There is no 16-Clue Sudoku: Solving the Sudoku Minimum Number of Clues Problem

Abstract: The sudoku minimum number of clues problem is the following question: what is the smallest number of clues that a sudoku puzzle can have? For several years it had been conjectured that the answer is 17. We have performed an exhaustive computer search for 16-clue sudoku puzzles, and did not find any, thus proving that the answer is indeed 17. In this article we describe our method and the actual search. As a part of this project we developed a novel way for enumerating hitting sets. The hitting set problem is computationally hard; it is one of Karp's 21 classic NP-complete problems. A standard backtracking algorithm for finding hitting sets would not be fast enough to search for a 16-clue sudoku puzzle exhaustively, even at today's supercomputer speeds. To make an exhaustive search possible, we designed an algorithm that allowed us to efficiently enumerate hitting sets of a suitable size.


Umgebungserfassungssystem fuer mobile Roboter (environment logging system for mobile autonomous robots)

Abstract: This diploma thesis describes the theoretical bases, the conception of the module and the final result of the development process in application. for the environment logging with a small mobile robot for interiors should be sketched an economical alternative to the expensive laser scanners. the structure, color or the material of the objects in the radius of action, as well as the environment brightness and illuminating are to have thereby no influence on the results of measurement.


Topological Trends of Internet Content Providers

Abstract: The Internet is constantly changing, and its hierarchy was recently shown to become flatter. Recent studies of inter-domain traffic showed that large content providers drive this change by bypassing tier-1 networks and reaching closer to their users, enabling them to save transit costs and reduce reliance of transit networks as new services are being deployed, and traffic shaping is becoming increasingly popular. In this paper we take a first look at the evolving connectivity of large content provider networks, from a topological point of view of the autonomous systems (AS) graph. We perform a 5-year longitudinal study of the topological trends of large content providers, by analyzing several large content providers and comparing these trends to those observed for large tier-1 networks. We study trends in the connectivity of the networks, neighbor diversity and geographical spread, their hierarchy, the adoption of IXPs as a convenient method for peering, and their centrality. Our observations indicate that content providers gradually increase and diversify their connectivity, enabling them to improve their centrality in the graph, and as a result, tier-1 networks lose dominance over time.


A Topic Modeling Toolbox Using Belief Propagation

Abstract: Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important applications in text mining, computer vision and computational biology. This paper introduces a topic modeling toolbox (TMBP) based on the belief propagation (BP) algorithms. TMBP toolbox is implemented by MEX C++/Matlab/Octave for either Windows 7 or Linux. Compared with existing topic modeling packages, the novelty of this toolbox lies in the BP algorithms for learning LDA-based topic models. The current version includes BP algorithms for latent Dirichlet allocation (LDA), author-topic models (ATM), relational topic models (RTM), and labeled LDA (LaLDA). This toolbox is an ongoing project and more BP-based algorithms for various topic models will be added in the near future. Interested users may also extend BP algorithms for learning more complicated topic models. The source codes are freely available under the GNU General Public Licence, Version 1.0 at https://mloss.org/software/view/399/.


Performance of Modeling wireless networks in realistic environment

Abstract: A wireless network is realized by mobile devices which communicate over radio channels. Since, experiments of real life problem with real devices are very difficult, simulation is used very often. Among many other important properties that have to be defined for simulative experiments, the mobility model and the radio propagation model have to be selected carefully. Both have strong impact on the performance of mobile wireless networks, e.g., the performance of routing protocols varies with these models. There are many mobility and radio propagation models proposed in literature. Each of them was developed with different objectives and is not suited for every physical scenario. The radio propagation models used in common wireless network simulators, in general researcher consider simple radio propagation models and neglect obstacles in the propagation environment. In this paper, we study the performance of wireless networks simulation by consider different Radio propagation models with considering obstacles in the propagation environment. In this paper we analyzed the performance of wireless networks by OPNET Modeler .In this paper we quantify the parameters such as throughput, packet received attenuation.


Order Handling in Convergent Environments

Abstract: The rapid development of IT&T technology had big impact on the traditional telecommunications market, transforming it from monopolistic market to highly competitive high-tech market where new services are required to be created frequently. This paper aims to describe a design approach that puts order management process (as part of enterprise application integration) in function of rapid service creation. In the text we will present a framework for collaborative order handling supporting convergent services. The design splits the order handling processes in convergent environments in three business process groups: order capture, order management and order fulfillment. The paper establishes abstract framework for order handling and provides design guidelines for transaction handling implementation based on the checkpoint and inverse command strategy. The proposed design approach is based in a convergent telecommunication environment. Same principles are applicable in solving problems of collaboration in function of order processing in any given heterogeneous environment.


Rapid Application Development Using Software Factories

Abstract: Software development is still based on manufactory production, and most of the programming code is still hand-crafted. Software development is very far away from the ultimate goal of industrialization in software production, something which has been achieved long time ago in the other industries. The lack of software industrialization creates an inability to cope with fast and frequent changes in user requirements, and causes cost and time inefficiencies during their implementation. Analogous to what other industries had done long time ago, industrialization of software development has been proposed using the concept of software factories. We have accepted this vision about software factories, and developed our own software factory which produces three-layered ASP.NET web applications. In this paper we report about our experience with using this approach in the process of software development, and present comparative results on performances and deliverables in both traditional development and development using software factories.


Applicative Bisimulations for Delimited-Control Operators

Abstract: We develop a behavioral theory for the untyped call-by-value lambda calculus extended with the delimited-control operators shift and reset. For this calculus, we discuss the possible observable behaviors and we define an applicative bisimilarity that characterizes contextual equivalence. We then compare the applicative bisimilarity and the CPS equivalence, a relation on terms often used in studies of control operators. In the process, we illustrate how bisimilarity can be used to prove equivalence of terms with delimited-control effects.


Towards Self-Service Governance by Means of Information Technology

Abstract: In this paper we present a novel model for governing societies based on modern information technology, which neither relies on manual bureaucratic labor, nor depends on process-based e-government services for governance. We expose the flaws of the later and argue that it is not feasible for sustainable governance due to permanently changing laws and instead propose a model in which people can govern themselves in a self-service manner by relying on constellations of data stored in a network of governmental databases to which citizen and officials have read- and write access under rules defined by temporary valid law.


Weaknesses of a dynamic identity based authentication protocol for multi-server architecture

Abstract: Recently, Li et al. proposed a dynamic identity based authentication protocol for multi-server architecture. They claimed their protocol is secure and can withstand various attacks. But we found some security loopholes in the protocol. Accordingly, the current paper demonstrates that Li et al.'s protocol is vulnerable to the replay attack, the password guessing attack and the masquerade attack.


Symbian `vulnerability' and Mobile Threats

Abstract: Modern technologies are becoming ever more integrated with each other. Mobile phones are becoming increasing intelligent, and handsets are growing ever more like computers in functionality. We are entering a new era - the age of smart houses, global advanced networks which encompass a wide range of devices, all of them exchanging data with each other. Such trends clearly open new horizons to malicious users, and the potential threats are self evident. In this paper, we study and discuss one of the most famous mobile operating systems 'Symbian'; its vulnerabilities and recommended protection technologies.


Some Recommended Protection Technologies for Cyber Crime Based on Social Engineering Techniques -- Phishing

Abstract: Phishing (password + fishing) is a form of cyber crime based on social engineering and site spoofing techniques. The name of 'phishing' is a conscious misspelling of the word 'fishing' and involves stealing confidential data from a user's computer and subsequently using the data to steal the user's money. In this paper, we study, discuss and propose the phishing attack stages and types, technologies for detection of phishing web pages, and conclude our paper with some important recommendations for preventing phishing for both consumer and company.


Information Analysis Infrastructure for Diagnosis

Abstract: A high-speed multiprocessor architecture for brain-like analyzing information represented in analytic, graph- and table forms of associative relations to search, recognize and make a decision in n-dimensional vector discrete space is offered. Vector-logical process models of actual applications, where the quality of solution is estimated by the proposed integral non-arithmetical metric of the interaction between binary vectors, are described. The theoretical proof of the metric for a vector logical space and the quality criteria for estimating solutions is created.


Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Abstract: Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed.


Un protocole de routage \`a basse consommation d'\'energie selon l'approche de clustering pour les r\'eseaux de capteurs sans fils

Abstract: In this paper we propose a new routing protocol with low energy consumption for wireless sensor networks based on the clustering approach. Our protocol is based on a strategy which aims at providing a more equitable exploitation of the selected nodes (cluster-heads) energy by distributing their load of the managed sensors during the clustering process. In order to save the energy dissipated while transmitting sensed data to the base station, the multi-hops routing strategy is used to arrange the communication of the data between cluster-heads nodes. Simulation results demonstrate that our proposed protocol decreases the energy consumption and prolongs the network lifetime.


