is done for different emotions like neutral, happy, disgust, sad, boredom and anger. Emotion recognition is used in lie detector, database access systems, and in military for recognition of soldiers' emotion identification during the war.


Developing an Activity-Based Costing Approach to Maximize the Efficiency of Customer Relationship Management Projects

Abstract: In today's competitive environment, profitability analysis is not just about looking at the profit and loss statement. It is more about knowing which of your customers are making you money and which are losing you money. This paper considers how activity-based costing approach may complement a customer relationship management effort. The model presented in this paper combines the principles of activity-based costing with performance measurement. Applying this model helps managers understand the true costs of providing products and services, and the factors that drive these costs, while addressing other concerns such as customer satisfaction. This approach has the potential to integrate all business processes around the requirements of significant profitable customers, a fact that most of the previous researches fail to acknowledge.


Piecewise Linear Patch Reconstruction for Segmentation and Description of Non-smooth Image Structures

Abstract: In this paper, we propose a unified energy minimization model for the segmentation of non-smooth image structures. The energy of piecewise linear patch reconstruction is considered as an objective measure of the quality of the segmentation of non-smooth structures. The segmentation is achieved by minimizing the single energy without any separate process of feature extraction. We also prove that the error of segmentation is bounded by the proposed energy functional, meaning that minimizing the proposed energy leads to reducing the error of segmentation. As a by-product, our method produces a dictionary of optimized orthonormal descriptors for each segmented region. The unique feature of our method is that it achieves the simultaneous segmentation and description for non-smooth image structures under the same optimization framework. The experiments validate our theoretical claims and show the clear superior performance of our methods over other related methods for segmentation of various image textures. We show that our model can be coupled with the piecewise smooth model to handle both smooth and non-smooth structures, and we demonstrate that the proposed model is capable of coping with multiple different regions through the one-against-all strategy.


Ethernet Packet Processor for SoC Application

Abstract: As the demand for Internet expands significantly in numbers of users, servers, IP addresses, switches and routers, the IP based network architecture must evolve and change. The design of domain specific processors that require high performance, low power and high degree of programmability is the bottleneck in many processor based applications. This paper describes the design of ethernet packet processor for system-on-chip (SoC) which performs all core packet processing functions, including segmentation and reassembly, packetization classification, route and queue management which will speedup switching/routing performance. Our design has been configured for use with multiple projects ttargeted to a commercial configurable logic device the system is designed to support 10/100/1000 links with a speed advantage. VHDL has been used to implement and simulated the required functions in FPGA.


Stator flux optimization on direct torque control with fuzzy logic

Abstract: The Direct Torque Control (DTC) is well known as an effective control technique for high performance drives in a wide variety of industrial applications and conventional DTC technique uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC.


Clown: a Microprocessor Simulator for Operating System Studies

Abstract: In this paper, I present the design and implementation of Clown--a simulator of a microprocessor-based computer system specifically optimized for teaching operating system courses at undergraduate or graduate levels. The package includes the simulator itself, as well as a collection of basic I/O devices, an assembler, a linker, and a disk formatter. The simulator architecturally resembles mainstream microprocessors from the Intel 80386 family, but is much easier to learn and program. The simulator is fast enough to be used as an emulator--in the direct user interaction mode.


Improved Concentration Bounds for Count-Sketch

Abstract: We present a refined analysis of the classic Count-Sketch streaming heavy hitters algorithm [CCF02]. Count-Sketch uses O(k log n) linear measurements of a vector x in R^n to give an estimate x' of x. The standard analysis shows that this estimate x' satisfies ||x'-x||_infty^2 < ||x_tail||_2^2 / k, where x_tail is the vector containing all but the largest k coordinates of x. Our main result is that most of the coordinates of x' have substantially less error than this upper bound; namely, for any c < O(log n), we show that each coordinate i satisfies (x'_i - x_i)^2 < (c/log n) ||x_tail||_2^2/k with probability 1-2^{-Omega(c)}, as long as the hash functions are fully independent. This subsumes the previous bound and is optimal for all c. Using these improved point estimates, we prove a stronger concentration result for set estimates by first analyzing the covariance matrix and then using a median-of-median-of-medians argument to bootstrap the failure probability bounds. These results also give improved results for l_2 recovery of exactly k-sparse estimates x^* when x is drawn from a distribution with suitable decay, such as a power law or lognormal. We complement our results with simulations of Count-Sketch on a power law distribution. The empirical evidence indicates that our theoretical bounds give a precise characterization of the algorithm's performance: the asymptotics are correct and the associated constants are small. Our proof shows that any symmetric random variable with finite variance and positive Fourier transform concentrates around 0 at least as well as a Gaussian. This result, which may be of independent interest, gives good concentration even when the noise does not converge to a Gaussian.


On the Hardness of Network Design for Bottleneck Routing Games

Abstract: In routing games, the network performance at equilibrium can be significantly improved if we remove some edges from the network. This counterintuitive fact, widely known as Braess's paradox, gives rise to the (selfish) network design problem, where we seek to recognize routing games suffering from the paradox, and to improve the equilibrium performance by edge removal. In this work, we investigate the computational complexity and the approximability of the network design problem for non-atomic bottleneck routing games, where the individual cost of each player is the bottleneck cost of her path, and the social cost is the bottleneck cost of the network. We first show that bottleneck routing games do not suffer from Braess's paradox either if the network is series-parallel, or if we consider only subpath-optimal Nash flows. On the negative side, we prove that even for games with strictly increasing linear latencies, it is NP-hard not only to recognize instances suffering from the paradox, but also to distinguish between instances for which the Price of Anarchy (PoA) can decrease to 1 and instances for which the PoA is as large as \Omega(n^{0.121}) and cannot improve by edge removal. Thus, the network design problem for such games is NP-hard to approximate within a factor of O(n^{0.121-\eps}), for any constant \eps > 0. On the positive side, we show how to compute an almost optimal subnetwork w.r.t. the bottleneck cost of its worst Nash flow, when the worst Nash flow in the best subnetwork routes a non-negligible amount of flow on all used edges. The running time is determined by the total number of paths, and is quasipolynomial when the number of paths is quasipolynomial.


Density Functions subject to a Co-Matroid Constraint

Abstract: In this paper we consider the problem of finding the {\em densest} subset subject to {\em co-matroid constraints}. We are given a {\em monotone supermodular} set function $f$ defined over a universe $U$, and the density of a subset $S$ is defined to be $f(S)/\crd{S}$. This generalizes the concept of graph density. Co-matroid constraints are the following: given matroid $\calM$ a set $S$ is feasible, iff the complement of $S$ is {\em independent} in the matroid. Under such constraints, the problem becomes $\np$-hard. The specific case of graph density has been considered in literature under specific co-matroid constraints, for example, the cardinality matroid and the partition matroid. We show a 2-approximation for finding the densest subset subject to co-matroid constraints. Thus, for instance, we improve the approximation guarantees for the result for partition matroids in the literature.


