Law-Aware Access Control and its Information Model

Abstract: Cross-border access to a variety of data such as market information, strategic information, or customer-related information defines the daily business of many global companies, including financial institutions. These companies are obliged by law to keep a data processing legal for all offered services. They need to fulfill different security objectives specified by the legislation. Therefore, they control access to prevent unauthorized users from using data. Those security objectives, for example confidentiality or secrecy, are often defined in the eXtensible Access Control Markup Language that promotes interoperability between different systems. In this paper, we show the necessity of incorporating the requirements of legislation into access control. Based on the work flow in a banking scenario we describe a variety of available contextual information and their interrelations. Different from other access control systems our main focus is on law-compliant cross-border data access. By including legislation directly into access decisions, this lawfulness can be ensured. We also describe our information model to demonstrate how these policies can be implemented into an existing network and how the components and contextual information interrelate. Finally, we outline an event flow for a request made from a remote user exemplifying how such a system decides about access.


A New Energy Efficient Routing Algorithm Based on a New Cost Function in Wireless Ad hoc Networks

Abstract: Wireless ad hoc networks are power constrained since nodes operate with limited battery energy. Thus, energy consumption is crucial in the design of new ad hoc routing protocols. In order to maximize the lifetime of ad hoc networks, traffic should be sent via a route that can be avoid nodes with low energy. In addition, considering that the nodes of ad hoc networks are mobile, it is possible that a created path is broken because of nodes mobility and establishment of a new path would be done again. This is because of sending additional control packets, accordingly, energy consumption increases. Also, it should avoid nodes which have more buffered packets. Maybe, because of long queue, some of these packets are dropped and transmitted again. This is the reason for wasting of energy. In this paper we propose a new energy efficient algorithm, that uses a new cost function and avoid nodes with characteristics which mentioned above. We show that this algorithm improves the network energy consumption by using this new cost function.


Search Engine Optimization Techniques Practiced in Organizations: A Study of Four Organizations

Abstract: Web spammers used Search Engine Optimization (SEO) techniques to increase search-ranking of web sites. In this paper we have study the essentials SEO techniques, such as; directory submission, keyword generation and link exchanges. The impact of SEO techniques can be applied as marketing technique and to get top listing in major search engines like Google, Yahoo, and MSN. Our study focuses on these techniques from four different companies' perspectives of United Kingdom and Pakistan. According to the these companies, these techniques are low cost and high impacts in profit, because mostly customers focus on major search engine to find different products on internet, so SEO technique provides best opportunity to grow their business. This paper also describes the pros and cons of using these searh engine optimization techniques in above four companies. We have concluded that these techniques are essential to increase their business profit and minimize their marketing cost.


Analytical Study on Internet Banking System

Abstract: The Internet era is a period in the information age in which communication and commerce via the Internet became a central focus for businesses, consumers, government, and the media. The Internet era also marks the convergence of the computer and communications industries and their associated services and products. Nowadays, the availability of the Internet make it widely used for everyday life. In order to led business to success, the business and specially the services should provide comfort use to its costumer. The bank system is one of the most important businesses who may use the website. The using for the web-based systems should contain special requirements to achieve the business goal. Since that the paper will present the functional and non-functional for the web-based banking system.


An Efficient Technique for Similarity Identification between Ontologies

Abstract: Ontologies usually suffer from the semantic heterogeneity when simultaneously used in information sharing, merging, integrating and querying processes. Therefore, the similarity identification between ontologies being used becomes a mandatory task for all these processes to handle the problem of semantic heterogeneity. In this paper, we propose an efficient technique for similarity measurement between two ontologies. The proposed technique identifies all candidate pairs of similar concepts without omitting any similar pair. The proposed technique can be used in different types of operations on ontologies such as merging, mapping and aligning. By analyzing its results a reasonable improvement in terms of completeness, correctness and overall quality of the results has been found.