UMTS-WiMAX Vertical Handover in Next Generation Wireless Networks

Abstract: The vision of next generation wireless network (NGWN) is to integrate different wireless access technologies, each with its own characteristics, into a common IP-based core network to provide mobile user with service continuity and seamless roaming. One of the major issues for the converged heterogeneous networks is providing a seamless vertical handover (VHO) with QoS support. In this paper we have reviewed the various interworking architectures and handover scenarios between UMTS and WiMAX. Also, we have compared the proposed solutions based on different criteria and revealed the pros and cons of each scheme. The comparison aids to adopt a better interworking and handover mechanism in NGWN.


Secure SQL Server - Enabling Secure Access to Remote Relational Data

Abstract: The Secure SQL Server - SecSS, is a technology primarily developed to enable self-service governance of states, as described in (Paulin 2012). Self-service governance is a novel model of governance that rejects service-based public administration and instead proposes that governed subjects manage their legal relations in a self-service manner, based on ad-hoc determination of eligibilities. In this article we describe the prototype SecSS and its evaluation in a complex governmental scenario.


An Entertaining Example of Using the Concepts of Context-Free Grammar and Pushdown Automation

Abstract: A formal-linguistic approach for solving an entertaining task is made in this paper. The well-known task of the Hanoi towers is discussed in relation to some concepts of discrete mathematics. A context-free grammar which generate an algorithm for solving this task is described. A deterministic pushdown automation which in its work imitates the work of monks in solving the task of the Hanoi towers is built.


Expansion for Universal Quantifiers

Abstract: Expansion is an operation on typings (i.e., pairs of typing environments and result types) defined originally in type systems for the lambda-calculus with intersection types in order to obtain principal (i.e., most informative, strongest) typings. In a type inference scenario, expansion allows postponing choices for whether and how to use non-syntax-driven typing rules (e.g., intersection introduction) until enough information has been gathered to make the right decision. Furthermore, these choices can be equivalent to inserting uses of such typing rules at deeply nested positions in a typing derivation, without needing to actually inspect or modify (or even have) the typing derivation. Expansion has in recent years become simpler due to the use of expansion variables (e.g., in System E). This paper extends expansion and expansion variables to systems with forall-quantifiers. We present System Fs, an extension of System F with expansion, and prove its main properties. This system turns type inference into a constraint solving problem; this could be helpful to design a modular type inference algorithm for System F types in the future.


Implicit complexity for coinductive data: a characterization of corecurrence

Abstract: We propose a framework for reasoning about programs that manipulate coinductive data as well as inductive data. Our approach is based on using equational programs, which support a seamless combination of computation and reasoning, and using productivity (fairness) as the fundamental assertion, rather than bi-simulation. The latter is expressible in terms of the former. As an application to this framework, we give an implicit characterization of corecurrence: a function is definable using corecurrence iff its productivity is provable using coinduction for formulas in which data-predicates do not occur negatively. This is an analog, albeit in weaker form, of a characterization of recurrence (i.e. primitive recursion) in [Leivant, Unipolar induction, TCS 318, 2004].


Sublogarithmic uniform Boolean proof nets

Abstract: Using a proofs-as-programs correspondence, Terui was able to compare two models of parallel computation: Boolean circuits and proof nets for multiplicative linear logic. Mogbil et. al. gave a logspace translation allowing us to compare their computational power as uniform complexity classes. This paper presents a novel translation in AC0 and focuses on a simpler restricted notion of uniform Boolean proof nets. We can then encode constant-depth circuits and compare complexity classes below logspace, which were out of reach with the previous translations.


Provably Total Functions of Arithmetic with Basic Terms

Abstract: A new characterization of provably recursive functions of first-order arithmetic is described. Its main feature is using only terms consisting of 0, the successor S and variables in the quantifier rules, namely, universal elimination and existential introduction.


A type system for PSPACE derived from light linear logic

Abstract: We present a polymorphic type system for lambda calculus ensuring that well-typed programs can be executed in polynomial space: dual light affine logic with booleans (DLALB). To build DLALB we start from DLAL (which has a simple type language with a linear and an intuitionistic type arrow, as well as one modality) which characterizes FPTIME functions. In order to extend its expressiveness we add two boolean constants and a conditional constructor in the same way as with the system STAB. We show that the value of a well-typed term can be computed by an alternating machine in polynomial time, thus such a term represents a program of PSPACE (given that PSPACE = APTIME). We also prove that all polynomial space decision functions can be represented in DLALB. Therefore DLALB characterizes PSPACE predicates.


Formal security analysis of registration protocols for interactive systems: a methodology and a case of study

Abstract: In this work we present and formally analyze CHAT-SRP (CHAos based Tickets-Secure Registration Protocol), a protocol to provide interactive and collaborative platforms with a cryptographically robust solution to classical security issues. Namely, we focus on the secrecy and authenticity properties while keeping a high usability. In this sense, users are forced to blindly trust the system administrators and developers. Moreover, as far as we know, the use of formal methodologies for the verification of security properties of communication protocols isn't yet a common practice. We propose here a methodology to fill this gap, i.e., to analyse both the security of the proposed protocol and the pertinence of the underlying premises. In this concern, we propose the definition and formal evaluation of a protocol for the distribution of digital identities. Once distributed, these identities can be used to verify integrity and source of information. We base our security analysis on tools for automatic verification of security protocols widely accepted by the scientific community, and on the principles they are based upon. In addition, it is assumed perfect cryptographic primitives in order to focus the analysis on the exchange of protocol messages. The main property of our protocol is the incorporation of tickets, created using digests of chaos based nonces (numbers used only once) and users' personal data. Combined with a multichannel authentication scheme with some previous knowledge, these tickets provide security during the whole protocol by univocally linking each registering user with a single request. [..]


Method of the Multidimensional Sieve in the Practical Realization of some Combinatorial Algorithms

Abstract: Some difficulties regarding the application of the well-known sieve method are considered in the case when a practical (program) realization of selecting elements, having a particular property among the elements of a set with a sufficiently great cardinal number(cardinality). In this paper the problem has been resolved by using a modified version of the method, utilizing multidimensional arrays. As a theoretical illustration of the method of the multidimensional sieve, the problem of obtaining a single representative of each equivalence class with respect to a given relation of equivalence and obtaining the cardinality of the respective factor set is considered with relevant mathematical proofs.


DMFSGD: A Decentralized Matrix Factorization Algorithm for Network Distance Prediction

Abstract: The knowledge of end-to-end network distances is essential to many Internet applications. As active probing of all pairwise distances is infeasible in large-scale networks, a natural idea is to measure a few pairs and to predict the other ones without actually measuring them. This paper formulates the distance prediction problem as matrix completion where unknown entries of an incomplete matrix of pairwise distances are to be predicted. The problem is solvable because strong correlations among network distances exist and cause the constructed distance matrix to be low rank. The new formulation circumvents the well-known drawbacks of existing approaches based on Euclidean embedding. A new algorithm, so-called Decentralized Matrix Factorization by Stochastic Gradient Descent (DMFSGD), is proposed to solve the network distance prediction problem. By letting network nodes exchange messages with each other, the algorithm is fully decentralized and only requires each node to collect and to process local measurements, with neither explicit matrix constructions nor special nodes such as landmarks and central servers. In addition, we compared comprehensively matrix factorization and Euclidean embedding to demonstrate the suitability of the former on network distance prediction. We further studied the incorporation of a robust loss function and of non-negativity constraints. Extensive experiments on various publicly-available datasets of network delays show not only the scalability and the accuracy of our approach but also its usability in real Internet applications.


Computational Tutorial on Gr\"obner bases embedding Sage in LaTeX with SageTEX

Abstract: Elementary tutorial on implementation aspects of Gr\"obner bases computation.


Autenticazione biometrica: Realt\`a e fantasia

Abstract: Biometrical authentication systems are often presented as the best and simplest way to reach higher security levels. But a deeper analysis shows that several risks are hidden and the service provider adopting those system has to carefully check its liabilities before deploying them.


Formalization of semantic network of image constructions in electronic content

Abstract: A formal theory based on a binary operator of directional associative relation is constructed in the article and an understanding of an associative normal form of image constructions is introduced. A model of a commutative semigroup, which provides a presentation of a sentence as three components of an interrogative linguistic image construction, is considered.


Covering and Piercing Disks with Two Centers

Abstract: We give exact and approximation algorithms for two-center problems when the input is a set $\mathcal{D}$ of disks in the plane. We first study the problem of finding two smallest congruent disks such that each disk in $\mathcal{D}$ intersects one of these two disks. Then we study the problem of covering the set $\mathcal{D}$ by two smallest congruent disks.