Hierarchical Performance Modeling for Ranking Dense Linear Algebra Algorithms

Abstract: A large class of dense linear algebra operations, such as LU decomposition or inversion of a triangular matrix, are usually performed by blocked algorithms. For one such operation, typically, not only one but many algorithmic variants exist; depending on computing architecture, libraries and problem size, each variant attains a different performances. We propose methods and tools to rank the algorithmic variants according to their performance for a given scenario without executing them. For this purpose, we identify the routines upon which the algorithms are built. A first tool - the Sampler - measures the performance of these routines. Using the Sampler, a second tool models their performance. The generated models are then used to predict the performance of the considered algorithms. For a given scenario, these predictions allow us to correctly rank the algorithms according to their performance without executing them. With the help of the same tools, algorithmic parameters such as block-size can be optimally tuned.


Integer factoring and modular square roots

Abstract: Buresh-Oppenheim proved that the NP search problem to find nontrivial factors of integers of a special form belongs to Papadimitriou's class PPA, and is probabilistically reducible to a problem in PPP. In this paper, we use ideas from bounded arithmetic to extend these results to arbitrary integers. We show that general integer factoring is reducible in randomized polynomial time to a PPA problem and to the problem WEAKPIGEON in PPP. Both reductions can be derandomized under the assumption of the generalized Riemann hypothesis. We also show (unconditionally) that PPA contains some related problems, such as square root computation modulo n, and finding quadratic nonresidues modulo n.


On the Relative Trust between Inconsistent Data and Inaccurate Constraints

Abstract: Functional dependencies (FDs) specify the intended data semantics while violations of FDs indicate deviation from these semantics. In this paper, we study a data cleaning problem in which the FDs may not be completely correct, e.g., due to data evolution or incomplete knowledge of the data semantics. We argue that the notion of relative trust is a crucial aspect of this problem: if the FDs are outdated, we should modify them to fit the data, but if we suspect that there are problems with the data, we should modify the data to fit the FDs. In practice, it is usually unclear how much to trust the data versus the FDs. To address this problem, we propose an algorithm for generating non-redundant solutions (i.e., simultaneous modifications of the data and the FDs) corresponding to various levels of relative trust. This can help users determine the best way to modify their data and/or FDs to achieve consistency.


Building Blocks of Physical-layer Network Coding

Abstract: This paper investigates the fundamental building blocks of physical-layer network coding (PNC). Most prior work on PNC focused on its application in a simple two-way-relay channel (TWRC) consisting of three nodes only. Studies of the application of PNC in general networks are relatively few. This paper is an attempt to fill this gap. We put forth two ideas: 1) A general network can be decomposed into small building blocks of PNC, referred to as the PNC atoms, for scheduling of PNC transmissions. 2) We identify nine PNC atoms, with TWRC being one of them. Three major results are as follows. First, using the decomposition framework, the throughput performance of PNC is shown to be significantly better than those of the traditional multi-hop scheme and the conventional network coding scheme. For example, under heavy traffic volume, PNC can achieve 100% throughput gain relative to the traditional multi-hop scheme. Second, PNC decomposition based on a variety of different PNC atoms can yield much better performance than PNC decomposition based on the TWRC atom alone. Third, three out of the nine atoms are most important to good performance. Specifically, the decomposition based on these three atoms is good enough most of the time, and it is not necessary to use the other six atoms.


Semantic web based Sensor Planning Services (SPS) for Sensor Web Enablement (SWE)

Abstract: The Sensor Planning Service (SPS) is service model to define the web service interface for requesting user driven acquisitions and observation. It's defined by the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) group to provide standardized interface for tasking sensors to allow to defining, checking, modifying and cancelling tasks of sensor and sensor data. The goal of Sensor Planning Service (SPS) of OGC - SWE is standardize the interoperability between a client and a server collection management environment. The Sensor Planning Service (SPS) is need to automate complex data flow in a large enterprises that are depend on live & stored data from sensors and multimedia equipment. The obstacle are faced in Sensor Planning Service (SPS) are (I) Observation from sensor at the right time and right place will be problem, (II) acquisition information(data) that are collected at a specific time and specific place will be problem. The above two obstacle are accomplished and obtained by the web based semantic technology in order to provide & apply the ontology based semantic rule to user driven a acquisitions and observation of Sensor Planning Service (SPS). The novelty of our approach is by adding the semantic rule to Sensor Planning Service model in SWE and we implemented Sensor Planning Service (SPS) with semantic knowledge based to achieve high standardized service model for Sensor Planning Service (SPS) of OGC - SWE.


Cancellation-free circuits: An approach for proving superlinear lower bounds for linear Boolean operators

Abstract: We continue to study the notion of cancellation-free linear circuits. We show that every matrix can be computed by a cancellation- free circuit, and almost all of these are at most a constant factor larger than the optimum linear circuit that computes the matrix. It appears to be easier to prove statements about the structure of cancellation-free linear circuits than for linear circuits in general. We prove two nontrivial superlinear lower bounds. We show that a cancellation-free linear circuit computing the $n\times n$ Sierpinski gasket matrix must use at least 1/2 n logn gates, and that this is tight. This supports a conjecture by Aaronson. Furthermore we show that a proof strategy for proving lower bounds on monotone circuits can be almost directly converted to prove lower bounds on cancellation-free linear circuits. We use this together with a result from extremal graph theory due to Andreev to prove a lower bound of {\Omega}(n^(2- \epsilon)) for infinitely many $n \times n$ matrices for every $\epsilon > 0$ for. These lower bounds for concrete matrices are almost optimal since all matrices can be computed with $O(n^2/\log n)$ gates.


High Reliable secure data collection using Complexity exchanging code key method addressing protocol in Wireless Sensor Network

Abstract: A Wireless Sensor Network (WSN) is emerging field in Information and communication technology. In WSN data transmission and data collection are unsecure because of sensor node Incompatibility. So providing security to Sensor network is very important. The key based Mechanism is secure data collection and it's mainly used to guarantee data confidentiality. Range pair wise key is largely used due to the necessary of data encryption and decryption between each pair range of communication node. Fixed key mechanism difficult for the attacker to detect the regularity of the randomly generated key chain function in privacy homomorphism (PH).PH means no intermediate node to encrypt and decrypt only direct collect and aggregate data for encryption and decryption. It is special key based scheme. It's totally based on beta distribution and some statistical tool using key code method by using Complexity exchanging code key method addressing protocol. We show how to reduce significant attacks and secure data collection on wireless sensor network.


A prototype for projecting HPSG syntactic lexica towards LMF

Abstract: The comparative evaluation of Arabic HPSG grammar lexica requires a deep study of their linguistic coverage. The complexity of this task results mainly from the heterogeneity of the descriptive components within those lexica (underlying linguistic resources and different data categories, for example). It is therefore essential to define more homogeneous representations, which in turn will enable us to compare them and eventually merge them. In this context, we present a method for comparing HPSG lexica based on a rule system. This method is implemented within a prototype for the projection from Arabic HPSG to a normalised pivot language compliant with LMF (ISO 24613 - Lexical Markup Framework) and serialised using a TEI (Text Encoding Initiative) based representation. The design of this system is based on an initial study of the HPSG formalism looking at its adequacy for the representation of Arabic, and from this, we identify the appropriate feature structures corresponding to each Arabic lexical category and their possible LMF counterparts.


