Deterministic Distributed Vertex Coloring in Polylogarithmic Time

Abstract: Consider an n-vertex graph G = (V,E) of maximum degree Delta, and suppose that each vertex v \in V hosts a processor. The processors are allowed to communicate only with their neighbors in G. The communication is synchronous, i.e., it proceeds in discrete rounds. In the distributed vertex coloring problem the objective is to color G with Delta + 1, or slightly more than Delta + 1, colors using as few rounds of communication as possible. (The number of rounds of communication will be henceforth referred to as running time.) Efficient randomized algorithms for this problem are known for more than twenty years \cite{L86, ABI86}. Specifically, these algorithms produce a (Delta + 1)-coloring within O(log n) time, with high probability. On the other hand, the best known deterministic algorithm that requires polylogarithmic time employs O(Delta^2) colors. This algorithm was devised in a seminal FOCS'87 paper by Linial \cite{L87}. Its running time is O(log^* n). In the same paper Linial asked whether one can color with significantly less than Delta^2 colors in deterministic polylogarithmic time. By now this question of Linial became one of the most central long-standing open questions in this area. In this paper we answer this question in the affirmative, and devise a deterministic algorithm that employs \Delta^{1 +o(1)} colors, and runs in polylogarithmic time. Specifically, the running time of our algorithm is O(f(Delta) log Delta log n), for an arbitrarily slow-growing function f(Delta) = \omega(1). We can also produce O(Delta^{1 + \eta})-coloring in O(log Delta log n)-time, for an arbitrarily small constant \eta > 0, and O(Delta)-coloring in O(Delta^{\epsilon} log n) time, for an arbitrarily small constant \epsilon > 0.


Unification and Matching on Compressed Terms

Abstract: Term unification plays an important role in many areas of computer science, especially in those related to logic. The universal mechanism of grammar-based compression for terms, in particular the so-called Singleton Tree Grammars (STG), have recently drawn considerable attention. Using STGs, terms of exponential size and height can be represented in linear space. Furthermore, the term representation by directed acyclic graphs (dags) can be efficiently simulated. The present paper is the result of an investigation on term unification and matching when the terms given as input are represented using different compression mechanisms for terms such as dags and Singleton Tree Grammars. We describe a polynomial time algorithm for context matching with dags, when the number of different context variables is fixed for the problem. For the same problem, NP-completeness is obtained when the terms are represented using the more general formalism of Singleton Tree Grammars. For first-order unification and matching polynomial time algorithms are presented, each of them improving previous results for those problems.


A multivalued knowledge-base model

Abstract: The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these ideas the concept of multivalued knowledge-base will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At last a possible evaluation strategy is given.


An Entry Point for Formal Methods: Specification and Analysis of Event Logs

Abstract: Formal specification languages have long languished, due to the grave scalability problems faced by complete verification methods. Runtime verification promises to use formal specifications to automate part of the more scalable art of testing, but has not been widely applied to real systems, and often falters due to the cost and complexity of instrumentation for online monitoring. In this paper we discuss work in progress to apply an event-based specification system to the logging mechanism of the Mars Science Laboratory mission at JPL. By focusing on log analysis, we exploit the "instrumentation" already implemented and required for communicating with the spacecraft. We argue that this work both shows a practical method for using formal specifications in testing and opens interesting research avenues, including a challenging specification learning problem.


Generalised Rabin(1) synthesis

Abstract: We present a novel method for the synthesis of finite state systems that is a generalisation of the generalised reactivity(1) synthesis approach by Piterman, Pnueli and Sa'ar. In particular, we describe an efficient method to synthesize systems from linear-time temporal logic specifications for which all assumptions and guarantees have a Rabin index of one. We show how to build a parity game with at most five colours that captures all solutions to the synthesis problem from such a specification. This parity game has a structure that is amenable to symbolic implementations. We furthermore show that the results obtained are in some sense tight, i.e., that there does not exist a similar synthesis method for assumptions and specifications of higher Rabin index, unless P=NP.


Formalization and Validation of Safety-Critical Requirements

Abstract: The validation of requirements is a fundamental step in the development process of safety-critical systems. In safety critical applications such as aerospace, avionics and railways, the use of formal methods is of paramount importance both for requirements and for design validation. Nevertheless, while for the verification of the design, many formal techniques have been conceived and applied, the research on formal methods for requirements validation is not yet mature. The main obstacles are that, on the one hand, the correctness of requirements is not formally defined; on the other hand that the formalization and the validation of the requirements usually demands a strong involvement of domain experts. We report on a methodology and a series of techniques that we developed for the formalization and validation of high-level requirements for safety-critical applications. The main ingredients are a very expressive formal language and automatic satisfiability procedures. The language combines first-order, temporal, and hybrid logic. The satisfiability procedures are based on model checking and satisfiability modulo theory. We applied this technology within an industrial project to the validation of railways requirements.


Privacy Issues of the W3C Geolocation API

Abstract: The W3C's Geolocation API may rapidly standardize the transmission of location information on the Web, but, in dealing with such sensitive information, it also raises serious privacy concerns. We analyze the manner and extent to which the current W3C Geolocation API provides mechanisms to support privacy. We propose a privacy framework for the consideration of location information and use it to evaluate the W3C Geolocation API, both the specification and its use in the wild, and recommend some modifications to the API as a result of our analysis.


A Hybrid System based on Multi-Agent System in the Data Preprocessing Stage

Abstract: We describe the usage of the Multi-agent system in the data preprocessing stage of an on-going project, called e-Wedding. The aim of this project is to utilize MAS and various approaches, like Web services, Ontology, and Data mining techniques, in e-Business that want to improve responsiveness and efficiency of systems so as to extract customer behavior model on Wedding Businesses. However, in this paper, we propose and implement the multi-agent-system, based on JADE, to only cope data preprocessing stage specified on handle with missing value techniques. JADE is quite easy to learn and use. Moreover, it supports many agent approaches such as agent communication, protocol, behavior and ontology. This framework has been experimented and evaluated in the realization of a simple, but realistic. The results, though still preliminary, are quite.


New Approach to Identify Common Eigenvalues of real matrices using Gerschgorin Theorem and Bisection method

Abstract: In this paper, a new approach is presented to determine common eigenvalues of two matrices. It is based on Gerschgorin theorem and Bisection method. The proposed approach is simple and can be useful in image processing and noise estimation.


A Survey of Na\"ive Bayes Machine Learning approach in Text Document Classification

Abstract: Text Document classification aims in associating one or more predefined categories based on the likelihood suggested by the training set of labeled documents. Many machine learning algorithms play a vital role in training the system with predefined categories among which Na\"ive Bayes has some intriguing facts that it is simple, easy to implement and draws better accuracy in large datasets in spite of the na\"ive dependence. The importance of Na\"ive Bayes Machine learning approach has felt hence the study has been taken up for text document classification and the statistical event models available. This survey the various feature selection methods has been discussed and compared along with the metrics related to text document classification.


Content based Zero-Watermarking Algorithm for Authentication of Text Documents

Abstract: Copyright protection and authentication of digital contents has become a significant issue in the current digital epoch with efficient communication mediums such as internet. Plain text is the rampantly used medium used over the internet for information exchange and it is very crucial to verify the authenticity of information. There are very limited techniques available for plain text watermarking and authentication. This paper presents a novel zero-watermarking algorithm for authentication of plain text. The algorithm generates a watermark based on the text contents and this watermark can later be extracted using extraction algorithm to prove the authenticity of text document. Experimental results demonstrate the effectiveness of the algorithm against tampering attacks identifying watermark accuracy and distortion rate on 10 different text samples of varying length and attacks.


Secure Multicast Key Distribution for Mobile Ad Hoc Networks

Abstract: Many emerging applications in mobile adhoc networks involve group-oriented communication. Multicast is an efficient way of supporting group oriented applications, mainly in mobile environment with limited bandwidth and limited power. For using such applications in an adversarial environment as military, it is necessary to provide secure multicast communication. Key management is the fundamental challenge in designing secure multicast communications. In many multicast interactions, new member can join and current members can leave at any time and existing members must communicate securely using multicast key distribution within constrained energy for mobile adhoc networks. This has to overcome the challenging element of "1 affects n" problem which is due to high dynamicity of groups. Thus this paper shows the specific challenges towards multicast key management protocols for securing multicast key distribution in mobile ad hoc networks, and present relevant multicast key management protocols in mobile ad hoc networks. A comparison is done against some pertinent performance criteria.


Nonlinear Filter Based Image Denoising Using AMF Approach

Abstract: This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Median (CWM) filter has got a better average performance over the median filter [8]. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach by overcoming the existing problem, the proposed new scheme (AMF) Adaptive Median Filter has been simulated along with the standard ones and various performance measures have been compared.


