Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective

Abstract: This paper studies the optimal investment and pricing decisions of a cognitive mobile virtual network operator (C-MVNO) under spectrum supply uncertainty. Compared with a traditional MVNO who often leases spectrum via long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by both sensing the empty "spectrum holes" of licensed bands and dynamically leasing from the spectrum owner. As a result, a C-MVNO can make flexible investment and pricing decisions to match the current demands of the secondary unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is typically cheaper, but the obtained useful spectrum amount is random due to primary licensed users' stochastic traffic. The C-MVNO needs to determine the optimal amounts of spectrum sensing and leasing by evaluating the trade off between cost and uncertainty. The C-MVNO also needs to determine the optimal price to sell the spectrum to the secondary unlicensed users, taking into account wireless heterogeneity of users such as different maximum transmission power levels and channel gains. We model and analyze the interactions between the C-MVNO and secondary unlicensed users as a Stackelberg game. We show several interesting properties of the network equilibrium, including threshold structures of the optimal investment and pricing decisions, the independence of the optimal price on users' wireless characteristics, and guaranteed fair and predictable QoS among users. We prove that these properties hold for general SNR regime and general continuous distributions of sensing uncertainty. We show that spectrum sensing can significantly improve the C-MVNO's expected profit and users' payoffs.


Geometric and Combinatorial Properties of Well-Centered Triangulations in Three and Higher Dimensions

Abstract: An n-simplex is said to be n-well-centered if its circumcenter lies in its interior. We introduce several other geometric conditions and an algebraic condition that can be used to determine whether a simplex is n-well-centered. These conditions, together with some other observations, are used to describe restrictions on the local combinatorial structure of simplicial meshes in which every simplex is well-centered. In particular, it is shown that in a 3-well-centered (2-well-centered) tetrahedral mesh there are at least 7 (9) edges incident to each interior vertex, and these bounds are sharp. Moreover, it is shown that, in stark contrast to the 2-dimensional analog, where there are exactly two vertex links that prevent a well-centered triangle mesh in R^2, there are infinitely many vertex links that prohibit a well-centered tetrahedral mesh in R^3.


Complexity of Propositional Abduction for Restricted Sets of Boolean Functions

Abstract: Abduction is a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining how the world behaves it aims at finding an explanation for some observed manifestation. In this paper we focus on propositional abduction, where the knowledge base and the manifestation are represented by propositional formulae. The problem of deciding whether there exists an explanation has been shown to be SigmaP2-complete in general. We consider variants obtained by restricting the allowed connectives in the formulae to certain sets of Boolean functions. We give a complete classification of the complexity for all considerable sets of Boolean functions. In this way, we identify easier cases, namely NP-complete and polynomial cases; and we highlight sources of intractability. Further, we address the problem of counting the explanations and draw a complete picture for the counting complexity.


Derandomizing from Random Strings

Abstract: In this paper we show that BPP is truth-table reducible to the set of Kolmogorov random strings R_K. It was previously known that PSPACE, and hence BPP is Turing-reducible to R_K. The earlier proof relied on the adaptivity of the Turing-reduction to find a Kolmogorov-random string of polynomial length using the set R_K as oracle. Our new non-adaptive result relies on a new fundamental fact about the set R_K, namely each initial segment of the characteristic sequence of R_K is not compressible by recursive means. As a partial converse to our claim we show that strings of high Kolmogorov-complexity when used as advice are not much more useful than randomly chosen strings.


Robust Fault Tolerant uncapacitated facility location

Abstract: In the uncapacitated facility location problem, given a graph, a set of demands and opening costs, it is required to find a set of facilities R, so as to minimize the sum of the cost of opening the facilities in R and the cost of assigning all node demands to open facilities. This paper concerns the robust fault-tolerant version of the uncapacitated facility location problem (RFTFL). In this problem, one or more facilities might fail, and each demand should be supplied by the closest open facility that did not fail. It is required to find a set of facilities R, so as to minimize the sum of the cost of opening the facilities in R and the cost of assigning all node demands to open facilities that did not fail, after the failure of up to \alpha facilities. We present a polynomial time algorithm that yields a 6.5-approximation for this problem with at most one failure and a 1.5 + 7.5\alpha-approximation for the problem with at most \alpha > 1 failures. We also show that the RFTFL problem is NP-hard even on trees, and even in the case of a single failure.


On Backtracking in Real-time Heuristic Search

Abstract: Real-time heuristic search algorithms are suitable for situated agents that need to make their decisions in constant time. Since the original work by Korf nearly two decades ago, numerous extensions have been suggested. One of the most intriguing extensions is the idea of backtracking wherein the agent decides to return to a previously visited state as opposed to moving forward greedily. This idea has been empirically shown to have a significant impact on various performance measures. The studies have been carried out in particular empirical testbeds with specific real-time search algorithms that use backtracking. Consequently, the extent to which the trends observed are characteristic of backtracking in general is unclear. In this paper, we present the first entirely theoretical study of backtracking in real-time heuristic search. In particular, we present upper bounds on the solution cost exponential and linear in a parameter regulating the amount of backtracking. The results hold for a wide class of real-time heuristic search algorithms that includes many existing algorithms as a small subclass.


A Formal Framework for Mobile Robot Patrolling in Arbitrary Environments with Adversaries

Abstract: Using mobile robots for autonomous patrolling of environments to prevent intrusions is a topic of increasing practical relevance. One of the most challenging scientific issues is the problem of finding effective patrolling strategies that, at each time point, determine the next moves of the patrollers in order to maximize some objective function. In the very last years this problem has been addressed in a game theoretical fashion, explicitly considering the presence of an adversarial intruder. The general idea is that of modeling a patrolling situation as a game, played by the patrollers and the intruder, and of studying the equilibria of this game to derive effective patrolling strategies. In this paper we present a game theoretical formal framework for the determination of effective patrolling strategies that extends the previous proposals appeared in the literature, by considering environments with arbitrary topology and arbitrary preferences for the agents. The main original contributions of this paper are the formulation of the patrolling game for generic graph environments, an algorithm for finding a deterministic equilibrium strategy, which is a fixed path through the vertices of the graph, and an algorithm for finding a non-deterministic equilibrium strategy, which is a set of probabilities for moving between adjacent vertices of the graph. Both the algorithms are analytically studied and experimentally validated, to assess their properties and efficiency.


New Generalization Bounds for Learning Kernels

Abstract: This paper presents several novel generalization bounds for the problem of learning kernels based on the analysis of the Rademacher complexity of the corresponding hypothesis sets. Our bound for learning kernels with a convex combination of p base kernels has only a log(p) dependency on the number of kernels, p, which is considerably more favorable than the previous best bound given for the same problem. We also give a novel bound for learning with a linear combination of p base kernels with an L_2 regularization whose dependency on p is only in p^{1/4}.


Frugal and Truthful Auctions for Vertex Covers, Flows, and Cuts

Abstract: We study truthful mechanisms for hiring a team of agents in three classes of set systems: Vertex Cover auctions, k-flow auctions, and cut auctions. For Vertex Cover auctions, the vertices are owned by selfish and rational agents, and the auctioneer wants to purchase a vertex cover from them. For k-flow auctions, the edges are owned by the agents, and the auctioneer wants to purchase k edge-disjoint s-t paths, for given s and t. In the same setting, for cut auctions, the auctioneer wants to purchase an s-t cut. Only the agents know their costs, and the auctioneer needs to select a feasible set and payments based on bids made by the agents. We present constant-competitive truthful mechanisms for all three set systems. That is, the maximum overpayment of the mechanism is within a constant factor of the maximum overpayment of any truthful mechanism, for every set system in the class. The mechanism for Vertex Cover is based on scaling each bid by a multiplier derived from the dominant eigenvector of a certain matrix. The mechanism for k-flows prunes the graph to be minimally (k+1)-connected, and then applies the Vertex Cover mechanism. Similarly, the mechanism for cuts contracts the graph until all s-t paths have length exactly 2, and then applies the Vertex Cover mechanism.


NetEvo: A computational framework for the evolution of dynamical complex networks

Abstract: NetEvo is a computational framework designed to help understand the evolution of dynamical complex networks. It provides flexible tools for the simulation of dynamical processes on networks and methods for the evolution of underlying topological structures. The concept of a supervisor is used to bring together both these aspects in a coherent way. It is the job of the supervisor to rewire the network topology and alter model parameters such that a user specified performance measure is minimised. This performance measure can make use of current topological information and simulated dynamical output from the system. Such an abstraction provides a suitable basis in which to study many outstanding questions related to complex system design and evolution.