A New P2N Approach to Software Development Under the Clustering

Abstract: In this computer era of rapid development, software development can be seen everywhere, but a lot of softwares are dead in modern development of software. Just as The Mythical Man-Month said, it exists a problem in the software development, and the problem is interflow.A lock of interflow can be said great calamity. Clustering is a environment to breed new life. In this thesis, we elaborate how P2N can be used to thinking, planning, developing, collaborating, releasing. And the approach that make your team and organization more perfect.


Lattice based Least Fixed Point Logic

Abstract: As software systems become more complex, there is an increasing need for new static analyses. Thanks to the declarative style, logic programming is an attractive formalism for specifying them. However, prior work on using logic programming for static analysis focused on analyses defined over some powerset domain, which is quite limiting. In this paper we present a logic that lifts this restriction, called Lattice based Least Fixed Point Logic (LLFP), that allows interpretations over any complete lattice satisfying Ascending Chain Condition. The main theoretical contribution is a Moore Family result that guarantees that there always is a unique least solution for a given problem. Another contribution is the development of solving algorithm that computes the least model of LLFP formulae guaranteed by the Moore Family result.


FST Based Morphological Analyzer for Hindi Language

Abstract: Hindi being a highly inflectional language, FST (Finite State Transducer) based approach is most efficient for developing a morphological analyzer for this language. The work presented in this paper uses the SFST (Stuttgart Finite State Transducer) tool for generating the FST. A lexicon of root words is created. Rules are then added for generating inflectional and derivational words from these root words. The Morph Analyzer developed was used in a Part Of Speech (POS) Tagger based on Stanford POS Tagger. The system was first trained using a manually tagged corpus and MAXENT (Maximum Entropy) approach of Stanford POS tagger was then used for tagging input sentences. The morphological analyzer gives approximately 97% correct results. POS tagger gives an accuracy of approximately 87% for the sentences that have the words known to the trained model file, and 80% accuracy for the sentences that have the words unknown to the trained model file.


Basic Network Creation Games with Communication Interests

Abstract: Network creation games model the creation and usage costs of networks formed by a set of selfish peers. Each peer has the ability to change the network in a limited way, e.g., by creating or deleting incident links. In doing so, a peer can reduce its individual communication cost. Typically, these costs are modeled by the maximum or average distance in the network. We introduce a generalized version of the basic network creation game (BNCG). In the BNCG (by Alon et al., SPAA 2010), each peer may replace one of its incident links by a link to an arbitrary peer. This is done in a selfish way in order to minimize either the maximum or average distance to all other peers. That is, each peer works towards a network structure that allows himself to communicate efficiently with all other peers. However, participants of large networks are seldom interested in all peers. Rather, they want to communicate efficiently only with a small subset of peers. Our model incorporates these (communication) interests explicitly. In the MAX-version, each node tries to minimize its maximum distance to nodes it is interested in. Given peers with interests and a communication network forming a tree, we prove several results on the structure and quality of equilibria in our model. For the MAX-version, we give an upper worst case bound of O(\sqrt{n}) for the private costs in an equilibrium of n peers. Moreover, we give an equilibrium for a circular interest graph where a node has private cost \Omega(\sqrt{n}), showing that our bound is tight. This example can be extended such that we get a tight bound of \Theta(\sqrt{n}) for the price of anarchy. For the case of general communication networks we show the price of anarchy to be \Theta(n). Additionally, we prove an interesting connection between a maximum independent set in the interest graph and the private costs of the peers.


Ranked Document Retrieval in (Almost) No Space

Abstract: Ranked document retrieval is a fundamental task in search engines. Such queries are solved with inverted indexes that require additional 45%-80% of the compressed text space, and take tens to hundreds of microseconds per query. In this paper we show how ranked document retrieval queries can be solved within tens of milliseconds using essentially no extra space over an in-memory compressed representation of the document collection. More precisely, we enhance wavelet trees on bytecodes (WTBCs), a data structure that rearranges the bytes of the compressed collection, so that they support ranked conjunctive and disjunctive queries, using just 6%-18% of the compressed text space.


Efficient Identity-Based and Authenticated Key Agreement Protocol

Abstract: Several identity based and implicitly authenticated key agreement protocols have been proposed in recent years and none of them has achieved all required security properties. In this paper, we propose an efficient identity-based and authenticated key agreement protocol IDAK using Weil/Tate pairing. The security of IDAK is proved in Bellare-Rogaway model. Several required properties for key agreement protocols are not implied by the Bellare-Rogaway model. We proved these properties for IDAK separately.


Security Analysis of a Password-Based Authentication Protocol Proposed to IEEE 1363

Abstract: In recent years, several protocols for password-based authenticated key exchange have been proposed. These protocols aim to be secure even though the sample space of passwords may be small enough to be enumerated by an off-line adversary. In Eurocrypt 2000, Bellare, Pointcheval and Rogaway (BPR) presented a model and security definition for authenticated key exchange. They claimed that in the ideal-cipher model (random oracles), the two-flow protocol at the core of Encrypted Key Exchange (EKE) is secure. Bellare and Rogaway suggested several instantiations of the ideal cipher in their proposal to the IEEE P1363.2 working group. Since then there has been an increased interest in proving the security of password-based protocols in the ideal-cipher model. For example, Bresson, Chevassut, and Pointcheval have recently showed that the One-Encryption-Key-Exchange (OEKE) protocol is secure in the ideal cipher model. In this paper, we present examples of real (NOT ideal) ciphers (including naive implementations of the instantiations proposed to IEEE P1363.2) that would result in broken instantiations of the idealised AuthA protocol and OEKE protocol. Our result shows that the AuthA protocol can be instantiated in an insecure way, and that there are no well defined (let alone rigorous) ways to distinguish between secure and insecure instantiations. Thus, without a rigorous metric for ideal-ciphers, the value of provable security in ideal cipher model is limited.


Using mobile agent results to create hard-to-detect computer viruses

Abstract: The theory of computer viruses has been studied by several authors, though there is no systematic theoretical study up to now. The long time open question in this area is as follows: Is it possible to design a signature-free (including dynamic signatures which we will define late) virus? In this paper, we give an affirmative answer to this question from a theoretical viewpoint. We will introduce a new stronger concept: dynamic signatures of viruses, and present a method to design viruses which are static signature-free and whose dynamic signatures are hard to determine unless some cryptographic assumption fails. We should remark that our results are only for theoretical interest and may be resource intensive in practice.


Public Key Cryptography Standards: PKCS

Abstract: Cryptographic standards serve two important goals: making different implementations interoperable and avoiding various known pitfalls in commonly used schemes. This chapter discusses Public-Key Cryptography Standards (PKCS) which have significant impact on the use of public key cryptography in practice. PKCS standards are a set of standards, called PKCS #1 through #15. These standards cover RSA encryption, RSA signature, password-based encryption, cryptographic message syntax, private-key information syntax, selected object classes and attribute types, certification request syntax, cryptographic token interface, personal information exchange syntax, and cryptographic token information syntax. The PKCS standards are published by RSA Laboratories. Though RSA Laboratories solicits public opinions and advice for PKCS standards, RSA Laboratories retain sole decision-making authority on all aspects of PKCS standards. PKCS has been the basis for many other standards such as S/MIME.


