A Cognitive Mind-map Framework to Foster Trust

Abstract: The explorative mind-map is a dynamic framework, that emerges automatically from the input, it gets. It is unlike a verificative modeling system where existing (human) thoughts are placed and connected together. In this regard, explorative mind-maps change their size continuously, being adaptive with connectionist cells inside; mind-maps process data input incrementally and offer lots of possibilities to interact with the user through an appropriate communication interface. With respect to a cognitive motivated situation like a conversation between partners, mind-maps become interesting as they are able to process stimulating signals whenever they occur. If these signals are close to an own understanding of the world, then the conversational partner becomes automatically more trustful than if the signals do not or less match the own knowledge scheme. In this (position) paper, we therefore motivate explorative mind-maps as a cognitive engine and propose these as a decision support engine to foster trust.


Algorithmic Aspects of Several Data Transfer Service Optimization Problems

Abstract: Optimized data transfer services are highly demanded nowadays, due to the large amounts of data which are frequently being produced and accessed. In this paper we consider several data transfer service optimization problems (optimal server location in path networks, optimal packet sequencing and minimum makespan packet scheduling), for which we provide novel algorithmic solutions.


An Algorithmic Perspective on Some Network Design, Construction and Analysis Problems

Abstract: Efficient network design, construction and analysis are important topics, considering the highly dynamic environment in which data communication occurs nowadays. In this paper we address several problems concerning these topics from an algorithmic point of view.


Polynomial Time Algorithms for Minimum Energy Scheduling

Abstract: The aim of power management policies is to reduce the amount of energy consumed by computer systems while maintaining satisfactory level of performance. One common method for saving energy is to simply suspend the system during the idle times. No energy is consumed in the suspend mode. However, the process of waking up the system itself requires a certain fixed amount of energy, and thus suspending the system is beneficial only if the idle time is long enough to compensate for this additional energy expenditure. In the specific problem studied in the paper, we have a set of jobs with release times and deadlines that need to be executed on a single processor. Preemptions are allowed. The processor requires energy L to be woken up and, when it is on, it uses one unit of energy per one unit of time. It has been an open problem whether a schedule minimizing the overall energy consumption can be computed in polynomial time. We solve this problem in positive, by providing an O(n^5)-time algorithm. In addition we provide an O(n^4)-time algorithm for computing the minimum energy schedule when all jobs have unit length.


Predictability of Fixed-Job Priority Schedulers on Heterogeneous Multiprocessor Real-Time Systems

Abstract: The multiprocessor Fixed-Job Priority (FJP) scheduling of real-time systems is studied. An important property for the schedulability analysis, the predictability (regardless to the execution times), is studied for heterogeneous multiprocessor platforms. Our main contribution is to show that any FJP schedulers are predictable on unrelated platforms. A convenient consequence is the fact that any FJP schedulers are predictable on uniform multiprocessors.


Cognitive Dimensions Analysis of Interfaces for Information Seeking

Abstract: Cognitive Dimensions is a framework for analyzing human-computer interaction. It is used for meta-analysis, that is, for talking about characteristics of systems without getting bogged down in details of a particular implementation. In this paper, I discuss some of the dimensions of this theory and how they can be applied to analyze information seeking interfaces. The goal of this analysis is to introduce a useful vocabulary that practitioners and researchers can use to describe systems, and to guide interface design toward more usable and useful systems


Notes on large angle crossing graphs

Abstract: A graph G is an a-angle crossing (aAC) graph if every pair of crossing edges in G intersect at an angle of at least a. The concept of right angle crossing (RAC) graphs (a=Pi/2) was recently introduced by Didimo et. al. It was shown that any RAC graph with n vertices has at most 4n-10 edges and that there are infinitely many values of n for which there exists a RAC graph with n vertices and 4n-10 edges. In this paper, we give upper and lower bounds for the number of edges in aAC graphs for all 0 < a < Pi/2.


Tracing Technique for Blaster Attack

Abstract: Blaster worm of 2003 is still persistent, the infection appears to have successfully transitioned to new hosts as the original systems are cleaned or shut off, suggesting that the Blaster worm, and other similar worms, will remain significant Internet threats for many years after their initial release. This paper is to propose technique on tracing the Blaster attack from various logs in different OSI layers based on fingerprint of Blaster attack on victim logs, attacker logs and IDS alert log. The researchers intended to do a preliminary investigation upon this particular attack so that it can be used for further research in alert correlation and computer forensic investigation.


Maximizing profit using recommender systems

Abstract: Traditional recommendation systems make recommendations based solely on the customer's past purchases, product ratings and demographic data without considering the profitability the items being recommended. In this work we study the question of how a vendor can directly incorporate the profitability of items into its recommender so as to maximize its expected profit while still providing accurate recommendations. Our approach uses the output of any traditional recommender system and adjust them according to item profitabilities. Our approach is parameterized so the vendor can control how much the recommendation incorporating profits can deviate from the traditional recommendation. We study our approach under two settings and show that it achieves approximately 22% more profit than traditional recommendations.


Lazy mixin modules and disciplined effects

Abstract: Programming languages are expected to support programmer's effort to structure program code. The ML module system, object systems and mixins are good examples of language constructs promoting modular programming. Among the three, mixins can be thought of as a generalization of the two others in the sense that mixins can incorporate features of ML modules and objects with a set of primitive operators with clean semantics. Much work has been devoted to build mixin-based module systems for practical programming languages. In respect of the operational semantics, previous work notably investigated mixin calculi in call-by-name and call-by-value evaluation settings. In this paper we examine a mixin calculus in a call-by-need, or lazy, evaluation setting. We demonstrate how lazy mixins can be interesting in practice with a series of examples, and formalize the operational semantics by adapting Ancona and Zucca's concise formalization of call-by-name mixins. We then extend the semantics with constraints to control the evaluation order of components of mixins in several ways. The main motivation for considering the constraints is to produce side effects in a more explicit order than in a purely lazy, demand-driven setting. We explore the design space of possibly interesting constraints and consider two examples in detail.


Optimal Geometric Partitions, Covers and K-Centers

Abstract: In this paper we present some new, practical, geometric optimization techniques for computing polygon partitions, 1D and 2D point, interval, square and rectangle covers, as well as 1D and 2D interval and rectangle K-centers. All the techniques we present have immediate applications to several cost optimization and facility location problems which are quite common in practice. The main technique employed is dynamic programming, but we also make use of efficient data structures and fast greedy algorithms.


A DHT Based Measure of Randomness

Abstract: This paper presents a new discrete Hilbert transform (DHT) based measure of randomness for discrete sequences. The measure has been used to test three different classes of sequences with satisfactory results.


Overlapping Multi-hop Clustering for Wireless Sensor Networks

Abstract: Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Traditionally, clustering algorithms aim at generating a number of disjoint clusters that satisfy some criteria. In this paper, we formulate a novel clustering problem that aims at generating overlapping multi-hop clusters. Overlapping clusters are useful in many sensor network applications, including inter-cluster routing, node localization, and time synchronization protocols. We also propose a randomized, distributed multi-hop clustering algorithm (KOCA) for solving the overlapping clustering problem. KOCA aims at generating connected overlapping clusters that cover the entire sensor network with a specific average overlapping degree. Through analysis and simulation experiments we show how to select the different values of the parameters to achieve the clustering process objectives. Moreover, the results show that KOCA produces approximately equal-sized clusters, which allows distributing the load evenly over different clusters. In addition, KOCA is scalable; the clustering formation terminates in a constant time regardless of the network size.


Carnival of Samplings: Nets, Approximations, Relative and Sensitive

Abstract: We survey several results known on sampling in computational geometry.


An Oblivious O(1)-Approximation for Single Source Buy-at-Bulk

Abstract: We consider the single-source (or single-sink) buy-at-bulk problem with an unknown concave cost function. We want to route a set of demands along a graph to or from a designated root node, and the cost of routing x units of flow along an edge is proportional to some concave, non-decreasing function f such that f(0) = 0. We present a polynomial time algorithm that finds a distribution over trees such that the expected cost of a tree for any f is within an O(1)-factor of the optimum cost for that f. The previous best simultaneous approximation for this problem, even ignoring computation time, was O(log |D|), where D is the multi-set of demand nodes. We design a simple algorithmic framework using the ellipsoid method that finds an O(1)-approximation if one exists, and then construct a separation oracle using a novel adaptation of the Guha, Meyerson, and Munagala algorithm for the single-sink buy-at-bulk problem that proves an O(1) approximation is possible for all f. The number of trees in the support of the distribution constructed by our algorithm is at most 1+log |D|.


On Continuous Weighted Finite Automata

Abstract: We investigate the continuity of the \omega-functions and real functions defined by weighted finite automata (WFA). We concentrate on the case of average preserving WFA. We show that every continuous \omega-function definable by some WFA can be defined by an average preserving WFA and then characterize minimal average preserving WFA whose \omega-function or \omega-function and real function are continuous. We obtain several algorithmic reductions for WFA-related decision problems. In particular, we show that deciding whether the \omega-function and real function of an average preserving WFA are both continuous is computationally equivalent to deciding stability of a set of matrices. We also present a method for constructing WFA that compute continuous real functions.


On the Expressiveness of Line Drawings

Abstract: Can expressiveness of a drawing be traced with a computer? In this study a neural network (perceptron) and a support vector machine are used to classify line drawings. To do this the line drawings are attributed values according to a kinematic model and a diffusion model for the lines they consist of. The values for both models are related to looking times. Extreme values according to these models, that is both extremely short and extremely long looking times, are interpreted as indicating expressiveness. The results strongly indicate that expressiveness in this sense can be detected, at least with a neural network.