Frugal Mechanism Design via Spectral Techniques

Abstract: We study the design of truthful mechanisms for set systems, i.e., scenarios where a customer needs to hire a team of agents to perform a complex task. In this setting, frugality [Archer&Tardos'02] provides a measure to evaluate the "cost of truthfulness", that is, the overpayment of a truthful mechanism relative to the "fair" payment. We propose a uniform scheme for designing frugal truthful mechanisms for general set systems. Our scheme is based on scaling the agents' bids using the eigenvector of a matrix that encodes the interdependencies between the agents. We demonstrate that the r-out-of-k-system mechanism and the \sqrt-mechanism for buying a path in a graph [Karlin et. al'05] can be viewed as instantiations of our scheme. We then apply our scheme to two other classes of set systems, namely, vertex cover systems and k-path systems, in which a customer needs to purchase k edge-disjoint source-sink paths. For both settings, we bound the frugality of our mechanism in terms of the largest eigenvalue of the respective interdependency matrix. We show that our mechanism is optimal for a large subclass of vertex cover systems satisfying a simple local sparsity condition. For k-path systems, while our mechanism is within a factor of k + 1 from optimal, we show that it is, in fact, optimal, when one uses a modified definition of frugality proposed in [Elkind et al.'07]. Our lower bound argument combines spectral techniques and Young's inequality, and is applicable to all set systems. As both r-out-of-k systems and single path systems can be viewed as special cases of k-path systems, our result improves the lower bounds of [Karlin et al.'05] and answers several open questions proposed in that paper.


Decidability of the interval temporal logic ABBar over the natural numbers

Abstract: In this paper, we focus our attention on the interval temporal logic of the Allen's relations "meets", "begins", and "begun by" (ABBar for short), interpreted over natural numbers. We first introduce the logic and we show that it is expressive enough to model distinctive interval properties,such as accomplishment conditions, to capture basic modalities of point-based temporal logic, such as the until operator, and to encode relevant metric constraints. Then, we prove that the satisfiability problem for ABBar over natural numbers is decidable by providing a small model theorem based on an original contraction method. Finally, we prove the EXPSPACE-completeness of the problem


A simple and efficient explicit parallelization of logic programs using low-level threading primitives

Abstract: In this work, we present an automatic way to parallelize logic programs for finding all the answers to queries using a transformation to low level threading primitives. Although much work has been done in parallelization of logic programming more than a decade ago (e.g., Aurora, Muse, YapOR), the current state of parallelizing logic programs is still very poor. This work presents a way for parallelism of tabled logic programs in XSB Prolog under the well founded semantics. An important contribution of this work relies in merging answer-tables from multiple children threads without incurring copying or full-sharing and synchronization of data-structures. The implementation of the parent-children shared answer-tables surpasses in efficiency all the other data-structures currently implemented for completion of answers in parallelization using multi-threading. The transformation and its lower-level answer merging predicates were implemented as an extension to the XSB system.


A Metamodel of Unit Testing for Object-Oriented Programming Languages

Abstract: A unit test is a method for verifying the accuracy and the proper functioning of a portion of a program. This work consists to study the relation and the approaches to test Object-Oriented Programming (OOP) programs and to propose a metamodel that enables the programmer to write the tests while writing the source code to be tested by exploiting the key features of OOP programming languages such as inheritance, polymorphism, etc.


Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation

Abstract: Finding the three-dimensional representation of all or a part of a scene from a single two dimensional image is a challenging task. In this paper we propose a method for identifying the pose and location of objects with circular protrusions in three dimensions from a single image and a 3d representation or model of the object of interest. To do this, we present a method for identifying ellipses and their properties quickly and reliably with a novel technique that exploits intensity differences between objects and a geometric technique for matching an ellipse in 2d to a circle in 3d. We apply these techniques to the specific problem of determining the pose and location of vehicles, particularly cars, from a single image. We have achieved excellent pose recovery performance on artificially generated car images and show promising results on real vehicle images. We also make use of the ellipse detection method to identify car wheels from images, with a very high successful match rate.


New Learning and Testing Problems for Read-Once Functions

Abstract: In the paper, we consider several types of queries for classical and new problems of learning and testing read-once functions. In several cases, the border between polynomial and exponential complexities is obtained.


On the circuit-size of inverses

Abstract: We reprove a result of Boppana and Lagarias: If Pi_2^P is different from Sigma_2^P then there exists a partial function f that is computable by a polynomial-size family of circuits, but no inverse of f is computable by a polynomial-size family of circuits. We strengthen this result by showing that there exist length-preserving total functions that are one-way by circuit size and that are computable in uniform polynomial time. We also prove, if Pi_2^P is different from Sigma_2^P, that there exist polynomially balanced total surjective functions that are one-way by circuit size; here non-uniformity is used.


A Survey of Paraphrasing and Textual Entailment Methods

Abstract: Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.


The complexity of the list homomorphism problem for graphs

Abstract: We completely classify the computational complexity of the list H-colouring problem for graphs (with possible loops) in combinatorial and algebraic terms: for every graph H the problem is either NP-complete, NL-complete, L-complete or is first-order definable; descriptive complexity equivalents are given as well via Datalog and its fragments. Our algebraic characterisations match important conjectures in the study of constraint satisfaction problems.


On uniform sampling simple directed graph realizations of degree sequences

Abstract: Choosing a uniformly sampled simple directed graph realization of a degree sequence has many applications, in particular in social networks where self-loops are commonly not allowed. It has been shown in the past that one can perform a Markov chain arc-switching algorithm to sample a simple directed graph uniformly by performing two types of switches: a 2-switch and a directed 3-cycle reorientation. This paper discusses under what circumstances a directed 3-cycle reorientation is required. In particular, the class of degree sequences where this is required is a subclass of the directed 3-cycle anchored degree sequences. An important implication of this result is a reduced Markov chain algorithm that uses only 2-switches.


Sharp utilization thresholds for some real-time scheduling problems

Abstract: Scheduling policies for real-time systems exhibit threshold behavior that is related to the utilization of the task set they schedule, and in some cases this threshold is sharp. For the rate monotonic scheduling policy, we show that periodic workload with utilization less than a threshold $U_{RM}^{*}$ can be scheduled almost surely and that all workload with utilization greater than $U_{RM}^{*}$ is almost surely not schedulable. We study such sharp threshold behavior in the context of processor scheduling using static task priorities, not only for periodic real-time tasks but for aperiodic real-time tasks as well. The notion of a utilization threshold provides a simple schedulability test for most real-time applications. These results improve our understanding of scheduling policies and provide an interesting characterization of the typical behavior of policies. The threshold is sharp (small deviations around the threshold cause schedulability, as a property, to appear or disappear) for most policies; this is a happy consequence that can be used to address the limitations of existing utilization-based tests for schedulability. We demonstrate the use of such an approach for balancing power consumption with the need to meet deadlines in web servers.


Designing ISP-friendly Peer-to-Peer Networks Using Game-based Control

Abstract: The rapid growth of peer-to-peer (P2P) networks in the past few years has brought with it increases in transit cost to Internet Service Providers (ISPs), as peers exchange large amounts of traffic across ISP boundaries. This ISP oblivious behavior has resulted in misalignment of incentives between P2P networks--that seek to maximize user quality--and ISPs--that would seek to minimize costs. Can we design a P2P overlay that accounts for both ISP costs as well as quality of service, and attains a desired tradeoff between the two? We design a system, which we call MultiTrack, that consists of an overlay of multiple \emph{mTrackers} whose purpose is to align these goals. mTrackers split demand from users among different ISP domains while trying to minimize their individual costs (delay plus transit cost) in their ISP domain. We design the signals in this overlay of mTrackers in such a way that potentially competitive individual optimization goals are aligned across the mTrackers. The mTrackers are also capable of doing admission control in order to ensure that users who are from different ISP domains have a fair chance of being admitted into the system, while keeping costs in check. We prove analytically that our system is stable and achieves maximum utility with minimum cost. Our design decisions and control algorithms are validated by Matlab and ns-2 simulations.


Optimism in Games with Non-Probabilistic Uncertainty

Abstract: The paper studies one-shot two-player games with non-Bayesian uncertainty. The players have an attitude that ranges from optimism to pessimism in the face of uncertainty. Given the attitudes, each player forms a belief about the set of possible strategies of the other player. If these beliefs are consistent, one says that they form an uncertainty equilibrium. One then considers a two-phase game where the players first choose their attitude and then play the resulting game. The paper illustrates these notions with a number of games where the approach provides a new insight into the plausible strategies of the players.


Speech Recognition Oriented Vowel Classification Using Temporal Radial Basis Functions

Abstract: The recent resurgence of interest in spatio-temporal neural network as speech recognition tool motivates the present investigation. In this paper an approach was developed based on temporal radial basis function "TRBF" looking to many advantages: few parameters, speed convergence and time invariance. This application aims to identify vowels taken from natural speech samples from the Timit corpus of American speech. We report a recognition accuracy of 98.06 percent in training and 90.13 in test on a subset of 6 vowel phonemes, with the possibility to expend the vowel sets in future.


E-commerce between a large firm and a SME supplier: a screening model

Abstract: This paper derives a model of screening contracts in the presence of positive network effects when building an electronic commerce network (e-commerce) between a large firm and a small and medium sized enterprise (SME) supplier based on Compte (2008). Compte (2008) main insight is that when several potential candidates compete for the task, the principal will in general improve the performance of his firm by inducing the member candidates to assess their competence before signing the contract (through an appropriate choice of contracts). The large firm (principal) must choose between different SME suppliers (agents) to build a business to business e-commerce network. In the presence of positive network externalities, we show that social surplus increases.