Securing Our Bluetooth Mobiles From Intruder Attack Using Enhanced Authentication Scheme And Plausible Exchange Algorithm

Abstract: When Bluetooth devices come within the range of another, an electronic conversation takes place to determine whether the devices in range are known or whether one needs to control the other. Most Bluetooth devices do not require any form of user interaction for this to occur. If devices within range are known to one another, the devices automatically form a network known as a pairing. Authentication addresses the identity of each communicating device. The sender sends an encrypted authentication request frame to the receiver. The receiver sends an encrypted challenge frame back to the sender. Both perform a predefined algorithm. The sender sends its findings back to the receiver, which in turn either allows or denies the connection. There are three different functions for authentication in Bluetooth-E1, E2, and E3. E1 is used when encrypting the authorization challenge-response values.E2 is for generating different link keys.E3 is used when creating the encryption key.


Knowledge Management

Abstract: This paper discusses the important process of knowledge and its management, and differences between tacit and explicit knowledge and understanding the culture as a key issue for the successful implementation of knowledge management, in addition to, this paper is concerned with the four-stage model for the evolution of information technology (IT) support for knowledge management in law firms.


Wireless IP Telephony

Abstract: The convergence of traditional telecommunications and the Internet is creating new network-based service delivery opportunities for telecommunications companies carriers, service providers, and network equipment providers. Voice over Wireless IP is one of the most exciting new developments emerging within the telephony market. It is set to revolutionize the delivery of mobile voice Services and provide exciting new opportunities for operators and service providers alike. This survey discusses principal of Wireless IP Telephony.


Reconfigurable Parallel Data Flow Architecture

Abstract: This paper presents a reconfigurable parallel data flow architecture. This architecture uses the concepts of multi-agent paradigm in reconfigurable hardware systems. The utilization of this new paradigm has the potential to greatly increase the flexibility, efficiency, expandability of data flow systems and to provide an attractive alternative to the current set of disjoint approaches that are currently applied to this problem domain. The ability of methodology to implement data flow type processing with different models is presented in this paper.


Model Based Ceramic tile inspection using Discrete Wavelet Transform and Euclidean Distance

Abstract: Visual inspection of industrial products is used to determine the control quality for these products. This paper deals with the problem of visual inspection of ceramic tiles industry using Wavelet Transform. The third level the coefficients of two dimensions Haar Discrete Wavelet Transform (HDWT) is used in this paper to process the images and feature extraction. The proposed algorithm consists of two main phases. The first phase is to compute the wavelet transform for an image free of defects which known as reference image, and the image to be inspected which known as test image. The second phase is used to decide whether the tested image is defected or not using the Euclidean distance similarity measure. The experimentation results of the proposed algorithm give 97% for correct detection of ceramic defects.


An Analytical Approach to Document Clustering Based on Internal Criterion Function

Abstract: Fast and high quality document clustering is an important task in organizing information, search engine results obtaining from user query, enhancing web crawling and information retrieval. With the large amount of data available and with a goal of creating good quality clusters, a variety of algorithms have been developed having quality-complexity trade-offs. Among these, some algorithms seek to minimize the computational complexity using certain criterion functions which are defined for the whole set of clustering solution. In this paper, we are proposing a novel document clustering algorithm based on an internal criterion function. Most commonly used partitioning clustering algorithms (e.g. k-means) have some drawbacks as they suffer from local optimum solutions and creation of empty clusters as a clustering solution. The proposed algorithm usually does not suffer from these problems and converge to a global optimum, its performance enhances with the increase in number of clusters. We have checked our algorithm against three different datasets for four different values of k (required number of clusters).


Role of Data Mining in E-Payment systems

Abstract: Data Mining deals extracting hidden knowledge, unexpected pattern and new rules from large database. Various customized data mining tools have been developed for domain specific applications such as Biomedicine, DNA analysis and telecommunication. Trends in data mining include further efforts towards the exploration of new application areas and methods for handling complex data types, algorithm scalability, constraint based data mining and visualization methods. In this paper we will present domain specific Secure Multiparty computation technique and applications. Data mining has matured as a field of basic and applied research in computer science in general. In this paper, we survey some of the recent approaches and architectures where data mining has been applied in the fields of e-payment systems. In this paper we limit our discussion to data mining in the context of e-payment systems. We also mention a few directions for further work in this domain, based on the survey.


Facial Gesture Recognition Using Correlation And Mahalanobis Distance

Abstract: Augmenting human computer interaction with automated analysis and synthesis of facial expressions is a goal towards which much research effort has been devoted recently. Facial gesture recognition is one of the important component of natural human-machine interfaces; it may also be used in behavioural science, security systems and in clinical practice. Although humans recognise facial expressions virtually without effort or delay, reliable expression recognition by machine is still a challenge. The face expression recognition problem is challenging because different individuals display the same expression differently. This paper presents an overview of gesture recognition in real time using the concepts of correlation and Mahalanobis distance.We consider the six universal emotional categories namely joy, anger, fear, disgust, sadness and surprise.


FP-tree and COFI Based Approach for Mining of Multiple Level Association Rules in Large Databases

Abstract: In recent years, discovery of association rules among itemsets in a large database has been described as an important database-mining problem. The problem of discovering association rules has received considerable research attention and several algorithms for mining frequent itemsets have been developed. Many algorithms have been proposed to discover rules at single concept level. However, mining association rules at multiple concept levels may lead to the discovery of more specific and concrete knowledge from data. The discovery of multiple level association rules is very much useful in many applications. In most of the studies for multiple level association rule mining, the database is scanned repeatedly which affects the efficiency of mining process. In this research paper, a new method for discovering multilevel association rules is proposed. It is based on FP-tree structure and uses cooccurrence frequent item tree to find frequent items in multilevel concept hierarchy.


A GA based Window Selection Methodology to Enhance Window based Multi wavelet transformation and thresholding aided CT image denoising technique

Abstract: Image denoising is getting more significance, especially in Computed Tomography (CT), which is an important and most common modality in medical imaging. This is mainly due to that the effectiveness of clinical diagnosis using CT image lies on the image quality. The denoising technique for CT images using window-based Multi-wavelet transformation and thresholding shows the effectiveness in denoising, however, a drawback exists in selecting the closer windows in the process of window-based multi-wavelet transformation and thresholding. Generally, the windows of the duplicate noisy image that are closer to each window of original noisy image are obtained by the checking them sequentially. This leads to the possibility of missing out very closer windows and so enhancement is required in the aforesaid process of the denoising technique. In this paper, we propose a GA-based window selection methodology to include the denoising technique. With the aid of the GA-based window selection methodology, the windows of the duplicate noisy image that are very closer to every window of the original noisy image are extracted in an effective manner. By incorporating the proposed GA-based window selection methodology, the denoising the CT image is performed effectively. Eventually, a comparison is made between the denoising technique with and without the proposed GA-based window selection methodology.


Investigation and Assessment of Disorder of Ultrasound B-mode Images

Abstract: Digital image plays a vital role in the early detection of cancers, such as prostate cancer, breast cancer, lungs cancer, cervical cancer. Ultrasound imaging method is also suitable for early detection of the abnormality of fetus. The accurate detection of region of interest in ultrasound image is crucial. Since the result of reflection, refraction and deflection of ultrasound waves from different types of tissues with different acoustic impedance. Usually, the contrast in ultrasound image is very low and weak edges make the image difficult to identify the fetus region in the ultrasound image. So the analysis of ultrasound image is more challenging one. We try to develop a new algorithmic approach to solve the problem of non clarity and find disorder of it. Generally there is no common enhancement approach for noise reduction. This paper proposes different filtering techniques based on statistical methods for the removal of various noise. The quality of the enhanced images is measured by the statistical quantity measures: Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE).


Localization Technologies for Indoor Human Tracking

Abstract: The proliferation of wireless localization technologies provides a promising future for serving human beings in indoor scenarios. Their applications include real-time tracking, activity recognition, health care, navigation, emergence detection, and target-of-interest monitoring, among others. Additionally, indoor localization technologies address the inefficiency of GPS (Global Positioning System) inside buildings. Since people spend most of their time in indoor environments, indoor tracking service is in great public demand. Based on this observation, this paper aims to provide a better understanding of state-of-the-art technologies and stimulate new research efforts in this field. For these purposes, existing localization technologies that can be used for tracking individuals in indoor environments are reviewed, along with some further discussions.


Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron

Abstract: Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the present work in respect to handwritten Arabic numerals. Arabic is spoken throughout the Arab World and the fifth most popular language in the world slightly before Portuguese and Bengali. For the present work, we have developed a feature set of 88 features is designed to represent samples of handwritten Arabic numerals for this work. It includes 72 shadow and 16 octant features. A Multi Layer Perceptron (MLP) based classifier is used here for recognition handwritten Arabic digits represented with the said feature set. On experimentation with a database of 3000 samples, the technique yields an average recognition rate of 94.93% evaluated after three-fold cross validation of results. It is useful for applications related to OCR of handwritten Arabic Digit and can also be extended to include OCR of handwritten characters of Arabic alphabet.


A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron

Abstract: The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with both of two separate combinations of features. One of these combinations consists of shadow and centriod features, i. e. 88 features in all, and the other shadow, centroid and longest run features, i. e. 124 features in all. Out of these two, the former combination having a smaller number of features is finally considered effective for applications related to Optical Character Recognition (OCR) of handwritten Arabic numerals. The work can also be extended to include OCR of handwritten characters of Arabic alphabet.


Dual-hop transmissions with fixed-gain relays over Generalized-Gamma fading channels

Abstract: In this paper, a study on the end-to-end performance of dual-hop wireless communication systems equipped with fixed-gain relays and operating over Generalized-Gamma (GG) fading channels is presented. A novel closed form expression for the moments of the end-to-end signal-to-noise ratio (SNR) is derived. The average bit error probability for coherent and non-coherent modulation schemes as well as the end-to-end outage probability of the considered system are also studied. Extensive numerically evaluated and computer simulations results are presented that verify the accuracy of the proposed mathematical analysis.


Simulating Grover's Quantum Search in a Classical Computer

Abstract: The rapid progress of computer science has been accompanied by a corresponding evolution of computation, from classical computation to quantum computation. As quantum computing is on its way to becoming an established discipline of computing science, much effort is being put into the development of new quantum algorithms. One of quantum algorithms is Grover algorithm, which is used for searching an element in an unstructured list of N elements with quadratic speed-up over classical algorithms. In this work, Quantum Computer Language (QCL) is used to make a Grover's quantum search simulation in a classical computer


Efficient Parallel and Out of Core Algorithms for Constructing Large Bi-directed de Bruijn Graphs

Abstract: Assembling genomic sequences from a set of overlapping reads is one of the most fundamental problems in computational biology. Algorithms addressing the assembly problem fall into two broad categories -- based on the data structures which they employ. The first class uses an overlap/string graph and the second type uses a de Bruijn graph. However with the recent advances in short read sequencing technology, de Bruijn graph based algorithms seem to play a vital role in practice. Efficient algorithms for building these massive de Bruijn graphs are very essential in large sequencing projects based on short reads. In Jackson et. al. ICPP-2008, an $O(n/p)$ time parallel algorithm has been given for this problem. Here $n$ is the size of the input and $p$ is the number of processors. This algorithm enumerates all possible bi-directed edges which can overlap with a node and ends up generating $\Theta(n\Sigma)$ messages. In this paper we present a $\Theta(n/p)$ time parallel algorithm with a communication complexity equal to that of parallel sorting and is not sensitive to $\Sigma$. The generality of our algorithm makes it very easy to extend it even to the out-of-core model and in this case it has an optimal I/O complexity of $\Theta(\frac{n\log(n/B)}{B\log(M/B)})$. We demonstrate the scalability of our parallel algorithm on a SGI/Altix computer. A comparison of our algorithm with that of Jackson et. al. ICPP-2008 reveals that our algorithm is faster. We also provide efficient algorithms for the bi-directed chain compaction problem.


Distributed Principal Component Analysis for Wireless Sensor Networks

Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is based on a linear transform where the sensor measurements are projected on a set of principal components. When sensor measurements are correlated, a small set of principal components can explain most of the measurements variability. This allows to significantly decrease the amount of radio communication and of energy consumption. In this paper, we show that the power iteration method can be distributed in a sensor network in order to compute an approximation of the principal components. The proposed implementation relies on an aggregation service, which has recently been shown to provide a suitable framework for distributing the computation of a linear transform within a sensor network. We also extend this previous work by providing a detailed analysis of the computational, memory, and communication costs involved. A compression experiment involving real data validates the algorithm and illustrates the tradeoffs between accuracy and communication costs.


Asynchronous Bounded Expected Delay Networks

Abstract: The commonly used asynchronous bounded delay (ABD) network models assume a fixed bound on message delay. We propose a probabilistic network model, called asynchronous bounded expected delay (ABE) model. Instead of a strict bound, the ABE model requires only a bound on the expected message delay. While the conditions of ABD networks restrict the set of possible executions, in ABE networks all asynchronous executions are possible, but executions with extremely long delays are less probable. In contrast to ABD networks, ABE networks cannot be synchronised efficiently. At the example of an election algorithm, we show that the minimal assumptions of ABE networks are sufficient for the development of efficient algorithms. For anonymous, unidirectional ABE rings of known size N we devise a probabilistic leader election algorithm having average message and time complexity O(N).


Quantifying Shannon's Work Function for Cryptanalytic Attacks

Abstract: Attacks on cryptographic systems are limited by the available computational resources. A theoretical understanding of these resource limitations is needed to evaluate the security of cryptographic primitives and procedures. This study uses an Attacker versus Environment game formalism based on computability logic to quantify Shannon's work function and evaluate resource use in cryptanalysis. A simple cost function is defined which allows to quantify a wide range of theoretical and real computational resources. With this approach the use of custom hardware, e.g., FPGA boards, in cryptanalysis can be analyzed. Applied to real cryptanalytic problems, it raises, for instance, the expectation that the computer time needed to break some simple 90 bit strong cryptographic primitives might theoretically be less than two years.


Supermartingales in Prediction with Expert Advice

Abstract: We apply the method of defensive forecasting, based on the use of game-theoretic supermartingales, to prediction with expert advice. In the traditional setting of a countable number of experts and a finite number of outcomes, the Defensive Forecasting Algorithm is very close to the well-known Aggregating Algorithm. Not only the performance guarantees but also the predictions are the same for these two methods of fundamentally different nature. We discuss also a new setting where the experts can give advice conditional on the learner's future decision. Both the algorithms can be adapted to the new setting and give the same performance guarantees as in the traditional setting. Finally, we outline an application of defensive forecasting to a setting with several loss functions.


Automated selection of LEDs by luminance and chromaticity coordinate

Abstract: The increased use of LEDs for lighting purposes has led to the development of numerous applications requiring a pre-selection of LEDs by their luminance and / or their chromaticity coordinate. This paper demonstrates how a manual pre-selection process can be realized using a relatively simple configuration. Since a manual selection service can only be commercially viable as long as only small quantities of LEDs need to be sorted, an automated solution suggests itself. This paper introduces such a solution, which has been developed by Harzoptics in close cooperation with Rundfunk Gernrode. The paper also discusses current challenges in measurement technology as well as market trends.


The packing chromatic number of the square lattice is at least 12

Abstract: The packing chromatic number $\chi_\rho(G)$ of a graph $G$ is the smallest integer $k$ such that the vertex set $V(G)$ can be partitioned into disjoint classes $X_1, ..., X_k$, where vertices in $X_i$ have pairwise distance greater than $i$. For the 2-dimensional square lattice $\mathbb{Z}^2$ it is proved that $\chi_\rho(\mathbb{Z}^2) \geq 12$, which improves the previously known lower bound 10.


Stochastic Games for Security in Networks with Interdependent Nodes

Abstract: This paper studies a stochastic game theoretic approach to security and intrusion detection in communication and computer networks. Specifically, an Attacker and a Defender take part in a two-player game over a network of nodes whose security assets and vulnerabilities are correlated. Such a network can be modeled using weighted directed graphs with the edges representing the influence among the nodes. The game can be formulated as a non-cooperative zero-sum or nonzero-sum stochastic game. However, due to correlation among the nodes, if some nodes are compromised, the effective security assets and vulnerabilities of the remaining ones will not stay the same in general, which leads to complex system dynamics. We examine existence, uniqueness, and structure of the solution and also provide numerical examples to illustrate our model.


Up-sampling and Natural Sample Value Computation for Digital Pulse Width Modulators

Abstract: Digital pulse width modulation has been considered for high-fidelity and high-efficiency audio amplifiers for several years. It has been shown that the distortion can be reduced and the implementation of the system can be simplified if the switching frequency is much higher than the Nyquist rate of the modulating waveform. Hence, the input digital source is normally upsampled to a higher frequency. It was also proved that converting uniform samples to natural samples will decrease the harmonic distortion. Thus, in this paper, we examine a new approach that combines upsampling, digital interpolation and natural sampling conversion. This approach uses poly-phase implementation of the digital interpolation filter and digital differentiators. We will show that the structure consists of an FIR-type linear stage and a nonlinear stage. Some spectral simulation results of a pulse width modulation system based on this approach will also be presented. Finally, we will discuss the improvement of the new approach over old algorithms.