Engineering Semantic Web Applications by Using Object-Oriented Paradigm

Abstract: The web information resources are growing explosively in number and volume. Now to retrieve relevant data from web has become very difficult and time-consuming. Semantic Web envisions that these web resources should be developed in machine-processable way in order to handle irrelevancy and manual processing problems. Whereas, the Semantic Web is an extension of current web, in which web resources are equipped with formal semantics about their interpretation through machines. These web resources are usually contained in web applications and systems, and their formal semantics are normally represented in the form of web-ontologies. In this research paper, an object-oriented design methodology (OODM) is upgraded for developing semantic web applications. OODM has been developed for designing of web applications for the current web. This methodology is good enough to develop web applications. It also provides a systematic approach for the web applications development but it is not helpful in generating machine-pocessable content of web applications in their development. Therefore, this methodology needs to be extended. In this paper, we propose that extension in OODM. This new extended version is referred to as the semantic web object-oriented design methodology (SW-OODM).


The State of the Art: Ontology Web-Based Languages: XML Based

Abstract: Many formal languages have been proposed to express or represent Ontologies, including RDF, RDFS, DAML+OIL and OWL. Most of these languages are based on XML syntax, but with various terminologies and expressiveness. Therefore, choosing a language for building an Ontology is the main step. The main point of choosing language to represent Ontology is based mainly on what the Ontology will represent or be used for. That language should have a range of quality support features such as ease of use, expressive power, compatibility, sharing and versioning, internationalisation. This is because different kinds of knowledge-based applications need different language features. The main objective of these languages is to add semantics to the existing information on the web. The aims of this paper is to provide a good knowledge of existing language and understanding of these languages and how could be used.


An Overview: Extensible Markup Language Technology

Abstract: XML stands for the Extensible Markup Language. It is a markup language for documents, Nowadays XML is a tool to develop and likely to become a much more common tool for sharing data and store. XML can communicate structured information to other users. In other words, if a group of users agree to implement the same kinds of tags to describe a certain kind of information, XML applications can assist these users in communicating their information in an more robust and efficient manner. XML can make it easier to exchange information between cooperating entities. In this paper we will present the XML technique by fourth factors Strength of XML, XML Parser, XML Goals and Types of XML Parsers.


Understanding Semantic Web and Ontologies: Theory and Applications

Abstract: Semantic Web is actually an extension of the current one in that it represents information more meaningfully for humans and computers alike. It enables the description of contents and services in machine-readable form, and enables annotating, discovering, publishing, advertising and composing services to be automated. It was developed based on Ontology, which is considered as the backbone of the Semantic Web. In other words, the current Web is transformed from being machine-readable to machine-understandable. In fact, Ontology is a key technique with which to annotate semantics and provide a common, comprehensible foundation for resources on the Semantic Web. Moreover, Ontology can provide a common vocabulary, a grammar for publishing data, and can supply a semantic description of data which can be used to preserve the Ontologies and keep them ready for inference. This paper provides basic concepts of web services and the Semantic Web, defines the structure and the main applications of ontology, and provides many relevant terms are explained in order to provide a basic understanding of ontologies.


Approaches, Challenges and Future Direction of Image Retrieval

Abstract: This paper attempts to discuss the evolution of the retrieval approaches focusing on development, challenges and future direction of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users' mind. Hence, introducing an interpretation inconsistency between image descriptors and high level semantics that known as the semantic gap. This paper also discusses the semantic gap issues, user query mechanisms as well as common ways used to bridge the gap in image retrieval.


Advanced Trace Pattern For Computer Intrusion Discovery

Abstract: The number of crime committed based on the malware intrusion is never ending as the number of malware variants is growing tremendously and the usage of internet is expanding globally. Malicious codes easily obtained and use as one of weapon to gain their objective illegally. Hence, in this research, diverse logs from different OSI layer are explored to identify the traces left on the attacker and victim logs in order to establish worm trace pattern to defending against the attack and help revealing true attacker or victim. For the purpose of this paper, it focused on malware intrusion and traditional worm namely sasser worm variants. The concept of trace pattern is created by fusing the attacker's and victim's perspective. Therefore, the objective of this paper is to propose a general worm trace pattern for attacker's, victim's and multi-step (attacker/victim)'s by combining both perspectives. These three proposed worm trace patterns can be extended into research areas in alert correlation and computer forensic investigation.