Design of an Automated Intrusion Detection System incorporating an Alarm

Abstract: Security and safety are two intertwined terms. It is a common belief that when a place or system is secure, it is safe. This paper shows a means of integrating three devices for physical intrusion detection. This paper thus suggests a means of increasing the level of security in an enclosed area with the use three of the four security layers necessary for optimum security. This paper intends to show that a system with more than one security device in place tends to prevent unauthorized access. This paper would be illustrating the implementation of this in an enclosed area whose security level must be kept on the high at all times.


Alternate methods of evaluation for web sites concordant to IAS/IFRS Standards

Abstract: This work has as the principal theme, the study, analysis and implementation of the methodology for use the web sites in e-commerce. The authors try to deal with particular methodological and applied aspects inherent in the analysis of data from the interaction of man-Internet (Web-mining). The research methodology of this work will be focused on a prevalent optic multidisciplinary research based on the pillars of data mining and Web mining. The explosion of Internet and electronic commerce has made the most of business to have its own website. A company may engage internal costs for the development and operation of their website. The website can be designed for internal access (in which case it can be used for presentation and data storage company policies with references of customers) or for external access (they are created and used for promotional and advertising products and services company). The objective of this research, primarily concerns the definition of a repertoire of tools in analyzing e-business through the development process for web-usage mining; 2nd objective is oriented to management, recognizing and evaluating the web-sites in accountancy, as property intangible, which is a special case and very little studied in economic literature financial specialty, the authors try to achieve a national and international accounting treatment of the creation and development of web-sites.


Secure Watermarking Scheme for Color Image Using Intensity of Pixel and LSB Substitution

Abstract: In this paper a novel spatial domain LSB based watermarking scheme for color Images is proposed. The proposed scheme is of type blind and invisible watermarking. Our scheme introduces the concept of storing variable number of bits in each pixel based on the actual color value of pixel. Equal or higher the color value of channels with respect to intensity of pixel stores higher number of watermark bits. The Red, Green and Blue channel of the color image has been used for watermark embedding. The watermark is embedded into selected channels of pixel. The proposed method supports high watermark embedding capacity, which is equivalent to the size of cover image. The security of watermark is preserved by permuting the watermark bits using secret key. The proposed scheme is found robust to various image processing operations such as image compression, blurring, salt and pepper noise, filtering and cropping.


A Study on Feature Selection Techniques in Educational Data Mining

Abstract: Educational data mining (EDM) is a new growing research area and the essence of data mining concepts are used in the educational field for the purpose of extracting useful information on the behaviors of students in the learning process. In this EDM, feature selection is to be made for the generation of subset of candidate variables. As the feature selection influences the predictive accuracy of any performance model, it is essential to study elaborately the effectiveness of student performance model in connection with feature selection techniques. In this connection, the present study is devoted not only to investigate the most relevant subset features with minimum cardinality for achieving high predictive performance by adopting various filtered feature selection techniques in data mining but also to evaluate the goodness of subsets with different cardinalities and the quality of six filtered feature selection algorithms in terms of F-measure value and Receiver Operating Characteristics (ROC) value, generated by the NaiveBayes algorithm as base-line classifier method. The comparative study carried out by us on six filter feature section algorithms reveals the best method, as well as optimal dimensionality of the feature subset. Benchmarking of filter feature selection method is subsequently carried out by deploying different classifier models. The result of the present study effectively supports the well known fact of increase in the predictive accuracy with the existence of minimum number of features. The expected outcomes show a reduction in computational time and constructional cost in both training and classification phases of the student performance model.


A Simplified Proof For The Application Of Freivalds' Technique to Verify Matrix Multiplication

Abstract: Fingerprinting is a well known technique, which is often used in designing Monte Carlo algorithms for verifying identities involving ma- trices, integers and polynomials. The book by Motwani and Raghavan [1] shows how this technique can be applied to check the correctness of matrix multiplication -- check if AB = C where A, B and C are three nxn matrices. The result is a Monte Carlo algorithm running in time $Theta(n^2)$ with an exponentially decreasing error probability after each indepen- dent iteration. In this paper we give a simple alternate proof addressing the same problem. We also give further generalizations and relax various assumptions made in the proof.


Application of Radial Basis Network Model for HIV/AIDs Regimen Specifications

Abstract: HIV/AIDs Regimen specification one of many problems for which bioinformaticians have implemented and trained machine learning methods such as neural networks. Predicting HIV resistance would be much easier, but unfortunately we rarely have enough structural information available to train a neural network. To network model designed to predict how long the HIV patient can prolong his/her life time with certain regimen specification. To learn this model 300 patient's details have taken as a training set to train the network and 100 patients medical history has taken to test this model. This network model is trained using MAT lab implementation.


Logarithmic Barrier Optimization Problem Using Neural Network

Abstract: The combinatorial optimization problem is one of the important applications in neural network computation. The solutions of linearly constrained continuous optimization problems are difficult with an exact algorithm, but the algorithm for the solution of such problems is derived by using logarithm barrier function. In this paper we have made an attempt to solve the linear constrained optimization problem by using general logarithm barrier function to get an approximate solution. In this case the barrier parameters behave as temperature decreasing to zero from sufficiently large positive number satisfying convexity of the barrier function. We have developed an algorithm to generate decreasing sequence of solution converging to zero limit.


Studies on access: a review

Abstract: A review of the empirical literature on access to scholarly information. This review focuses on surveys of authors, article download and citation analysis.


Using Design Sketch to Teach Bubble Sort in High School

Abstract: Bubble Sort is simple. Yet, it seems a bit difficult for high school students. This paper presents a pedagogical methodology: Using Design Sketch to visualize the concepts in Bubble Sort, and to evaluate how this approach assists students to understand the pseudo code of Bubble Sort. An experiment is conducted in Wu-Ling Senior High School with 250 students taking part. The statistical analysis of experimental results shows that, for relatively high abstraction concepts, such as iteration number, Design Sketch helps significantly. However, it is not so for low abstraction concepts such as compare, swap, and iteration.


Modeling and Application of Series Elastic Actuators for Force Control Multi Legged Robots

Abstract: Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic Actuators employ a novel mechanical design architecture which goes against the common machine design principal of "stiffer is better". A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke's Law (F=Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions. We describe several variations of Series Elastic Actuators that have been developed using both electric and hydraulic components.


Realization of Semantic Atom Blog

Abstract: Web blog is used as a collaborative platform to publish and share information. The information accumulated in the blog intrinsically contains the knowledge. The knowledge shared by the community of people has intangible value proposition. The blog is viewed as a multimedia information resource available on the Internet. In a blog, information in the form of text, image, audio and video builds up exponentially. The multimedia information contained in an Atom blog does not have the capability, which is required by the software processes so that Atom blog content can be accessed, processed and reused over the Internet. This shortcoming is addressed by exploring OWL knowledge modeling, semantic annotation and semantic categorization techniques in an Atom blog sphere. By adopting these techniques, futuristic Atom blogs can be created and deployed over the Internet.


Web Based Cross Language Plagiarism Detection

Abstract: As the Internet help us cross language and cultural border by providing different types of translation tools, cross language plagiarism, also known as translation plagiarism are bound to arise. Especially among the academic works, such issue will definitely affect the student's works including the quality of their assignments and paper works. In this paper, we propose a new approach in detecting cross language plagiarism. Our web based cross language plagiarism detection system is specially tuned to detect translation plagiarism by implementing different techniques and tools to assist the detection process. Google Translate API is used as our translation tool and Google Search API, which is used in our information retrieval process. Our system is also integrated with the fingerprint matching technique, which is a widely used plagiarism detection technique. In general, our proposed system is started by translating the input documents from Malay to English, followed by removal of stop words and stemming words, identification of similar documents in corpus, comparison of similar pattern and finally summary of the result. Three least-frequent 4-grams fingerprint matching is used to implement the core comparison phase during the plagiarism detection process. In K-gram fingerprint matching technique, although any value of K can be considered, yet K = 4 was stated as an ideal choice. This is because smaller values of K (i.e., K = 1, 2, or 3), do not provide good discrimination between sentences. On the other hand, the larger the values of K (i.e., K = 5, 6, 7...etc), the better discrimination of words in one sentence from words in another.


Optimal Design of Fuzzy Based Power System Stabilizer Self Tuned by Robust Search Algorithm

Abstract: In the interconnected power system network, instability problems are caused mainly by the low frequency oscillations of 0.2 to 2.5 Hz. The supplementary control signal in addition with AVR and high gain excitation systems are provided by means of Power System Stabilizer (PSS). Conventional power system stabilizers provide effective damping only on a particular operating point. But fuzzy based PSS provides good damping for a wide range of operating points. The bottlenecks faced in designing a fuzzy logic controller can be minimized by using appropriate optimization techniques like Genetic Algorithm, Particle Swam Optimization, Ant Colony Optimization etc.In this paper the membership functions of FLC are optimized by the new breed optimization technique called Genetic Algorithm. This design methodology is implemented on a Single Machine Infinite Bus (SMIB) system. Simulation results on SMIB show the effectiveness and robustness of the proposed PSS over a wide range of operating conditions and system configurations.