Piecemeal Journey To 'HALCYON' World Of Pervasive Computing : From past progress to future challenges

Abstract: Although 'Halcyon' means serene environment which pervasive computing aims at, we have tried to present a different interpretation of this word. Through our approach, we look at it in context of achieving future 'calm technology'. The paper gives a general overview of the state of pervasive computing today, proposes the 'HALCYON Model' and outlines the 'social' challenges faced by system designers.


Revisiting the Examination Hypothesis with Query Specific Position Bias

Abstract: Click through rates (CTR) offer useful user feedback that can be used to infer the relevance of search results for queries. However it is not very meaningful to look at the raw click through rate of a search result because the likelihood of a result being clicked depends not only on its relevance but also the position in which it is displayed. One model of the browsing behavior, the {\em Examination Hypothesis} \cite{RDR07,Craswell08,DP08}, states that each position has a certain probability of being examined and is then clicked based on the relevance of the search snippets. This is based on eye tracking studies \cite{Claypool01, GJG04} which suggest that users are less likely to view results in lower positions. Such a position dependent variation in the probability of examining a document is referred to as {\em position bias}. Our main observation in this study is that the position bias tends to differ with the kind of information the user is looking for. This makes the position bias {\em query specific}. In this study, we present a model for analyzing a query specific position bias from the click data and use these biases to derive position independent relevance values of search results. Our model is based on the assumption that for a given query, the positional click through rate of a document is proportional to the product of its relevance and a {\em query specific} position bias. We compare our model with the vanilla examination hypothesis model (EH) on a set of queries obtained from search logs of a commercial search engine. We also compare it with the User Browsing Model (UBM) \cite{DP08} which extends the cascade model of Craswell et al\cite{Craswell08} by incorporating multiple clicks in a query session. We show that the our model, although much simpler to implement, consistently outperforms both EH and UBM on well-used measures such as relative error and cross entropy.


The C Object System: Using C as a High-Level Object-Oriented Language

Abstract: The C Object System (Cos) is a small C library which implements high-level concepts available in Clos, Objc and other object-oriented programming languages: uniform object model (class, meta-class and property-metaclass), generic functions, multi-methods, delegation, properties, exceptions, contracts and closures. Cos relies on the programmable capabilities of the C programming language to extend its syntax and to implement the aforementioned concepts as first-class objects. Cos aims at satisfying several general principles like simplicity, extensibility, reusability, efficiency and portability which are rarely met in a single programming language. Its design is tuned to provide efficient and portable implementation of message multi-dispatch and message multi-forwarding which are the heart of code extensibility and reusability. With COS features in hand, software should become as flexible and extensible as with scripting languages and as efficient and portable as expected with C programming. Likewise, Cos concepts should significantly simplify adaptive and aspect-oriented programming as well as distributed and service-oriented computing


Spectrum Trading: An Abstracted Bibliography

Abstract: This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{naldi@disp.uniroma2.it}).


Inductive Logic Programming in Databases: from Datalog to DL+log

Abstract: In this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e. the issue of how ontologies (and semantics conveyed by them) can help solving typical database problems, through a better understanding of KR aspects related to databases. In particular, we investigate this issue from the ILP perspective by considering two database problems, (i) the definition of views and (ii) the definition of constraints, for a database whose schema is represented also by means of an ontology. Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework DL+log. We illustrate the application scenarios by means of examples. Keywords: Inductive Logic Programming, Relational Databases, Ontologies, Description Logics, Hybrid Knowledge Representation and Reasoning Systems. Note: To appear in Theory and Practice of Logic Programming (TPLP).


Forming the COUNCIL Based Clusters in Securing Wireless Ad Hoc Networks

Abstract: In cluster-based routing protocol (CBRP), two-level hierarchical structure is successfully used to reduce over-flooding in wireless Ad Hoc networks. As it is vulnerable to a single point of failure, we propose a new adaptive distributed threshold scheme to replace the cluster head by a group of cluster heads within each cluster, called COUNCIL, and distribute the service of single cluster head to multiple cluster heads using (k,n) threshold secret sharing scheme. An Ad Hoc network formed by COUNCIL based clusters can work correctly when the number of compromised cluster heads is smaller than k. To implement this adaptive threshold scheme in wireless Ad Hoc Networks, membership of the clusters should be defined in an adaptive way. In this paper, we mainly discuss our algorithm for forming COUNCIL based clusters using the concept of dominating set from graph theory.


Vcache: Caching Dynamic Documents

Abstract: The traditional web caching is currently limited to static documents only. A page generated on the fly from a server side script may have different contents on different accesses and hence cannot be cached. A number of proposals for attacking the problem have emerged based on the observation that different instances of a dynamic document are usually quite similar in most cases, i.e. they have a lot of common HTML code. In this paper, we first review these related techniques and show their inadequacy for practical use. We then present a general and fully automatic technique called Vcache based on the decomposition of dynamic documents into a hierarchy of templates and bindings. The technique is designed keeping in mind languages like Perl and C etc that generate the documents using low-level print like statements. These languages together, account for the largest number of dynamic documents on the web.


Release ZERO.0.1 of package RefereeToolbox

Abstract: RefereeToolbox is a java package implementing combination operators for fusing evidences. It is downloadable from: http://refereefunction.fredericdambreville.com/releases RefereeToolbox is based on an interpretation of the fusion rules by means of Referee Functions. This approach implies a dissociation between the definition of the combination and its actual implementation, which is common to all referee-based combinations. As a result, RefereeToolbox is designed with the aim to be generic and evolutive.


Making Web Annotations Persistent over Time

Abstract: As Digital Libraries (DL) become more aligned with the web architecture, their functional components need to be fundamentally rethought in terms of URIs and HTTP. Annotation, a core scholarly activity enabled by many DL solutions, exhibits a clearly unacceptable characteristic when existing models are applied to the web: due to the representations of web resources changing over time, an annotation made about a web resource today may no longer be relevant to the representation that is served from that same resource tomorrow. We assume the existence of archived versions of resources, and combine the temporal features of the emerging Open Annotation data model with the capability offered by the Memento framework that allows seamless navigation from the URI of a resource to archived versions of that resource, and arrive at a solution that provides guarantees regarding the persistence of web annotations over time. More specifically, we provide theoretical solutions and proof-of-concept experimental evaluations for two problems: reconstructing an existing annotation so that the correct archived version is displayed for all resources involved in the annotation, and retrieving all annotations that involve a given archived version of a web resource.


An Educative Brain-Computer Interface

Abstract: In this paper we will describe all necessary parts of Brain-Computer Interface (BCI), such as source of signals, hardware, software, analysis, architectures of complete system. We also will go along various applications of BCI, view some subject fields and their specifics. After preface we will consider the main point of this work-concepts of using BCI in education. Represented direction of BCI development has not been reported prior. In this work a computer system, currently being elaborated in author's laboratory, will be specified. A purpose of it is to determine a degree of clearness of studied information for certain user according to their indications of brain electrical signals. On the basis of this information the system is able to find an optimal approach to interact with each single user. Feedback individualization leads to learning effectiveness increasing. Stated investigations will be supplemented by author's analytical reasoning on the nature of thinking process.


Classified Ads Harvesting Agent and Notification System

Abstract: The shift from an information society to a knowledge society require rapid information harvesting, reliable search and instantaneous on demand delivery. Information extraction agents are used to explore and collect data available from Web, in order to effectively exploit such data for business purposes, such as automatic news filtering, advertisement or product searching and price comparing. In this paper, we develop a real-time automatic harvesting agent for adverts posted on Servihoo web portal and an SMS-based notification system. It uses the URL of the web portal and the object model, i.e., the fields of interests and a set of rules written using the HTML parsing functions to extract latest adverts information. The extraction engine executes the extraction rules and stores the information in a database to be processed for automatic notification. This intelligent system helps to tremendously save time. It also enables users or potential product buyers to react more quickly to changes and newly posted sales adverts, paving the way to real-time best buy deals.


Table manipulation in simplicial databases

Abstract: In \cite{Spi}, we developed a category of databases in which the schema of a database is represented as a simplicial set. Each simplex corresponds to a table in the database. There, our main concern was to find a categorical formulation of databases; the simplicial nature of the schemas was to some degree unexpected and unexploited. In the present note, we show how to use this geometric formulation effectively on a computer. If we think of each simplex as a polygonal tile, we can imagine assembling custom databases by mixing and matching tiles. Queries on this database can be performed by drawing paths through the resulting tile formations, selecting records at the start-point of this path and retrieving corresponding records at its end-point.