Spreading grid cells

Abstract: Let $S$ be a set of $n^2$ symbols. Let $A$ be an $n\times n$ square grid with each cell labeled by a distinct symbol in $S$. Let $B$ be another $n\times n$ square grid, also with each cell labeled by a distinct symbol in $S$. Then each symbol in $S$ labels two cells, one in $A$ and one in $B$. Define the \emph{combined distance} between two symbols in $S$ as the distance between the two cells in $A$ plus the distance between the two cells in $B$ that are labeled by the two symbols. Bel\'en Palop asked the following question at the open problems session of CCCG 2009: How to arrange the symbols in the two grids such that the minimum combined distance between any two symbols is maximized? In this paper, we give a partial answer to Bel\'en Palop's question. Define $c_p(n) = \max_{A,B}\min_{s,t \in S} \{\dist_p(A,s,t) + \dist_p(B,s,t) \}$, where $A$ and $B$ range over all pairs of $n\times n$ square grids labeled by the same set $S$ of $n^2$ distinct symbols, and where $\dist_p(A,s,t)$ and $\dist_p(B,s,t)$ are the $L_p$ distances between the cells in $A$ and in $B$, respectively, that are labeled by the two symbols $s$ and $t$. We present asymptotically optimal bounds $c_p(n) = \Theta(\sqrt{n})$ for all $p=1,2,...,\infty$. The bounds also hold for generalizations to $d$-dimensional grids for any constant $d \ge 2$. Our proof yields a simple linear-time constant-factor approximation algorithm for maximizing the minimum combined distance between any two symbols in two grids.


Graph-Theoretic Solutions to Computational Geometry Problems

Abstract: Many problems in computational geometry are not stated in graph-theoretic terms, but can be solved efficiently by constructing an auxiliary graph and performing a graph-theoretic algorithm on it. Often, the efficiency of the algorithm depends on the special properties of the graph constructed in this way. We survey the art gallery problem, partition into rectangles, minimum-diameter clustering, rectilinear cartogram construction, mesh stripification, angle optimization in tilings, and metric embedding from this perspective.


A Dynamic Boundary Guarding Problem with Translating Targets

Abstract: We introduce a problem in which a service vehicle seeks to guard a deadline (boundary) from dynamically arriving mobile targets. The environment is a rectangle and the deadline is one of its edges. Targets arrive continuously over time on the edge opposite the deadline, and move towards the deadline at a fixed speed. The goal for the vehicle is to maximize the fraction of targets that are captured before reaching the deadline. We consider two cases; when the service vehicle is faster than the targets, and; when the service vehicle is slower than the targets. In the first case we develop a novel vehicle policy based on computing longest paths in a directed acyclic graph. We give a lower bound on the capture fraction of the policy and show that the policy is optimal when the distance between the target arrival edge and deadline becomes very large. We present numerical results which suggest near optimal performance away from this limiting regime. In the second case, when the targets are slower than the vehicle, we propose a policy based on servicing fractions of the translational minimum Hamiltonian path. In the limit of low target speed and high arrival rate, the capture fraction of this policy is within a small constant factor of the optimal.


SocialFilter: Collaborative Spam Mitigation using Social Networks

Abstract: Spam mitigation can be broadly classified into two main approaches: a) centralized security infrastructures that rely on a limited number of trusted monitors to detect and report malicious traffic; and b) highly distributed systems that leverage the experiences of multiple nodes within distinct trust domains. The first approach offers limited threat coverage and slow response times, and it is often proprietary. The second approach is not widely adopted, partly due to the lack of guarantees regarding the trustworthiness of nodes that comprise the system. Our proposal, SocialFilter, aims to achieve the trustworthiness of centralized security services and the wide coverage, responsiveness and inexpensiveness of large-scale collaborative spam mitigation. We propose a large-scale distributed system that enables clients with no email classification functionality to query the network on the behavior of a host. A SocialFilter node builds trust for its peers by auditing their behavioral reports and by leveraging the social network of SocialFilter administrators. The node combines the confidence its peers have in their own reports and the trust it places on its peers to derive the likelihood that a host is spamming. The simulation-based evaluation of our approach indicates its potential under a real-world deployment: during a simulated spam campaign, SocialFilternodes characterized 92% of spam bot connections with confidence greater than 50%, while yielding no false positives


Enhancing XML Data Warehouse Query Performance by Fragmentation

Abstract: XML data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. However, XML-native database systems currently suffer from limited performances in terms of manageable data volume and response time for complex analytical queries. Fragmenting and distributing XML data warehouses (e.g., on data grids) allow to address both these issues. In this paper, we work on XML warehouse fragmentation. In relational data warehouses, several studies recommend the use of derived horizontal fragmentation. Hence, we propose to adapt it to the XML context. We particularly focus on the initial horizontal fragmentation of dimensions' XML documents and exploit two alternative algorithms. We experimentally validate our proposal and compare these alternatives with respect to a unified XML warehouse model we advocate for.


An improved axiomatic definition of information granulation

Abstract: To capture the uncertainty of information or knowledge in information systems, various information granulations, also known as knowledge granulations, have been proposed. Recently, several axiomatic definitions of information granulation have been introduced. In this paper, we try to improve these axiomatic definitions and give a universal construction of information granulation by relating information granulations with a class of functions of multiple variables. We show that the improved axiomatic definition has some concrete information granulations in the literature as instances.


jYang : A YANG parser in java

Abstract: The NETCONF configuration protocol of the IETF Network Work- ing Group provides mechanisms to manipulate the configuration of network devices. YANG is the language currently under consideration within the IETF to specify the data models to be used in NETCONF . This report describes the design and development of a syntax and semantics parser for YANG in java.


Recombinations of Busy Beaver Machines

Abstract: Many programmers belive that Turing-based machines cannot think. We also believe in this, however it is interesting to note that the most sophisticated machines are not programmed by human beings. We have only discovered them. In this paper, using well-known Busy Beaver and Placid Platypus machines, we generate further very similar, but not exactly the same machines. We have found a recombinated BB_5 machine which can make 70.740.809 steps before halting.


On Relating Edges in Graphs without Cycles of Length 4

Abstract: An edge xy is relating in the graph G if there is an independent set S, containing neither x nor y, such that S_{x} and S_{y} are both maximal independent sets in G. It is an NP-complete problem to decide whether an edge is relating (Brown, Nowakowski, Zverovich, 2007). We show that the problem remains NP-complete even for graphs without cycles of length 4 and 5. On the other hand, for graphs without cycles of length 4 and 6, the problem can be solved in polynomial time.


Complexity of Planar Embeddability of Trees inside Simple Polygons

Abstract: Geometric embedding of graphs in a point set in the plane is a well known problem. In this paper, the complexity of a variant of this problem, where the point set is bounded by a simple polygon, is considered. Given a point set in the plane bounded by a simple polygon and a free tree, we show that deciding whether there is a planar straight-line embedding of the tree on the point set inside the simple polygon is NP-complete. This implies that the straight-line constrained point-set embedding of trees is also NP-complete, which was posed as an open problem in [8].


Semi-algebraic Range Reporting and Emptiness Searching with Applications

Abstract: In a typical range emptiness searching (resp., reporting) problem, we are given a set $P$ of $n$ points in $\reals^d$, and wish to preprocess it into a data structure that supports efficient range emptiness (resp., reporting) queries, in which we specify a range $\sigma$, which, in general, is a semi-algebraic set in $\reals^d$ of constant description complexity, and wish to determine whether $P\cap\sigma=\emptyset$, or to report all the points in $P\cap\sigma$. Range emptiness searching and reporting arise in many applications, and have been treated by Matou\v{s}ek \cite{Ma:rph} in the special case where the ranges are halfspaces bounded by hyperplanes. As shown in \cite{Ma:rph}, the two problems are closely related, and have solutions (for the case of halfspaces) with similar performance bounds. In this paper we extend the analysis to general semi-algebraic ranges, and show how to adapt Matou\v{s}ek's technique, without the need to {\em linearize} the ranges into a higher-dimensional space. This yields more efficient solutions to several useful problems, and we demonstrate the new technique in four applications.


Optimization of Bit Plane Combination for Efficient Digital Image Watermarking

Abstract: In view of the frequent multimedia data transfer authentication and protection of images has gained importance in todays world. In this paper we propose a new watermarking technique, based on bit plane, which enhances robustness and capacity of the watermark, as well as maintains transparency of the watermark and fidelity of the image. In the proposed technique, higher strength bit plane of digital signature watermark is embedded in to a significant bit plane of the original image. The combination of bit planes (image and watermark) selection is an important issue. Therefore, a mechanism is developed for appropriate bit plane selection. Ten different attacks are selected to test different alternatives. These attacks are given different weightings as appropriate to user requirement. A weighted correlation coefficient for retrieved watermark is estimated for each of the alternatives. Based on these estimated values optimal bit plane combination is identified for a given user requirement. The proposed method is found to be useful for authentication and to prove legal ownership. We observed better results by our proposed method in comparison with the previously reported work on pseudorandom watermark embedded in least significant bit (LSB) plane.