Enhancing Multi-Agent Based Simulation with Human-Agents Interactive Spatial Behaviour

Abstract: We are exploring the enhancement of models of agent behaviour with more "human-like" decision making strategies than are presently available. Our motivation is to developed with a view to as the decision analysis and support for electric taxi company under the mission of energy saving and reduction of CO2, in particular car-pool and car-sharing management policies. In order to achieve the object of decision analysis for user, we provide a human-agents interactive spatial behaviour to support user making decision real time. We adopt passenger average waiting time and electric taxi average idle time as the performance measures and decision support fro electric taxi company. Finally, according to the analysis result, we demonstrate that our multi-agent simulation and GUI can help users or companies quickly make a quality and accurate decision to reduce the decision-making cost and time.


Speed Control of Multi Level Inverter Designed DC Series Motor with Neuro-Fuzzy Controllers

Abstract: This paper describes the speed control of a DC series motor for an accurate and high-speed performance. A neural network based controlling operation with fuzzy modeling is suggested in this paper. The driver units of these machines are designed with a Multi-level inverter operation and are controlled by a common current control mechanism for an accurate and efficient driving technique for DC series motor. The neuro-fuzzy logic control technique is introduced to eliminate uncertainties in the plant parameters of the DC Series motors, and also considered as potential candidate for different applications to prove adequacy of the proposed control algorithm through simulations. The simulation result with such an approach is made and observed efficient over other controlling technique.


Fast Fraction-Integer Method for Computing Multiplicative Inverse

Abstract: Multiplicative inverse is a crucial operation in public key cryptography, and been widely used in cryptography. Public key cryptography has given rise to such a need, in which we need to generate a related public and private pair of numbers, each of which is the inverse of the other. The basic method to find multiplicative inverses is Extended-Euclidean method. In this paper we will propose a new algorithm for computing the inverse, based on continues subtract fraction from integer and divide by fraction to obtain integer that will be used to compute the inverse d. The authors claim that the proposed method more efficient and faster than the existed methods.


Analysis on the Study of QoS-Aware Web Services Discovery

Abstract: Web service technology has gained more important role in developing distributed applications and systems on the Internet. Rapid growth of published Web services makes their discovery more and more difficult. There exist many web services which exhibit similar functional characteristics. It is imperative to provide service consumers with facilities for selecting required web services according to their non-functional characteristics or QoS. The QoS-based web service discovery mechanisms will play an essential role in SOA, as e-Business applications want to use services that most accurately meet their requirements. However, representing and storing the values of QoS attributes are problematic, as the current UDDI was not designed to accommodate these emerging requirements. To solve the problems of storing QoS in UDDI and aggregating QoS values using the tModel approach. The aim is to study these approaches and other existing QoS tModel representation for their efficiency and consistency in service discovery. This paper discusses a broad range of research issues such as web service discovery or web service selection based on QoS in the E-Business domain.


Towards Expeditious and Unswerving Routing to Corroborate Nascent Internet

Abstract: The internet is now-a-days experiencing a stress due to some inherent problems with the main interdomain routing protocol, boarder gateway protocol (BGP), the amount of time it takes to converge, number of update message exchanged followed by a failure to stabilize, the amount of time required to get a valid alternate path following the failure, the way size of routing table increasing, and security issues like integrity and privacy of routing tables and routing updates exchanged among the routers, are of our primary concern. In our proposed research work we plan to address aforementioned issues related to internet routing specially in boarder gateway protocol to enable BGP to offer expeditious unswerving routing to corroborate nascent internet. We plan to make some changes in the design of boarder gateway protocol and may introduce addition of extra features in BGP to help support above mentioned objective.


Advanced Technology in Speech Disorder Therapy of Romanian Language

Abstract: One of the key challenges of the society development is related to public health and one of its specific targets includes better treatments of diseases. It is true that there are affections which by their nature do not endanger the life of a person, but they may have negative implications during his/her lifetime. Various language or speech disorders are part of this category. Discovered and treated in time, they can be corrected, most often in childhood. Because the Romanian language is a phonetic one that has its own special linguistic particularities, there is a real need to develop advanced information systems, which can be used to assist and help specialists in different speech disorders therapy. The aim of this paper is to present a few CBTS developed for the treatment of various language and speech disorders specific to the Romanian language.


Penetration Testing: A Roadmap to Network Security

Abstract: Network penetration testing identifies the exploits and vulnerabilities those exist within computer network infrastructure and help to confirm the security measures. The objective of this paper is to explain methodology and methods behind penetration testing and illustrate remedies over it, which will provide substantial value for network security Penetration testing should model real world attacks as closely as possible. An authorized and scheduled penetration testing will probably detected by IDS (Intrusion Detection System). Network penetration testing is done by either or manual automated tools. Penetration test can gather evidence of vulnerability in the network. Successful testing provides indisputable evidence of the problem as well as starting point for prioritizing remediation. Penetration testing focuses on high severity vulnerabilities and there are no false positive.


The Effected Oxide Capacitor in CMOS Structure of Integrated Circuit Level 5 Micrometer Technology

Abstract: This article is present the effected oxide capacitor in CMOS structure of integrated circuit level 5 micrometer technology. It has designed and basic structure of MOS diode. It establish with aluminum metallization layer by sputtering method, oxide insulator layer mode from silicon dioxide, n+ and p+ semiconductor layer, it has high capacitance concentrate. From the MOS diode structure silicon dioxide thickness 0.5 micrometer, it will get capacitance between aluminum metal layer and p+ semiconductor at 28.62 pF, the capacitance between aluminum metal layer and n+ semiconductor at 29.55 pF. In this article establish second metal layer for measurement density values of first aluminum metal layer with second aluminum metal layer, it has density values at 16 pF.


Network Traffic Management

Abstract: The purposes of this paper have to discuss issues related to Network Traffic Management. A relatively new category of network management is fast becoming a necessity in converged business Networks. Mid-sized and large organizations are finding they must control network traffic behavior to assure that their strategic applications always get the resources they need to perform optimally. Controlling network traffic requires limiting bandwidth to certain applications, guaranteeing minimum bandwidth to others, and marking traffic with high or low priorities. This exercise is called Network Traffic Management.


A Novel Feature Extraction for Robust EMG Pattern Recognition

Abstract: Varieties of noises are major problem in recognition of Electromyography (EMG) signal. Hence, methods to remove noise become most significant in EMG signal analysis. White Gaussian noise (WGN) is used to represent interference in this paper. Generally, WGN is difficult to be removed using typical filtering and solutions to remove WGN are limited. In addition, noise removal is an important step before performing feature extraction, which is used in EMG-based recognition. This research is aimed to present a novel feature that tolerate with WGN. As a result, noise removal algorithm is not needed. Two novel mean and median frequencies (MMNF and MMDF) are presented for robust feature extraction. Sixteen existing features and two novelties are evaluated in a noisy environment. WGN with various signal-to-noise ratios (SNRs), i.e. 20-0 dB, was added to the original EMG signal. The results showed that MMNF performed very well especially in weak EMG signal compared with others. The error of MMNF in weak EMG signal with very high noise, 0 dB SNR, is about 5-10 percent and closed by MMDF and Histogram, whereas the error of other features is more than 20 percent. While in strong EMG signal, the error of MMNF is better than those from other features. Moreover, the combination of MMNF, Histrogram of EMG and Willison amplitude is used as feature vector in classification task. The experimental result shows the better recognition result in noisy environment than other success feature candidates. From the above results demonstrate that MMNF can be used for new robust feature extraction.


Spherical Layout Implementation using Centroidal Voronoi Tessellations

Abstract: The 3D tree visualization faces multiple challenges: the election of an appropriate layout, the use of the interactions that make the data exploration easier and a metaphor that helps in the process of information understanding. A good combination of these elements will result in a visualization that effectively conveys the key features of a complex structure or system to a wide range of users and permits the analytical reasoning process. In previous works we presented the Spherical Layout, a technique for 3D tree visualization that provides an excellent base to achieve those key features. The layout was implemented using the TriSphere algorithm, a method that discretized the spheres's surfaces with triangles to achieve a uniform distribution of the nodes. The goal of this work was centered in a new algorithm for the implementation of the Spherical layout; we called it the Weighted Spherical Centroidal Voronoi Tessellations (WSCVT). In this paper we present a detailed description of this new implementation and a comparison with the TriSphere algorithm.


Teaching Result Analysis Using Rough Sets and Data Mining

Abstract: The development of IT and WWW provides different teaching strategies, which are chosen by teachers. Students can acquire knowledge through different learning models. The problem based learning is a popular teaching strategy for teachers. Based on the educational theory, students increase their learning motivation, which can increase learning effectiveness. In this paper, we propose a concept map for each student and staff. This map finds the result of the subjects and also recommends a sequence of remedial teaching. Here, rough set theory is used for dealing with uncertainty in the hidden pattern of data. For each competence the lower and upper approximations are calculated based on the brainstorm maps.