Optimization of reversible sequential circuits

Abstract: In recent years reversible logic has been considered as an important issue for designing low power digital circuits. It has voluminous applications in the present rising nanotechnology such as DNA computing, Quantum Computing, low power VLSI and quantum dot automata. In this paper we have proposed optimized design of reversible sequential circuits in terms of number of gates, delay and hardware complexity. We have designed the latches with a new reversible gate and reduced the required number of gates, garbage outputs, and delay and hardware complexity. As the number of gates and garbage outputs increase the complexity of reversible circuits, this design will significantly enhance the performance. We have proposed reversible D-latch and JK latch which are better than the existing designs available in literature.


A Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications

Abstract: We propose a framework for deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.


Vertex Sparsifiers: New Results from Old Techniques

Abstract: Given a capacitated graph $G = (V,E)$ and a set of terminals $K \subseteq V$, how should we produce a graph $H$ only on the terminals $K$ so that every (multicommodity) flow between the terminals in $G$ could be supported in $H$ with low congestion, and vice versa? (Such a graph $H$ is called a flow-sparsifier for $G$.) What if we want $H$ to be a "simple" graph? What if we allow $H$ to be a convex combination of simple graphs? Improving on results of Moitra [FOCS 2009] and Leighton and Moitra [STOC 2010], we give efficient algorithms for constructing: (a) a flow-sparsifier $H$ that maintains congestion up to a factor of $O(\log k/\log \log k)$, where $k = |K|$, (b) a convex combination of trees over the terminals $K$ that maintains congestion up to a factor of $O(\log k)$, and (c) for a planar graph $G$, a convex combination of planar graphs that maintains congestion up to a constant factor. This requires us to give a new algorithm for the 0-extension problem, the first one in which the preimages of each terminal are connected in $G$. Moreover, this result extends to minor-closed families of graphs. Our improved bounds immediately imply improved approximation guarantees for several terminal-based cut and ordering problems.


Efficient Region-Based Image Querying

Abstract: Retrieving images from large and varied repositories using visual contents has been one of major research items, but a challenging task in the image management community. In this paper we present an efficient approach for region-based image classification and retrieval using a fast multi-level neural network model. The advantages of this neural model in image classification and retrieval domain will be highlighted. The proposed approach accomplishes its goal in three main steps. First, with the help of a mean-shift based segmentation algorithm, significant regions of the image are isolated. Secondly, color and texture features of each region are extracted by using color moments and 2D wavelets decomposition technique. Thirdly the multi-level neural classifier is trained in order to classify each region in a given image into one of five predefined categories, i.e., "Sky", "Building", "SandnRock", "Grass" and "Water". Simulation results show that the proposed method is promising in terms of classification and retrieval accuracy results. These results compare favorably with the best published results obtained by other state-of-the-art image retrieval techniques.


Metric Extension Operators, Vertex Sparsifiers and Lipschitz Extendability

Abstract: We study vertex cut and flow sparsifiers that were recently introduced by Moitra, and Leighton and Moitra. We improve and generalize their results. We give a new polynomial-time algorithm for constructing O(log k / log log k) cut and flow sparsifiers, matching the best existential upper bound on the quality of a sparsifier, and improving the previous algorithmic upper bound of O(log^2 k / log log k). We show that flow sparsifiers can be obtained from linear operators approximating minimum metric extensions. We introduce the notion of (linear) metric extension operators, prove that they exist, and give an exact polynomial-time algorithm for finding optimal operators. We then establish a direct connection between flow and cut sparsifiers and Lipschitz extendability of maps in Banach spaces, a notion studied in functional analysis since 1930s. Using this connection, we prove a lower bound of Omega(sqrt{log k/log log k}) for flow sparsifiers and a lower bound of Omega(sqrt{log k}/log log k) for cut sparsifiers. We show that if a certain open question posed by Ball in 1992 has a positive answer, then there exist \tilde O(sqrt{log k}) cut sparsifiers. On the other hand, any lower bound on cut sparsifiers better than \tilde Omega(sqrt{log k}) would imply a negative answer to this question.