Retrieval of Remote Sensing Images Using Colour and Texture Attribute

Abstract: Grouping images into semantically meaningful categories using low-level visual feature is a challenging and important problem in content-based image retrieval. The groupings can be used to build effective indices for an image database. Digital image analysis techniques are being used widely in remote sensing assuming that each terrain surface category is characterized with spectral signature observed by remote sensors. Even with the remote sensing images of IRS data, integration of spatial information is expected to assist and to improve the image analysis of remote sensing data. In this paper we present a satellite image retrieval based on a mixture of old fashioned ideas and state of the art learning tools. We have developed a methodology to classify remote sensing images using HSV color features and Haar wavelet texture features and then grouping them on the basis of particular threshold value. The experimental results indicate that the use of color and texture feature extraction is very useful for image retrieval.


Efficient Authenticated Data Structures for Graph Connectivity and Geometric Search Problems

Abstract: Authenticated data structures provide cryptographic proofs that their answers are as accurate as the author intended, even if the data structure is being controlled by a remote untrusted host. We present efficient techniques for authenticating data structures that represent graphs and collections of geometric objects. We introduce the path hash accumulator, a new primitive based on cryptographic hashing for efficiently authenticating various properties of structured data represented as paths, including any decomposable query over sequences of elements. We show how to employ our primitive to authenticate queries about properties of paths in graphs and search queries on multi-catalogs. This allows the design of new, efficient authenticated data structures for fundamental problems on networks, such as path and connectivity queries over graphs, and complex queries on two-dimensional geometric objects, such as intersection and containment queries.


ABC-LogitBoost for Multi-class Classification

Abstract: We develop abc-logitboost, based on the prior work on abc-boost and robust logitboost. Our extensive experiments on a variety of datasets demonstrate the considerable improvement of abc-logitboost over logitboost and abc-mart.


Consideration Points Detecting Cross-Site Scripting

Abstract: Web application (WA) expands its usages to provide more and more services and it has become one of the most essential communication channels between service providers and the users. To augment the users experience many web applications are using client side scripting languages such as JavaScript but this growing of JavaScript is increasing serious security vulnerabilities in web application too, such as cross site scripting (XSS). In this paper, I survey all the techniques those have been used to detect XSS and arrange a number of analyses to evaluate performances of those methodologies. This paper points major difficulties to detect XSS. I do not implement any solution of this vulnerability problem because my focus is for reviewing this issue. But, I believe that this assessment will be cooperative for further research on this concern as this treatise figure out everything on this transcendent security problem.


Experimental Performances Analysis of Load Balancing Algorithms in IEEE 802.11

Abstract: In IEEE 802.11, load balancing algorithms (LBA) consider only the associated stations to balance the load of the available access points (APs). However, although the APs are balanced, it causes a bad situation if the AP has a lower signal length (SNR) less than the neighbor APs. So, balance the load and associate one mobile station to an access point without care about the signal to noise ratio (SNR) of the AP cause possibly an unforeseen QoS, such as the bit rate, the end to end delay, the packet loss. In this way, we study an improvement load balancing algorithm with SNR integration at the selection policy.


Bridging the Gap between Crisis Response Operations and Systems

Abstract: There exist huge problems in the current practice of crisis response operations. Response problems are projected as a combination of failure in communication, failure in technology, failure in methodology, failure of management, and finally failure of observation. In this paper we compare eight crisis response systems namely: DrillSim [2, 13], DEFACTO [12, 17], ALADDIN [1, 6], RoboCup Rescue [11, 15], FireGrid [3, 8, 18], WIPER [16], D-AESOP [4], and PLAN C [14]. Comparison results will disclose the cause of failure of current crisis response operations (the response gap). Based on comparison results; we provide recommendations for bridging this gap between response operations and systems.


Algorithms for Placing Monitors in a Flow Network

Abstract: In the Flow Edge-Monitor Problem, we are given an undirected graph G=(V,E), an integer k > 0 and some unknown circulation \psi on G. We want to find a set of k edges in G, so that if we place k monitors on those edges to measure the flow along them, the total number of edges for which the flow can be uniquely determined is maximized. In this paper, we first show that the Flow Edge-Monitor Problem is NP-hard, and then we give two approximation algorithms: a 3-approximation algorithm with running time O((m+n)^2) and a 2-approximation algorithm with running time O((m+n)^3), where n = |V| and m=|E|.


Automated Composition of Security Protocols

Abstract: Determining if two protocols can be securely composed requires analyzing not only their additive properties but also their destructive properties. In this paper we propose a new composition method for constructing protocols based on existing ones found in the literature that can be fully automatized. The additive properties of the composed protocols are ensured by the composition of protocol preconditions and effects, denoting, respectively, the conditions that must hold for protocols to be executed and the conditions that hold after executing the protocols. The non-destructive property of the final composed protocol is verified by analyzing the independence of the involved protocols, a method proposed by the authors in their previous work. The fully automatized property is ensured by constructing a rich protocol model that contains explicit description of protocol preconditions, effects, generated terms and exchanged messages. The proposed method is validated by composing 17 protocol pairs and by verifying the correctness of the composed protocols with an existing tool.


Exploration of the Gap Between Computer Science Curriculum and Industrial I.T Skills Requirements

Abstract: This paper sets out to examine the skills gaps between the industrial application of Information Technology and university academic programmes (curriculum). It looks at some of the causes, and considers the probable solutions for bridging the gap between them and suggests the possibilities of exploring a new role for our universities and employers of labor. It also highlights strategies to abolish the misalignment between university and industry. The main concept is to blend the academic rigidity with the industrial relevance.


Visualization of Mined Pattern and Its Human Aspects

Abstract: Researchers got success in mining the Web usage data effectively and efficiently. But representation of the mined patterns is often not in a form suitable for direct human consumption. Hence mechanisms and tools that can represent mined patterns in easily understandable format are utilized. Different techniques are used for pattern analysis, one of them is visualization. Visualization can provide valuable assistance for data analysis and decision making tasks. In the data visualization process, technical representations of web pages are replaced by user attractive text interpretations. Experiments with the real world problems showed that the visualization can significantly increase the quality and usefulness of web log mining results. However, how decision makers perceive and interact with a visual representation can strongly influence their understanding of the data as well as the usefulness of the visual presentation. Human factors therefore contribute significantly to the visualization process and should play an important role in the design and evaluation of visualization tools. This electronic document is a live template. The various components of your paper, title, text, heads, etc., are already defined on the style sheet, as illustrated by the portions given in this document.


Handwritten Farsi Character Recognition using Artificial Neural Network

Abstract: Neural Networks are being used for character recognition from last many years but most of the work was confined to English character recognition. Till date, a very little work has been reported for Handwritten Farsi Character recognition. In this paper, we have made an attempt to recognize handwritten Farsi characters by using a multilayer perceptron with one hidden layer. The error backpropagation algorithm has been used to train the MLP network. In addition, an analysis has been carried out to determine the number of hidden nodes to achieve high performance of backpropagation network in the recognition of handwritten Farsi characters. The system has been trained using several different forms of handwriting provided by both male and female participants of different age groups. Finally, this rigorous training results an automatic HCR system using MLP network. In this work, the experiments were carried out on two hundred fifty samples of five writers. The results showed that the MLP networks trained by the error backpropagation algorithm are superior in recognition accuracy and memory usage. The result indicates that the backpropagation network provides good recognition accuracy of more than 80% of handwritten Farsi characters.


Multiple Retrieval Models and Regression Models for Prior Art Search

Abstract: This paper presents the system called PATATRAS (PATent and Article Tracking, Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach presents three main characteristics: 1. The usage of multiple retrieval models (KL, Okapi) and term index definitions (lemma, phrase, concept) for the three languages considered in the present track (English, French, German) producing ten different sets of ranked results. 2. The merging of the different results based on multiple regression models using an additional validation set created from the patent collection. 3. The exploitation of patent metadata and of the citation structures for creating restricted initial working sets of patents and for producing a final re-ranking regression model. As we exploit specific metadata of the patent documents and the citation relations only at the creation of initial working sets and during the final post ranking step, our architecture remains generic and easy to extend.


Spreadsheets and the Financial Collapse

Abstract: We briefly review the well-known risks, weaknesses and limitations of spreadsheets and then introduce some more. We review and slightly extend our previous work on the importance and criticality of spreadsheets in the City of London, introducing the notions of ubiquity, centrality, legality and contagion. We identify the sector of the financial market that we believed in 2005 to be highly dependant on the use of spreadsheets and relate this to its recent catastrophic financial performance. We outline the role of spreadsheets in the collapse of the Jamaican banking system in the late 1990's and then review the UK financial regulator's knowledge of the risks of spreadsheets in the contemporary financial system. We summarise the available evidence and suggest that there is a link between the use of spreadsheets and the recent collapse of the global financial system. We provide governments and regulating authorities with some simple recommendations to reduce the risks of continued overdependence on unreliable spreadsheets. We conclude with three fundamental lessons from a century of human error research.


Mesh Algorithms for PDE with Sieve I: Mesh Distribution

Abstract: We have developed a new programming framework, called Sieve, to support parallel numerical PDE algorithms operating over distributed meshes. We have also developed a reference implementation of Sieve in C++ as a library of generic algorithms operating on distributed containers conforming to the Sieve interface. Sieve makes instances of the incidence relation, or \emph{arrows}, the conceptual first-class objects represented in the containers. Further, generic algorithms acting on this arrow container are systematically used to provide natural geometric operations on the topology and also, through duality, on the data. Finally, coverings and duality are used to encode not only individual meshes, but all types of hierarchies underlying PDE data structures, including multigrid and mesh partitions. In order to demonstrate the usefulness of the framework, we show how the mesh partition data can be represented and manipulated using the same fundamental mechanisms used to represent meshes. We present the complete description of an algorithm to encode a mesh partition and then distribute a mesh, which is independent of the mesh dimension, element shape, or embedding. Moreover, data associated with the mesh can be similarly distributed with exactly the same algorithm. The use of a high level of abstraction within the Sieve leads to several benefits in terms of code reuse, simplicity, and extensibility. We discuss these benefits and compare our approach to other existing mesh libraries.