Compressed Beamforming Applied to B-Mode Ultrasound Imaging

Abstract: Emerging sonography techniques often imply increasing in the number of transducer elements involved in the imaging process. Consequently, larger amounts of data must be acquired and processed by the beamformer. The significant growth in the amounts of data effects both machinery size and power consumption. Within the classical sampling framework, state of the art systems reduce processing rates by exploiting the bandpass bandwidth of the detected signals. It has been recently shown, that a much more significant sample-rate reduction may be obtained, by treating ultrasound signals within the Finite Rate of Innovation framework. These ideas follow the spirit of Xampling, which combines classic methods from sampling theory with recent developments in Compressed Sensing. Applying such low-rate sampling schemes to individual transducer elements, which detect energy reflected from biological tissues, is limited by the noisy nature of the signals. This often results in erroneous parameter extraction, bringing forward the need to enhance the SNR of the low-rate samples. In our work, we manage to achieve such SNR enhancement, by beamforming the sub-Nyquist samples obtained from multiple elements. We refer to this process as "compressed beamforming". Applying it to cardiac ultrasound data, we successfully image macroscopic perturbations, while achieving a nearly eight-fold reduction in sample-rate, compared to standard techniques.


New results on variants of covering codes in Sierpinski graphs

Abstract: In this paper we study identifying codes, locating-dominating codes, and total-dominating codes in Sierpinski graphs. We compute the minimum size of such codes in Sierpinski graphs.


Transparent caching of virtual stubs for improved performance in ubiquitous environments

Abstract: Context-awareness is an essential requirement for pervasive computing applications, which enables them to adapt and perform tasks based on context. One of the adaptive features of context-awareness is contextual reconfiguration. Contextual reconfiguration involves discovering remote service(s) based on context and binding them to the application components to realize new behaviors, which may be needed to satisfy user needs or to enrich user experience. One of the steps in the reconfiguration process involves a remote lookup to discover the service(s) based on context. This remote lookup process provides the largest contribution to reconfiguration time and this is due to fact that the remote calls are much slower than local calls. Consequently, it affects system performance. In pervasive computing applications, this may turn out to be undesirable in terms of user experience. Moreover, other distributed applications using the network may be affected as every remote method call decreases the amount of bandwidth available on the network. Various systems provide reconfiguration support and offer high-level reconfiguration directives to develop adaptive context-aware applications, but do not address this performance bottleneck. We address this issue and implement seamless caching of virtual stubs within our PCRA1 for improved performance. In this paper we present and describe our transparent caching support and also provide its performance evaluation.


Statistical Algorithms and a Lower Bound for Detecting Planted Clique

Abstract: We introduce a framework for proving lower bounds on computational problems over distributions against algorithms that can be implemented using access to a statistical query oracle. For such algorithms, access to the input distribution is limited to obtaining an estimate of the expectation of any given function on a sample drawn randomly from the input distribution, rather than directly accessing samples. Most natural algorithms of interest in theory and in practice, e.g., moments-based methods, local search, standard iterative methods for convex optimization, MCMC and simulated annealing can be implemented in this framework. Our framework is based on, and generalizes, the statistical query model in learning theory (Kearns, 1998). Our main application is a nearly optimal lower bound on the complexity of any statistical query algorithm for detecting planted bipartite clique distributions (or planted dense subgraph distributions) when the planted clique has size $O(n^{1/2-\delta})$ for any constant $\delta > 0$. The assumed hardness of variants of these problems has been used to prove hardness of several other problems and as a guarantee for security in cryptographic applications. Our lower bounds provide concrete evidence of hardness, thus supporting these assumptions.


Turing Machines and Understanding Computational Complexity

Abstract: We describe the Turing Machine, list some of its many influences on the theory of computation and complexity of computations, and illustrate its importance.


Structural Analysis: Shape Information via Points-To Computation

Abstract: This paper introduces a new hybrid memory analysis, Structural Analysis, which combines an expressive shape analysis style abstract domain with efficient and simple points-to style transfer functions. Using data from empirical studies on the runtime heap structures and the programmatic idioms used in modern object-oriented languages we construct a heap analysis with the following characteristics: (1) it can express a rich set of structural, shape, and sharing properties which are not provided by a classic points-to analysis and that are useful for optimization and error detection applications (2) it uses efficient, weakly-updating, set-based transfer functions which enable the analysis to be more robust and scalable than a shape analysis and (3) it can be used as the basis for a scalable interprocedural analysis that produces precise results in practice. The analysis has been implemented for .Net bytecode and using this implementation we evaluate both the runtime cost and the precision of the results on a number of well known benchmarks and real world programs. Our experimental evaluations show that the domain defined in this paper is capable of precisely expressing the majority of the connectivity, shape, and sharing properties that occur in practice and, despite the use of weak updates, the static analysis is able to precisely approximate the ideal results. The analysis is capable of analyzing large real-world programs (over 30K bytecodes) in less than 65 seconds and using less than 130MB of memory. In summary this work presents a new type of memory analysis that advances the state of the art with respect to expressive power, precision, and scalability and represents a new area of study on the relationships between and combination of concepts from shape and points-to analyses.


Abstracting Runtime Heaps for Program Understanding

Abstract: Modern programming environments provide extensive support for inspecting, analyzing, and testing programs based on the algorithmic structure of a program. Unfortunately, support for inspecting and understanding runtime data structures during execution is typically much more limited. This paper provides a general purpose technique for abstracting and summarizing entire runtime heaps. We describe the abstract heap model and the associated algorithms for transforming a concrete heap dump into the corresponding abstract model as well as algorithms for merging, comparing, and computing changes between abstract models. The abstract model is designed to emphasize high-level concepts about heap-based data structures, such as shape and size, as well as relationships between heap structures, such as sharing and connectivity. We demonstrate the utility and computational tractability of the abstract heap model by building a memory profiler. We then use this tool to check for, pinpoint, and correct sources of memory bloat from a suite of programs from DaCapo.


Minimizing the Switch and Link Conflicts in an Optical Multi-stage Interconnection Network

Abstract: Multistage Interconnection Networks (MINs) are very popular in switching and communication applications. A MIN connects N inputs to N outputs and is referred as an N \times N MIN; having size N. Optical Multistage Interconnection Network (OMIN) represents an important class of Interconnection networks. Crosstalk is the basic problem of OMIN. Switch Conflict and Link Conflict are the two main reason of crosstalk. In this paper, we are considering both problems. A number of techniques like Optical window, Improved Window, Heuristic, Genetic, and Zero have been proposed earlier in this research domain. In this paper, we have proposed two algorithms called Address Selection Algorithm and Route Selection Algorithm (RSA). RSA is based on Improved Window Method. We have applied the proposed algorithms on existing Omega network, having shuffle-exchange connection pattern. The main functionality of ASA and RSA is to minimize the number of switch and link conflicts in the network and to provide conflict free routes.


Near-Optimal Random Walk Sampling in Distributed Networks

Abstract: Performing random walks in networks is a fundamental primitive that has found numerous applications in communication networks such as token management, load balancing, network topology discovery and construction, search, and peer-to-peer membership management. While several such algorithms are ubiquitous, and use numerous random walk samples, the walks themselves have always been performed naively. In this paper, we focus on the problem of performing random walk sampling efficiently in a distributed network. Given bandwidth constraints, the goal is to minimize the number of rounds and messages required to obtain several random walk samples in a continuous online fashion. We present the first round and message optimal distributed algorithms that present a significant improvement on all previous approaches. The theoretical analysis and comprehensive experimental evaluation of our algorithms show that they perform very well in different types of networks of differing topologies. In particular, our results show how several random walks can be performed continuously (when source nodes are provided only at runtime, i.e., online), such that each walk of length $\ell$ can be performed exactly in just $\tilde{O}(\sqrt{\ell D})$ rounds, (where $D$ is the diameter of the network), and $O(\ell)$ messages. This significantly improves upon both, the naive technique that requires $O(\ell)$ rounds and $O(\ell)$ messages, and the sophisticated algorithm of [DasSarma et al. PODC 2010] that has the same round complexity as this paper but requires $\Omega(m\sqrt{\ell})$ messages (where $m$ is the number of edges in the network). Our theoretical results are corroborated through extensive experiments on various topological data sets. Our algorithms are fully decentralized, lightweight, and easily implementable, and can serve as building blocks in the design of topologically-aware networks.


On Zarankiewicz Problem and Depth-Two Superconcentrators

Abstract: We show tight necessary and sufficient conditions on the sizes of small bipartite graphs whose union is a larger bipartite graph that has no large bipartite independent set. Our main result is a common generalization of two classical results in graph theory: the theorem of K\H{o}v\'{a}ri, S\'{o}s and Tur\'{a}n on the minimum number of edges in a bipartite graph that has no large independent set, and the theorem of Hansel (also Katona and Szemer\'{e}di, Krichevskii) on the sum of the sizes of bipartite graphs that can be used to construct a graph (non-necessarily bipartite) that has no large independent set. As an application of our results, we show how they unify the underlying combinatorial principles developed in the proof of tight lower bounds for depth-two superconcentrators.