The Question of Expressiveness in the Generation of Referring Expressions

Abstract: We study the problem of generating referring expressions modulo different notions of expressive power. We define the notion of $\+L$-referring expression, for a formal language $\+L$ equipped with a semantics in terms of relational models. We show that the approach is independent of the particular algorithm used to generate the referring expression by providing examples using the frameworks of \cite{AKS08} and \cite{Krahmer2003}. We provide some new complexity bounds, discuss the issue of the length of the generated descriptions, and propose ways in which the two approaches can be combined.


State Complexity of Two Combined Operations: Reversal-Catenation and Star-Catenation

Abstract: In this paper, we show that, due to the structural properties of the resulting automaton obtained from a prior operation, the state complexity of a combined operation may not be equal but close to the mathematical composition of the state complexities of its component operations. In particular, we provide two witness combined operations: reversal combined with catenation and star combined with catenation.


Using Repeating Decimals As An Alternative To Prime Numbers In Encryption

Abstract: This article is meant to provide an additional point of view, applying known knowledge, to supply keys that have a series of non-repeating digits, in a manner that is not usually thought of. Traditionally, prime numbers are used in encryption as keys that have non-repeating sequences. Usually, non-repetition, especially of digits in a key, is very sought after in encryption. Uniqueness in a digit sequence defeats decryption. In searching for methods of non-decryptable encryption as well as ways to provide unique sequences, other than using prime numbers [5], the idea of using repeating decimals came to me. Applied correctly, a repeating decimal series of sufficient length will stand in as well for a prime number. This is so, because only numbers prime to each other will produce repeating decimals and; within the repeating sequence there is uniqueness of digit sequence.


Dynamic Observers for Fault Diagnosis of Timed Systems

Abstract: In this paper we extend the work on \emph{dynamic ob\-servers} for fault diagnosis to timed automata. We study sensor minimization problems with static observers and then address the problem of computing the most permissive dynamic observer for a system given by a timed automaton.


Competitive Equilibria in Two Sided Matching Markets with Non-transferable Utilities

Abstract: We consider two sided matching markets consisting of agents with non-transferable utilities; agents from the opposite sides form matching pairs (e.g., buyers-sellers) and negotiate the terms of their math which may include a monetary transfer. Competitive equilibria are the elements of the core of this game. We present the first combinatorial characterization of competitive equilibria that relates the utility of each agent at equilibrium to the equilibrium utilities of other agents in a strictly smaller market excluding that agent; thus automatically providing a constructive proof of existence of competitive equilibria in such markets. Our characterization also yields a group strategyproof mechanism for allocating indivisible goods to unit demand buyers with non-quasilinear utilities that highly resembles the Vickrey Clarke Groves (VCG) mechanism. As a direct application of this, we present a group strategyproof welfare maximizing mechanism for Ad-Auctions without requiring the usual assumption that search engine and advertisers have consistent estimates of the clickthrough rates.


Arithmetic circuits: the chasm at depth four gets wider

Abstract: In their paper on the "chasm at depth four", Agrawal and Vinay have shown that polynomials in m variables of degree O(m) which admit arithmetic circuits of size 2^o(m) also admit arithmetic circuits of depth four and size 2^o(m). This theorem shows that for problems such as arithmetic circuit lower bounds or black-box derandomization of identity testing, the case of depth four circuits is in a certain sense the general case. In this paper we show that smaller depth four circuits can be obtained if we start from polynomial size arithmetic circuits. For instance, we show that if the permanent of n*n matrices has circuits of size polynomial in n, then it also has depth 4 circuits of size n^O(sqrt(n)*log(n)). Our depth four circuits use integer constants of polynomial size. These results have potential applications to lower bounds and deterministic identity testing, in particular for sums of products of sparse univariate polynomials. We also give an application to boolean circuit complexity, and a simple (but suboptimal) reduction to polylogarithmic depth for arithmetic circuits of polynomial size and polynomially bounded degree.


A Survey on Peer-to-Peer and DHT

Abstract: Distributed systems with different levels of dependence to central services have been designed and used during recent years. Pure peer-to-peer systems among distributed systems have no dependence on a central resource. DHT is one of the main techniques behind these systems resulting into failure tolerant systems which are also able to isolate continuous changes to the network to a small section of it and therefore making it possible to scale up such networks to millions of nodes. This survey takes a look at P2P in general and DHT algorithms and implementations in more detail.


A Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications (Extended Abstract)

Abstract: We propose a framework for the deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.


A Middleware Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications

Abstract: We propose a middleware framework for deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.


Support for Evolving Software Architectures in the ArchWare ADL

Abstract: Software that cannot evolve is condemned to atrophy: it cannot accommodate the constant revision and re-negotiation of its business goals nor intercept the potential of new technology. To accommodate change in software systems we have defined an active software architecture to be: dynamic in that the structure and cardinality of the components and interactions are changeable during execution; updatable in that components can be replaced; decomposable in that an executing system may be (partially) stopped and split up into its components and interactions; and reflective in that the specification of components and interactions may be evolved during execution. Here we describe the facilities of the ArchWare architecture description language (ADL) for specifying active architectures. The contribution of the work is the unique combination of concepts including: a {\pi}-calculus based communication and expression language for specifying executable architectures; hyper-code as an underlying representation of system execution that can be used for introspection; a decomposition operator to incrementally break up executing systems; and structural reflection for creating new components and binding them into running systems.


Active Architecture for Pervasive Contextual Services

Abstract: Pervasive services may be defined as services that are available "to any client (anytime, anywhere)". Here we focus on the software and network infrastructure required to support pervasive contextual services operating over a wide area. One of the key requirements is a matching service capable of as-similating and filtering information from various sources and determining matches relevant to those services. We consider some of the challenges in engineering a globally distributed matching service that is scalable, manageable, and able to evolve incrementally as usage patterns, data formats, services, network topologies and deployment technologies change. We outline an approach based on the use of a peer-to-peer architecture to distribute user events and data, and to support the deployment and evolution of the infrastructure itself.


Active Sites model for the B-Matrix Approach

Abstract: This paper continues on the work of the B-Matrix approach in hebbian learning proposed by Dr. Kak. It reports the results on methods of improving the memory retrieval capacity of the hebbian neural network which implements the B-Matrix approach. Previously, the approach to retrieving the memories from the network was to clamp all the individual neurons separately and verify the integrity of these memories. Here we present a network with the capability to identify the "active sites" in the network during the training phase and use these "active sites" to generate the memories retrieved from these neurons. Three methods are proposed for obtaining the update order of the network from the proximity matrix when multiple neurons are to be clamped. We then present a comparison between the new methods to the classical case and also among the methods themselves.


Cut-Elimination and Proof Search for Bi-Intuitionistic Tense Logic

Abstract: We consider an extension of bi-intuitionistic logic with the traditional modalities from tense logic Kt. Proof theoretically, this extension is obtained simply by extending an existing sequent calculus for bi-intuitionistic logic with typical inference rules for the modalities used in display logics. As it turns out, the resulting calculus, LBiKt, seems to be more basic than most intuitionistic tense or modal logics considered in the literature, in particular, those studied by Ewald and Simpson, as it does not assume any a priori relationship between the diamond and the box modal operators. We recover Ewald's intuitionistic tense logic and Simpson's intuitionistic modal logic by modularly extending LBiKt with additional structural rules. The calculus LBiKt is formulated in a variant of display calculus, using a form of sequents called nested sequents. Cut elimination is proved for LBiKt, using a technique similar to that used in display calculi. As in display calculi, the inference rules of LBiKt are ``shallow'' rules, in the sense that they act on top-level formulae in a nested sequent. The calculus LBiKt is ill-suited for backward proof search due to the presence of certain structural rules called ``display postulates'' and the contraction rules on arbitrary structures. We show that these structural rules can be made redundant in another calculus, DBiKt, which uses deep inference, allowing one to apply inference rules at an arbitrary depth in a nested sequent. We prove the equivalence between LBiKt and DBiKt and outline a proof search strategy for DBiKt. We also give a Kripke semantics and prove that LBiKt is sound with respect to the semantics, but completeness is still an open problem. We then discuss various extensions of LBiKt.


Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems

Abstract: In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA system (named as secondary system) dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed for the secondary system, where relay stations are employed for minimizing the interference to the users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an asymptotically optimal solution is derived for jointly controlling data rates, transmission power, and subchannel allocation to optimize the average weighted sum goodput where the proportional fair scheduling (PFS) is included as a special case. This solution supports decentralized implementation, requires small communication overhead, and is robust against imperfect channel state information at the transmitter (CSIT) and sensing measurement. The proposed solution achieves significant throughput gains and better user-fairness compared with the existing designs. Finally, we derived a simple and asymptotically optimal scheduling solution as well as the associated closed-form performance under the proportional fair scheduling for a large number of users. The system throughput is shown to be $\mathcal{O}\left(N(1-q_p)(1-q_p^N)\ln\ln K_c\right)$, where $K_c$ is the number of users in one cluster, $N$ is the number of subchannels and $q_p$ is the active probability of primary users.


Architectural Support for Global Smart Spaces

Abstract: A GLObal Smart Space (GLOSS) provides support for interaction amongst people, artefacts and places while taking account of both context and movement on a global scale. Crucial to the definition of a GLOSS is the provision of a set of location-aware services that detect, convey, store and exploit location information. We use one of these services, hearsay, to illustrate the implementation dimensions of a GLOSS. The focus of the paper is on both local and global software architecture to support the implementation of such services. The local architecture is based on XML pipe-lines and is used to construct location-aware components. The global architecture is based on a hybrid peer-to-peer routing scheme and provides the local architectures with the means to communicate in the global context.


An Efficient Algorithm For Chinese Postman Walk on Bi-directed de Bruijn Graphs

Abstract: Sequence assembly from short reads is an important problem in biology. It is known that solving the sequence assembly problem exactly on a bi-directed de Bruijn graph or a string graph is intractable. However finding a Shortest Double stranded DNA string (SDDNA) containing all the k-long words in the reads seems to be a good heuristic to get close to the original genome. This problem is equivalent to finding a cyclic Chinese Postman (CP) walk on the underlying un-weighted bi-directed de Bruijn graph built from the reads. The Chinese Postman walk Problem (CPP) is solved by reducing it to a general bi-directed flow on this graph which runs in O(|E|2 log2(|V |)) time. In this paper we show that the cyclic CPP on bi-directed graphs can be solved without reducing it to bi-directed flow. We present a ?(p(|V | + |E|) log(|V |) + (dmaxp)3) time algorithm to solve the cyclic CPP on a weighted bi-directed de Bruijn graph, where p = max{|{v|din(v) - dout(v) > 0}|, |{v|din(v) - dout(v) < 0}|} and dmax = max{|din(v) - dout(v)}. Our algorithm performs asymptotically better than the bidirected flow algorithm when the number of imbalanced nodes p is much less than the nodes in the bi-directed graph. From our experimental results on various datasets, we have noticed that the value of p/|V | lies between 0.08% and 0.13% with 95% probability.


Constructing Active Architectures in the ArchWare ADL

Abstract: Software that cannot change is condemned to atrophy: it cannot accommodate the constant revision and re-negotiation of its business goals nor intercept the potential of new technology. To accommodate change in such systems we have defined an active software architecture to be: dynamic in that the structure and cardinality of the components and interactions are not statically known; updatable in that components can be replaced dynamically; and evolvable in that it permits its executing specification to be changed. Here we describe the facilities of the ArchWare architecture description language (ADL) for specifying active architectures. The contribution of the work is the unique combination of concepts including: a {\pi}-calculus based communication and expression language for specifying executable architectures; hyper-code as an underlying representation of system execution; a decomposition operator to break up and introspect on executing systems; and structural reflection for creating new components and binding them into running systems.