Least periods of k-automatic sequences

Abstract: Currie and Saari initiated the study of least periods of infinite words, and they showed that every integer n >= 1 is a least period of the Thue-Morse sequence. We generalize this result to show that the characteristic sequence of least periods of a k-automatic sequence is (effectively) k-automatic. Through an implementation of our construction, we confirm the result of Currie and Saari, and we obtain similar results for the period-doubling sequence, the Rudin-Shapiro sequence, and the paperfolding sequence.


Enhancing Data Security in Medical Information System Using the Watermarking Techniques and Oracle SecureFile LOBs

Abstract: In this paper, we propose an efficient digital watermarking scheme to strengthen the security level already present in the database management system and to avoid illegal access to comprehensive content of database including patient's information. Doctors diagnose medical images by seeing Region of Interest (ROI). A ROI of a medical image is an area including important information and must be stored without any distortion. If a medical image is illegally obtained or if its content is changed, it may lead to wrong diagnosis. We substitute the part out of ROI of LSB bitplane of the image with the patient data and a binary feature map. This latter is obtained by extracting edges of the resized image to the quarter of its size using Laplacian operator. This image is directly integrated into the database. The edge map and invariant moments are used to check the integrity of the image.


Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation

Abstract: In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data sets. The characteristics that could be used for this purpose include the frequent itemsets and association rules. The problem of generating synthetic basket data sets from frequent itemsets is generally referred to as inverse frequent itemset mining. In this paper, we show that the problem of approximate inverse frequent itemset mining is {\bf NP}-complete. Then we propose and analyze an approximate algorithm for approximate inverse frequent itemset mining, and discuss privacy issues related to the synthetic basket data set. In particular, we propose an approximate algorithm to determine the privacy leakage in a synthetic basket data set.


Survey and comparison for Open and closed sources in cloud computing

Abstract: Cloud computing is a new technology widely studied in recent years. Now there are many cloud platforms both in industry and in academic circle. How to understand and use these platforms is a big issue. A detailed comparison has been presented in this paper focused on the aspects such as the architecture, characteristics, application and so on. To know the differences between open source and close source in cloud environment we mention some examples for Software-as-a-Service, Platform-as-a-Service, and Infrastructure-as-a-Service. We made comparison between them. Before conclusion we demonstrate some convergences and differences between open and closed platform, but we realized open source should be the best option.


Password Protected Smart Card and Memory Stick Authentication Against Off-line Dictionary Attacks

Abstract: In this paper, we study the security requirements for remote authentication with password protected smart card. In recent years, several protocols for password-based authenticated key exchange have been proposed. These protocols are used for the protection of password based authentication between a client and a remote server. In this paper, we will focus on the password based authentication between a smart card owner and smart card via an untrusted card reader. In a typical scenario, a smart card owner inserts the smart card into an untrusted card reader and input the password via the card reader in order for the smart card to carry out the process of authentication with a remote server. In this case, we want to guarantee that the card reader will not be able to impersonate the card owner in future without the smart card itself. Furthermore, the smart card could be stolen. If this happens, we want the assurance that an adversary could not use the smart card to impersonate the card owner even though the sample space of passwords may be small enough to be enumerated by an off-line adversary. At the end of this paper, we further extend our results to credential storage on portable non-tamper resistant storage devices such as USB memory sticks.


Optimal Multi-Dimensional Mechanism Design: Reducing Revenue to Welfare Maximization

Abstract: We provide a reduction from revenue maximization to welfare maximization in multi-dimensional Bayesian auctions with arbitrary (possibly combinatorial) feasibility constraints and independent bidders with arbitrary (possibly combinatorial) demand constraints, appropriately extending Myerson's result to this setting. We also show that every feasible Bayesian auction can be implemented as a distribution over virtual VCG allocation rules. A virtual VCG allocation rule has the following simple form: Every bidder's type t_i is transformed into a virtual type f_i(t_i), via a bidder-specific function. Then, the allocation maximizing virtual welfare is chosen. Using this characterization, we show how to find and run the revenue-optimal auction given only black box access to an implementation of the VCG allocation rule. We generalize this result to arbitrarily correlated bidders, introducing the notion of a second-order VCG allocation rule. We obtain our reduction from revenue to welfare optimization via two algorithmic results on reduced forms in settings with arbitrary feasibility and demand constraints. First, we provide a separation oracle for determining feasibility of a reduced form. Second, we provide a geometric algorithm to decompose any feasible reduced form into a distribution over virtual VCG allocation rules. In addition, we show how to execute both algorithms given only black box access to an implementation of the VCG allocation rule. Our results are computationally efficient for all multi-dimensional settings where the bidders are additive. In this case, our mechanisms run in time polynomial in the total number of bidder types, but not type profiles. For generic correlated distributions, this is the natural description complexity of the problem. The runtime can be further improved to poly(#items, #bidders) in item-symmetric settings by making use of recent techniques.


MCTS Based on Simple Regret

Abstract: UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs from MAB in that in MCTS it is usually only the final "arm pull" (the actual move selection) that collects a reward, rather than all "arm pulls". Therefore, it makes more sense to minimize the simple regret, as opposed to the cumulative regret. We begin by introducing policies for multi-armed bandits with lower finite-time and asymptotic simple regret than UCB, using it to develop a two-stage scheme (SR+CR) for MCTS which outperforms UCT empirically. Optimizing the sampling process is itself a metareasoning problem, a solution of which can use value of information (VOI) techniques. Although the theory of VOI for search exists, applying it to MCTS is non-trivial, as typical myopic assumptions fail. Lacking a complete working VOI theory for MCTS, we nevertheless propose a sampling scheme that is "aware" of VOI, achieving an algorithm that in empirical evaluation outperforms both UCT and the other proposed algorithms.


An analysis of social network connect services

Abstract: Social network platforms are increasingly becoming identity providers and a media for showing multiple types of activity from third-party web sites. In this article, we analyze the services provided by seven of the most popular social network platforms. Results show OAuth emerging as the authentication and authorization protocol, giving support to three types of APIs, client-side or Javascript, server-side or representational state transfer (REST) and streaming. JSON is the most popular format, but there a considerable variety of resource types and a lack of representation standard, which makes harder for the third-party developer integrating with several services.