An OLAC Extension for Dravidian Languages

Abstract: OLAC was founded in 2000 for creating online databases of language resources. This paper intends to review the bottom-up distributed character of the project and proposes an extension of the architecture for Dravidian languages. An ontological structure is considered for effective natural language processing (NLP) and its advantages over statistical methods are reviewed


Monadic second-order model-checking on decomposable matroids

Abstract: A notion of branch-width, which generalizes the one known for graphs, can be defined for matroids. We first give a proof of the polynomial time model-checking of monadic second-order formulas on representable matroids of bounded branch-width, by reduction to monadic second-order formulas on trees. This proof is much simpler than the one previously known. We also provide a link between our logical approach and a grammar that allows to build matroids of bounded branch-width. Finally, we introduce a new class of non-necessarily representable matroids, described by a grammar and on which monadic second-order formulas can be checked in linear time.


Predictors Of Java Programming Self Efficacy Among Engineering Students In A Nigerian University

Abstract: The study examined the relationship between Java programming self-efficacy and programming background of engineering students in a Nigerian University. One hundred and ninety two final year engineering students randomly selected from six engineering departments of the university participated in the study. Two research instruments: Programming Background Questionnaire and Java Programming Self-Efficacy Scale were used in collecting relevant information from the subjects. The resulting data were analyzed using Pearson product correlation and Multiple regression analysis. Findings revealed that Java Programming self-efficacy has no significant relationship with each of the computing and programming background factors. It was additionally obtained that the number of programming courses offered and programming courses weighed scores were the only predictors of Java self-efficacy.


Energy Efficient Location Aided Routing Protocol for Wireless MANETs

Abstract: A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network without using any centralized access point, infrastructure, or centralized administration. In this paper we introduce an Energy Efficient Location Aided Routing (EELAR) Protocol for MANETs that is based on the Location Aided Routing (LAR). EELAR makes significant reduction in the energy consumption of the mobile nodes batteries by limiting the area of discovering a new route to a smaller zone. Thus, control packets overhead is significantly reduced. In EELAR a reference wireless base station is used and the network's circular area centered at the base station is divided into six equal sub-areas. At route discovery instead of flooding control packets to the whole network area, they are flooded to only the sub-area of the destination mobile node. The base station stores locations of the mobile nodes in a position table. To show the efficiency of the proposed protocol we present simulations using NS-2. Simulation results show that EELAR protocol makes an improvement in control packet overhead and delivery ratio compared to AODV, LAR, and DSR protocols.


Online Algorithms for Self-Organizing Sequential Search - A Survey

Abstract: The main objective of this survey is to present the important theoretical and experimental results contributed till date in the area of online algorithms for the self organizing sequential search problem, also popularly known as the List Update Problem(LUP) in a chronological way. The survey includes competitiveness results of deterministic and randomized online algorithms and complexity results of optimal off line algorithms for the list update problem. We also present the results associated with list update with look ahead, list update with locality of reference and other variants of the list update problem. We investigate research issues, explore scope of future work associated with each issue so that future researchers can find it useful to work on.


Constraint Minimum Vertex Cover in K Partite Graph, Approximation Algorithm and Complexity Analysis

Abstract: Generally, a graph G, an independent set is a subset S of vertices in G such that no two vertices in S are adjacent (connected by an edge) and a vertex cover is a subset S of vertices such that each edge of G has at least one of its endpoints in S. Again, the minimum vertex cover problem is to find a vertex cover with the smallest number of vertices. This study shows that the constrained minimum vertex cover problem in k-partite graph (MIN CVCK) is NP-Complete which is an important property of k partite graph. Many combinatorial problems on general graphs are NP-complete, but when restricted to k partite graph with at most k vertices then many of these problems can be solved in polynomial time. This paper also illustrates an approximation algorithm for MIN CVCK and analyzes its complexity. In future work section, we specified a number of dimensions which may be interesting for the researchers such as developing algorithm for maximum matching and polynomial algorithm for constructing k-partite graph from general graph.


Hardware Virtualization Support In INTEL, AMD And IBM Power Processors

Abstract: At present, the mostly used and developed mechanism is hardware virtualization which provides a common platform to run multiple operating systems and applications in independent partitions. More precisely, it is all about resource virtualization as the term hardware virtualization is emphasized. In this paper, the aim is to find out the advantages and limitations of current virtualization techniques, analyze their cost and performance and also depict which forthcoming hardware virtualization techniques will able to provide efficient solutions for multiprocessor operating systems. This is done by making a methodical literature survey and statistical analysis of the benchmark reports provided by SPEC (Standard Performance Evaluation Corporation) and TPC (Transaction processing Performance Council). Finally, this paper presents the current aspects of hardware virtualization which will help the IT managers of the large organizations to take effective decision while choosing server with virtualization support. Again, the future works described in section 4 of this paper focuses on some real world challenges such as abstraction of multiple servers, language level virtualization, pre-virtualization etc. which may be point of great interest for the researchers.


On the optimal design of parallel robots taking into account their deformations and natural frequencies

Abstract: This paper discusses the utility of using simple stiffness and vibrations models, based on the Jacobian matrix of a manipulator and only the rigidity of the actuators, whenever its geometry is optimised. In many works, these simplified models are used to propose optimal design of robots. However, the elasticity of the drive system is often negligible in comparison with the elasticity of the elements, especially in applications where high dynamic performances are needed. Therefore, the use of such a simplified model may lead to the creation of robots with long legs, which will be submitted to large bending and twisting deformations. This paper presents an example of manipulator for which it is preferable to use a complete stiffness or vibration model to obtain the most suitable design and shows that the use of simplified models can lead to mechanisms with poorer rigidity.


On the Internal Topological Structure of Plane Regions

Abstract: The study of topological information of spatial objects has for a long time been a focus of research in disciplines like computational geometry, spatial reasoning, cognitive science, and robotics. While the majority of these researches emphasised the topological relations between spatial objects, this work studies the internal topological structure of bounded plane regions, which could consist of multiple pieces and/or have holes and islands to any finite level. The insufficiency of simple regions (regions homeomorphic to closed disks) to cope with the variety and complexity of spatial entities and phenomena has been widely acknowledged. Another significant drawback of simple regions is that they are not closed under set operations union, intersection, and difference. This paper considers bounded semi-algebraic regions, which are closed under set operations and can closely approximate most plane regions arising in practice.


Dynamic Multimedia Content Retrieval System in Distributed Environment

Abstract: WiCoM enables remote management of web resources. Our application Mobile reporter is aimed at Journalist, who will be able to capture the events in real-time using their mobile phones and update their web server on the latest event. WiCoM has been developed using J2ME technology on the client side and PHP on the server side. The communication between the client and the server is established through GPRS. Mobile reporter will be able to upload, edit and remove both textual as well as multimedia contents in the server.


Reasoning with Topological and Directional Spatial Information

Abstract: Current research on qualitative spatial representation and reasoning mainly focuses on one single aspect of space. In real world applications, however, multiple spatial aspects are often involved simultaneously. This paper investigates problems arising in reasoning with combined topological and directional information. We use the RCC8 algebra and the Rectangle Algebra (RA) for expressing topological and directional information respectively. We give examples to show that the bipath-consistency algorithm BIPATH is incomplete for solving even basic RCC8 and RA constraints. If topological constraints are taken from some maximal tractable subclasses of RCC8, and directional constraints are taken from a subalgebra, termed DIR49, of RA, then we show that BIPATH is able to separate topological constraints from directional ones. This means, given a set of hybrid topological and directional constraints from the above subclasses of RCC8 and RA, we can transfer the joint satisfaction problem in polynomial time to two independent satisfaction problems in RCC8 and RA. For general RA constraints, we give a method to compute solutions that satisfy all topological constraints and approximately satisfy each RA constraint to any prescribed precision.


Reasoning about Cardinal Directions between Extended Objects

Abstract: Direction relations between extended spatial objects are important commonsense knowledge. Recently, Goyal and Egenhofer proposed a formal model, known as Cardinal Direction Calculus (CDC), for representing direction relations between connected plane regions. CDC is perhaps the most expressive qualitative calculus for directional information, and has attracted increasing interest from areas such as artificial intelligence, geographical information science, and image retrieval. Given a network of CDC constraints, the consistency problem is deciding if the network is realizable by connected regions in the real plane. This paper provides a cubic algorithm for checking consistency of basic CDC constraint networks, and proves that reasoning with CDC is in general an NP-Complete problem. For a consistent network of basic CDC constraints, our algorithm also returns a 'canonical' solution in cubic time. This cubic algorithm is also adapted to cope with cardinal directions between possibly disconnected regions, in which case currently the best algorithm is of time complexity O(n^5).


Canonical extension and canonicity via DCPO presentations

Abstract: The canonical extension of a lattice is in an essential way a two-sided completion. Domain theory, on the contrary, is primarily concerned with one-sided completeness. In this paper, we show two things. Firstly, that the canonical extension of a lattice can be given an asymmetric description in two stages: a free co-directed meet completion, followed by a completion by \emph{selected} directed joins. Secondly, we show that the general techniques for dcpo presentations of dcpo algebras used in the second stage of the construction immediately give us the well-known canonicity result for bounded lattices with operators.