Fair Exchange of Digital Signatures using RSA-based CEMBS and Offline STTP

Abstract: One of the essential security services needed to safeguard online transactions is fair exchange. In fair exchange protocols two parties can exchange their signatures in a fair manner, so that either each party gain the other's signature or no one obtain anything useful. This paper examines security solutions for achieving fair exchange. It proposes new security protocols based on the "Certified Encrypted Message Being Signature" (CEMBS) by using RSA signature scheme. This protocol relies on the help of an "off-line Semi-Trusted Third Party" (STTP) to achieve fairness. They provide with confidential protection from the STTP for the exchanged items by limiting the role and power of the STTP. Three different protocols have been proposed. In the first protocol, the two main parties exchange their signatures on a common message. In the second protocol, the signatures are exchanged on two different messages. While in the third one, the exchange is between confidential data and signature.


Retail Market analysis in targeting sales based on Consumer Behaviour using Fuzzy Clustering - A Rule Based Mode

Abstract: Product Bundling and offering products to customers is of critical importance in retail marketing. In general, product bundling and offering products to customers involves two main issues, namely identification of product taste according to demography and product evaluation and selection to increase sales. The former helps to identify, analyze and understand customer needs according to the demo-graphical characteristics and correspondingly transform them into a set of specifications and offerings for people. The latter, concerns with how to determine the best product strategy and offerings for the customer in helping the retail market to improve their sales. Existing research has focused only on identifying patterns for a particular dataset and for a particular setting. This work aims to develop an explicit decision support for the retailers to improve their product segmentation for different settings based on the people characteristics and thereby promoting sales by efficient knowledge discovery from the existing sales and product records. The work presents a framework, which models an association relation mapping between the customers and the clusters of products they purchase in an existing location and helps in finding rules for a new location. The methodology is based on the integration of popular data mining approaches such as clustering and association rule mining. It focuses on the discovery of rules that vary according to the economic and demographic characteristics and concentrates on marketing of products based on the population.


Performance Analysis of AIM-K-means & K-means in Quality Cluster Generation

Abstract: Among all the partition based clustering algorithms K-means is the most popular and well known method. It generally shows impressive results even in considerably large data sets. The computational complexity of K-means does not suffer from the size of the data set. The main disadvantage faced in performing this clustering is that the selection of initial means. If the user does not have adequate knowledge about the data set, it may lead to erroneous results. The algorithm Automatic Initialization of Means (AIM), which is an extension to K-means, has been proposed to overcome the problem of initial mean generation. In this paper an attempt has been made to compare the performance of the algorithms through implementation


Multi-Agent Model using Secure Multi-Party Computing in e-Governance

Abstract: Information management and retrieval of all the citizen occurs in almost all the public service functions. Electronic Government system is an emerging trend in India through which efforts are made to strive maximum safety and security. Various solutions for this have been proposed like Shibboleth, Public Key Infrastructure, Smart Cards and Light Weight Directory Access Protocols. Still, none of these guarantee 100 percent security. Efforts are being made to provide common national identity solution to various diverse Government identity cards. In this paper, we discuss issues related to these solutions.


New Model of Network- a Future Aspect of the Computer Networks

Abstract: As the number and size of the Network increases, the deficiencies persist, including network security problems. But there is no shortage of technologies offered as universal remedy - EIGRP,BGP, OSPF, VoIP, IPv6, IPTV, MPLS, WiFi, to name a few. There are multiple factors for the current situation. Now a day during emergent and blossoming stages of network development is no longer sufficient when the networks are mature and have become everyday tool for social and business interactions. A new model of network is necessary to find solutions for today's pressing problems, especially those related to network security. In this paper out factors leading to current stagnation discusses critical assumptions behind current networks, how many of them are no longer valid and have become barriers for implementing real solutions. The paper concludes by offering new directions for future needs and solving current challenges.


Frame Selected Approach for Hiding Data within MPEG Video Using Bit Plane Complexity Segmentation

Abstract: Bit Plane Complexity Segmentation (BPCS) digital picture steganography is a technique to hide data inside an image file. BPCS achieves high embedding rates with low distortion based on the theory that noise-like regions in an image's bit-planes can be replaced with noise-like secret data without significant loss in image quality. . In this framework we will propose a collaborate approach for select frame for Hiding Data within MPEG Video Using Bit Plane Complexity Segmentation. This approach will invent high secure data hidden using select frame form MPEG Video and furthermore we will assign the well-built of the approach; during this review the author will answer the question why they used select frame steganography. In additional to the security issues we will use the digital video as a cover to the data hidden. The reason behind opt the video cover in this approach is the huge amount of single frames image per sec which in turn overcome the problem of the data hiding quantity, as the experiment result shows the success of the hidden data within select frame, extract data from the frames sequence. These function without affecting the quality of the video.


Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Abstract: Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multi-armed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization. We analyze GP-UCB, an intuitive upper-confidence based algorithm, and bound its cumulative regret in terms of maximal information gain, establishing a novel connection between GP optimization and experimental design. Moreover, by bounding the latter in terms of operator spectra, we obtain explicit sublinear regret bounds for many commonly used covariance functions. In some important cases, our bounds have surprisingly weak dependence on the dimensionality. In our experiments on real sensor data, GP-UCB compares favorably with other heuristical GP optimization approaches.


Configuration Structures, Event Structures and Petri Nets

Abstract: In this paper the correspondence between safe Petri nets and event structures, due to Nielsen, Plotkin and Winskel, is extended to arbitrary nets without self-loops, under the collective token interpretation. To this end we propose a more general form of event structure, matching the expressive power of such nets. These new event structures and nets are connected by relating both notions with configuration structures, which can be regarded as representations of either event structures or nets that capture their behaviour in terms of action occurrences and the causal relationships between them, but abstract from any auxiliary structure. A configuration structure can also be considered logically, as a class of propositional models, or - equivalently - as a propositional theory in disjunctive normal from. Converting this theory to conjunctive normal form is the key idea in the translation of such a structure into a net. For a variety of classes of event structures we characterise the associated classes of configuration structures in terms of their closure properties, as well as in terms of the axiomatisability of the associated propositional theories by formulae of simple prescribed forms, and in terms of structural properties of the associated Petri nets.


Process Description of COM Object Life Cycle

Abstract: The objective of this article is to provide for the reader a basic description of all the steps involved in the COM object life-cycle process. COM is a software technology and process performer. The first section briefly introduces the Component Object Model (COM), considering the process of the COM object life cycle as the baseline of all COM issues. The second part describes in detail the basic steps of the process - client request, server location, object creation, interaction, and disconnection. A brief description is given for the components involved in each step. Finally, the third section provides a brief conclusion summarizing all the process steps.


Windtalking Computers: Frequency Normalization, Binary Coding Systems and Encryption

Abstract: This paper discusses the application of known techniques, knowledge and technology in a novel way for encryption. Two distinct and separate methods are presented. Method 1: Alter the symbol set of the language by adding additional redundant symbols for frequent symbols. This will reduce the high frequency of more commonly used symbols. Hence, frequency analysis upon ciphertext will not be possible. Hence, decryption will be possible. Method 2: Computers use binary base 2. Most encryption systems use ciphering to convert data to ciphertext. The author presents the theory and several possible implementations of a method for computers analogous to speaking another language. This is done by using a binary base other than base 2. Ex. Fibonacci, Phi or Prime. In addition, steganography may be used for creating alternate binary bases. This kind of encryption significantly increases the complexity of decryption. First the binary base must be known. Only then, can decryption begin. This kind of encryption also breaks the transitivity of plaintext-codebook-binary; the correlation of letters-ASCII-base2. With this transitivity broken, decryption is logically impossible. Coupled with encrypting the plaintext, binary encryption makes decryption uncrackable. It may produce false positives--information theoretic secure, and requires much more computing power to resolve than is currently used in brute force decryption. Hence, the assertion that these combination of methods are computationally secure--impervious to brute force. The proposed system has a drawback. It is not as compressed as a base2. (Similar to adding random padding to the encryption.) However, this is acceptable, since the goal is very strong encryption: Both methods are not decryptable by method uncrackable - by conventional, statistical means.


Computing an Integer Prime Factoring in O(n^2.5)

Abstract: Paper is withdrawn. On review the paper contributes little of significance. The runtime analysis of the algorithms presented, while correct in terms of number of operations, does not represent the complexity of the algorithms in terms of "bits input". A naive mistake in reasoning.


On the Connectivity and Multihop Delay of Ad Hoc Cognitive Radio Networks

Abstract: We analyze the multihop delay of ad hoc cognitive radio networks, where the transmission delay of each hop consists of the propagation delay and the waiting time for the availability of the communication channel (i.e., the occurrence of a spectrum opportunity at this hop). Using theories and techniques from continuum percolation and ergodicity, we establish the scaling law of the minimum multihop delay with respect to the source-destination distance in cognitive radio networks. When the propagation delay is negligible, we show the starkly different scaling behavior of the minimum multihop delay in instantaneously connected networks as compared to networks that are only intermittently connected due to scarcity of spectrum opportunities. Specifically, if the network is instantaneously connected, the minimum multihop delay is asymptotically independent of the distance; if the network is only intermittently connected, the minimum multihop delay scales linearly with the distance. When the propagation delay is nonnegligible but small, we show that although the scaling order is always linear, the scaling rate for an instantaneously connected network can be orders of magnitude smaller than the one for an intermittently connected network.