The role of semantics in mining frequent patterns from knowledge bases in description logics with rules

Abstract: We propose a new method for mining frequent patterns in a language that combines both Semantic Web ontologies and rules. In particular we consider the setting of using a language that combines description logics with DL-safe rules. This setting is important for the practical application of data mining to the Semantic Web. We focus on the relation of the semantics of the representation formalism to the task of frequent pattern discovery, and for the core of our method, we propose an algorithm that exploits the semantics of the combined knowledge base. We have developed a proof-of-concept data mining implementation of this. Using this we have empirically shown that using the combined knowledge base to perform semantic tests can make data mining faster by pruning useless candidate patterns before their evaluation. We have also shown that the quality of the set of patterns produced may be improved: the patterns are more compact, and there are fewer patterns. We conclude that exploiting the semantics of a chosen representation formalism is key to the design and application of (onto-)relational frequent pattern discovery methods. Note: To appear in Theory and Practice of Logic Programming (TPLP)


Particle Swarm Optimization Based Diophantine Equation Solver

Abstract: The paper introduces particle swarm optimization as a viable strategy to find numerical solution of Diophantine equation, for which there exists no general method of finding solutions. The proposed methodology uses a population of integer particles. The candidate solutions in the feasible space are optimized to have better positions through particle best and global best positions. The methodology, which follows fully connected neighborhood topology, can offer many solutions of such equations.


Near-Optimal Evasion of Convex-Inducing Classifiers

Abstract: Classifiers are often used to detect miscreant activities. We study how an adversary can efficiently query a classifier to elicit information that allows the adversary to evade detection at near-minimal cost. We generalize results of Lowd and Meek (2005) to convex-inducing classifiers. We present algorithms that construct undetected instances of near-minimal cost using only polynomially many queries in the dimension of the space and without reverse engineering the decision boundary.


Security Games with Decision and Observation Errors

Abstract: We study two-player security games which can be viewed as sequences of nonzero-sum matrix games played by an Attacker and a Defender. The evolution of the game is based on a stochastic fictitious play process. Players do not have access to each other's payoff matrix. Each has to observe the other's actions up to present and plays the action generated based on the best response to these observations. However, when the game is played over a communication network, there are several practical issues that need to be taken into account: First, the players may make random decision errors from time to time. Second, the players' observations of each other's previous actions may be incorrect. The players will try to compensate for these errors based on the information they have. We examine convergence property of the game in such scenarios, and establish convergence to the equilibrium point under some mild assumptions when both players are restricted to two actions.


Some Remarks on the Model Theory of Epistemic Plausibility Models

Abstract: Classical logics of knowledge and belief are usually interpreted on Kripke models, for which a mathematically well-developed model theory is available. However, such models are inadequate to capture dynamic phenomena. Therefore, epistemic plausibility models have been introduced. Because these are much richer structures than Kripke models, they do not straightforwardly inherit the model-theoretical results of modal logic. Therefore, while epistemic plausibility structures are well-suited for modeling purposes, an extensive investigation of their model theory has been lacking so far. The aim of the present paper is to fill exactly this gap, by initiating a systematic exploration of the model theory of epistemic plausibility models. Like in 'ordinary' modal logic, the focus will be on the notion of bisimulation. We define various notions of bisimulations (parametrized by a language L) and show that L-bisimilarity implies L-equivalence. We prove a Hennesy-Milner type result, and also two undefinability results. However, our main point is a negative one, viz. that bisimulations cannot straightforwardly be generalized to epistemic plausibility models if conditional belief is taken into account. We present two ways of coping with this issue: (i) adding a modality to the language, and (ii) putting extra constraints on the models. Finally, we make some remarks about the interaction between bisimulation and dynamic model changes.


A New Framework for Cognitive Medium Access Control: POSG Approach

Abstract: In this paper, we propose a new analytical framework to solve medium access problem for secondary users (SUs) in cognitive radio networks. Partially Observable Stochastic Games (POSG) and Decentralized Markov Decision Process (Dec-POMDP) are two multi-agent Markovian decision processes which are used to present a solution. A primary network with two SUs is considered as an example to demonstrate our proposed framework. Two different scenarios are assumed. In the first scenario, SUs compete to acquire the licensed channel which is modeled using POSG framework. In the second one, SUs cooperate to access channel for which the solution is based on Dec-POMDP. Besides, the dominant strategy for both of the above mentioned scenarios is presented for a three slot horizon length.


The complexity of UNO

Abstract: This paper investigates the popular card game UNO from the viewpoint of algorithmic combinatorial game theory. We define simple and concise mathematical models for the game, including both cooperative and uncooperative versions, and analyze their computational complexity. In particular, we prove that even a single-player version of UNO is NP-complete, although some restricted cases are in P. Surprisingly, we show that the uncooperative two-player version is also in P.


Implementing Multi-Periodic Critical Systems: from Design to Code Generation

Abstract: This article presents a complete scheme for the development of Critical Embedded Systems with Multiple Real-Time Constraints. The system is programmed with a language that extends the synchronous approach with high-level real-time primitives. It enables to assemble in a modular and hierarchical manner several locally mono-periodic synchronous systems into a globally multi-periodic synchronous system. It also allows to specify flow latency constraints. A program is translated into a set of real-time tasks. The generated code (\C\ code) can be executed on a simple real-time platform with a dynamic-priority scheduler (EDF). The compilation process (each algorithm of the process, not the compiler itself) is formally proved correct, meaning that the generated code respects the real-time semantics of the original program (respect of periods, deadlines, release dates and precedences) as well as its functional semantics (respect of variable consumption).


Approaching optimality for solving SDD systems

Abstract: We present an algorithm that on input of an $n$-vertex $m$-edge weighted graph $G$ and a value $k$, produces an {\em incremental sparsifier} $\hat{G}$ with $n-1 + m/k$ edges, such that the condition number of $G$ with $\hat{G}$ is bounded above by $\tilde{O}(k\log^2 n)$, with probability $1-p$. The algorithm runs in time $$\tilde{O}((m \log{n} + n\log^2{n})\log(1/p)).$$ As a result, we obtain an algorithm that on input of an $n\times n$ symmetric diagonally dominant matrix $A$ with $m$ non-zero entries and a vector $b$, computes a vector ${x}$ satisfying $||{x}-A^{+}b||_A<\epsilon ||A^{+}b||_A $, in expected time $$\tilde{O}(m\log^2{n}\log(1/\epsilon)).$$ The solver is based on repeated applications of the incremental sparsifier that produces a chain of graphs which is then used as input to a recursive preconditioned Chebyshev iteration.


Non-oblivious Strategy Improvement

Abstract: We study strategy improvement algorithms for mean-payoff and parity games. We describe a structural property of these games, and we show that these structures can affect the behaviour of strategy improvement. We show how awareness of these structures can be used to accelerate strategy improvement algorithms. We call our algorithms non-oblivious because they remember properties of the game that they have discovered in previous iterations. We show that non-oblivious strategy improvement algorithms perform well on examples that are known to be hard for oblivious strategy improvement. Hence, we argue that previous strategy improvement algorithms fail because they ignore the structural properties of the game that they are solving.


On Generalizations of Network Design Problems with Degree Bounds

Abstract: Iterative rounding and relaxation have arguably become the method of choice in dealing with unconstrained and constrained network design problems. In this paper we extend the scope of the iterative relaxation method in two directions: (1) by handling more complex degree constraints in the minimum spanning tree problem (namely, laminar crossing spanning tree), and (2) by incorporating `degree bounds' in other combinatorial optimization problems such as matroid intersection and lattice polyhedra. We give new or improved approximation algorithms, hardness results, and integrality gaps for these problems.


An Algorithm for Index Multimedia Data (Video) using the Movement Oriented Method for Real-time Online Services

Abstract: Multimedia data is a form of data that can represent all types of data (images, sound and text). The use of multimedia data for the online application requires a more comprehensive database in the use of storage media, Sorting / indexing, search and system / data searching. This is necessary in order to help providers and users to access multimedia data online. Systems that use of the index image as a reference requires storage media so that the rules and require special expertise to obtain the desired file. Changes in multimedia data into a series of stories / storyboard in the form of a text will help reduce the consumption of media storage, system index / sorting and search applications. Oriented Movement is one method that is being developed to change the form of multimedia data into a storyboard.