State Space Reduction with Message Inspection in Security Protocol Model Checking

Abstract: Model checking is a widespread automatic formal analysis that has been successful in discovering flaws in security protocols. However existing possibilities for state space explosion still hinder analyses of complex protocols and protocol configurations. Message Inspection, is a technique that delimits the branching of the state space due to the intruder model without excluding possible attacks. In a preliminary simulation, the intruder model tags the eavesdropped messages with specific metadata that enable validation of feasibility of possible attack actions. The Message Inspection algorithm then decides based on these metadata, which attacks will certainly fail according to known security principles. Thus, it is a priori known that i.e. an encryption scheme attack cannot succeed if the intruder does not posses the right key in his knowledge. The simulation terminates with a report of the attack actions that can be safely removed, resulting in a model with a reduced state space.


Normal Elliptic Bases and Torus-Based Cryptography

Abstract: We consider representations of algebraic tori $T_n(F_q)$ over finite fields. We make use of normal elliptic bases to show that, for infinitely many squarefree integers $n$ and infinitely many values of $q$, we can encode $m$ torus elements, to a small fixed overhead and to $m$ $\phi(n)$-tuples of $F_q$ elements, in quasi-linear time in $\log q$. This improves upon previously known algorithms, which all have a quasi-quadratic complexity. As a result, the cost of the encoding phase is now negligible in Diffie-Hellman cryptographic schemes.


Is the crowd's wisdom biased? A quantitative asessment of three online communities

Abstract: This paper presents a study of user voting on three websites: Imdb, Amazon and BookCrossings. It reports on an expert evaluation of the voting mechanisms of each website and a quantitative data analysis of users' aggregate voting behavior. The results suggest that voting follows different patterns across the websites, with higher barrier to vote introducing a more of one-off voters and attracting mostly experts. The results also show that that one-off voters tend to vote on popular items, while experts mostly vote for obscure, low-rated items. The study concludes with design suggestions to address the "wisdom of the crowd" bias.


Enhanced Mode Selection Algorithm for H.264 encoder for Application in Low Computational power devices

Abstract: The intent of the H.264 AVC project was to create a standard capable of providing good video quality at substantially lower bit rates than previous standards without increasing the complexity of design so much that it would be impractical or excessively expensive to implement. An additional goal was to provide enough flexibility to allow the standard to be applied to a wide variety of applications. To achieve better coding efficiency, H.264 AVC uses several techniques such as inter mode and intra mode prediction with variable size motion compensation, which adopts Rate Distortion Optimization (RDO). This increases the computational complexity of the encoder especially for devices with lower processing capabilities such as mobile and other handheld devices. In this paper, we propose an algorithm to reduce the number of mode and sub mode evaluations in inter mode prediction. Experimental results show that this fast intra mode selection algorithm can lessen about 75 percent encoding time with little loss of bit rate and visual quality.


Strong Nash Equilibria in Games with the Lexicographical Improvement Property

Abstract: We introduce a class of finite strategic games with the property that every deviation of a coalition of players that is profitable to each of its members strictly decreases the lexicographical order of a certain function defined on the set of strategy profiles. We call this property the Lexicographical Improvement Property (LIP) and show that it implies the existence of a generalized strong ordinal potential function. We use this characterization to derive existence, efficiency and fairness properties of strong Nash equilibria. We then study a class of games that generalizes congestion games with bottleneck objectives that we call bottleneck congestion games. We show that these games possess the LIP and thus the above mentioned properties. For bottleneck congestion games in networks, we identify cases in which the potential function associated with the LIP leads to polynomial time algorithms computing a strong Nash equilibrium. Finally, we investigate the LIP for infinite games. We show that the LIP does not imply the existence of a generalized strong ordinal potential, thus, the existence of SNE does not follow. Assuming that the function associated with the LIP is continuous, however, we prove existence of SNE. As a consequence, we prove that bottleneck congestion games with infinite strategy spaces and continuous cost functions possess a strong Nash equilibrium.


Kinematic analysis of a class of analytic planar 3-RPR parallel manipulators

Abstract: A class of analytic planar 3-RPR manipulators is analyzed in this paper. These manipulators have congruent base and moving platforms and the moving platform is rotated of 180 deg about an axis in the plane. The forward kinematics is reduced to the solution of a 3rd-degree polynomial and a quadratic equation in sequence. The singularities are calculated and plotted in the joint space. The second-order singularities (cups points), which play an important role in non-singular change of assembly-mode motions, are also analyzed.


Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation

Abstract: By a "covering" we mean a Gaussian mixture model fit to observed data. Approximations of the Bayes factor can be availed of to judge model fit to the data within a given Gaussian mixture model. Between families of Gaussian mixture models, we propose the R\'enyi quadratic entropy as an excellent and tractable model comparison framework. We exemplify this using the segmentation of an MRI image volume, based (1) on a direct Gaussian mixture model applied to the marginal distribution function, and (2) Gaussian model fit through k-means applied to the 4D multivalued image volume furnished by the wavelet transform. Visual preference for one model over another is not immediate. The R\'enyi quadratic entropy allows us to show clearly that one of these modelings is superior to the other.


On the Set Multi-Cover Problem in Geometric Settings

Abstract: We consider the set multi-cover problem in geometric settings. Given a set of points P and a collection of geometric shapes (or sets) F, we wish to find a minimum cardinality subset of F such that each point p in P is covered by (contained in) at least d(p) sets. Here d(p) is an integer demand (requirement) for p. When the demands d(p)=1 for all p, this is the standard set cover problem. The set cover problem in geometric settings admits an approximation ratio that is better than that for the general version. In this paper, we show that similar improvements can be obtained for the multi-cover problem as well. In particular, we obtain an O(log Opt) approximation for set systems of bounded VC-dimension, where Opt is the cardinality of an optimal solution, and an O(1) approximation for covering points by half-spaces in three dimensions and for some other classes of shapes.


QoS Provisioning Using Hybrid FSO RF Based Hierarchical Model for Wireless Multimedia Sensor Networks

Abstract: Our objective is to provide guaranteed packet delivery service in time constrained sensor networks. The wireless network is a highly variable environment, where available link bandwidth may vary with network load. Since multimedia applications require higher bandwidth so we use FSO links for their transmission. The main advantage of FSO links is that they offer higher bandwidth and security, while RF links offer more reliability. The routing in this multitier network is based on directional geographic routing protocol, in which sensors route their data via multihop paths, to a powerful base station, through a cluster head. Some modifications have also been incorporated in the MAC layer to improve the QoS of such systems.


A Method for Accelerating the HITS Algorithm

Abstract: We present a new method to accelerate the HITS algorithm by exploiting hyperlink structure of the web graph. The proposed algorithm extends the idea of authority and hub scores from HITS by introducing two diagonal matrices which contain constants that act as weights to make authority pages more authoritative and hub pages more hubby. This method works because in the web graph good authorities are pointed to by good hubs and good hubs point to good authorities. Consequently, these pages will collect their scores faster under the proposed algorithm than under the standard HITS. We show that the authority and hub vectors of the proposed algorithm exist but are not necessarily be unique, and then give a treatment to ensure the uniqueness property of the vectors. The experimental results show that the proposed algorithm can improve HITS computations, especially for back button datasets.


Minimizing Cache Timing Attack Using Dynamic Cache Flushing (DCF) Algorithm

Abstract: Rijndael algorithm was unanimously chosen as the Advanced Encryption Standard (AES) by the panel of researchers at National Institute of Standards and Technology (NIST) in October 2000. Since then, Rijndael was destined to be used massively in various software as well as hardware entities for encrypting data. However, a few years back, Daniel Bernstein devised a cache timing attack that was capable enough to break Rijndael seal that encapsulates the encryption key. In this paper, we propose a new Dynamic Cache Flushing (DCF) algorithm which shows a set of pragmatic software measures that would make Rijndael impregnable to cache timing attack. The simulation results demonstrate that the proposed DCF algorithm provides better security by encrypting key at a constant time.


A Survey of Attacks, Security Mechanisms and Challenges in Wireless Sensor Networks

Abstract: Wireless Sensor networks (WSN) is an emerging technology and have great potential to be employed in critical situations like battlefields and commercial applications such as building, traffic surveillance, habitat monitoring and smart homes and many more scenarios. One of the major challenges wireless sensor networks face today is security. While the deployment of sensor nodes in an unattended environment makes the networks vulnerable to a variety of potential attacks, the inherent power and memory limitations of sensor nodes makes conventional security solutions unfeasible. The sensing technology combined with processing power and wireless communication makes it profitable for being exploited in great quantity in future. The wireless communication technology also acquires various types of security threats. This paper discusses a wide variety of attacks in WSN and their classification mechanisms and different securities available to handle them including the challenges faced.


Computational Complexities and Breaches in Authentication Frameworks of Broadband Wireless Access

Abstract: Secure access of communication networks has become an increasingly important area of consideration for the communication service providers of present day. Broadband Wireless Access (BWA) networks are proving to be an efficient and cost effective solution for the provisioning of high rate wireless traffic links in static and mobile domains. The secure access of these networks is necessary to ensure their superior operation and revenue efficacy. Although authentication process is a key to secure access in BWA networks, the breaches present in them limit the networks performance. In this paper, the vulnerabilities in the authentication frameworks of BWA networks have been unveiled. Moreover, this paper also describes the limitations of these protocols and of the solutions proposed to them due to the involved computational complexities and overheads. The possible attacks on privacy and performance of BWA networks have been discussed and explained in detail.