On Channel-Discontinuity-Constraint Routing in Wireless Networks

Abstract: Multi-channel wireless networks are increasingly being employed as infrastructure networks, e.g. in metro areas. Nodes in these networks frequently employ directional antennas to improve spatial throughput. In such networks, given a source and destination, it is of interest to compute an optimal path and channel assignment on every link in the path such that the path bandwidth is the same as that of the link bandwidth and such a path satisfies the constraint that no two consecutive links on the path are assigned the same channel, referred to as "Channel Discontinuity Constraint" (CDC). CDC-paths are also quite useful for TDMA system, where preferably every consecutive links along a path are assigned different time slots. This paper contains several contributions. We first present an $O(N^{2})$ distributed algorithm for discovering the shortest CDC-path between given source and destination. This improves the running time of the $O(N^{3})$ centralized algorithm of Ahuja et al. for finding the minimum-weight CDC-path. Our second result is a generalized $t$-spanner for CDC-path; For any $\theta>0$ we show how to construct a sub-network containing only $O(\frac{N}{\theta})$ edges, such that that length of shortest CDC-paths between arbitrary sources and destinations increases by only a factor of at most $(1-2\sin{\tfrac{\theta}{2}})^{-2}$. We propose a novel algorithm to compute the spanner in a distributed manner using only $O(n\log{n})$ messages. An important conclusion of this scheme is in the case of directional antennas are used. In this case, it is enough to consider only the two closest nodes in each cone.


Branching-time model checking of one-counter processes

Abstract: One-counter processes (OCPs) are pushdown processes which operate only on a unary stack alphabet. We study the computational complexity of model checking computation tree logic (CTL) over OCPs. A PSPACE upper bound is inherited from the modal mu-calculus for this problem. First, we analyze the periodic behaviour of CTL over OCPs and derive a model checking algorithm whose running time is exponential only in the number of control locations and a syntactic notion of the formula that we call leftward until depth. Thus, model checking fixed OCPs against CTL formulas with a fixed leftward until depth is in P. This generalizes a result of the first author, Mayr, and To for the expression complexity of CTL's fragment EF. Second, we prove that already over some fixed OCP, CTL model checking is PSPACE-hard. Third, we show that there already exists a fixed CTL formula for which model checking of OCPs is PSPACE-hard. For the latter, we employ two results from complexity theory: (i) Converting a natural number in Chinese remainder presentation into binary presentation is in logspace-uniform NC^1 and (ii) PSPACE is AC^0-serializable. We demonstrate that our approach can be used to answer further open questions.


Scope Logic: Extending Hoare Logic for Pointer Program Verification

Abstract: This paper presents an extension to Hoare logic for pointer program verification. First, the Logic for Partial Function (LPF) used by VDM is extended to specify memory access using pointers and memory layout of composite types. Then, the concepts of data-retrieve functions (DRF) and memory-scope functions (MSF) are introduced in this paper. People can define DRFs to retrieve abstract values from interconnected concrete data objects. The definition of the corresponding MSF of a DRF can be derived syntactically from the definition of the DRF. This MSF computes the set of memory units accessed when the DRF retrieves an abstract value. This memory unit set is called the memory scope of the abstract value. Finally, the proof rule of assignment statements in Hoare's logic is modified to deal with pointers. The basic idea is that a virtual value keeps unmodified as long as no memory unit in its scope is over-written. Another proof rule is added for memory allocation statements. The consequence rule and the rules for control-flow statements are slightly modified. They are essentially same as their original version in Hoare logic. An example is presented to show the efficacy of this logic. We also give some heuristics on how to verify pointer programs.


The skewness of computer science

Abstract: Computer science is a relatively young discipline combining science, engineering, and mathematics. The main flavors of computer science research involve the theoretical development of conceptual models for the different aspects of computing and the more applicative building of software artifacts and assessment of their properties. In the computer science publication culture, conferences are an important vehicle to quickly move ideas, and journals often publish deeper versions of papers already presented at conferences. These peculiarities of the discipline make computer science an original research field within the sciences, and, therefore, the assessment of classical bibliometric laws is particularly important for this field. In this paper, we study the skewness of the distribution of citations to papers published in computer science publication venues (journals and conferences). We find that the skewness in the distribution of mean citedness of different venues combines with the asymmetry in citedness of articles in each venue, resulting in a highly asymmetric citation distribution with a power law tail. Furthermore, the skewness of conference publications is more pronounced than the asymmetry of journal papers. Finally, the impact of journal papers, as measured with bibliometric indicators, largely dominates that of proceeding papers.


Computing Least Fixed Points of Probabilistic Systems of Polynomials

Abstract: We study systems of equations of the form X1 = f1(X1, ..., Xn), ..., Xn = fn(X1, ..., Xn), where each fi is a polynomial with nonnegative coefficients that add up to 1. The least nonnegative solution, say mu, of such equation systems is central to problems from various areas, like physics, biology, computational linguistics and probabilistic program verification. We give a simple and strongly polynomial algorithm to decide whether mu=(1, ..., 1) holds. Furthermore, we present an algorithm that computes reliable sequences of lower and upper bounds on mu, converging linearly to mu. Our algorithm has these features despite using inexact arithmetic for efficiency. We report on experiments that show the performance of our algorithms.


Dynamic routing based on call quality

Abstract: The telephony over IP (ToIP) is becoming a new trend in technology widely used nowadays in almost all business sectors. Its concepts rely on transiting the telephone communications through the IP network. Today, this technology is deployed increasingly what the cause of emergence of companies is offering this service as Switzernet. For several highly demanded destinations, recently fake vendors appeared in the market offering voice termination but providing only false answer supervision. The answered signal is returned immediately and calls are being charged without being connected. Different techniques are used to keep the calling party on the line. One of these techniques is to play a record of a ring back tone (while the call is already being charged). Another, more sophisticated technique is to play a human voice randomly picked up from a set of records containing contents similar to: hello, hello, I cannot hear you Apart the fact that the fallaciously established calls are charged at rates of real calls, such malicious routes seriously handicap the switching process. The system does not detect a failure on signaling level and is unable to attempt the call via backup routes, the call technically being already connected. Once the call flow falls into such trap, the calls will continue being routed via the fraudulent route until a manual intervention.


Modified Minimum Connected Dominating Set formation for Wireless Adhoc Networks

Abstract: Nodes of minimum connected dominating set (MCDS) form a virtual backbone in a wireless adhoc network. In this paper, a modified approach is presented to determine MCDS of an underlying graph of a Wireless Adhoc network. Simulation results for a variety of graphs indicate that the approach is efficient in determining the MCDS as compared to other existing techniques.


Routing in Wireless Adhoc Networks: A New Horizon

Abstract: A lot of work has been done on routing protocols for mobile ad hoc networks, but still standardization of them requires some more issues less addressed by the existing routing protocols. In this paper a new paradigm of maintaining multiple connections in adhoc routing protocols has been highlighted which may be crucial for efficient routing in mobile ad hoc networks. The problem of multiple connections has been hardly worked on in adhoc networks. In this paper the solution of route maintenance if nodes are maintaining multiple connections has been proposed. This idea not only helps to solve the multiple connections problem, but also take care of proper bandwidth distribution to different connections as per different traffic types. Study has been incorporated on existing AODV with changes. Simulation studies have been performed over packet delivery ratio, throughput and message overheads. Results show that the proposed solution for multiple connections is efficient and worth implementing in existing as well as new protocols.


Polytool: polynomial interpretations as a basis for termination analysis of Logic programs

Abstract: Our goal is to study the feasibility of porting termination analysis techniques developed for one programming paradigm to another paradigm. In this paper, we show how to adapt termination analysis techniques based on polynomial interpretations - very well known in the context of term rewrite systems (TRSs) - to obtain new (non-transformational) ter- mination analysis techniques for definite logic programs (LPs). This leads to an approach that can be seen as a direct generalization of the traditional techniques in termination analysis of LPs, where linear norms and level mappings are used. Our extension general- izes these to arbitrary polynomials. We extend a number of standard concepts and results on termination analysis to the context of polynomial interpretations. We also propose a constraint-based approach for automatically generating polynomial interpretations that satisfy the termination conditions. Based on this approach, we implemented a new tool, called Polytool, for automatic termination analysis of LPs.