Stereo image Transference & Retrieval over SMS

Abstract: Paper presents the way of transferring stereo images using SMS over GSM network. Generally, Stereo image is composed of two stereoscopic images in such way that gives three dimensional affect when viewed. GSM have two short messaging services, which can transfer images and sounds etc. Such services are known as; MMS (Multimedia Messaging Service) and EMS (Extended Messaging Service). EMS can send Predefined sounds, animation and images but have limitation that it does not support widely. MMS can send much higher contents than EMS but need 3G and other network capability in order to send large size data up to 1000 bytes. Other limitations are Portability, content adaption etc. Our major aim in this paper is to provide an alternative way of sending stereo images over SMS which is widely supported than EMS. We develop an application using J2ME Platform.


Interactive Character Posing by Sparse Coding

Abstract: Character posing is of interest in computer animation. It is difficult due to its dependence on inverse kinematics (IK) techniques and articulate property of human characters . To solve the IK problem, classical methods that rely on numerical solutions often suffer from the under-determination problem and can not guarantee naturalness. Existing data-driven methods address this problem by learning from motion capture data. When facing a large variety of poses however, these methods may not be able to capture the pose styles or be applicable in real-time environment. Inspired from the low-rank motion de-noising and completion model in \cite{lai2011motion}, we propose a novel model for character posing based on sparse coding. Unlike conventional approaches, our model directly captures the pose styles in Euclidean space to provide intuitive training error measurements and facilitate pose synthesis. A pose dictionary is learned in training stage and based on it natural poses are synthesized to satisfy users' constraints . We compare our model with existing models for tasks of pose de-noising and completion. Experiments show our model obtains lower de-noising and completion error. We also provide User Interface(UI) examples illustrating that our model is effective for interactive character posing.


Is it a "Good" Encoding of Mixed Choice? (Technical Report)

Abstract: This technical report contains the proofs to the lemmata and theorems of [PN12] as well as some additional material. As main contributions [PN12] presents an encoding of mixed choice in the context of the pi-calculus and a criterion to measure whether the degree of distribution in process networks is preserved.


Picture Collage with Genetic Algorithm and Stereo vision

Abstract: In this paper, a salient region extraction method for creating picture collage based on stereo vision is proposed. Picture collage is a kind of visual image summary to arrange all input images on a given canvas, allowing overlay, to maximize visible visual information. The salient regions of each image are firstly extracted and represented as a depth map. The output picture collage shows as many visible salient regions (without being overlaid by others) from all images as possible. A very efficient Genetic algorithm is used here for the optimization. The experimental results showed the superior performance of the proposed method.


Minutiae Extraction from Fingerprint Images - a Review

Abstract: Fingerprints are the oldest and most widely used form of biometric identification. Everyone is known to have unique, immutable fingerprints. As most Automatic Fingerprint Recognition Systems are based on local ridge features known as minutiae, marking minutiae accurately and rejecting false ones is very important. However, fingerprint images get degraded and corrupted due to variations in skin and impression conditions. Thus, image enhancement techniques are employed prior to minutiae extraction. A critical step in automatic fingerprint matching is to reliably extract minutiae from the input fingerprint images. This paper presents a review of a large number of techniques present in the literature for extracting fingerprint minutiae. The techniques are broadly classified as those working on binarized images and those that work on gray scale images directly.


Interconnection of Communities of Practice: A Web Platform for Knowledge Management

Abstract: Our works aim at developing a Web platform to connect various Communities of Practice (CoPs) and to capitalise on all their knowledge. This platform addresses CoPs interested in a same general activity, for example tutoring. For that purpose, we propose a general model of Interconnection of Communities of Practice (ICP), based on the concept of Constellation of Practice (CCP) developed by Wenger (1998). The model of ICP was implemented and has been used to develop the TE-Cap 2 platform which has, as its field of application, educational tutoring activities. In particular, we propose an indexation and search tool for the ICP knowledge base. The TE-Cap 2 platform has been used in real conditions. We present the main results of this descriptive investigation to validate this work.


Packet Skipping and Network Coding for Delay-Sensitive Network Communication

Abstract: We provide an analytical study of the impact of packet skipping and opportunistic network coding on the timely communication of messages through a single network element. In a first step, we consider a single-server queueing system with Poisson arrivals, exponential service times, and a single buffer position. Packets arriving at a network node have a fixed deadline before which they should reach the destination. To preserve server capacity, we introduce a thresholding policy, based on remaining time until deadline expiration, to decide whether to serve a packet or skip its service. The obtained goodput improvement of the system is derived, as well as the operating conditions under which thresholding can enhance performance. Subsequently, we focus our analysis on a system that supports network coding instead of thresholding. We characterize the impact of network coding at a router node on the delivery of packets associated with deadlines. We model the router node as a queueing system where packets arrive from two independent Poisson flows and undergo opportunistic coding operations. We obtain an exact expression for the goodput of the system and study the achievable gain. Finally, we provide an analytical model that considers both network coding and packet skipping, capturing their joint performance. A comparative analysis between the aforementioned approaches is provided.


A Novel Chaotic Encryption Scheme based on Pseudorandom Bit Padding

Abstract: Cryptography is always very important in data origin authentications, entity authentication, data integrity and confidentiality. In recent years, a variety of chaotic cryptographic schemes have been proposed. These schemes have typical structure which performed the permutation and the diffusion stages, alternatively. The random number generators are intransitive in cryptographic schemes and be used in the diffusion functions of the image encryption for diffused pixels of plain image. In this paper, we propose a chaotic encryption scheme based on pseudorandom bit padding that the bits be generated by a novel logistic pseudorandom image algorithm. To evaluate the security of the cipher image of this scheme, the key space analysis, the correlation of two adjacent pixels and differential attack were performed. This scheme tries to improve the problem of failure of encryption such as small key space and level of security.


A Representation of Binary Matrices

Abstract: In this article we discuss the presentation of a random binary matrix using sequence of whole nonnegative numbers. We examine some advantages and disadvantages of this presentation as an alternative of the standard presentation using two-dimensional array. It is shown that the presentation of binary matrices using ordered n-tuples of natural numbers makes the algorithms faster and saves a lot of memory. In this work we use object-oriented programming using the syntax and the semantic of C++ programming language.


A MDA approach for defining WS-Policy semantic non-functional properties

Abstract: A lot of works has been especially interested to the functional aspect of Web services. Nevertheless, it is necessary to describe their non-functional properties such as the security characteristics and the quality of service. The WS-Policy standard was recommended in 2007 to describe Web services policies including the non-functional properties. However, it doesn't provide any information of their meaning necessary for automatic processes. In this paper, we propose a Model Driven Architecture approach founded on W3C standards to generate WSDL language based files including semantic policies. We use a package of WSDL and WS-Policy profiles and transformations rules to generate Web services interfaces files including policies. We extend a XML schema profile according to SAWSDL standard to define semantic non-functional properties domains. This work contributes to minimize the development cost of Web services including semantic policies. Moreover, the generated services can be automatically processed in discovery, selection and negotiation tasks.


A United Image Force for Deformable Models and Direct Transforming Geometric Active Contorus to Snakes by Level Sets

Abstract: A uniform distribution of the image force field around the object fasts the convergence speed of the segmentation process. However, to achieve this aim, it causes the force constructed from the heat diffusion model unable to indicate the object boundaries accurately. The image force based on electrostatic field model can perform an exact shape recovery. First, this study introduces a fusion scheme of these two image forces, which is capable of extracting the object boundary with high precision and fast speed. Until now, there is no satisfied analysis about the relationship between Snakes and Geometric Active Contours (GAC). The second contribution of this study addresses that the GAC model can be deduced directly from Snakes model. It proves that each term in GAC and Snakes is correspondent and has similar function. However, the two models are expressed using different mathematics. Further, since losing the ability of rotating the contour, adoption of level sets can limits the usage of GAC in some circumstances.


Temporal Psychovisual Modulation: a new paradigm of information display

Abstract: We report on a new paradigm of information display that greatly extends the utility and versatility of current optoelectronic displays. The main innovation is to let a display of high refresh rate optically broadcast so-called atom frames, which are designed through non-negative matrix factorization to form bases for a class of images, and different viewers perceive selfintended images by using display-synchronized viewing devices and their own human visual systems to fuse appropriately weighted atom frames. This work is essentially a scheme of temporal psychovisual modulation in visible spectrum, using an optoelectronic modulator coupled with a biological demodulator.


Identifying Clusters of Concepts in a Low Cohesive Class for Extract Class Refactoring Using Metrics Supplemented Agglomerative Clustering Technique

Abstract: Object oriented software with low cohesive classes can increase maintenance cost. Low cohesive classes are likely to be introduced into the software during initial design due to deviation from design principles and during evolution due to software deterioration. Low cohesive class performs operations that should be done by two or more classes. The low cohesive classes need to be identified and refactored using extract class refactoring to improve the cohesion. In this regard, two aspects are involved; the first one is to identify the low cohesive classes and the second one is to identify the clusters of concepts in the low cohesive classes for extract class refactoring. In this paper, we propose metrics supplemented agglomerative clustering technique for covering the above two aspects. The proposed metrics are validated using Weyuker's properties. The approach is applied successfully on two examples and on a case study.