Evolving Musical Counterpoint: The Chronopoint Musical Evolution System

Abstract: Musical counterpoint, a musical technique in which two or more independent melodies are played simultaneously with the goal of creating harmony, has been around since the baroque era. However, to our knowledge computational generation of aesthetically pleasing linear counterpoint based on subjective fitness assessment has not been explored by the evolutionary computation community (although generation using objective fitness has been attempted in quite a few cases). The independence of contrapuntal melodies and the subjective nature of musical aesthetics provide an excellent platform for the application of genetic algorithms. In this paper, a genetic algorithm approach to generating contrapuntal melodies is explained, with a description of the various musical heuristics used and of how variable-length chromosome strings are used to avoid generating "jerky" rhythms and melodic phrases, as well as how subjectivity is incorporated into the algorithm's fitness measures. Next, results from empirical testing of the algorithm are presented, with a focus on how a user's musical sophistication influences their experience. Lastly, further musical and compositional applications of the algorithm are discussed along with planned future work on the algorithm.


VOI-aware MCTS

Abstract: UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB1, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs from MAB in that in MCTS it is usually only the final "arm pull" (the actual move selection) that collects a reward, rather than all "arm pulls". In this paper, an MCTS sampling policy based on Value of Information (VOI) estimates of rollouts is suggested. Empirical evaluation of the policy and comparison to UCB1 and UCT is performed on random MAB instances as well as on Computer Go.


Linear Dependent Types in a Call-by-Value Scenario (Long Version)

Abstract: Linear dependent types allow to precisely capture both the extensional behaviour and the time complexity of lambda terms, when the latter are evaluated by Krivine's abstract machine. In this work, we show that the same paradigm can be applied to call-by-value evaluation. A system of linear dependent types for Plotkin's PCF is introduced, called dlPCFV, whose types reflect the complexity of evaluating terms in the so-called CEK machine. dlPCFV is proved to be sound, but also relatively complete: every true statement about the extensional and intentional behaviour of terms can be derived, provided all true index term inequalities can be used as assumptions.


An Authentication Protocol Based on Combined RFID-Biometric System RFID-Biometric System

Abstract: Radio Frequency Identification (RFID) and biometric technologies saw fast evolutions during the last years and which are used in several applications, such as access control. Among important characteristics in the RFID tags, we mention the limitation of resources (memory, energy, ...). Our work focuses on the design of a RFID authentication protocol which uses biometric data and which confirms the secrecy, the authentication and the privacy. Our protocol requires a PRNG (Pseud-Random Number Generator), a robust hash function and Biometric hash function. The Biometric hash function is used to optimize and to protect biometric data. For Security analysis of protocol proposed, we will use AVISPA and SPAN tools to verify the authentication and the secrecy.


Bin Packing/Covering with Delivery: Some variations, theoretical results and efficient offline algorithms

Abstract: In the recent paper \cite{BDT10} we introduced a new problem that we call Bin Packing/Covering with Delivery, or BP/CD for short. Mainly we mean under this expression that we look for not only a good, but a "good and fast" packing or covering. In that paper we mainly dealt with only one possible online BP/CD model, and proposed a new method that we call the Evolution of Algorithms. In case of such methods a neighborhood structure is defined among algorithms, and using a metaheuristic (for example simulated annealing) in some sense the best algorithm is chosen to solve the problem. Now we turn to investigate the offline case. We define several ways to treat such a BP/CD problem, although we investigate only one of them here. For the analysis, a novel view on "offline optimum" is introduced, which appears to be relevant concerning all problems where a final solution is ordering-dependent. We prove that if the item sizes are not allowed to be arbitrarily close to zero, then an optimal offline solution can be found in polynomial time. On the other hand, for unrestricted problem instances, no polynomial-time algorithm can achieve an approximation ratio better than 6/7 if $P\ne NP$.


Improved Interference in Wireless Sensor Networks

Abstract: Given a set ${\cal V}$ of $n$ sensor node distributed on a 2-dimensional plane and a source node $s \in {\cal V}$, the {\it interference problem} deals with assigning transmission range to each $v \in {\cal V}$ such that the members in ${\cal V}$ maintain connectivity predicate ${\cal P}$, and the maximum/total interference is minimum. We propose algorithm for both {\it minimizing maximum interference} and {\it minimizing total interference} of the networks. For minimizing maximum interference we present optimum solution with running time $O(({\cal P}_n + n^2) \log n)$ for connectivity predicate ${\cal P}$ like strong connectivity, broadcast ($s$ is the source), $k$-edge(vertex) connectivity, spanner, where $O({\cal P}_n)$ is the time complexity for checking the connectivity predicate ${\cal P}$. The running time of the previous best known solution was $O({\cal P}_n \times n^2)$ [Bil$\grave{o}$ and Proietti, 2008]. For the minimizing total interference we propose optimum algorithm for the connectivity predicate broadcast. The running time of the propose algorithm is O(n). For the same problem, the previous best known result was $2(1 + \ln (n-1))$-factor approximation algorithm [Bil$\grave{o}$ and Proietti, 2008]. We also propose a heuristic for minimizing total interference in the case of strongly connected predicate and compare our result with the best result available in the literature. Experimental results demonstrate that our heuristic outperform existing result.


Approximating Minimum-Cost Connected T-Joins

Abstract: We design and analyse approximation algorithms for the minimum-cost connected T-join problem: given an undirected graph G = (V;E) with nonnegative costs on the edges, and a subset of nodes T, find (if it exists) a spanning connected subgraph H of minimum cost such that every node in T has odd degree and every node not in T has even degree; H may have multiple copies of any edge of G. Two well-known special cases are the TSP (|T| = 0) and the s-t path TSP (|T| = 2). Recently, An, Kleinberg, and Shmoys [STOC 2012] improved on the long-standing 5/3-approximation guarantee for the latter problem and presented an algorithm based on LP rounding that achieves an approximation guarantee of (1+sqrt(5))/2 < 1.6181. We show that the methods of An et al. extend to the minimum-cost connected T-join problem. They presented a new proof for a 5/3-approximation guarantee for the s-t path TSP; their proof extends easily to the minimum-cost connected T-join problem. Next, we improve on the approximation guarantee of 5/3 by extending their LP-rounding algorithm to get an approximation guarantee of 13/8 = 1.625 for all |T| >= 4. Finally, we focus on the prize-collecting version of the problem, and present a primal-dual algorithm that is "Lagrangian multiplier preserving" and that achieves an approximation guarantee 3 - 2/(|T|-1) when |T| >= 4. Our primal-dual algorithm is a generalization of the known primal-dual 2-approximation for the prize-collecting s-t path TSP. Furthermore, we show that our analysis is tight by presenting instances with |T| >= 4 such that the cost of the solution found by the algorithm is exactly 3 - 2/(|T|-1) times the cost of the constructed dual solution.


Fewest repetitions in infinite binary words

Abstract: A square is the concatenation of a nonempty word with itself. A word has period p if its letters at distance p match. The exponent of a nonempty word is the quotient of its length over its smallest period. In this article we give a proof of the fact that there exists an infinite binary word which contains finitely many squares and simultaneously avoids words of exponent larger than 7/3. Our infinite word contains 12 squares, which is the smallest possible number of squares to get the property, and 2 factors of exponent 7/3. These are the only factors of exponent larger than 2. The value 7/3 introduces what we call the finite-repetition threshold of the binary alphabet. We conjecture it is 7/4 for the ternary alphabet, like its repetitive threshold.