MINLIP for the Identification of Monotone Wiener Systems

Abstract: This paper studies the MINLIP estimator for the identification of Wiener systems consisting of a sequence of a linear FIR dynamical model, and a monotonically increasing (or decreasing) static function. Given $T$ observations, this algorithm boils down to solving a convex quadratic program with $O(T)$ variables and inequality constraints, implementing an inference technique which is based entirely on model complexity control. The resulting estimates of the linear submodel are found to be almost consistent when no noise is present in the data, under a condition of smoothness of the true nonlinearity and local Persistency of Excitation (local PE) of the data. This result is novel as it does not rely on classical tools as a 'linearization' using a Taylor decomposition, nor exploits stochastic properties of the data. It is indicated how to extend the method to cope with noisy data, and empirical evidence contrasts performance of the estimator against other recently proposed techniques.


A Generic Storage API

Abstract: We present a generic API suitable for provision of highly generic storage facilities that can be tailored to produce various individually customised storage infrastructures. The paper identifies a candidate set of minimal storage system building blocks, which are sufficiently simple to avoid encapsulating policy where it cannot be customised by applications, and composable to build highly flexible storage architectures. Four main generic components are defined: the store, the namer, the caster and the interpreter. It is hypothesised that these are sufficiently general that they could act as building blocks for any information storage and retrieval system. The essential characteristics of each are defined by an interface, which may be implemented by multiple implementing classes.


Quotient Complexity of Bifix-, Factor-, and Subword-Free Regular Languages

Abstract: A language L is prefix-free if, whenever words u and v are in L and u is a prefix of v, then u=v. Suffix-, factor-, and subword-free languages are defined similarly, where "subword" means "subsequence". A language is bifix-free if it is both prefix- and suffix-free. We study the quotient complexity, more commonly known as state complexity, of operations in the classes of bifix-, factor-, and subword-free regular languages. We find tight upper bounds on the quotient complexity of intersection, union, difference, symmetric difference, concatenation, star, and reversal in these three classes of languages.


Mapping Business Process Modeling constructs to Behavior Driven Development Ubiquitous Language

Abstract: Behavior-Driven Development (BDD) is a specification technique that automatically certifies that all functional requirements are treated properly by source code, through the connection of the textual description of these requirements to automated tests. Given that in some areas, in special Enterprise Information Systems, requirements are identified by Business Process Modeling - which uses graphical notations of the underlying business processes, this paper aims to provide a mapping from the basic constructs that form the most common BPM languages to Behavior Driven Development constructs.


Optimal Degree Distributions for Uniform Small World Rings

Abstract: Motivated by Kleinberg's (2000) and subsequent work, we consider the performance of greedy routing on a directed ring of $n$ nodes augmented with long-range contacts. In this model, each node $u$ is given an additional $D_u$ edges, a degree chosen from a specified probability distribution. Each such edge from $u$ is linked to a random node at distance $r$ ahead in the ring with probability proportional to $1/r$, a "harmonic" distance distribution of contacts. Aspnes et al. (2002) have shown an $O(\log^2 n / \ell)$ bound on the expected length of greedy routes in the case when each node is assigned exactly $\ell$ contacts and, as a consequence of recent work by Dietzfelbinger and Woelfel (2009), this bound is known to be tight. In this paper, we generalize Aspnes' upper bound to show that any degree distribution with mean $\ell$ and maximum value $O(\log n)$ has greedy routes of expected length $O(\log^2n / \ell)$, implying that any harmonic ring in this family is asymptotically optimal. Furthermore, for a more general family of rings, we show that a fixed degree distribution is optimal. More precisely, if each random contact is chosen at distance $r$ with a probability that decreases with $r$, then among degree distributions with mean $\ell$, greedy routing time is smallest when every node is assigned $\floor{\ell}$ or $\ceiling{\ell}$ contacts.


Kalman Filters and Homography: Utilizing the Matrix $A$

Abstract: Many problems in Computer Vision can be reduced to either working around a known transform, or given a model for the transform computing the inverse problem of the transform itself. We will look at two ways of working with the matrix $A$ and see how transforms are at the root of image processing and vision problems.