Delay-Constrained Utility Maximization in Multihop Random Access Networks

Abstract: Multi-hop random access networks have received much attention due to their distributed nature which facilitates deploying many new applications over the sensor and computer networks. Recently, utility maximization framework is applied in order to optimize performance of such networks however delay is not limited and proposed algorithms result in very large transmission delays. In this paper, we will analyze delay in random access multi-hop networks and solve the delay-constrained utility maximization problem. We define the network utility as a combination of rate utility and energy cost functions and solve the following two problems: 'optimal medium access control with link delay constraint' and, 'optimal congestion and contention control with end-to-end delay constraint'. The optimal tradeoff between delay, rate, and energy is achieved for different values of delay constraint and the scaling factors between rate and energy. Different distributed solutions will be proposed for each problem and their performance will be compared in terms of convergence and complexity.


Simplex Subdivisions and Nonnegativity Decision of Forms

Abstract: This paper mainly studies nonnegativity decision of forms based on variable substitutions. Unlike existing research, the paper regards simplex subdivisions as new perspectives to study variable substitutions, gives some subdivisions of the simplex T_n, introduces the concept of convergence of the subdivision sequence, and presents a sufficient and necessary condition for the convergent self-similar subdivision sequence. Then the relationships between subdivisions and their corresponding substitutions are established. Moreover, it is proven that if the form F is indefinite on T_n and the sequence of the successive L-substitution sets is convergent, then the sequence of sets {SLS^(m)(F)} is negatively terminating, and an algorithm for deciding indefinite forms with a counter-example is obtained. Thus, various effective substitutions for deciding positive semi-definite forms and indefinite forms are gained, which are beyond the weighted difference substitutions characterized by "difference".


The weighted difference substitutions and Nonnegativity Decision of Forms

Abstract: In this paper, we study the weighted difference substitutions from geometrical views. First, we give the geometric meanings of the weighted difference substitutions, and introduce the concept of convergence of the sequence of substitution sets. Then it is proven that the sequence of the successive weighted difference substitution sets is convergent. Based on the convergence of the sequence of the successive weighted difference sets, a new, simpler method to prove that if the form F is positive definite on T_n, then the sequence of sets {SDS^m(F)} is positively terminating is presented, which is different from the one given in [11]. That is, we can decide the nonnegativity of a positive definite form by successively running the weighted difference substitutions finite times. Finally, an algorithm for deciding an indefinite form with a counter-example is obtained, and some examples are listed by using the obtained algorithm.


Learning to Predict Combinatorial Structures

Abstract: The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.


Multicore-aware parallel temporal blocking of stencil codes for shared and distributed memory

Abstract: New algorithms and optimization techniques are needed to balance the accelerating trend towards bandwidth-starved multicore chips. It is well known that the performance of stencil codes can be improved by temporal blocking, lessening the pressure on the memory interface. We introduce a new pipelined approach that makes explicit use of shared caches in multicore environments and minimizes synchronization and boundary overhead. For clusters of shared-memory nodes we demonstrate how temporal blocking can be employed successfully in a hybrid shared/distributed-memory environment.


Consensus Dynamics in a non-deterministic Naming Game with Shared Memory

Abstract: In the naming game, individuals or agents exchange pairwise local information in order to communicate about objects in their common environment. The goal of the game is to reach a consensus about naming these objects. Originally used to investigate language formation and self-organizing vocabularies, we extend the classical naming game with a globally shared memory accessible by all agents. This shared memory can be interpreted as an external source of knowledge like a book or an Internet site. The extended naming game models an environment similar to one that can be found in the context of social bookmarking and collaborative tagging sites where users tag sites using appropriate labels, but also mimics an important aspect in the field of human-based image labeling. Although the extended naming game is non-deterministic in its word selection, we show that consensus towards a common vocabulary is reached. More importantly, we show the qualitative and quantitative influence of the external source of information, i.e. the shared memory, on the consensus dynamics between the agents.


A Note on the Middle Levels Conjecture

Abstract: The middle levels conjecture asserts that there is a Hamiltonian cycle in the middle two levels of $2k+1$-dimensional hypercube. The conjecture is known to be true for $k \leq 17$ [I.Shields, B.J.Shields and C.D.Savage, Disc. Math., 309, 5271--5277 (2009)]. In this note, we verify that the conjecture is also true for $k=18$ by constructing a Hamiltonian cycle in the middle two levels of 37-dimensional hypercube with the aid of the computer. We achieve this by introducing a new decomposition technique and an efficient algorithm for ordering the Narayana objects.


Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window

Abstract: The past decade has witnessed many interesting algorithms for maintaining statistics over a data stream. This paper initiates a theoretical study of algorithms for monitoring distributed data streams over a time-based sliding window (which contains a variable number of items and possibly out-of-order items). The concern is how to minimize the communication between individual streams and the root, while allowing the root, at any time, to be able to report the global statistics of all streams within a given error bound. This paper presents communication-efficient algorithms for three classical statistics, namely, basic counting, frequent items and quantiles. The worst-case communication cost over a window is $O(\frac{k} {\epsilon} \log \frac{\epsilon N}{k})$ bits for basic counting and $O(\frac{k}{\epsilon} \log \frac{N}{k})$ words for the remainings, where $k$ is the number of distributed data streams, $N$ is the total number of items in the streams that arrive or expire in the window, and $\epsilon < 1$ is the desired error bound. Matching and nearly matching lower bounds are also obtained.


A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem

Abstract: This paper formulates a necessary and sufficient condition for a generic graph matching problem to be equivalent to the maximum vertex and edge weight clique problem in a derived association graph. The consequences of this results are threefold: first, the condition is general enough to cover a broad range of practical graph matching problems; second, a proof to establish equivalence between graph matching and clique search reduces to showing that a given graph matching problem satisfies the proposed condition; and third, the result sets the scene for generic continuous solutions for a broad range of graph matching problems. To illustrate the mathematical framework, we apply it to a number of graph matching problems, including the problem of determining the graph edit distance.


Elkan's k-Means for Graphs

Abstract: This paper extends k-means algorithms from the Euclidean domain to the domain of graphs. To recompute the centroids, we apply subgradient methods for solving the optimization-based formulation of the sample mean of graphs. To accelerate the k-means algorithm for graphs without trading computational time against solution quality, we avoid unnecessary graph distance calculations by exploiting the triangle inequality of the underlying distance metric following Elkan's k-means algorithm proposed in \cite{Elkan03}. In experiments we show that the accelerated k-means algorithm are faster than the standard k-means algorithm for graphs provided there is a cluster structure in the data.


Log-space Algorithms for Paths and Matchings in k-trees

Abstract: Reachability and shortest path problems are NL-complete for general graphs. They are known to be in L for graphs of tree-width 2 [JT07]. However, for graphs of tree-width larger than 2, no bound better than NL is known. In this paper, we improve these bounds for k-trees, where k is a constant. In particular, the main results of our paper are log-space algorithms for reachability in directed k-trees, and for computation of shortest and longest paths in directed acyclic k-trees. Besides the path problems mentioned above, we also consider the problem of deciding whether a k-tree has a perfect macthing (decision version), and if so, finding a perfect match- ing (search version), and prove that these two problems are L-complete. These problems are known to be in P and in RNC for general graphs, and in SPL for planar bipartite graphs [DKR08]. Our results settle the complexity of these problems for the class of k-trees. The results are also applicable for bounded tree-width graphs, when a tree-decomposition is given as input. The technique central to our algorithms is a careful implementation of divide-and-conquer approach in log-space, along with some ideas from [JT07] and [LMR07].


Chain Routing: A new routing framework for the Internet based on complete orders

Abstract: A new framework to perform routing at the Autonomous System level is proposed in this paper. This mechanism, called Chain Routing, uses complete orders as its main topological unit. Since complete orders are acyclic digraphs that possess a known topology, it is possible to define an acyclic structure to route packets between a group of Autonomous Systems. The adoption of complete orders also allows easy identification and avoidance of persistent route oscillations, eliminates the possibility of developing transient loops in paths, and provides a structure that facilitates the implementation of traffic engineering. Moreover, by combining Chain Routing with other mechanisms that implement complete orders in time, we suggest that it is possible to design a new routing protocol which could be more reliable and stable than BGP's current implementation. Although Chain Routing will require an increase of the message overhead and greater coordination between network administrators, the rewards in stability and resilience should more than compensate for this effort.


Local and Global Trust Based on the Concept of Promises

Abstract: We use the notion of a promise to define local trust between agents possessing autonomous decision-making. An agent is trustworthy if it is expected that it will keep a promise. This definition satisfies most commonplace meanings of trust. Reputation is then an estimation of this expectation value that is passed on from agent to agent. Our definition distinguishes types of trust, for different behaviours, and decouples the concept of agent reliability from the behaviour on which the judgement is based. We show, however, that trust is fundamentally heuristic, as it provides insufficient information for agents to make a rational judgement. A global trustworthiness, or community trust can be defined by a proportional, self-consistent voting process, as a weighted eigenvector-centrality function of the promise theoretical graph.


Discovery of Elliptic Curve Cryptographic Private Key in O(n)

Abstract: An algorithm is presented that in context of public key use of Elliptic Curve Cryptography allows discovery of the private key in worst case O(n).