A Review of routing protocols for mobile cognitive radio ad hoc networks

Abstract: Ad hoc network is a collection of wireless mobile nodes that dynamically form a temporary network without the use of any existing network infrastructure or centralized administration. A cognitive radio is a radio that can change its transmitter parameters based on interaction with the environment in which it operates. The basic idea of cognitive radio networks is that the unlicensed devices (cognitive radio users or secondary users) need to vacate the spectrum band once the licensed device (primary user) is detected. Cognitive capability and reconfigurability are the key characteristics of cognitive radio. Routing is an important issue in Mobile Cognitive Radio Ad Hoc Networks (MCRAHNs). In this paper, a survey of routing protocols for mobile cognitive radio ad networks is discussed.


Differentiated QoS with Modified C/I Based Scheduling Algorithm

Abstract: Second-generation (2G) digital cellular systems constitute the majority of cellular communication deployed today. A variety of services of 2G systems has increased significantly and this will continue to grow even further in the emerging third-generation (3G) systems. Universal Mobile Telecommunication System (UMTS) is a third-generation mobile communications system which uses the Wide-Band Code Division Multiple Access (WCDMA) technique to support a wide variety of services, like speech, video telephony, Internet browsing, etc. These services require a wide range of Quality of Service (QoS) requirements. QoS is an important issue as the number of multimedia services increases day by day. Differentiated QoS methods allow the differentiation of users based on their priority levels and channel conditions so that the network can allocate the bandwidth for a particular request based on the QoS requirements. These requirements are controlled by Radio Resource Management (RRM) mechanisms. In this paper we have proposed two RRM algorithms which are modification to the existing scheduling algorithms. One is Prioritized C/I scheduling, which takes the priorities into consideration, and this algorithm serves the user with highest priority. Other algorithm is Modified Inverse C/I scheduling, which takes channel conditions into consideration and serves the users in degraded conditions, thereby improving QoS. The performance evaluation of two algorithms is done with EURANE extensions for NS-2. Simulation results shows the improvement in QoS for the users who are at equidistance from Base Station (BS) but requesting for different services by implementing Prioritized C/I scheduling and also for the users who are in degraded conditions by implementing Modified Inverse C/I scheduling when compared to Max C/I and Inverse C/I scheduling algorithm respectively.


Semantic Information Retrieval Using Ontology In University Domain

Abstract: Today's conventional search engines hardly do provide the essential content relevant to the user's search query. This is because the context and semantics of the request made by the user is not analyzed to the full extent. So here the need for a semantic web search arises. SWS is upcoming in the area of web search which combines Natural Language Processing and Artificial Intelligence. The objective of the work done here is to design, develop and implement a semantic search engine- SIEU(Semantic Information Extraction in University Domain) confined to the university domain. SIEU uses ontology as a knowledge base for the information retrieval process. It is not just a mere keyword search. It is one layer above what Google or any other search engines retrieve by analyzing just the keywords. Here the query is analyzed both syntactically and semantically. The developed system retrieves the web results more relevant to the user query through keyword expansion. The results obtained here will be accurate enough to satisfy the request made by the user. The level of accuracy will be enhanced since the query is analyzed semantically. The system will be of great use to the developers and researchers who work on web. The Google results are re-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied which fetches more apt results for the user query.


A New Training Algorithm for Kanerva's Sparse Distributed Memory

Abstract: The Sparse Distributed Memory proposed by Pentii Kanerva (SDM in short) was thought to be a model of human long term memory. The architecture of the SDM permits to store binary patterns and to retrieve them using partially matching patterns. However Kanerva's model is especially efficient only in handling random data. The purpose of this article is to introduce a new approach of training Kanerva's SDM that can handle efficiently non-random data, and to provide it the capability to recognize inverted patterns. This approach uses a signal model which is different from the one proposed for different purposes by Hely, Willshaw and Hayes in [4]. This article additionally suggests a different way of creating hard locations in the memory despite the Kanerva's static model.


Algorithm to suppress scanner noise in recorded speech during functional magnetic resonance imaging

Abstract: The high-intensity, repetitive noise associated with functional magnetic resonance imaging hinders on-line monitoring of subjects' speech and/or recording speech signals suitable for off-line analysis. The proposed algorithm enhances the speech signal by suppressing the scanner noise in the signal recorded by a single-channel microphone. Significant increases in signal-to-noise ratio are achieved using an adaptive filter that combines time and frequency domain elements. In addition to providing a recording suitable for speech analysis, such a real-time system provides an alternative means (to, e.g., the "panic ball") for communication between the patient and the operator during image acquisition.


The Impact of Communication Delays on Distributed Consensus Algorithms

Abstract: We study the effect of communication delays on distributed consensus algorithms. Two ways to model delays on a network are presented. The first model assumes that each link delivers messages with a fixed (constant) amount of delay, and the second model is more realistic, allowing for i.i.d. time-varying bounded delays. In contrast to previous work studying the effects of delays on consensus algorithms, the models studied here allow for a node to receive multiple messages from the same neighbor in one iteration. The analysis of the fixed delay model shows that convergence to a consensus is guaranteed and the rate of convergence is reduced by no more than a factor O(B^2) where B is the maximum delay on any link. For the time-varying delay model we also give a convergence proof which, for row-stochastic consensus protocols, is not a trivial consequence of ergodic matrix products. In both delay models, the consensus value is no longer the average, even if the original protocol was an averaging protocol. For this reason, we propose the use of a different consensus algorithm called Push-Sum [Kempe et al. 2003]. We model delays in the Push-Sum framework and show that convergence to the average consensus is guaranteed. This suggests that Push-Sum might be a better choice from a practical standpoint.


SODEXO: A System Framework for Deployment and Exploitation of Deceptive Honeybots in Social Networks

Abstract: As social networking sites such as Facebook and Twitter are becoming increasingly popular, a growing number of malicious attacks, such as phishing and malware, are exploiting them. Among these attacks, social botnets have sophisticated infrastructure that leverages compromised users accounts, known as bots, to automate the creation of new social networking accounts for spamming and malware propagation. Traditional defense mechanisms are often passive and reactive to non-zero-day attacks. In this paper, we adopt a proactive approach for enhancing security in social networks by infiltrating botnets with honeybots. We propose an integrated system named SODEXO which can be interfaced with social networking sites for creating deceptive honeybots and leveraging them for gaining information from botnets. We establish a Stackelberg game framework to capture strategic interactions between honeybots and botnets, and use quantitative methods to understand the tradeoffs of honeybots for their deployment and exploitation in social networks. We design a protection and alert system that integrates both microscopic and macroscopic models of honeybots and optimally determines the security strategies for honeybots. We corroborate the proposed mechanism with extensive simulations and comparisons with passive defenses.