Two Hands Are Better Than One (up to constant factors)

Abstract: We study the difference between the standard seeded model of tile self-assembly, and the "seedless" two-handed model of tile self-assembly. Most of our results suggest that the two-handed model is more powerful. In particular, we show how to simulate any seeded system with a two-handed system that is essentially just a constant factor larger. We exhibit finite shapes with a busy-beaver separation in the number of distinct tiles required by seeded versus two-handed, and exhibit an infinite shape that can be constructed two-handed but not seeded. Finally, we show that verifying whether a given system uniquely assembles a desired supertile is co-NP-complete in the two-handed model, while it was known to be polynomially solvable in the seeded model.


Toward a Motor Theory of Sign Language Perception

Abstract: Researches on signed languages still strongly dissociate lin- guistic issues related on phonological and phonetic aspects, and gesture studies for recognition and synthesis purposes. This paper focuses on the imbrication of motion and meaning for the analysis, synthesis and evaluation of sign language gestures. We discuss the relevance and interest of a motor theory of perception in sign language communication. According to this theory, we consider that linguistic knowledge is mapped on sensory-motor processes, and propose a methodology based on the principle of a synthesis-by-analysis approach, guided by an evaluation process that aims to validate some hypothesis and concepts of this theory. Examples from existing studies illustrate the di erent concepts and provide avenues for future work.


Slick Packets

Abstract: Source-controlled routing has been proposed as a way to improve flexibility of future network architectures, as well as simplifying the data plane. However, if a packet specifies its path, this precludes fast local re-routing within the network. We propose SlickPackets, a novel solution that allows packets to slip around failures by specifying alternate paths in their headers, in the form of compactly-encoded directed acyclic graphs. We show that this can be accomplished with reasonably small packet headers for real network topologies, and results in responsiveness to failures that is competitive with past approaches that require much more state within the network. Our approach thus enables fast failure response while preserving the benefits of source-controlled routing.


A direct product theorem for bounded-round public-coin randomized communication complexity

Abstract: In this paper, we show a direct product theorm in the model of two-party bounded-round public-coin randomized communication complexity. For a relation f subset of X times Y times Z (X,Y,Z are finite sets), let R^{(t), pub}_e (f) denote the two-party t-message public-coin communication complexity of f with worst case error e. We show that for any relation f and positive integer k: R^{(t), pub}_{1 - 2^{-Omega(k/t^2)}}(f^k) = Omega(k/t (R^{(t), pub}_{1/3}(f) - O(t^2))) . In particular, it implies a strong direct product theorem for the two-party constant-message public-coin randomized communication complexity of all relations f. Our result for example implies a strong direct product theorem for the pointer chasing problem. This problem has been well studied for understanding round v/s communication trade-offs in both classical and quantum communication protocols. We show our result using information theoretic arguments. Our arguments and techniques build on the ones used in [Jain 2011], where a strong direct product theorem for the two-party one-way public-coin communication complexity of all relations is shown (that is the special case of our result when t=1). One key tool used in our work and also in [Jain 2011] is a message compression technique due to [Braverman and Rao 2011], who used it to show a direct sum theorem for the two-party bounded-round public-coin randomized communication complexity of all relations. Another important tool that we use is a correlated sampling protocol, which for example, has been used in [Holenstein 2007] for proving a parallel repetition theorem for two-prover games.


Identifying and Analysis of Scene Mining Methods Beased on Scenes Extracted Features

Abstract: Scene mining is a subset of image mining in which scenes are classified to a distinct set of classes based on analysis of their content. In other word in scene mining, a label is given to visual content of scene, for example, mountain, beach. Scene mining is used in applications such as medicine, movie, information retrieval, computer vision, recognition of traffic scene. Reviewing of represented methods shows there are various methods in scene mining. Scene mining applications extension and existence of various scenes, make comparison of methods hard. Scene mining can be followed by identifying scene mining components and representing a framework to analyzing and evaluating methods. In this paper, at first, components of scene mining are introduced, then a framework based on extracted features of scene is represented to classify scene mining methods. Finally, these methods are analyzed and evaluated via a proposal framework.


Customers Behavior Modeling by Semi-Supervised Learning in Customer Relationship Management

Abstract: Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies in this information age. Data mining technologies extract hidden information and knowledge from large data stored in databases or data warehouses, thereby supporting the corporate decision making process. CRM uses data mining (one of the elements of CRM) techniques to interact with customers. This study investigates the use of a technique, semi-supervised learning, for the management and analysis of customer-related data warehouse and information. The idea of semi-supervised learning is to learn not only from the labeled training data, but to exploit also the structural information in additionally available unlabeled data. The proposed semi-supervised method is a model by means of a feed-forward neural network trained by a back propagation algorithm (multi-layer perceptron) in order to predict the category of an unknown customer (potential customers). In addition, this technique can be used with Rapid Miner tools for both labeled and unlabeled data.


Theoretical Modeling and Simulation of Phase-Locked Loop (PLL) for Clock Data Recovery (CDR)

Abstract: Modern communication and computer systems require rapid (Gbps), efficient and large bandwidth data transfers. Agressive scaling of digital integrated systems allow buses and communication controller circuits to be integrated with the microprocessor on the same chip. The Peripheral Component Interconnect Express (PCIe) protocol handles all communcation between the central processing unit (CPU) and hardware devices. PCIe buses require efficient clock data recovery circuits (CDR) to recover clock signals embedded in data during transmission. This paper describes the theoretical modeling and simulation of a phase-locked loop (PLL) used in a CDR circuit. A simple PLL architecture for a 5 GHz CDR circuit is proposed and elaborated in this work. Simulations were carried out using a Hardware Description Language, Verilog- AMS. The effect of jitter on the proposed design is also simulated and evaluated in this work. It was found that the proposed design is robust against both input and VCO jitter.


Some Observations on Optimal Frequency Selection in DVFS-based Energy Consumption Minimization

Abstract: In recent years, the issue of energy consumption in parallel and distributed computing systems has attracted a great deal of attention. In response to this, many energy-aware scheduling algorithms have been developed primarily using the dynamic voltage-frequency scaling (DVFS) capability which has been incorporated into recent commodity processors. Majority of these algorithms involve two passes: schedule generation and slack reclamation. The former pass involves the redistribution of tasks among DVFS-enabled processors based on a given cost function that includes makespan and energy consumption; and, while the latter pass is typically achieved by executing individual tasks with slacks at a lower processor frequency. In this paper, a new slack reclamation algorithm is proposed by approaching the energy reduction problem from a different angle. Firstly, the problem of task slack reclamation by using combinations of processors' frequencies is formulated. Secondly, several proofs are provided to show that (1) if the working frequency set of processor is assumed to be continues, the optimal energy will be always achieved by using only one frequency, (2) for real processors with a discrete set of working frequencies, the optimal energy is always achieved by using at most two frequencies, and (3) these two frequencies are adjacent/neighbouring when processor energy consumption is a convex function of frequency. Thirdly, a novel algorithm to find the best combination of frequencies to result the optimal energy is presented. The presented algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 3000 randomly generated task graphs, and 600 task graphs for two popular applications (Gauss-Jordan and LU decomposition). The results show the superiority of the proposed algorithm in comparison with other techniques.


On completeness of reducibility candidates as a semantics of strong normalization

Abstract: This paper defines a sound and complete semantic criterion, based on reducibility candidates, for strong normalization of theories expressed in minimal deduction modulo \`a la Curry. The use of Curry-style proof-terms allows to build this criterion on the classic notion of pre-Heyting algebras and makes that criterion concern all theories expressed in minimal deduction modulo. Compared to using Church-style proof-terms, this method provides both a simpler definition of the criterion and a simpler proof of its completeness.


A type reduction theory for systems with replicated components

Abstract: The Parameterised Model Checking Problem asks whether an implementation Impl(t) satisfies a specification Spec(t) for all instantiations of parameter t. In general, t can determine numerous entities: the number of processes used in a network, the type of data, the capacities of buffers, etc. The main theme of this paper is automation of uniform verification of a subclass of PMCP with the parameter of the first kind, i.e. the number of processes in the network. We use CSP as our formalism. We present a type reduction theory, which, for a given verification problem, establishes a function \phi that maps all (sufficiently large) instantiations T of the parameter to some fixed type T^ and allows us to deduce that if Spec(T^) is refined by \phi(Impl(T)), then (subject to certain assumptions) Spec(T) is refined by Impl(T). The theory can be used in practice by combining it with a suitable abstraction method that produces a t-independent process Abstr that is refined by {\phi}(Impl(T)) for all sufficiently large T. Then, by testing (with a model checker) if the abstract model Abstr refines Spec(T^), we can deduce a positive answer to the original uniform verification problem. The type reduction theory relies on symbolic representation of process behaviour. We develop a symbolic operational semantics for CSP processes that satisfy certain normality requirements, and we provide a set of translation rules that allow us to concretise symbolic transition graphs. Based on this, we prove results that allow us to infer behaviours of a process instantiated with uncollapsed types from known behaviours of the same process instantiated with a reduced type. One of the main advantages of our symbolic operational semantics and the type reduction theory is their generality, which makes them applicable in a wide range of settings.