Optimizing Histogram Queries under Differential Privacy

Abstract: Differential privacy is a robust privacy standard that has been successfully applied to a range of data analysis tasks. Despite much recent work, optimal strategies for answering a collection of correlated queries are not known. We study the problem of devising a set of strategy queries, to be submitted and answered privately, that will support the answers to a given workload of queries. We propose a general framework in which query strategies are formed from linear combinations of counting queries, and we describe an optimal method for deriving new query answers from the answers to the strategy queries. Using this framework we characterize the error of strategies geometrically, and we propose solutions to the problem of finding optimal strategies.


Demand-Supply Optimization with Risk Management for a Multi-Connection Water Reservoir Network

Abstract: In this paper, we propose a framework to solve a demand-supply optimization problem of long-term water resource allocation on a multi-connection reservoir network which, in two aspects, is different to the problem considered in previous works. First, while all previous works consider a problem where each reservoir can transfer water to only one fixed reservoir, we consider a multi-connection network being constructed in Thailand in which each reservoir can transfer water to many reservoirs in one period of time. Second, a demand-supply plan considered here is static, in contrast to a dynamic policy considered in previous works. Moreover, in order to efficiently develop a long-term static plan, a severe loss (a risk) is taken into account, i.e. a risk occurs if the real amount of water stored in each reservoir in each time period is less than what planned by the optimizer. The multi-connection function and the risk make the problem rather complex such that traditional stochastic dynamic programming and deterministic/heuristic approaches are inappropriate. Our framework is based on a novel convex programming formulation in which stochastic information can be naturally taken into account and an optimal solution is guaranteed to be found efficiently. Extensive experimental results show promising results of the framework.


Typing rule-based transformations over topological collections

Abstract: Pattern-matching programming is an example of a rule-based programming style developed in functional languages. This programming style is intensively used in dialects of ML but is restricted to algebraic data-types. This restriction limits the field of application. However, as shown by Giavitto and Michel at RULE'02, case-based function definitions can be extended to more general data structures called topological collections. We show in this paper that this extension retains the benefits of the typed discipline of the functional languages. More precisely, we show that topological collections and the rule-based definition of functions associated with them fit in a polytypic extension of mini-ML where type inference is still possible.


Typage fort et typage souple des collections topologiques et des transformations

Abstract: Topological collections allow to consider uniformly many data structures in programming languages and are handled by functions defined by pattern matching called transformations. We present two type systems for languages with topological collections and transformations. The first one is a strong type system \`a la Hindley/Milner which can be entirely typed at compile time. The second one is a mixed static and dynamic type system allowing to handle heterogeneous collections, that is collections which contain values with different types. In the two cases, automatic type inference is possible.


Similarit\'e en intension vs en extension : \`a la crois\'ee de l'informatique et du th\'e\^atre

Abstract: Traditional staging is based on a formal approach of similarity leaning on dramaturgical ontologies and instanciation variations. Inspired by interactive data mining, that suggests different approaches, we give an overview of computer science and theater researches using computers as partners of the actor to escape the a priori specification of roles.


How Do Interactive Virtual Operas Shift Relationships between Music, Text and Image?

Abstract: In this paper we present the new genre of interactive operas implemented on personal computers. They differ from traditional ones not only because they are virtual, but mainly because they offer to composers and listeners new perspectives of combinations and interactions between music, text and visual aspects.


Music-ripping: des pratiques qui provoquent la musicologie

Abstract: Out of the scope of the usual positions of computing in the field of music and musicology, one notices the emergence of human-computer systems that do exist by breaking off. Though these singular systems take effect in the usual fields of expansion of music, they do not make any systematic reference to known musicological categories. On the contrary, they make possible experiments that open uses where listening, composition and musical transmission get merged in a gesture sometimes named as ?music-ripping?. We will show in which way the music-ripping practices provoke traditional musicology, whose canonical categories happen to be ineffectual to explain here. To achieve that purpose, we shall need: - to make explicit a minimal set of categories that is sufficient to underlie the usual models of computer assisted music;- to do the same for human-computer systems (anti-musicological?) that disturb us; - to examine the possibility conditions of reduction of the second set to the first; - to conclude on the nature of music-ripping.


Interagir avec un contenu op\'eratique : le projet d'op\'era virtuel interactif Virtualis

Abstract: In this article, we present the interactive opera project on CD-ROM Virtualis. This project includes a scientific dimension as well as artistic. It gave us the opportunity to design a model of the opera performance using formalisms from organization sciences. Moreover, our investigation on interactions between a user and opera contents led us to use models of relationships between entities based on physical forces, where the user is in a way absent. We detail some aspects of a reading but also writing environment on artistic complex contents between text, music and graphics.


Inapproximability of maximal strip recovery

Abstract: In comparative genomic, the first step of sequence analysis is usually to decompose two or more genomes into syntenic blocks that are segments of homologous chromosomes. For the reliable recovery of syntenic blocks, noise and ambiguities in the genomic maps need to be removed first. Maximal Strip Recovery (MSR) is an optimization problem proposed by Zheng, Zhu, and Sankoff for reliably recovering syntenic blocks from genomic maps in the midst of noise and ambiguities. Given $d$ genomic maps as sequences of gene markers, the objective of \msr{d} is to find $d$ subsequences, one subsequence of each genomic map, such that the total length of syntenic blocks in these subsequences is maximized. For any constant $d \ge 2$, a polynomial-time 2d-approximation for \msr{d} was previously known. In this paper, we show that for any $d \ge 2$, \msr{d} is APX-hard, even for the most basic version of the problem in which all gene markers are distinct and appear in positive orientation in each genomic map. Moreover, we provide the first explicit lower bounds on approximating \msr{d} for all $d \ge 2$. In particular, we show that \msr{d} is NP-hard to approximate within $\Omega(d/\log d)$. From the other direction, we show that the previous 2d-approximation for \msr{d} can be optimized into a polynomial-time algorithm even if $d$ is not a constant but is part of the input. We then extend our inapproximability results to several related problems including \cmsr{d}, \gapmsr{\delta}{d}, and \gapcmsr{\delta}{d}.


Genus Computing for 3D digital objects: algorithm and implementation

Abstract: This paper deals with computing topological invariants such as connected components, boundary surface genus, and homology groups. For each input data set, we have designed or implemented algorithms to calculate connected components, boundary surfaces and their genus, and homology groups. Due to the fact that genus calculation dominates the entire task for 3D object in 3D space, in this paper, we mainly discuss the calculation of the genus. The new algorithms designed in this paper will perform: (1) pathological cases detection and deletion, (2) raster space to point space (dual space) transformation, (3) the linear time algorithm for boundary point classification, and (4) genus calculation.


Parameterized Modal Satisfiability

Abstract: We investigate the parameterized computational complexity of the satisfiability problem for modal logic and attempt to pinpoint relevant structural parameters which cause the problem's combinatorial explosion, beyond the number of propositional variables v. To this end we study the modality depth, a natural measure which has appeared in the literature, and show that, even though modal satisfiability parameterized by v and the modality depth is FPT, the running time's dependence on the parameters is a tower of exponentials (unless P=NP). To overcome this limitation we propose several possible alternative parameters, namely diamond dimension, box dimension and modal width. We show fixed-parameter tractability results using these measures where the exponential dependence on the parameters is much milder than in the case of modality depth thus leading to FPT algorithms for modal satisfiability with much more reasonable running times.


Infinitary Combinatory Reduction Systems: Normalising Reduction Strategies

Abstract: We study normalising reduction strategies for infinitary Combinatory Reduction Systems (iCRSs). We prove that all fair, outermost-fair, and needed-fair strategies are normalising for orthogonal, fully-extended iCRSs. These facts properly generalise a number of results on normalising strategies in first-order infinitary rewriting and provide the first examples of normalising strategies for infinitary lambda calculus.


Cognitive MAC Protocols Using Memory for Distributed Spectrum Sharing Under Limited Spectrum Sensing

Abstract: The main challenges of cognitive radio include spectrum sensing at the physical (PHY) layer to detect the activity of primary users and spectrum sharing at the medium access control (MAC) layer to coordinate access among coexisting secondary users. In this paper, we consider a cognitive radio network in which a primary user shares a channel with secondary users that cannot distinguish the signals of the primary user from those of a secondary user. We propose a class of distributed cognitive MAC protocols to achieve efficient spectrum sharing among the secondary users while protecting the primary user from potential interference by the secondary users. By using a MAC protocol with one-slot memory, we can obtain high channel utilization by the secondary users while limiting interference to the primary user at a low level. The results of this paper suggest the possibility of utilizing MAC design in cognitive radio networks to overcome limitations in spectrum sensing at the PHY layer as well as to achieve spectrum sharing at the MAC layer.


A User's Guide to Zot

Abstract: Zot is an agile and easily extendible bounded model checker, which can be downloaded at http://home.dei.polimi.it/pradella/. The tool supports different logic languages through a multi-layered approach: its core uses PLTL, and on top of it a decidable predicative fragment of TRIO is defined. An interesting feature of Zot is its ability to support different encodings of temporal logic as SAT problems by means of plug-ins. This approach encourages experimentation, as plug-ins are expected to be quite simple, compact (usually around 500 lines of code), easily modifiable, and extendible.