Sudoku Associated Two Dimensional Bijections for Image Scrambling

Abstract: Sudoku puzzles are now popular among people in many countries across the world with simple constraints that no repeated digits in each row, each column, or each block. In this paper, we demonstrate that the Sudoku configuration provides us a new alternative way of matrix element representation by using block-grid pair besides the conventional row-column pair. Moreover, we discover six more matrix element representations by using row-digit pair, digit-row pair, column-digit pair, digit-column pair, block-digit pair, and digit-block pair associated with a Sudoku matrix. These parametric Sudoku associated matrix element representations not only allow us to denote matrix elements in secret ways, but also provide us new parametric two-dimensional bijective mappings. We study these two-dimensional bijections in the problem of image scrambling and propose a simple but effective Sudoku Associated Image Scrambler only using Sudoku associated two dimensional bijections for image scrambling without bandwidth expansion. Our simulation results over a wide collection of image types and contents demonstrate the effectiveness and robustness of the proposed method. Scrambler performance analysis with comparisons to peer algorithms under various investigation methods, including human visual inspections, gray degree of scrambling, autocorrelation coefficient of adjacent pixels, and key space and key sensitivities, suggest that the proposed method outperforms or at least reaches state-of-the-art. Similar scrambling ideas are also applicable to other digital data forms such as audio and video.


Selecting Computations: Theory and Applications

Abstract: Sequential decision problems are often approximately solvable by simulating possible future action sequences. {\em Metalevel} decision procedures have been developed for selecting {\em which} action sequences to simulate, based on estimating the expected improvement in decision quality that would result from any particular simulation; an example is the recent work on using bandit algorithms to control Monte Carlo tree search in the game of Go. In this paper we develop a theoretical basis for metalevel decisions in the statistical framework of Bayesian {\em selection problems}, arguing (as others have done) that this is more appropriate than the bandit framework. We derive a number of basic results applicable to Monte Carlo selection problems, including the first finite sampling bounds for optimal policies in certain cases; we also provide a simple counterexample to the intuitive conjecture that an optimal policy will necessarily reach a decision in all cases. We then derive heuristic approximations in both Bayesian and distribution-free settings and demonstrate their superiority to bandit-based heuristics in one-shot decision problems and in Go.


Redundant Sudoku Rules

Abstract: The rules of Sudoku are often specified using twenty seven \texttt{all\_different} constraints, referred to as the {\em big} \mrules. Using graphical proofs and exploratory logic programming, the following main and new result is obtained: many subsets of six of these big \mrules are redundant (i.e., they are entailed by the remaining twenty one \mrules), and six is maximal (i.e., removing more than six \mrules is not possible while maintaining equivalence). The corresponding result for binary inequality constraints, referred to as the {\em small} \mrules, is stated as a conjecture.


Using Open Standards for Interoperability - Issues, Solutions, and Challenges facing Cloud Computing

Abstract: Virtualization offers several benefits for optimal resource utilization over traditional non-virtualized server farms. With improvements in internetworking technologies and increase in network bandwidth speeds, a new era of computing has been ushered in, that of grids and clouds. With several commercial cloud providers coming up, each with their own APIs, application description formats, and varying support for SLAs, vendor lock-in has become a serious issue for end users. This article attempts to describe the problem, issues, possible solutions and challenges in achieving cloud interoperability. These issues will be analyzed in the ambit of the European project Contrail that is trying to adopt open standards with available virtualization solutions to enhance users' trust in the clouds by attempting to prevent vendor lock-ins, supporting and enforcing SLAs together with adequate data protection for sensitive data.


Tight Analysis of Priority Queuing Policy for Egress Traffic

Abstract: Recently, the problems of evaluating performances of switches and routers have been formulated as online problems, and a great amount of results have been presented. In this paper, we focus on managing outgoing packets (called {\em egress traffic}) on switches that support Quality of Service (QoS), and analyze the performance of one of the most fundamental scheduling policies {\em Priority Queuing} ($PQ$) using competitive analysis. We formulate the problem of managing egress queues as follows: An output interface is equipped with $m$ queues, each of which has a buffer of size $B$. The size of a packet is unit, and each buffer can store up to $B$ packets simultaneously. Each packet is associated with one of $m$ priority values $\alpha_{j}$ ($1 \leq j \leq m$), where $\alpha_{1} \leq \alpha_{2} \leq \cdots \leq \alpha_{m}$, $\alpha_{1} = 1$, and $\alpha_{m} = \alpha$ and the task of an online algorithm is to select one of $m$ queues at each scheduling step. The purpose of this problem is to maximize the sum of the values of the scheduled packets. For any $B$ and any $m$, we show that the competitive ratio of $PQ$ is exactly $2 - \min_{x \in [1, m-1] } \{ \frac{ \alpha_{x+1} }{ \sum_{j = 1}^{x+1} \alpha_{j} } \}$. That is, we conduct a complete analysis of the performance of $PQ$ using worst case analysis. Moreover, we show that no deterministic online algorithm can have a competitive ratio smaller than $1 + \frac{ \alpha^3 + \alpha^2 + \alpha }{ \alpha^4 + 4 \alpha^3 + 3 \alpha^2 + 4 \alpha + 1 }$.


File system on CRDT

Abstract: In this report we show how to manage a distributed hierarchical structure representing a file system. This structure is optimistically replicated, each user work on his local replica, and updates are sent to other replica. The different replicas eventually observe same view of file systems. At this stage, conflicts between updates are very common. We claim that conflict resolution should rely as little as possible on users. In this report we propose a simple and modular solution to resolve these problems and maintain data consistency.


Analysis of cloud storage prices

Abstract: Cloud storage is fast securing its role as a major repository for both consumers and business customers. Many companies now offer storage solutions, sometimes for free for limited amounts of capacity. We have surveyed the pricing plans of a selection of major cloud providers and compared them using the unit price as the means of comparison. All the providers, excepting Amazon, adopt a bundling pricing scheme; Amazon follows instead a block-declining pricing policy. We compare the pricing plans through a double approach: a pointwise comparison for each value of capacity, and an overall comparison using a two-part tariff approximation and a Pareto-dominance criterion. Under both approaches, most providers appear to offer pricing plans that are more expensive and can be excluded from a procurement selection in favour of a limited number of dominant providers.


The 2008 Australian study of remnant data contained on 2nd hand hard disks: the saga continues

Abstract: This study looked for remnant data on enterprise level hard drives that were purchased through auctions. The drives were analysed for information, be it topical or formatted. In the event that drives were formatted, forensic tools were used to recover this data. This years study revealed a high level of not simply un-erased drives, but drives which contained information that related to critical infrastructure providers. That such a small sample size yielded such a high rate of un-erased drives is of considerable concern, and it may be necessary for the government to become involved.


Effective Retrieval of Resources in Folksonomies Using a New Tag Similarity Measure

Abstract: Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. However, as tags are informally defined, continually changing, and ungoverned, it has often been criticised for lowering, rather than increasing, the efficiency of searching. To address this issue, a variety of approaches have been proposed that recommend users what tags to use, both when labeling and when looking for resources. These techniques work well in dense folksonomies, but they fail to do so when tag usage exhibits a power law distribution, as it often happens in real-life folksonomies. To tackle this issue, we propose an approach that induces the creation of a dense folksonomy, in a fully automatic and transparent way: when users label resources, an innovative tag similarity metric is deployed, so to enrich the chosen tag set with related tags already present in the folksonomy. The proposed metric, which represents the core of our approach, is based on the mutual reinforcement principle. Our experimental evaluation proves that the accuracy and coverage of searches guaranteed by our metric are higher than those achieved by applying classical metrics.