Codebook Design Method for Noise Robust Speaker Identification based on Genetic Algorithm

Abstract: In this paper, a novel method of designing a codebook for noise robust speaker identification purpose utilizing Genetic Algorithm has been proposed. Wiener filter has been used to remove the background noises from the source speech utterances. Speech features have been extracted using standard speech parameterization method such as LPC, LPCC, RCC, MFCC, (delta)MFCC and (delta)(delta) MFCC. For each of these techniques, the performance of the proposed system has been compared. In this codebook design method, Genetic Algorithm has the capability of getting global optimal result and hence improves the quality of the codebook. Comparing with the NOIZEOUS speech database, the experimental result shows that 79.62 percent accuracy has been achieved.


Effects of Mechanical Coupling on the Dynamics of Balancing Tasks

Abstract: Coupled human balancing tasks are investigated based on both pseudo-neural controllers characterized by time-delayed feedback with random gain and natural human balancing tasks. It is shown numerically that, compared to single balancing tasks, balancing tasks coupled by mechanical structures exhibit enhanced stability against balancing errors in terms of both amplitude and velocity and also improve the tracking ability of the controllers. We then perform an experiment in which numerical pseudo-neural controllers are replaced with natural human balancing tasks carried out using computer mice. The results reveal that the coupling structure generates asymmetric tracking abilities in subjects whose tracking abilities are nearly symmetric in their single balancing tasks.


Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic

Abstract: Fractional Brownian motion (fBm) emerged as a useful model for self-similar and long-range dependent Internet traffic. Approximate performance measures are known from large deviations theory for single queuing systems with fBm through traffic. In this paper we derive end-to-end performance bounds for a through flow in a network of tandem queues under fBm cross traffic. To this end, we prove a rigorous sample path envelope for fBm that complements previous approximate results. We find that both approaches agree in their outcome that overflow probabilities for fBm traffic have a Weibullian tail. We employ the sample path envelope and the concept of leftover service curves to model the remaining service after scheduling fBm cross traffic at a system. Using composition results for tandem systems from the stochastic network calculus we derive end-to-end statistical performance bounds for individual flows in networks under fBm cross traffic. We discover that these bounds grow in O(n (log n)^(1/(2-2H))) for n systems in series where H is the Hurst parameter of the fBm cross traffic. We show numerical results on the impact of the variability and the correlation of fBm traffic on network performance.


On Planning with Preferences in HTN

Abstract: In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich qualitative user preferences. The outcome of our work is a language for specifyin user preferences, tailored to HTN planning, together with a provably optimal preference-based planner, HTNPLAN, that is implemented as an extension of SHOP2. To compute preferred plans, we propose an approach based on forward-chaining heuristic search. Our heuristic uses an admissible evaluation function measuring the satisfaction of preferences over partial plans. Our empirical evaluation demonstrates the effectiveness of our HTNPLAN heuristics. We prove our approach sound and optimal with respect to the plans it generates by appealing to a situation calculus semantics of our preference language and of HTN planning. While our implementation builds on SHOP2, the language and techniques proposed here are relevant to a broad range of HTN planners.


In-Network Outlier Detection in Wireless Sensor Networks

Abstract: To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy usage,(3) only uses single hop communication thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance using simulation with real sensor data streams. Our results demonstrate that our approach is accurate and imposes a reasonable communication load and level of power consumption.


Relative $(p,\epsilon)$-Approximations in Geometry

Abstract: We re-examine the notion of relative $(p,\eps)$-approximations, recently introduced in [CKMS06], and establish upper bounds on their size, in general range spaces of finite VC-dimension, using the sampling theory developed in [LLS01] and in several earlier studies [Pol86, Hau92, Tal94]. We also survey the different notions of sampling, used in computational geometry, learning, and other areas, and show how they relate to each other. We then give constructions of smaller-size relative $(p,\eps)$-approximations for range spaces that involve points and halfspaces in two and higher dimensions. The planar construction is based on a new structure--spanning trees with small relative crossing number, which we believe to be of independent interest. Relative $(p,\eps)$-approximations arise in several geometric problems, such as approximate range counting, and we apply our new structures to obtain efficient solutions for approximate range counting in three dimensions. We also present a simple solution for the planar case.


A Step towards Software Corrective Maintenance Using RCM model

Abstract: From the preliminary stage of software engineering, selection of appropriate enforcement of standards remained a challenge for stakeholders during entire cycle of software development, but it can lead to reduce the efforts desired for software maintenance phase. Corrective maintenance is the reactive modification of a software product performed after delivery to correct discovered faults. Studies conducted by different researchers reveal that approximately 50 to 75 percent of the effort is spent on maintenance, out of which about 17 to 21 percent is exercised on corrective maintenance. In this paper, authors proposed a RCM (Reduce Corrective Maintenance) model which represents the implementation process of number of checklists to guide the stakeholders of all phases of software development. These check lists will be filled by corresponding stake holder of all phases before its start. More precise usage of the check list in relevant phase ensures successful enforcement of analysis, design, coding and testing standards for reducing errors in operation stage. Moreover authors represent the step by step integration of checklists in software development life cycle through RCM model.


The Asymptotic Behavior of Minimum Buffer Size Requirements in Large P2P Streaming Networks

Abstract: The growth of real-time content streaming over the Internet has resulted in the use of peer-to-peer (P2P) approaches for scalable content delivery. In such P2P streaming systems, each peer maintains a playout buffer of content chunks which it attempts to fill by contacting other peers in the network. The objective is to ensure that the chunk to be played out is available with high probability while keeping the buffer size small. Given that a particular peer has been selected, a \emph{policy} is a rule that suggests which chunks should be requested by the peer from other peers.. We consider consider a number of recently suggested policies consistent with buffer minimization for a given target of skip free playout. We first study a \emph{rarest-first} policy that attempts to obtain chunks farthest from playout, and a \emph{greedy} policy that attempts to obtain chunks nearest to playout. We show that they both have similar buffer scalings (as a function of the number of peers of target probability of skip-free probability). We then study a hybrid policy which achieves order sense improvements over both policies and can achieve order optimal performance. We validate our results using simulations.


Object-Oriented Intensional Programming: Intensional Classes Using Java and Lucid

Abstract: This article introduces Object-Oriented Intensional Programming (OO-IP), a new hybrid language between Object-Oriented and Intensional Programming Languages in the sense of the latest evolutions of Lucid. This new hybrid language combines the essential characteristics of Lucid and Java, and introduces the notion of object streams which makes it is possible that each element in a Lucid stream to be an object with embedded intensional properties. Interestingly, this hybrid language also brings to Java objects the power to explicitly express and manipulate the notion of context, creating the novel concept of intensional object, i.e. objects whose evaluation is context-dependent, which are here demonstrated to be translatable into standard objects. By this new approach, we extend the use and meaning of the notion of intensional objects and enrich the meaning of object streams in Lucid and semantics of intensional objects in Java.


Computation of Spatial Skyline Points

Abstract: We discuss a method of finding skyline or non-dominated sites in a set $P$ of $n$ point sites with respect to a set $S$ of $m$ points. A site $p \in P$ is non-dominated if and only if for each $q \in P \setminus \{p\}$, there exists at least one point $s \in S$ that is closer to $p$ than to $q$. We reduce this problem of determining non-dominated sites to the problem of finding sites that have non-empty cells in an additively weighted Voronoi diagram under a convex distance function. The weights of said Voronoi diagram are derived from the coordinates of the sites of $P$, while the convex distance function is derived from $S$. In the two-dimensional plane, this reduction gives an $O((n + m) \log (n + m))$-time algorithm to find the non-dominated points.


Inferring Loop Invariants using Postconditions

Abstract: One of the obstacles in automatic program proving is to obtain suitable loop invariants. The invariant of a loop is a weakened form of its postcondition (the loop's goal, also known as its contract); the present work takes advantage of this observation by using the postcondition as the basis for invariant inference, using various heuristics such as "uncoupling" which prove useful in many important algorithms. Thanks to these heuristics, the technique is able to infer invariants for a large variety of loop examples. We present the theory behind the technique, its implementation (freely available for download and currently relying on Microsoft Research's Boogie tool), and the results obtained.


Price of Anarchy for Greedy Auctions

Abstract: We consider auctions in which greedy algorithms, paired with first-price or critical-price payment rules, are used to resolve multi-parameter combinatorial allocation problems. We study the price of anarchy for social welfare in such auctions. We show for a variety of equilibrium concepts, including Bayes-Nash equilibrium and correlated equilibrium, the resulting price of anarchy bound is close to the approximation factor of the underlying greedy algorithm.


Assessing the Impact of Informedness on a Consultant's Profit

Abstract: We study the notion of informedness in a client-consultant setting. Using a software simulator, we examine the extent to which it pays off for consultants to provide their clients with advice that is well-informed, or with advice that is merely meant to appear to be well-informed. The latter strategy is beneficial in that it costs less resources to keep up-to-date, but carries the risk of a decreased reputation if the clients discover the low level of informedness of the consultant. Our experimental results indicate that under different circumstances, different strategies yield the optimal results (net profit) for the consultants.


A Randomized Rounding Algorithm for the Asymmetric Traveling Salesman Problem

Abstract: We present an algorithm for the asymmetric traveling salesman problem on instances which satisfy the triangle inequality. Like several existing algorithms, it achieves approximation ratio O(log n). Unlike previous algorithms, it uses randomized rounding.