Agreement Maintenance Based on Schema and Ontology Change in P2P Environment

Abstract: This paper is concern about developing a semantic agreement maintenance method based on semantic distance by calculating the change of local schema or ontology. This approach is important in dynamic and autonomous environment, in which the current approach assumed that agreement or mapping in static environment. The contribution of this research is to develop a framework based on semantic agreement maintenance approach for P2P environment. This framework based on two level hybrid P2P model architecture, which consist of two peer type: (1) super peer that use to register and manage the other peers, and (2) simple peer, as a simple peer, it exports and shares its contents with others. This research develop a model to maintain the semantic agreement in P2P environment, so the current approach which does not have the mechanism to know the change, since it assumed that ontology and local schema are in the static condition, and it is different in dynamic condition. The main issues are how to calculate the change of local schema or common ontology and the calculation result is used to determine which algorithm in maintaining the agreement. The experiment on the job matching domain in Indonesia have been done to show how far the performance of the approach. From the experiment, the main result are (i) the more change so the F-measure value tend to be decreased, (ii) there is no significant different in F-measure value for various modification type (add, delete, rename), and (iii) the correct choice of algorithm would improve the F-measure value.


Node Isolation Probability of Wireless Adhoc Networks in Nagakami Fading Channel

Abstract: This paper investigates the issue of connectivity of a wireless adhoc network in the presence of channel impairments. We derive analytical expressions for the node isolation probability in an adhoc network in the presence of Nakagami-m fading with superimposed lognormal shadowing. The node isolation probability is the probability that a randomly chosen node is not able to communicate with none of the other nodes in the network. An extensive investigation into the impact of path loss exponent, lognormal shadowing, Nakagami fading severity index, node density, and diversity order on the node isolation probability is conducted. The presented results are beneficial for the practical design of ad hoc networks.


Wireless Mesh Network Performance for Urban Search and Rescue Missions

Abstract: In this paper we demonstrate that the Canine Pose Estimation (CPE) system can provide a reliable estimate for some poses and when coupled with effective wireless transmission over a mesh network. Pose estimates are time sensitive, thus it is important that pose data arrives at its destination quickly. Propagation delay and packet delivery ratio measuring algorithms were developed and used to appraise Wireless Mesh Network (WMN) performance as a means of carriage for this time-critical data. The experiments were conducted in the rooms of a building where the radio characteristics closely resembled those of a partially collapsed building-a typical US&R environment. This paper presents the results of the experiments, which demonstrate that it is possible to receive the canine pose estimation data in realtime although accuracy of the results depend on the network size and the deployment environment.


Hierarchical Location Service with Prediction in Mobile Ad-Hoc Networks

Abstract: Position-based routing protocols take advantage of location information to perform a stateless and efficient routing. To enable position-based routing, a node must be able to discover the location of the messages' destination node. This task is typically accomplished by a location service. Recently, several location service protocols have been developed for ad hoc networks. In this paper we propose a novel location service called PHLS: Predictive Hierarchical Location Service. In PHLS, the entire network is partitioned into a hierarchy of smaller and smaller regions. For each node, one node in each-level region of the hierarchy is chosen as its local location server. When the network initializes or when a node attaches the network, nodes contact their local location server with their current location information (ie. position and velocity). Then, they only need to update their location server when they move away from their current region. Finally, nodes query their location servers and get the exact or predicted location of destination nodes.


Graphically E-Learning introduction and its benefits in Virtual Learning

Abstract: E-learning with using multimedia and graphical interfaces is now fashionable in some virtual learning environments. Especially, in open colleges, universities and E-learning databases, using these interfaces can improve quality of educating by increasing attraction of educational subjects. In this paper, we introduce this technology and its aspects by defining some Graphical User Interfaces (GUI). Improving some indexes in E-learning environments can be measured by using GUI. Adding some plug-ins in E-learning softwares and environments like relative sound, electronic noting paper and virtual classrooms can be created by E-learning GUI (ELGUI) as explain in this paper.


New designing of E-Learning systems with using network learning

Abstract: One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable for every education system and it is flexible with too positive results.


Strategic Cooperation in Cost Sharing Games

Abstract: In this paper we consider strategic cost sharing games with so-called arbitrary sharing based on various combinatorial optimization problems, such as vertex and set cover, facility location, and network design problems. We concentrate on the existence and computational complexity of strong equilibria, in which no coalition can improve the cost of each of its members. Our main result reveals a connection between strong equilibrium in strategic games and the core in traditional coalitional cost sharing games studied in economics. For set cover and facility location games this results in a tight characterization of the existence of strong equilibrium using the integrality gap of suitable linear programming formulations. Furthermore, it allows to derive all existing results for strong equilibria in network design cost sharing games with arbitrary sharing via a unified approach. In addition, we are able to show that in general the strong price of anarchy is always 1. This should be contrasted with the price of anarchy of \Theta(n) for Nash equilibria. Finally, we indicate that the LP-approach can also be used to compute near-optimal and near-stable approximate strong equilibria.


Querying Incomplete Data over Extended ER Schemata

Abstract: Since Chen's Entity-Relationship (ER) model, conceptual modeling has been playing a fundamental role in relational data design. In this paper we consider an extended ER (EER) model enriched with cardinality constraints, disjointness assertions, and is-a relations among both entities and relationships. In this setting, we consider the case of incomplete data, which is likely to occur, for instance, when data from different sources are integrated. In such a context, we address the problem of providing correct answers to conjunctive queries by reasoning on the schema. Based on previous results about decidability of the problem, we provide a query answering algorithm that performs rewriting of the initial query into a recursive Datalog query encoding the information about the schema. We finally show extensions to more general settings. This paper will appear in the special issue of Theory and Practice of Logic Programming (TPLP) titled Logic Programming in Databases: From Datalog to Semantic-Web Rules.


Private Information Disclosure from Web Searches. (The case of Google Web History)

Abstract: As the amount of personal information stored at remote service providers increases, so does the danger of data theft. When connections to remote services are made in the clear and authenticated sessions are kept using HTTP cookies, data theft becomes extremely easy to achieve. In this paper, we study the architecture of the world's largest service provider, i.e., Google. First, with the exception of a few services that can only be accessed over HTTPS (e.g., Gmail), we find that many Google services are still vulnerable to simple session hijacking. Next, we present the Historiographer, a novel attack that reconstructs the web search history of Google users, i.e., Google's Web History, even though such a service is supposedly protected from session hijacking by a stricter access control policy. The Historiographer uses a reconstruction technique inferring search history from the personalized suggestions fed by the Google search engine. We validate our technique through experiments conducted over real network traffic and discuss possible countermeasures. Our attacks are general and not only specific to Google, and highlight privacy concerns of mixed architectures using both secure and insecure connections.


Pattern recognition using inverse resonance filtration

Abstract: An approach to textures pattern recognition based on inverse resonance filtration (IRF) is considered. A set of principal resonance harmonics of textured image signal fluctuations eigen harmonic decomposition (EHD) is used for the IRF design. It was shown that EHD is invariant to textured image linear shift. The recognition of texture is made by transfer of its signal into unstructured signal which simple statistical parameters can be used for texture pattern recognition. Anomalous variations of this signal point on foreign objects. Two methods of 2D EHD parameters estimation are considered with the account of texture signal breaks presence. The first method is based on the linear symmetry model that is not sensitive to signal phase jumps. The condition of characteristic polynomial symmetry provides the model stationarity and periodicity. Second method is based on the eigenvalues problem of matrices pencil projection into principal vectors space of singular values decomposition (SVD) of 2D correlation matrix. Two methods of classification of retrieval from textured image foreign objects are offered.


Scalable, Time-Responsive, Digital, Energy-Efficient Molecular Circuits using DNA Strand Displacement

Abstract: We propose a novel theoretical biomolecular design to implement any Boolean circuit using the mechanism of DNA strand displacement. The design is scalable: all species of DNA strands can in principle be mixed and prepared in a single test tube, rather than requiring separate purification of each species, which is a barrier to large-scale synthesis. The design is time-responsive: the concentration of output species changes in response to the concentration of input species, so that time-varying inputs may be continuously processed. The design is digital: Boolean values of wires in the circuit are represented as high or low concentrations of certain species, and we show how to construct a single-input, single-output signal restoration gate that amplifies the difference between high and low, which can be distributed to each wire in the circuit to overcome signal degradation. This means we can achieve a digital abstraction of the analog values of concentrations. Finally, the design is energy-efficient: if input species are specified ideally (meaning absolutely 0 concentration of unwanted species), then output species converge to their ideal concentrations at steady-state, and the system at steady-state is in (dynamic) equilibrium, meaning that no energy is consumed by irreversible reactions until the input again changes. Drawbacks of our design include the following. If input is provided non-ideally (small positive concentration of unwanted species), then energy must be continually expended to maintain correct output concentrations even at steady-state. In addition, our fuel species - those species that are permanently consumed in irreversible reactions - are not "generic"; each gate in the circuit is powered by its own specific type of fuel species. Hence different circuits must be powered by different types of fuel. Finally, we require input to be given according to the dual-rail convention, so that an input of 0 is specified not only by the absence of a certain species, but by the presence of another. That is, we do not construct a "true NOT gate" that sets its output to high concentration if and only if its input's concentration is low. It remains an open problem to design scalable, time-responsive, digital, energy-efficient molecular circuits that additionally solve one of these problems, or to prove that some subset of their resolutions are mutually incompatible.