Measuring Similarity in Large-scale Folksonomies

Abstract: Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. Unlike taxonomies, which overimpose a hierarchical categorisation of content, folksonomies enable end-users to freely create and choose the categories (in this case, tags) that best describe some content. However, as tags are informally defined, continually changing, and ungoverned, social tagging has often been criticised for lowering, rather than increasing, the efficiency of searching, due to the number of synonyms, homonyms, polysemy, as well as the heterogeneity of users and the noise they introduce. To address this issue, a variety of approaches have been proposed that recommend users what tags to use, both when labelling and when looking for resources. As we illustrate in this paper, real world folksonomies are characterized by power law distributions of tags, over which commonly used similarity metrics, including the Jaccard coefficient and the cosine similarity, fail to compute. We thus propose a novel metric, specifically developed to capture similarity in large-scale folksonomies, that is based on a mutual reinforcement principle: that is, two tags are deemed similar if they have been associated to similar resources, and vice-versa two resources are deemed similar if they have been labelled by similar tags. We offer an efficient realisation of this similarity metric, and assess its quality experimentally, by comparing it against cosine similarity, on three large-scale datasets, namely Bibsonomy, MovieLens and CiteULike.


Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems

Abstract: Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust event in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).


Accurate and Efficient Private Release of Datacubes and Contingency Tables

Abstract: A central problem in releasing aggregate information about sensitive data is to do so accurately while providing a privacy guarantee on the output. Recent work focuses on the class of linear queries, which include basic counting queries, data cubes, and contingency tables. The goal is to maximize the utility of their output, while giving a rigorous privacy guarantee. Most results follow a common template: pick a "strategy" set of linear queries to apply to the data, then use the noisy answers to these queries to reconstruct the queries of interest. This entails either picking a strategy set that is hoped to be good for the queries, or performing a costly search over the space of all possible strategies. In this paper, we propose a new approach that balances accuracy and efficiency: we show how to improve the accuracy of a given query set by answering some strategy queries more accurately than others. This leads to an efficient optimal noise allocation for many popular strategies, including wavelets, hierarchies, Fourier coefficients and more. For the important case of marginal queries we show that this strictly improves on previous methods, both analytically and empirically. Our results also extend to ensuring that the returned query answers are consistent with an (unknown) data set at minimal extra cost in terms of time and noise.


Customer Empowerment in Healthcare Organisations Through CRM 2.0: Survey Results from Brunei Tracking a Future Path in E-Health Research

Abstract: Customer Relationship Management (CRM) with the Web technology provides healthcare organizations the ability to broaden services beyond its usual practices, and thus provides a particular advantageous environment to achieve complex e-health goals. This paper discusses and demonstrates how a new approach in CRM based on Web 2.0 namely CRM 2.0 will help customers to have greater control in the sense of controlling the process of interaction (empowerment) between healthcare organizations with its customers, and among customers themselves. A survey was conducted to gather preliminary requirements and expectations on empowerment in Brunei. The survey revealed that there is a high demand for empowering customers in Brunei through the Web. Regardless of the limitations of the survey, the general public has responded with a great support for the capabilities of empowerment listed from the questionnaires. The data were analyzed to provide initial ideas and recommendation to a future direction on research for customers' empowerment in e-health services.


Framework of Social Customer Relationship Management in E-Health Services

Abstract: Healthcare organization is implementing Customer Relationship Management (CRM) as a strategy for managing interactions with patients involving technology to organize, automate, and coordinate business processes. Web-based CRM provides healthcare organization with the ability to broaden service beyond its usual practices in achieving a complex patient care goal, and this paper discusses and demonstrates how a new approach in CRM based on Web 2.0 or Social CRM helps healthcare organizations to improve their customer support, and at the same time avoiding possible conflicts, and promoting better healthcare to patients. A conceptual framework of the new approach will be proposed and highlighted. The framework includes some important features of Social CRM such as customer's empowerment, social interactivity between healthcare organization-patients, and patients-patients. The framework offers new perspective in building relationships between healthcare organizations and customers and among customers in e-health scenario. It is developed based on the latest development of CRM literatures and case studies analysis. In addition, customer service paradigm in social network's era, the important of online health education, and empowerment in healthcare organization will be taken into consideration.


A Unified Approach of Observability Analysis for Airborne SLAM

Abstract: Observability is a key aspect of the state estimation problem of SLAM, However, the dimension and variables of SLAM system might be changed with new features, to which little attention is paid in the previous work. In this paper, a unified approach of observability analysis for SLAM system is provided, whether the dimension and variables of SLAM system are changed or not, we can use this approach to analyze the local or total observability of the SLAM system.


Identity-based Trusted Authentication in Wireless Sensor Network

Abstract: Secure communication mechanisms in Wireless Sensor Networks (WSNs) have been widely deployed to ensure confidentiality, authenticity and integrity of the nodes and data. Recently many WSNs applications rely on trusted communication to ensure large user acceptance. Indeed, the trusted relationship thus far can only be achieved through Trust Management System (TMS) or by adding external security chip on the WSN platform. In this study an alternative mechanism is proposed to accomplish trusted communication between sensors based on the principles defined by Trusted Computing Group (TCG). The results of other related study have also been analyzed to validate and support our findings. Finally the proposed trusted mechanism is evaluated for the potential application on resource constraint devices by quantifying their power consumption on selected major processes. The result proved the proposed scheme can establish trust in WSN with less computation and communication and most importantly eliminating the need for neighboring evaluation for TMS or relying on external security chip.


Kolmogorov Complexity: Clustering Objects and Similarity

Abstract: The clustering objects has become one of themes in many studies, and do not few researchers use the similarity to cluster the instances automatically. However, few research consider using Kommogorov Complexity to get information about objects from documents, such as Web pages, where the rich information from an approach proved to be difficult to. In this paper, we proposed a similarity measure from Kolmogorov Complexity, and we demonstrate the possibility of exploiting features from Web based on hit counts for objects of Indonesia Intellectual.


Achieving Approximate Soft Clustering in Data Streams

Abstract: In recent years, data streaming has gained prominence due to advances in technologies that enable many applications to generate continuous flows of data. This increases the need to develop algorithms that are able to efficiently process data streams. Additionally, real-time requirements and evolving nature of data streams make stream mining problems, including clustering, challenging research problems. In this paper, we propose a one-pass streaming soft clustering (membership of a point in a cluster is described by a distribution) algorithm which approximates the "soft" version of the k-means objective function. Soft clustering has applications in various aspects of databases and machine learning including density estimation and learning mixture models. We first achieve a simple pseudo-approximation in terms of the "hard" k-means algorithm, where the algorithm is allowed to output more than $k$ centers. We convert this batch algorithm to a streaming one (using an extension of the k-means++ algorithm recently proposed) in the "cash register" model. We also extend this algorithm when the clustering is done over a moving window in the data stream.