A multiagent urban traffic simulation Part I: dealing with the ordinary

Abstract: We describe in this article a multiagent urban traffic simulation, as we believe individual-based modeling is necessary to encompass the complex influence the actions of an individual vehicle can have on the overall flow of vehicles. We first describe how we build a graph description of the network from purely geometric data, ESRI shapefiles. We then explain how we include traffic related data to this graph. We go on after that with the model of the vehicle agents: origin and destination, driving behavior, multiple lanes, crossroads, and interactions with the other vehicles in day-to-day, ?ordinary? traffic. We conclude with the presentation of the resulting simulation of this model on the Rouen agglomeration.


The Euler Path to Static Level-Ancestors

Abstract: Suppose that a rooted tree T is given for preprocessing. The Level-Ancestor Problem is to answer quickly queries of the following form. Given a vertex v and an integer i > 0, find the i-th vertex on the path from the root to v. Algorithms that achieve a linear time bound for preprocessing and a constant time bound for a query have been published by Dietz (1991), Alstrup and Holm (2000), and Bender and Farach (2002). The first two algorithms address dynamic versions of the problem; the last addresses the static version only and is the simplest so far. The purpose of this note is to expose another simple algorithm, derived from a complicated PRAM algorithm by Berkman and Vishkin (1990,1994). We further show some easy extensions of its functionality, adding queries for descendants and level successors as well as ancestors, extensions for which the formerly known algorithms are less suitable.


Randomized Shellsort: A Simple Oblivious Sorting Algorithm

Abstract: In this paper, we describe randomized Shellsort--a simple, randomized, data-oblivious version of the Shellsort algorithm that always runs in O(n log n) time and, as we show, succeeds in sorting any given input permutation with very high probability. Thus, randomized Shellsort is simultaneously simple, time-optimal, and data-oblivious. Taken together, these properties imply applications in the design of new efficient privacy-preserving computations based on the secure multi-party computation (SMC) paradigm. In addition, by a trivial conversion of this Monte Carlo algorithm to its Las Vegas equivalent, one gets the first version of Shellsort with a running time that is provably O(n log n) with very high probability.


A Novel Model for Optimized GSM Network Design

Abstract: GSM networks are very expensive. The network design process requires too many decisions in a combinatorial explosion. For this reason, the larger is the network, the harder is to achieve a totally human based optimized solution. The BSC (Base Station Control) nodes have to be geographically well allocated to reduce the transmission costs. There are decisions of association between BTS and BSC those impacts in the correct dimensioning of these BSC. The choice of BSC quantity and model capable of carrying the cumulated traffic of its affiliated BTS nodes in turn reflects on the total cost. In addition, the last component of the total cost is due to transmission for linking BSC nodes to MSC. These trunks have a major significance since the number of required E1 lines is larger than BTS to BSC link. This work presents an integer programming model and a computational tool for designing GSM (Global System for Mobile Communications) networks, regarding BSS (Base Station Subsystem) with optimized cost.


Electronic Authority Variation

Abstract: When a person joins in an organization, he becomes authorize to take some decisions on behalf of that organization; means he is given some authority to exercise. After some time, on the basis of his performance in the organization, he is given promotion and he becomes eligible to exercise to some higher authorities. And further, he may get some higher promotion or he may leave the organization. So, during his stay in the organization, the authority of that person varies from the time he joins the organization until he/she leaves the organization. This paper presents the variation in authorities of a person in the organization. The method implements the queuing model to analyze the various people in the queue of their promotion and looks at various parameters like average waiting time etc.


New Approximation Algorithms for Minimum Enclosing Convex Shapes

Abstract: Given $n$ points in a $d$ dimensional Euclidean space, the Minimum Enclosing Ball (MEB) problem is to find the ball with the smallest radius which contains all $n$ points. We give a $O(nd\Qcal/\sqrt{\epsilon})$ approximation algorithm for producing an enclosing ball whose radius is at most $\epsilon$ away from the optimum (where $\Qcal$ is an upper bound on the norm of the points). This improves existing results using \emph{coresets}, which yield a $O(nd/\epsilon)$ greedy algorithm. Finding the Minimum Enclosing Convex Polytope (MECP) is a related problem wherein a convex polytope of a fixed shape is given and the aim is to find the smallest magnification of the polytope which encloses the given points. For this problem we present a $O(mnd\Qcal/\epsilon)$ approximation algorithm, where $m$ is the number of faces of the polytope. Our algorithms borrow heavily from convex duality and recently developed techniques in non-smooth optimization, and are in contrast with existing methods which rely on geometric arguments. In particular, we specialize the excessive gap framework of \citet{Nesterov05a} to obtain our results.


Envy-Free Makespan Approximation

Abstract: We study envy-free mechanisms for scheduling tasks on unrelated machines (agents) that approximately minimize the makespan. For indivisible tasks, we put forward an envy-free poly-time mechanism that approximates the minimal makespan to within a factor of $O(\log m)$, where $m$ is the number of machines. We also show a lower bound of $\Omega(\log m / \log\log m)$. This improves the recent result of Hartline {\sl et al.} \cite{Ahuva:2008} who give an upper bound of $(m+1)/2$, and a lower bound of $2-1/m$. For divisible tasks, we show that there always exists an envy-free poly-time mechanism with optimal makespan.


Branching-time model checking of one-counter processes

Abstract: One-counter processes (OCPs) are pushdown processes which operate only on a unary stack alphabet. We study the computational complexity of model checking computation tree logic (CTL) over OCPs. A PSPACE upper bound is inherited from the modal mu-calculus for this problem. First, we analyze the periodic behaviour of CTL over OCPs and derive a model checking algorithm whose running time is exponential only in the number of control locations and a syntactic notion of the formula that we call leftward until depth. Thus, model checking fixed OCPs against CTL formulas with a fixed leftward until depth is in P. This generalizes a result of the first author, Mayr, and To for the expression complexity of CTL's fragment EF. Second, we prove that already over some fixed OCP, CTL model checking is PSPACE-hard. Third, we show that there already exists a fixed CTL formula for which model checking of OCPs is PSPACE-hard. To obtain the latter result, we employ two results from complexity theory: (i) Converting a natural number in Chinese remainder presentation into binary presentation is in logspace-uniform NC^1 and (ii) PSPACE is AC^0-serializable. We demonstrate that our approach can be used to obtain further results. We show that model-checking CTL's fragment EF over OCPs is hard for P^NP, thus establishing a matching lower bound and answering an open question of the first author, Mayr, and To. We moreover show that the following problem is hard for PSPACE: Given a one-counter Markov decision process, a set of target states with counter value zero each, and an initial state, to decide whether the probability that the initial state will eventually reach one of the target states is arbitrarily close to 1. This improves a previously known lower bound for every level of the Boolean hierarchy by Brazdil et al.


Anonymization with Worst-Case Distribution-Based Background Knowledge

Abstract: Background knowledge is an important factor in privacy preserving data publishing. Distribution-based background knowledge is one of the well studied background knowledge. However, to the best of our knowledge, there is no existing work considering the distribution-based background knowledge in the worst case scenario, by which we mean that the adversary has accurate knowledge about the distribution of sensitive values according to some tuple attributes. Considering this worst case scenario is essential because we cannot overlook any breaching possibility. In this paper, we propose an algorithm to anonymize dataset in order to protect individual privacy by considering this background knowledge. We prove that the anonymized datasets generated by our proposed algorithm protects individual privacy. Our empirical studies show that our method preserves high utility for the published data at the same time.


User Experience, Software Interfaces, and The Unconscious

Abstract: Ideas about how to increase the unconscious participation in interaction between 'a human' and 'a computer' are developed in this paper. Evidence of impact of the unconscious functioning is presented. The unconscious is characterised as being a responsive, contextual, and autonomous participant of human-computer interaction. The unconscious participation occurs independently of one's cognitive and educational levels and, if ignored, leads to learning inefficiencies and compulsive behaviours, illustrations of which are provided. Three practical approaches to a study of subjective user experience are outlined as follows: (a) tracing operant conditioning effects of software, (b) registering signs of brain activity psychological or information processing meaning of which is well-explored and (c) exploring submodality interfaces. Implications for improvement of current usability study methods, such as eye-tracking, are generally considered. Conclusions consider advantages and disadvantages of unconscious-embracing design and remind about a loss of human evolutionary choices if unconscious participation is ignored, complicated or blocked in interaction with computer interfaces and built environment.


A Study on the Factors That Influence the Consumers Trust on Ecommerce Adoption

Abstract: The development of electronic commerce is characterized with anonymity, uncertainty, lack of control and potential opportunism. Therefore, the success of electronic commerce significantly depends on providing security and privacy for its consumers sensitive personal data. Consumers lack of acceptance in electronic commerce adoption today is not merely due to the concern on security and privacy of their personal data, but also lack of trust and reliability of Web vendors. Consumers trust in online transactions is crucial for the continuous growth and development of electronic commerce. Since Business to Consumer (B2C) ecommerce requires the consumers to engage the technologies, the consumers face a variety of security risks. This study addressed the role of security, privacy and risk perceptions of consumers to shop online in order to establish a consensus among them. The analyses provided descriptive frequencies for the research variables and for each of the study s research constructs. In addition, the analyses were completed with factor analysis and Pearson correlation coefficients. The findings suggested that perceived privacy of online transaction on trust is mediated by perceived security, and consumers trust in online transaction is significantly related with the trustworthiness of Web vendors. Also, consumers trust is negatively associated with perceived risks in online transactions. However, there is no significant impact from perceived security and perceived privacy to trust in online transactions.