Towards trusted volunteer grid environments

Abstract: Intensive experiences show and confirm that grid environments can be considered as the most promising way to solve several kinds of problems relating either to cooperative work especially where involved collaborators are dispersed geographically or to some very greedy applications which require enough power of computing or/and storage. Such environments can be classified into two categories; first, dedicated grids where the federated computers are solely devoted to a specific work through its end. Second, Volunteer grids where federated computers are not completely devoted to a specific work but instead they can be randomly and intermittently used, at the same time, for any other purpose or they can be connected or disconnected at will by their owners without any prior notification. Each category of grids includes surely several advantages and disadvantages; nevertheless, we think that volunteer grids are very promising and more convenient especially to build a general multipurpose distributed scalable environment. Unfortunately, the big challenge of such environments is, however, security and trust. Indeed, owing to the fact that every federated computer in such an environment can randomly be used at the same time by several users or can be disconnected suddenly, several security problems will automatically arise. In this paper, we propose a novel solution based on identity federation, agent technology and the dynamic enforcement of access control policies that lead to the design and implementation of trusted volunteer grid environments.


H-MAC: A Hybrid MAC Protocol for Wireless Sensor Networks

Abstract: In this paper, we propose a hybrid medium access control protocol (H-MAC) for wireless sensor networks. It is based on the IEEE 802.11's power saving mechanism (PSM) and slotted aloha, and utilizes multiple slots dynamically to improve performance. Existing MAC protocols for sensor networks reduce energy consumptions by introducing variation in an active/sleep mechanism. But they may not provide energy efficiency in varying traffic conditions as well as they did not address Quality of Service (QoS) issues. H-MAC, the propose MAC protocol maintains energy efficiency as well as QoS issues like latency, throughput, and channel utilization. Our numerical results show that H-MAC has significant improvements in QoS parameters than the existing MAC protocols for sensor networks while consuming comparable amount of energy.


A Novel Solution to the Dynamic Routing and Wavelength Assignment Problem in Transparent Optical Networks

Abstract: We present an evolutionary programming algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in optical wavelength-division multiplexing (WDM) networks under wavelength continuity constraint. We assume an ideal physical channel and therefore neglect the blocking of connection requests due to the physical impairments. The problem formulation includes suitable constraints that enable the algorithm to balance the load among the individuals and thus results in a lower blocking probability and lower mean execution time than the existing bio-inspired algorithms available in the literature for the DRWA problems. Three types of wavelength assignment techniques, such as First fit, Random, and Round Robin wavelength assignment techniques have been investigated here. The ability to guarantee both low blocking probability without any wavelength converters and small delay makes the improved algorithm very attractive for current optical switching networks.


A Powerful Optimization Approach for the Multi Channel Dissemination Networks

Abstract: In the wireless environment, dissemination techniques may improve data access for the users. In this paper, we show a description of dissemination architecture that fits the overall telecommunication network. This architecture is designed to provide efficient data access and power saving for the mobile units. A concurrency control approach, MCD, is suggested for data consistency and conflict checking. A performance study shows that the power consumption, space overhead, and response time associated with MCD is far less than other previous techniques.


An Efficient Approach for Generalized Load Balancing in Multipath Packet Switched Networks

Abstract: This paper is a quantitative analysis on packet switched network with a view to generalize load balancing and determination of appropriate routing algorithm in multipath environment. Several routing algorithms have been introduced for routing of packets from source to destination. Some of them route packets accurately with increased workload and some of them drastically cut down the workload. A few of them can find out a minimum workload deviation for both UDP and TCP packets. We simulated these approaches in a well defined simulator, analyzed and evaluated their performance. After expanding our analysis with varying weights and number of paths we found that the recently proposed routing algorithm Mixed Weighted Fair Routing (MWFR) outperforms the existing routing algorithms by reducing the routing and network overhead and saving the scarce bandwidth as well as CPU consumption for packet switching networks.


Delay-Constrained Multicast Routing Algorithm Based on Average Distance Heuristic

Abstract: Multicast is the ability of a communication network to accept a single message from an application and to deliver copies of the message to multiple recipients at different location. With the development of Internet, Multicast is widely applied in all kinds of multimedia real-time application: distributed multimedia systems, collaborative computing, video-conferencing, distance education, etc. In order to construct a delay-constrained multicast routing tree, average distance heuristic (ADH) algorithm is analyzed firstly. Then a delay-constrained algorithm called DCADH (delay-constrained average distance heuristic) is presented. By using ADH a least cost multicast routing tree can be constructed; if the path delay can't meet the delay upper bound, a shortest delay path which is computed by Dijkstra algorithm will be merged into the existing multicast routing tree to meet the delay upper bound. Simulation experiments show that DCADH has a good performance in achieving a low-cost multicast routing tree.


Mobile Codes Localization in Ad hoc Networks: a Comparative Study of Centralized and Distributed Approaches

Abstract: This paper presents a new approach in the management of mobile ad hoc networks. Our alternative, based on mobile agent technology, allows the design of mobile centralized server in ad hoc network, where it is not obvious to think about a centralized management, due to the absence of any administration or fixed infrastructure in these networks. The aim of this centralized approach is to provide permanent availability of services in ad hoc networks which are characterized by a distributed management. In order to evaluate the performance of the proposed approach, we apply it to solve the problem of mobile code localization in ad hoc networks. A comparative study, based upon a simulation, of centralized and distributed localization protocols in terms of messages number exchanged and response time shows that the centralized approach in a distributed form is more interesting than a totally centralized approach.


Resource Pricing In A Dynamic Multi-Commodity Market For Computational Resources

Abstract: The adoption of market-based principles in resource management systems for computational infrastructures such as grids and clusters allows for matching demand and supply for resources in a utility maximizing manner. As such, they offer a promise of producing more efficient resource allocations, compared to traditional system-centric approaches that do not allow consumers and providers to express their valuations for computational resources. In this paper, we investigate the pricing of resources in grids through the use of a computational commodity market of CPU resources, where resource prices are determined through the computation of a supply-and-demand equilibrium. In particular, we introduce several categories of CPUs characterized by their execution speed. These differ in cost and performance but may be used interchangeably in executing jobs and thus represent so-called substitutable resources. We investigate the performance of the algorithms for computing the supply-and-demand equilibrium in this multi-commodity setting under dynamically varying consumer and provider populations.


Innovative Rated-Resource Peer-to-Peer Network

Abstract: Peer-to-Peer (P2P) networks provide a significant solution for file sharing among peers connected to Internet. It is fast and completely decentralised system with robustness. But due to absence of a server documents on a P2P network are not rated which makes it difficult for a peer to obtain precise information in result of a query. In past, some researchers tried to attach ratings to the peers itself but it was complex and less effective. In this paper, a novel P2P architecture is proposed which attaches ratings to the uploaded document directly. These ratings then become as <Rating> element in its XML advertisement which has several child elements for information classification. The attached <Rating> element is extracted from the advertisement in real time and the document is then sorted accordingly. Therefore, the information can be easily sorted based on a request by a peer according to the relevance of matter. The information regarding relevance is obtained by the peer issuing the query. This research leads to a smart P2P model, the Rated-Resource P2P network (R2P2P).


Cloud Process Execution Engine - Evaluation of the Core Concepts

Abstract: In this technical report we describe describe the Domain Specific Language (DSL) of the Workflow Execution Execution (WEE). Instead of interpreting an XML based workflow description language like BPEL, the WEE uses a minimized but expressive set of statements that runs directly on to of a virtual machine that supports the Ruby language.Frameworks/Virtual Machines supporting supporting this language include Java, .NET and there exists also a standalone Virtual Machine. Using a DSL gives us the advantage of maintaining a very compact code base of under 400 lines of code, as the host programming language implements all the concepts like parallelism, threads, checking for syntactic correctness. The implementation just hooks into existing statements to keep track of the workflow and deliver information about current existing context variables and state to the environment that embeds WEE.


An Algebraic Formalization of the GoF Design Patterns

Abstract: This document reports on the use of an algebraic, visual, formal approach to the specification of patterns for the formalization of the GoF design patterns. The approach is based on graphs, morphisms and operations from category theory and exploits triple graphs to annotate model elements with pattern roles. Being based on category theory, the approach can be applied to formalize patterns in different domains. Novel in our proposal is the possibility of describing (nested) variable submodels, inter-pattern synchronization across several diagrams (e.g. class and sequence diagrams for UML design patterns), pattern composition, and conflict analysis.