On Conditional Decomposability

Abstract: The requirement of a language to be conditionally decomposable is imposed on a specification language in the coordination supervisory control framework of discrete-event systems. In this paper, we present a polynomial-time algorithm for the verification whether a language is conditionally decomposable with respect to given alphabets. Moreover, we also present a polynomial-time algorithm to extend the common alphabet so that the language becomes conditionally decomposable. A relationship of conditional decomposability to nonblockingness of modular discrete-event systems is also discussed in this paper in the general settings. It is shown that conditional decomposability is a weaker condition than nonblockingness.


A Note on Undecidability of Observation Consistency for Non-Regular Languages

Abstract: One of the most interesting questions concerning hierarchical control of discrete-event systems with partial observations is a condition under which the language observability is preserved between the original and the abstracted plant. Recently, we have characterized two such sufficient conditions---observation consistency and local observation consistency. In this paper, we prove that the condition of observation consistency is undecidable for non-regular (linear, deterministic context-free) languages. The question whether the condition is decidable for regular languages is open.


Stochastic Loss Aversion for Random Medium Access

Abstract: We consider a slotted-ALOHA LAN with loss-averse, noncooperative greedy users. To avoid non-Pareto equilibria, particularly deadlock, we assume probabilistic loss-averse behavior. This behavior is modeled as a modulated white noise term, in addition to the greedy term, creating a diffusion process modeling the game. We observe that when player's modulate with their throughput, a more efficient exploration of play-space results, and so finding a Pareto equilibrium is more likely over a given interval of time.


Abstract unordered and ordered trees CRDT

Abstract: Trees are fundamental data structure for many areas of computer science and system engineering. In this report, we show how to ensure eventual consistency of optimistically replicated trees. In optimistic replication, the different replicas of a distributed system are allowed to diverge but should eventually reach the same value if no more mutations occur. A new method to ensure eventual consistency is to design Conflict-free Replicated Data Types (CRDT). In this report, we design a collection of tree CRDT using existing set CRDTs. The remaining concurrency problems particular to tree data structure are resolved using one or two layers of correction algorithm. For each of these layer, we propose different and independent policies. Any combination of set CRDT and policies can be constructed, giving to the distributed application programmer the entire control of the behavior of the shared data in face of concurrent mutations. We also propose to order these trees by adding a positioning layer which is also independent to obtain a collection of ordered tree CRDTs.


Sitting closer to friends than enemies, revisited

Abstract: Signed graphs, i.e., undirected graphs with edges labelled with a plus or minus sign, are commonly used to model relationships in social networks. Recently, Kermarrec and Thraves initiated the study of the problem of appropriately visualising the network: They asked whether any signed graph can be embedded into the metric space R^l in such a manner that every vertex is closer to all its friends (neighbours via positive edges) than to all its enemies (neighbours via negative edges). Interestingly, embeddability into R^1 can be expressed as a purely combinatorial problem. In this paper we pursue a deeper study of this particular case, answering several questions posed by Kermarrec and Thraves. First, we refine the approach of Kermarrec and Thraves for the case of complete signed graphs by showing that the problem is closely related to the recognition of proper interval graphs. Second, we prove that the general case, whose polynomial-time tractability remained open, is in fact NP-complete. Finally, we provide lower and upper bounds for the time complexity of the general case: we prove that the existence of a subexponential time (in the number of vertices and edges of the input signed graph) algorithm would violate the Exponential Time Hypothesis, whereas a simple dynamic programming approach gives a running time single-exponential in the number of vertices.


Knowledge Ecologies in International Affairs: A New Paradigm for Dialog and Collaboration

Abstract: To have command over increasingly complicated social, political, economic and environmental challenges, fragmentary knowledge, or rather the simple accumulation of basic research is inadequate (Kim). International affairs professionals operating in government, academia and the private sector are progressively more aware that access to, and the blending of, interdisciplinary policy-related knowledge is critical to effective problem solving and decision-making. But how can one do so effectively?


A Survey on Dynamic Spectrum Access Techniques for Cognitive Radio

Abstract: Cognitive radio (CR) is a new paradigm that utilizes the available spectrum band. The key characteristic of CR system is to sense the electromagnetic environment to adapt their operation and dynamically vary its radio operating parameters. The technique of dynamically accessing the unused spectrum band is known as Dynamic Spectrum Access (DSA). The dynamic spectrum access technology helps to minimize unused spectrum bands. In this paper, main functions of Cognitive Radio (CR) i.e. spectrum sensing, spectrum management, spectrum mobility and spectrum sharing are discussed. Then DSA models are discussed along with different methods of DSA such as Command and Control, Exclusive-Use, Shared Use of Primary Licensed User and Commons method. Game-theoretic approach using Bertrand game model, Markovian Queuing Model for spectrum allocation in centralized architecture and Fuzzy logic based method are also discussed and result are shown.


Single bit full adder design using 8 transistors with novel 3 transistors XNOR gate

Abstract: In present work a new XNOR gate using three transistors has been presented, which shows power dissipation of 550.7272$\mu$W in 0.35$\mu$m technology with supply voltage of 3.3V. Minimum level for high output of 2.05V and maximum level for low output of 0.084V have been obtained. A single bit full adder using eight transistors has been designed using proposed XNOR cell, which shows power dissipation of 581.542$\mu$W. Minimum level for high output of 1.97V and maximum level for low output of 0.24V is obtained for sum output signal. For carry signal maximum level for low output of 0.32V and minimum level for high output of 3.2V have been achieved. Simulations have been performed by using SPICE based on TSMC 0.35$\mu$m CMOS technology. Power consumption of proposed XNOR gate and full adder has been compared with earlier reported circuits and proposed circuit's shows better performance in terms of power consumption and transistor count.


Investigating the Awareness of Applying the Important Web Application Development and Measurement Practices in Small Software Firms

Abstract: This paper aims to discuss the pilot study and analysis of the current development and measurement practices in Jordanian small software firms. It is conducted because most developers build web applications without using any specific development method and don't know how to integrate the suitable measurements inside the process to improve and reduce defect, time and rework of the development life cycle. Furthermore the objectives of this pilot study are firstly; determine the real characteristics of small software firms in Jordan. Secondly, investigate the current development and measurement practices. Thirdly, examine the need of new development methodology for building web application in small software firms. Consequently, Pilot survey was conducted in Jordanian small software firms. Descriptive statistics analysis was used to rank the development and measurements methods according to their importance. This paper presents the data, analysis and finding based on pilot survey. These actual findings of this survey will contribute to build new methodology for developing web applications in small software firms taking to account how to integrate the suitable measurement program to the whole development process and also will provide useful information to those who are doing research in the same area.


Information Hiding in CSS : A Secure Scheme Text-Steganography using Public Key Cryptosystem

Abstract: In many recent years, the programming world has been introduced about a new programming language for designing websites, it is CSS that can be be used together with HTML to develop a web interface. And now, these two programming languages as if inseparably from each other. As a client-side scripting, CSS is visible by all users as the original script, but it can not be granted changed. Website is a tool of information disseminator throughout the world, this is certainly can be used to a secret communication by using CSS as a message hider. This paper proposed a new scheme using web tools like CSS for hiding informations. This is a secret communication mechanism using text steganography techniques that is embedded messages on CSS files and is further encrypted using RSA as a public key cryptographic algorithm.


Low Power Low Voltage Bulk Driven Balanced OTA

Abstract: The last few decades, a great deal of attention has been paid to low-voltage (LV) low-power (LP) integrated circuits design since the power consumption has become a critical issue. Among many techniques used for the design of LV LP analog circuits, the Bulk-driven principle offers a promising route towards this design for many aspects mainly the simplicity and using the conventional MOS technology to implement these designs. This paper is devoted to the Bulk-driven (BD) principle and utilizing this principle to design LV LP building block of Operational Transconductance Amplifier (OTA) in standard CMOS processes and supply voltage 0.9V. The simulation results have been carried out by the Spice simulator using the 130nm CMOS technology from TSMC.


Hybrid LS-LMMSE Channel Estimation Technique for LTE Downlink Systems

Abstract: In this paper, we propose to improve the performance of the channel estimation for LTE Downlink systems under the effect of the channel length. As LTE Downlink system is a MIMO-OFDMA based system, a cyclic prefix (CP) is inserted at the beginning of each transmitted OFDM symbol in order to mitigate both inter-carrier interference (ICI) and inter-symbol interference (ISI). The inserted CP is usually equal to or longer than the channel length. However, the cyclic prefix can be shorter because of some unforeseen channel behaviour. Previous works have shown that in the case where the cyclic prefix is equal to or longer than the channel length, LMMSE performs better than LSE but at the cost of computational complexity .In the other case, LMMSE performs also better than LS only for low SNR values. However, LS shows better performance for LTE Downlink systems for high SNR values. Therefore, we propose a hybrid LS-LMMSE channel estimation technique robust to the channel length effect. MATLAB Monte-Carlo simulations are used to evaluate the performance of the proposed estimator in terms of Mean Square Error (MSE) and Bit Error Rate (BER) for 2x2 LTE Downlink systems.