Energy-Efficient Scheduling of HPC Applications in Cloud Computing Environments

Abstract: The use of High Performance Computing (HPC) in commercial and consumer IT applications is becoming popular. They need the ability to gain rapid and scalable access to high-end computing capabilities. Cloud computing promises to deliver such a computing infrastructure using data centers so that HPC users can access applications and data from a Cloud anywhere in the world on demand and pay based on what they use. However, the growing demand drastically increases the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high energy cost, which will reduce the profit margin of Cloud providers, but also high carbon emissions which is not environmentally sustainable. Hence, energy-efficient solutions are required that can address the high increase in the energy consumption from the perspective of not only Cloud provider but also from the environment. To address this issue we propose near-optimal scheduling policies that exploits heterogeneity across multiple data centers for a Cloud provider. We consider a number of energy efficiency factors such as energy cost, carbon emission rate, workload, and CPU power efficiency which changes across different data center depending on their location, architectural design, and management system. Our carbon/energy based scheduling policies are able to achieve on average up to 30% of energy savings in comparison to profit based scheduling policies leading to higher profit and less carbon emissions.


Empowering OLAC Extension using Anusaaraka and Effective text processing using Double Byte coding

Abstract: The paper reviews the hurdles while trying to implement the OLAC extension for Dravidian / Indian languages. The paper further explores the possibilities which could minimise or solve these problems. In this context, the Chinese system of text processing and the anusaaraka system are scrutinised.


n-Opposition theory to structure debates

Abstract: 2007 was the first international congress on the ?square of oppositions?. A first attempt to structure debate using n-opposition theory was presented along with the results of a first experiment on the web. Our proposal for this paper is to define relations between arguments through a structure of opposition (square of oppositions is one structure of opposition). We will be trying to answer the following questions: How to organize debates on the web 2.0? How to structure them in a logical way? What is the role of n-opposition theory, in this context? We present in this paper results of three experiments (Betapolitique 2007, ECAP 2008, Intermed 2008).


FastFlow: Efficient Parallel Streaming Applications on Multi-core

Abstract: Shared memory multiprocessors come back to popularity thanks to rapid spreading of commodity multi-core architectures. As ever, shared memory programs are fairly easy to write and quite hard to optimise; providing multi-core programmers with optimising tools and programming frameworks is a nowadays challenge. Few efforts have been done to support effective streaming applications on these architectures. In this paper we introduce FastFlow, a low-level programming framework based on lock-free queues explicitly designed to support high-level languages for streaming applications. We compare FastFlow with state-of-the-art programming frameworks such as Cilk, OpenMP, and Intel TBB. We experimentally demonstrate that FastFlow is always more efficient than all of them in a set of micro-benchmarks and on a real world application; the speedup edge of FastFlow over other solutions might be bold for fine grain tasks, as an example +35% on OpenMP, +226% on Cilk, +96% on TBB for the alignment of protein P01111 against UniProt DB using Smith-Waterman algorithm.


A rich hierarchy of functionals of finite types

Abstract: We are considering typed hierarchies of total, continuous functionals using complete, separable metric spaces at the base types. We pay special attention to the so called Urysohn space constructed by P. Urysohn. One of the properties of the Urysohn space is that every other separable metric space can be isometrically embedded into it. We discuss why the Urysohn space may be considered as the universal model of possibly infinitary outputs of algorithms. The main result is that all our typed hierarchies may be topologically embedded, type by type, into the corresponding hierarchy over the Urysohn space. As a preparation for this, we prove an effective density theorem that is also of independent interest.


Optimal Timer Based Selection Schemes

Abstract: Timer-based mechanisms are often used to help a given (sink) node select the best helper node among many available nodes. Specifically, a node transmits a packet when its timer expires, and the timer value is a monotone non-increasing function of its local suitability metric. The best node is selected successfully if no other node's timer expires within a 'vulnerability' window after its timer expiry, and so long as the sink can hear the available nodes. In this paper, we show that the optimal metric-to-timer mapping that (i) maximizes the probability of success or (ii) minimizes the average selection time subject to a minimum constraint on the probability of success, maps the metric into a set of discrete timer values. We specify, in closed-form, the optimal scheme as a function of the maximum selection duration, the vulnerability window, and the number of nodes. An asymptotic characterization of the optimal scheme turns out to be elegant and insightful. For any probability distribution function of the metric, the optimal scheme is scalable, distributed, and performs much better than the popular inverse metric timer mapping. It even compares favorably with splitting-based selection, when the latter's feedback overhead is accounted for.


Practical Schemes For Privacy & Security Enhanced RFID

Abstract: Proper privacy protection in RFID systems is important. However, many of the schemes known are impractical, either because they use hash functions instead of the more hardware efficient symmetric encryption schemes as a efficient cryptographic primitive, or because they incur a rather costly key search time penalty at the reader. Moreover, they do not allow for dynamic, fine-grained access control to the tag that cater for more complex usage scenarios. In this paper we investigate such scenarios, and propose a model and corresponding privacy friendly protocols for efficient and fine-grained management of access permissions to tags. In particular we propose an efficient mutual authentication protocol between a tag and a reader that achieves a reasonable level of privacy, using only symmetric key cryptography on the tag, while not requiring a costly key-search algorithm at the reader side. Moreover, our protocol is able to recover from stolen readers.


Efficient Learning of Sparse Conditional Random Fields for Supervised Sequence Labelling

Abstract: Conditional Random Fields (CRFs) constitute a popular and efficient approach for supervised sequence labelling. CRFs can cope with large description spaces and can integrate some form of structural dependency between labels. In this contribution, we address the issue of efficient feature selection for CRFs based on imposing sparsity through an L1 penalty. We first show how sparsity of the parameter set can be exploited to significantly speed up training and labelling. We then introduce coordinate descent parameter update schemes for CRFs with L1 regularization. We finally provide some empirical comparisons of the proposed approach with state-of-the-art CRF training strategies. In particular, it is shown that the proposed approach is able to take profit of the sparsity to speed up processing and hence potentially handle larger dimensional models.


Lower Bounds for BMRM and Faster Rates for Training SVMs

Abstract: Regularized risk minimization with the binary hinge loss and its variants lies at the heart of many machine learning problems. Bundle methods for regularized risk minimization (BMRM) and the closely related SVMStruct are considered the best general purpose solvers to tackle this problem. It was recently shown that BMRM requires $O(1/\epsilon)$ iterations to converge to an $\epsilon$ accurate solution. In the first part of the paper we use the Hadamard matrix to construct a regularized risk minimization problem and show that these rates cannot be improved. We then show how one can exploit the structure of the objective function to devise an algorithm for the binary hinge loss which converges to an $\epsilon$ accurate solution in $O(1/\sqrt{\epsilon})$ iterations.


Reordering Columns for Smaller Indexes

Abstract: Column-oriented indexes-such as projection or bitmap indexes-are compressed by run-length encoding to reduce storage and increase speed. Sorting the tables improves compression. On realistic data sets, permuting the columns in the right order before sorting can reduce the number of runs by a factor of two or more. Unfortunately, determining the best column order is NP-hard. For many cases, we prove that the number of runs in table columns is minimized if we sort columns by increasing cardinality. Experimentally, sorting based on Hilbert space-filling curves is poor at minimizing the number of runs.


Statechart Verification with iState

Abstract: This paper is the longer version of the extended abstract with the same name published in FM 06. We describe in detail the algorithm to generate verification conditions from statechart structures implemented in the iState tool. This approach also suggests us a novel method to define a version of predicate semantics for statecharts analogous to how we assign predicate semantics to programming languages.


High level architecture evolved modular federation object model

Abstract: To improve the agility, dynamics, composability, reusability, and development efficiency restricted by monolithic Federation Object Model (FOM), a modular FOM was proposed by High Level Architecture (HLA) Evolved product development group. This paper reviews the state-of-the-art of HLA Evolved modular FOM. In particular, related concepts, the overall impact on HLA standards, extension principles, and merging processes are discussed. Also permitted and restricted combinations, and merging rules are provided, and the influence on HLA interface specification is given. The comparison between modular FOM and Base Object Model (BOM) is performed to illustrate the importance of their combination. The applications of modular FOM are summarized. Finally, the significance to facilitate composable simulation both in academia and practice is presented and future directions are pointed out.


The Uniformization Process of the Fast Congestion Notification (FN)

Abstract: Fast Congestion Notification (FN) is one of the proactive queue management mechanisms that practices congestion avoidance to help avoid the beginning of congestion by marking or dropping packets before the routers queue gets full; and exercises congestion control, when congestion avoidance fails, by increasing the rate of packet marking or dropping. Technically, FN avoids the queue overflows by controlling the instantaneous queue size below the optimal queue size, and control congestion by keeping the average arrival rate close to the outgoing link capacity. Upon arrival of each packet, FN uses the instantaneous queue size and the average arrival rate to calculate the packet marking or dropping probability. FN marks or drops packets at fairly regular intervals to avoid long intermarking intervals and clustered packet marks or drops. Too many marked or dropped packets close together can cause global synchronization, and also too long packet intermarking times between marked or dropped packets can cause large queue sizes and congestion. This paper shows how FN controls the queue size, avoids congestion, and reduces global synchronization by uniformizing marked or dropped packet intervals.