Adding HL7 version 3 data types to PostgreSQL

Abstract: The HL7 standard is widely used to exchange medical information electronically. As a part of the standard, HL7 defines scalar communication data types like physical quantity, point in time and concept descriptor but also complex types such as interval types, collection types and probabilistic types. Typical HL7 applications will store their communications in a database, resulting in a translation from HL7 concepts and types into database types. Since the data types were not designed to be implemented in a relational database server, this transition is cumbersome and fraught with programmer error. The purpose of this paper is two fold. First we analyze the HL7 version 3 data type definitions and define a number of conditions that must be met, for the data type to be suitable for implementation in a relational database. As a result of this analysis we describe a number of possible improvements in the HL7 specification. Second we describe an implementation in the PostgreSQL database server and show that the database server can effectively execute scientific calculations with units of measure, supports a large number of operations on time points and intervals, and can perform operations that are akin to a medical terminology server. Experiments on synthetic data show that the user defined types perform better than an implementation that uses only standard data types from the database server.


Stability and Capacity Regions or Discrete Time Queueing Networks

Abstract: We consider stability and network capacity in discrete time queueing systems. Relationships between four common notions of stability are described. Specifically, we consider rate stability, mean rate stability, steady state stability, and strong stability. We then consider networks of queues with random events and control actions that can be implemented over time to affect arrivals and service at the queues. The control actions also generate a vector of additional network attributes. We characterize the network capacity region, being the closure of the set of all rate vectors that can be supported subject to network stability and to additional time average attribute constraints. We show that (under mild technical assumptions) the capacity region is the same under all four stability definitions. Our capacity achievability proof uses the drift-plus-penalty method of Lyapunov optimization, and provides full details for the case when network states obey a decaying memory property, which holds for finite state ergodic systems and more general systems.


Exponential Lower Bounds For Policy Iteration

Abstract: We study policy iteration for infinite-horizon Markov decision processes. It has recently been shown policy iteration style algorithms have exponential lower bounds in a two player game setting. We extend these lower bounds to Markov decision processes with the total reward and average-reward optimality criteria.


Hiding Inside HTML and Other Source Codes

Abstract: Many steganographic techniques were proposed for hiding secret message inside images, the simplest of them being the LSB data hiding. In this paper, we suggest a novel data hiding technique in an HTML Web page and also propose some simple techniques to extend the embedding technique to source codes written in any programming language (both case insensitive like HTML, Pascal and case sensitive languages like C, C++, Java). We basically try to exploit the case-redundancy in case-insensitive language, while we try hiding data with minimal changes in the source code (almost not raising suspicion). HTML Tags are case insensitive and hence an alphabet in lowercase and one in uppercase present inside an HTML tag are interpreted in the same manner by the browser, i.e., change in case in a web page is imperceptible to the browser. We first exploit this redundancy and use it to embed secret data inside an web page, with no changes visible to the user of the web page, so that he can not even suspect about the data hiding. The embedded data can be recovered by viewing the source of the HTML page. This technique can easily be extended to embed secret message inside any piece of source-code where the standard interpreter of that language is case-insensitive. For case-sensitive programming languages we do minimal changes in the source code (e.g., add an extra character in the token identified by the lexical analyzer) without violating the lexical and syntactic notation for that language) and try to make the change almost imperceptible.


Geometric reconstruction from point-normal data

Abstract: Creating virtual models of real spaces and objects is cumbersome and time consuming. This paper focuses on the problem of geometric reconstruction from sparse data obtained from certain image-based modeling approaches. A number of elegant and simple-to-state problems arise concerning when the geometry can be reconstructed. We describe results and counterexamples, and list open problems.


Topic Map: An Ontology Framework for Information Retrieval

Abstract: The basic classification techniques for organizing information are thesauri, taxonomy and faceted classification. Topic map is relatively a new entrant to this information space. Topic map standard describes how complex relationships between abstract concepts and real world resources can be represented using XML syntax. This paper explores how topic map incorporates the traditional techniques and what are its advantages and disadvantages in several dimensions such as content management, indexing, knowledge representation, constraint specification and query languages in the context of information retrieval. The constructs of topic maps are illustrated with a use-case implemented in XTM


Towards Automated Lecture Capture, Navigation and Delivery System for Web-Lecture on Demand

Abstract: Institutions all over the world are continuously exploring ways to use ICT in improving teaching and learning effectiveness. The use of course web pages, discussion groups, bulletin boards, and e-mails have shown considerable impact on teaching and learning in significant ways, across all disciplines. ELearning has emerged as an alternative to traditional classroom-based education and training and web lectures can be a powerful addition to traditional lectures. They can even serve as a main content source for learning, provided users can quickly navigate and locate relevant pages in a web lecture. A web lecture consists of video and audio of the presenter and slides complemented with screen capturing. In this paper, an automated approach for recording live lectures and for browsing available web lectures for on-demand applications by end users is presented.


Computing the Fewest-turn Map Directions based on the Connectivity of Natural Roads

Abstract: In this paper, we introduced a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach relies on the connectivity of natural roads rather than that of road segments for computing routes or map directions. Because of this, the derived routes posses the fewest turns. However, what we intend to achieve are the routes that not only possess the fewest turns, but are also as short as possible. This kind of map direction is more effective and favorable by people, because they bear less cognitive burden. Furthermore, the computation of the routes is more efficient, since it is based on the graph encoding the connectivity of roads, which is significantly smaller than the graph of road segments. We made experiments applied to eight urban street networks from North America and Europe in order to illustrate the above stated advantages. The experimental results indicate that the fewest-turn routes posses fewer turns and shorter distances than the simplest paths and the routes provided by Google Maps. For example, the fewest-turn-and-shortest routes are on average 15% shorter than the routes suggested by Google Maps, while the number of turns is just half as much. This approach is a key technology behind FromToMap.org - a web mapping service using openstreetmap data.


Simulated Annealing for Location Area Planning in Cellular networks

Abstract: LA planning in cellular network is useful for minimizing location management cost in GSM network. In fact, size of LA can be optimized to create a balance between the LA update rate and expected paging rate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithm is used. Simulated annealing give optimal results in acceptable run-time.


Simulation to track 3D location in GSM through NS2 and real life

Abstract: In recent times the cost of mobile communication has dropped significantly leading to a dramatic increase in mobile phone usage. The widespread usage has led mobiles to emerge as a strong alternative for other applications one of which is tracking. This has enabled law-enforcing agencies to detect overspeeding vehicles and organizations to keep track its employees. The 3 major ways of tracking being employed presently are (a) via GPS [1] (b) signal attenuation property of a packet [3] and (c) using GSM Network [2]. The initial cost of GPS is very high resulting in low usage whereas (b) needs a very high precision measuring device. The paper presents a GSM-based tracking technique which eliminates the above mentioned overheads, implements it in NS2 and shows the limitations of the real life simulation. An accuracy of 97% was achieved during NS2 simulation which is comparable to the above mentioned alternate methods of tracking.


Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless Personal Area Network System

Abstract: For high data rate ultra wideband communication system, performance comparison of Rake, MMSE and Rake-MMSE receivers is attempted in this paper. Further a detail study on Rake-MMSE time domain equalizers is carried out taking into account all the important parameters such as the effect of the number of Rake fingers and equalizer taps on the error rate performance. This receiver combats inter-symbol interference by taking advantages of both the Rake and equalizer structure. The bit error rate performances are investigated using MATLAB simulation on IEEE 802.15.3a defined UWB channel models. Simulation results show that the bit error rate probability of Rake-MMSE receiver is much better than Rake receiver and MMSE equalizer. Study on non-line of sight indoor channel models illustrates that bit error rate performance of Rake-MMSE (both LE and DFE) improves for CM3 model with smaller spread compared to CM4 channel model. It is indicated that for a MMSE equalizer operating at low to medium SNR values, the number of Rake fingers is the dominant factor to improve system performance, while at high SNR values the number of equalizer taps plays a more significant role in reducing the error rate.


Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing in Wireless Sensor Networks

Abstract: There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.


Secure Key Exchange and Encryption Mechanism for Group Communication in Wireless Ad Hoc Networks

Abstract: Secured communication in ad hoc wireless networks is primarily important, because the communication signals are openly available as they propagate through air and are more susceptible to attacks ranging from passive eavesdropping to active interfering. The lack of any central coordination and shared wireless medium makes them more vulnerable to attacks than wired networks. Nodes act both as hosts and routers and are interconnected by Multi- hop communication path for forwarding and receiving packets to/from other nodes. The objective of this paper is to propose a key exchange and encryption mechanism that aims to use the MAC address as an additional parameter as the message specific key[to encrypt]and forward data among the nodes. The nodes are organized in spanning tree fashion, as they avoid forming cycles and exchange of key occurs only with authenticated neighbors in ad hoc networks, where nodes join or leave the network dynamically.