Order-Degree Curves for Hypergeometric Creative Telescoping

Abstract: Creative telescoping applied to a bivariate proper hypergeometric term produces linear recurrence operators with polynomial coefficients, called telescopers. We provide bounds for the degrees of the polynomials appearing in these operators. Our bounds are expressed as curves in the (r,d)-plane which assign to every order r a bound on the degree d of the telescopers. These curves are hyperbolas, which reflect the phenomenon that higher order telescopers tend to have lower degree, and vice versa.


Dynamic Scope-Based Dijkstra's Algorithm

Abstract: We briefly report on the current state of a new dynamic algorithm for the route planning problem based on a concept of scope (the static variant presented at ESA'11, HM2011A). We first motivate dynamization of the concept of scope admissibility, and then we briefly describe a modification of the scope-aware query algorithm of HM2011A to dynamic road networks. Finally, we outline our future work on this concept.


Optimal Fuzzy Model Construction with Statistical Information using Genetic Algorithm

Abstract: Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical information criteria such as the Akaike information criterion (AIC), the Bhansali-Downham information criterion (BDIC), and the Schwarz-Rissanen information criterion (SRIC) are used to construct optimal fuzzy models by reducing fuzzy rules. A genetic scheme is used to design Takagi-Sugeno-Kang (TSK) model for identification of the antecedent rule parameters and the identification of the consequent parameters. Computer simulations are presented confirming the performance of the constructed fuzzy logic controller.


Distributed Denial of Service (DDoS) Attacks Detection Mechanism

Abstract: Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the router's resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host.


Recognizing Bangla Grammar using Predictive Parser

Abstract: We describe a Context Free Grammar (CFG) for Bangla language and hence we propose a Bangla parser based on the grammar. Our approach is very much general to apply in Bangla Sentences and the method is well accepted for parsing a language of a grammar. The proposed parser is a predictive parser and we construct the parse table for recognizing Bangla grammar. Using the parse table we recognize syntactical mistakes of Bangla sentences when there is no entry for a terminal in the parse table. If a natural language can be successfully parsed then grammar checking from this language becomes possible. The proposed scheme is based on Top down parsing method and we have avoided the left recursion of the CFG using the idea of left factoring.


Improvement of Anomoly Detection Algorithms in Hyperspectral Images using Discrete Wavelet Transform

Abstract: Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images. In many applications, in addition to high accuracy of detection we need a fast and reliable algorithm as well. This paper presents a novel method to improve the performance of current AD algorithms. The proposed method first calculates Discrete Wavelet Transform (DWT) of every pixel vector of image using Daubechies4 wavelet. Then, AD algorithm performs on four bands of "Wavelet transform" matrix which are the approximation of main image. In this research some benchmark AD algorithms including Local RX, DWRX and DWEST have been implemented on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral datasets. Experimental results demonstrate significant improvement of runtime in proposed method. In addition, this method improves the accuracy of AD algorithms because of DWT's power in extracting approximation coefficients of signal, which contain the main behaviour of signal, and abandon the redundant information in hyperspectral image data.


General Methodology for developing UML models from UI

Abstract: In recent past every discipline and every industry have their own methods of developing products. It may be software development, mechanics, construction, psychology and so on. These demarcations work fine as long as the requirements are within one discipline. However, if the project extends over several disciplines, interfaces have to be created and coordinated between the methods of these disciplines. Performance is an important quality aspect of Web Services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In Industry, Prototype of these applications is developed during analysis phase of Software Development Life Cycle (SDLC). However, Performance models are generated from UML models. Methodologies for predicting the performance from UML models is available. Hence, In this paper, a methodology for developing Use Case model and Activity model from User Interface is presented. The methodology is illustrated with a case study on Amazon.com.


Early Performance Prediction of Web Services

Abstract: Web Service is an interface which implements business logic. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the performance of web services during early stages of software development is significant. In this paper we model web service using Unified Modeling Language, Use Case Diagram, Sequence Diagram, Deployment Diagram. We obtain the Performance metrics by simulating the web services model using a simulation tool Simulation of Multi-Tier Queuing Architecture. We have identified the bottle neck resources.


A New Full Adder Cell for Molecular Electronics

Abstract: Due to high power consumption and difficulties with minimizing the CMOS transistor size, molecular electronics has been introduced as an emerging technology. Further, there have been noticeable advances in fabrication of molecular wires and switches and also molecular diodes can be used for designing different logic circuits. Considering this novel technology, we use molecules as the active components of the circuit, for transporting electric charge. In this paper, a full adder cell based on molecular electronics is presented. This full adder is consisted of resonant tunneling diodes and transistors which are implemented via molecular electronics. The area occupied by this kind of full adder would be much times smaller than the conventional designs and it can be used as the building block of more complex molecular arithmetic circuits.


Adaptive Noise Reduction Scheme for Salt and Pepper

Abstract: In this paper, a new adaptive noise reduction scheme for images corrupted by impulse noise is presented. The proposed scheme efficiently identifies and reduces salt and pepper noise. MAG (Mean Absolute Gradient) is used to identify pixels which are most likely corrupted by salt and pepper noise that are candidates for further median based noise reduction processing. Directional filtering is then applied after noise reduction to achieve a good tradeoff between detail preservation and noise removal. The proposed scheme can remove salt and pepper noise with noise density as high as 90% and produce better result in terms of qualitative and quantitative measures of images.


Pbm: A new dataset for blog mining

Abstract: Text mining is becoming vital as Web 2.0 offers collaborative content creation and sharing. Now Researchers have growing interest in text mining methods for discovering knowledge. Text mining researchers come from variety of areas like: Natural Language Processing, Computational Linguistic, Machine Learning, and Statistics. A typical text mining application involves preprocessing of text, stemming and lemmatization, tagging and annotation, deriving knowledge patterns, evaluating and interpreting the results. There are numerous approaches for performing text mining tasks, like: clustering, categorization, sentimental analysis, and summarization. There is a growing need to standardize the evaluation of these tasks. One major component of establishing standardization is to provide standard datasets for these tasks. Although there are various standard datasets available for traditional text mining tasks, but there are very few and expensive datasets for blog-mining task. Blogs, a new genre in web 2.0 is a digital diary of web user, which has chronological entries and contains a lot of useful knowledge, thus offers a lot of challenges and opportunities for text mining. In this paper, we report a new indigenous dataset for Pakistani Political Blogosphere. The paper describes the process of data collection, organization, and standardization. We have used this dataset for carrying out various text mining tasks for blogosphere, like: blog-search, political sentiments analysis and tracking, identification of influential blogger, and clustering of the blog-posts. We wish to offer this dataset free for others who aspire to pursue further in this domain.


Reflection Scan: an Off-Path Attack on TCP

Abstract: The paper demonstrates how traffic load of a shared packet queue can be exploited as a side channel through which protected information leaks to an off-path attacker. The attacker sends to a victim a sequence of identical spoofed segments. The victim responds to each segment in the sequence (the sequence is reflected by the victim) if the segments satisfy a certain condition tested by the attacker. The responses do not reach the attacker directly, but induce extra load on a routing queue shared between the victim and the attacker. Increased processing time of packets traversing the queue reveal that the tested condition was true. The paper concentrates on the TCP, but the approach is generic and can be effective against other protocols that allow to construct requests which are conditionally answered by the victim. A proof of concept was created to assess applicability of the method in real-life scenarios.


Fostering continuous innovation in design with an integrated knowledge management approach

Abstract: In the global competition, companies are propelled by an immense pressure to innovate. The trend to produce more new knowledge-intensive products or services and the rapid progress of information technologies arouse huge interest on knowledge management for innovation. However the strategy of knowledge management is not widely adopted for innovation in industries due to a lack of an effective approach of their integration. This study aims to help the designers to innovate more efficiently based on an integrated approach of knowledge management. Based on this integrated approach, a prototype of distributed knowledge management system for innovation is developed. An industrial application is presented and its initial results indicate the applicability of the approach and the prototype in practice.


Sentence based semantic similarity measure for blog-posts

Abstract: Blogs-Online digital diary like application on web 2.0 has opened new and easy way to voice opinion, thoughts, and like-dislike of every Internet user to the World. Blogosphere has no doubt the largest user-generated content repository full of knowledge. The potential of this knowledge is still to be explored. Knowledge discovery from this new genre is quite difficult and challenging as it is totally different from other popular genre of web-applications like World Wide Web (WWW). Blog-posts unlike web documents are small in size, thus lack in context and contain relaxed grammatical structures. Hence, standard text similarity measure fails to provide good results. In this paper, specialized requirements for comparing a pair of blog-posts is thoroughly investigated. Based on this we proposed a novel algorithm for sentence oriented semantic similarity measure of a pair of blog-posts. We applied this algorithm on a subset of political blogosphere of Pakistan, to cluster the blogs on different issues of political realm and to identify the influential bloggers.


Partial Searchlight Scheduling is Strongly PSPACE-Complete

Abstract: The problem of searching a polygonal region for an unpredictably moving intruder by a set of stationary guards, each carrying an orientable laser, is known as the Searchlight Scheduling Problem. Determining the computational complexity of deciding if the polygon can be searched by a given set of guards is a long-standing open problem. Here we propose a generalization called the Partial Searchlight Scheduling Problem, in which only a given subregion of the environment has to be searched, as opposed to the entire area. We prove that the corresponding decision problem is strongly PSPACE-complete, both in general and restricted to orthogonal polygons where the region to be searched is a rectangle. Our technique is to reduce from the "edge-to-edge" problem for nondeterministic constraint logic machines, after showing that the computational power of such machines does not change if we allow "asynchronous" edge reversals (as opposed to "sequential").


Biologically inspired design framework for Robot in Dynamic Environments using Framsticks

Abstract: Robot design complexity is increasing day by day especially in automated industries. In this paper we propose biologically inspired design framework for robots in dynamic world on the basis of Co-Evolution, Virtual Ecology, Life time learning which are derived from biological creatures. We have created a virtual khepera robot in Framsticks and tested its operational credibility in terms hardware and software components by applying the above suggested techniques. Monitoring complex and non complex behaviors in different environments and obtaining the parameters that influence software and hardware design of the robot that influence anticipated and unanticipated failures, control programs of robot generation are the major concerns of our techniques.


Mobile node localization in cellular networks

Abstract: Location information is the major component in location based applications. This information is used in different safety and service oriented applications to provide users with services according to their Geolocation. There are many approaches to locate mobile nodes in indoor and outdoor environments. In this paper, we are interested in outdoor localization particularly in cellular networks of mobile nodes and presented a localization method based on cell and user location information. Our localization method is based on hello message delay (sending and receiving time) and coordinate information of Base Transceiver Station (BTSs). To validate our method across cellular network, we implemented and simulated our method in two scenarios i.e. maintaining database of base stations in centralize and distributed system. Simulation results show the effectiveness of our approach and its implementation applicability in telecommunication systems.


An Active Defense Mechanism for TCP SYN flooding attacks

Abstract: Distributed denial-of-service attacks on public servers have recently become a serious problem. To assure that network services will not be interrupted and more effective defense mechanisms to protect against malicious traffic, especially SYN floods. One problem in detecting SYN flood traffic is that server nodes or firewalls cannot distinguish the SYN packets of normal TCP connections from those of a SYN flood attack. Another problem is single-point defenses (e.g. firewalls) lack the scalability needed to handle an increase in the attack traffic. We have designed a new defense mechanism to detect the SYN flood attacks. First, we introduce a mechanism for detecting SYN flood traffic more accurately by taking into consideration the time variation of arrival traffic. We investigate the statistics regarding the arrival rates of both normal TCP SYN packets and SYN flood attack packets. We then describe a new detection mechanism based on these statistics. Through the trace driven approach defense nodes which receive the alert messages can identify legitimate traffic and block malicious traffic by delegating SYN/ACK packets.


Design and ASIC implementation of DUC/DDC for communication systems

Abstract: Communication systems use the concept of transmitting information using the electrical distribution network as a communication channel. To enable the transmission data signal modulated on a carrier signal is superimposed on the electrical wires. Typical power lines are designed to handle 50/60 Hz of AC power signal; however they can carry the signals up to 500 KHz frequency. This work aims to aid transmission/reception of an audio signal in the spectrum from 300 Hz to 4000 Hz using PLCC on a tunable carrier frequency in the spectrum from 200 KHz to 500 KHz. For digital amplitude modulation the sampling rate of the carrier and the audio signal has to be matched. Tunable carrier generation can be achieved with Direct Digital Synthesizers at a desired sampling rate. DSP Sample rate conversion techniques are very useful to make the sampling circuits to work on their own sampling rates which are fine for the data/modulated-carrier signal's bandwidth. This also simplifies the complexity of the sampling circuits. Digital Up Conversion (DUC) and Digital Down Conversion (DDC) are DSP sample rate conversion techniques which refer to increasing and decreasing the sampling rate of a signal respectively.


A Massive Data Parallel Computational Framework for Petascale/Exascale Hybrid Computer Systems

Abstract: Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA and OpenCL it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include Merge (a library based framework for heterogeneous multi-core systems), Zippy (a framework for parallel execution of codes on multiple GPUs), BSGP (a new programming language for general purpose computation on the GPU) and CUDA-lite (an enhancement to CUDA that transforms code based on annotations). In addition, efforts are underway to improve compiler tools for automatic parallelization and optimization of affine loop nests for GPUs and for automatic translation of OpenMP parallelized codes to CUDA. In this paper we present an alternative approach: a new computational framework for the development of massively data parallel scientific codes applications suitable for use on such petascale/exascale hybrid systems built upon the highly scalable Cactus framework. As the first non-trivial demonstration of its usefulness, we successfully developed a new 3D CFD code that achieves improved performance.


Purging of untrustworthy recommendations from a grid

Abstract: In grid computing, trust has massive significance. There is lot of research to propose various models in providing trusted resource sharing mechanisms. The trust is a belief or perception that various researchers have tried to correlate with some computational model. Trust on any entity can be direct or indirect. Direct trust is the impact of either first impression over the entity or acquired during some direct interaction. Indirect trust is the trust may be due to either reputation gained or recommendations received from various recommenders of a particular domain in a grid or any other domain outside that grid or outside that grid itself. Unfortunately, malicious indirect trust leads to the misuse of valuable resources of the grid. This paper proposes the mechanism of identifying and purging the untrustworthy recommendations in the grid environment. Through the obtained results, we show the way of purging of untrustworthy entities.


Automatic Detection of Diabetes Diagnosis using Feature Weighted Support Vector Machines based on Mutual Information and Modified Cuckoo Search

Abstract: Diabetes is a major health problem in both developing and developed countries and its incidence is rising dramatically. In this study, we investigate a novel automatic approach to diagnose Diabetes disease based on Feature Weighted Support Vector Machines (FW-SVMs) and Modified Cuckoo Search (MCS). The proposed model consists of three stages: Firstly, PCA is applied to select an optimal subset of features out of set of all the features. Secondly, Mutual Information is employed to construct the FWSVM by weighting different features based on their degree of importance. Finally, since parameter selection plays a vital role in classification accuracy of SVMs, MCS is applied to select the best parameter values. The proposed MI-MCS-FWSVM method obtains 93.58% accuracy on UCI dataset. The experimental results demonstrate that our method outperforms the previous methods by not only giving more accurate results but also significantly speeding up the classification procedure.


Multi-sensor Information Processing using Prediction Market-based Belief Aggregation

Abstract: We consider the problem of information fusion from multiple sensors of different types with the objective of improving the confidence of inference tasks, such as object classification, performed from the data collected by the sensors. We propose a novel technique based on distributed belief aggregation using a multi-agent prediction market to solve this information fusion problem. To monitor the improvement in the confidence of the object classification as well as to dis-incentivize agents from misreporting information, we have introduced a market maker that rewards the agents instantaneously as well as at the end of the inference task, based on the quality of the submitted reports. We have implemented the market maker's reward calculation in the form of a scoring rule and have shown analytically that it incentivizes truthful revelation or accurate reporting by each agent. We have experimentally verified our technique for multi-sensor information fusion for an automated landmine detection scenario. Our experimental results show that, for identical data distributions and settings, using our information aggregation technique increases the accuracy of object classification favorably as compared to two other commonly used techniques for information fusion for landmine detection.


A simulation model for the lifetime of wireless sensor networks

Abstract: In this paper we present a model for the lifetime of wireless sensor networks. The model takes into consideration several parameters such as the total number of sensors, network size, percentage of sink nodes, location of sensors, the mobility of sensors, and power consumption. A definition of the life time of the network based on three different criteria is introduced; percentage of available power to total power, percentage of alive sensors to total sensors, and percentage of alive sink sensors to total sink sensors. A Matlab based simulator is developed for the introduced model. A number of wireless sensor networks scenarios are presented and discussed.


Bengali text summarization by sentence extraction

Abstract: Text summarization is a process to produce an abstract or a summary by selecting significant portion of the information from one or more texts. In an automatic text summarization process, a text is given to the computer and the computer returns a shorter less redundant extract or abstract of the original text(s). Many techniques have been developed for summarizing English text(s). But, a very few attempts have been made for Bengali text summarization. This paper presents a method for Bengali text summarization which extracts important sentences from a Bengali document to produce a summary.