Complexity Classifications for Propositional Abduction in Post's Framework

Abstract: In this paper we investigate the complexity of abduction, a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining the world's behavior it aims at finding an explanation for some observed manifestation. In this paper we consider propositional abduction, where the knowledge base and the manifestation are represented by propositional formulae. The problem of deciding whether there exists an explanation has been shown to be \SigPtwo-complete in general. We focus on formulae in which the allowed connectives are taken from certain sets of Boolean functions. We consider different variants of the abduction problem in restricting both the manifestations and the hypotheses. For all these variants we obtain a complexity classification for all possible sets of Boolean functions. In this way, we identify easier cases, namely \NP-complete, \coNP-complete and polynomial cases. Thus, we get a detailed picture of the complexity of the propositional abduction problem, hence highlighting sources of intractability. Further, we address the problem of counting the explanations and draw a complete picture for the counting complexity.


Simulating information creation in social Semantic Web applications

Abstract: Appropriate ranking algorithms and incentive mechanisms are essential to the creation of high-quality information by users of a social network. However, evaluating such mechanisms in a quantifiable way is a difficult problem. Studies of live social networks of limited utility, due to the subjective nature of ranking and the lack of experimental control. Simulation provides a valuable alternative: insofar as the simulation resembles the live social network, fielding a new algorithm within a simulated network can predict the effect it will have on the live network. In this paper, we propose a simulation model based on the actor-conceptinstance model of semantic social networks, then we evaluate the model against a number of common ranking algorithms.We observe their effects on information creation in such a network, and we extend our results to the evaluation of generic ranking algorithms and incentive mechanisms.


Proof-theoretic Analysis of Rationality for Strategic Games with Arbitrary Strategy Sets

Abstract: In the context of strategic games, we provide an axiomatic proof of the statement Common knowledge of rationality implies that the players will choose only strategies that survive the iterated elimination of strictly dominated strategies. Rationality here means playing only strategies one believes to be best responses. This involves looking at two formal languages. One is first-order, and is used to formalise optimality conditions, like avoiding strictly dominated strategies, or playing a best response. The other is a modal fixpoint language with expressions for optimality, rationality and belief. Fixpoints are used to form expressions for common belief and for iterated elimination of non-optimal strategies.


Distributed Greedy Scheduling for Multihop Wireless Networks

Abstract: We consider the problem of scheduling in multihop wireless networks subject to interference constraints. We consider a graph based representation of wireless networks, where scheduled links adhere to the K-hop link interference model. We develop a distributed greedy heuristic for this scheduling problem. Further, we show that this distributed greedy heuristic computes the exact same schedule as the centralized greedy heuristic.


Sound Bisimulations for Higher-Order Distributed Process Calculus

Abstract: While distributed systems with transfer of processes have become pervasive, methods for reasoning about their behaviour are underdeveloped. In this paper we propose a bisimulation technique for proving behavioural equivalence of such systems modelled in the \emph{higher-order $\pi$-calculus with passivation} (and restriction). Previous research for this calculus is limited to context bisimulations and normal bisimulations which are either impractical or unsound. In contrast, we provide a sound and useful definition of \emph{environmental bisimulations}, with several non-trivial examples. Technically, a central point in our bisimulations is the clause for parallel composition, which must account for passivation of the spawned processes in the middle of their execution.


A Virtual Queue Approach for Online Estimation of Loss Probability Based on MVA Theory

Abstract: In network quality of service provisioning, premium services generally require to keep a very small loss probability, which is infeasible to measure directly. The proposed virtual queue scheme estimates the small packet loss probability of a real queueing system by measuring queue statistics in a set of separate virtual queues. A novel scaling property between the real queue and the virtual queues is deduced on the basis of the maximum variance asymptotic (MVA) theory. The new scheme retains the high accuracy and wide applicability of the MVA method for aggregated traffic while avoiding the high computational complexity in a direct application of the original MVA analysis in real time. This makes it suitable for online measurement applications such as network performance monitoring and measurement-based admission control.


Automatic Music Composition using Answer Set Programming

Abstract: Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).


Artificial Immune Systems (2010)

Abstract: The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the mechanisms of AIS; these are the idiotypic network approach and the Dendritic Cell Algorithm.


Large scale link based latent Dirichlet allocation for web document classification

Abstract: In this paper we demonstrate the applicability of latent Dirichlet allocation (LDA) for classifying large Web document collections. One of our main results is a novel influence model that gives a fully generative model of the document content taking linkage into account. In our setup, topics propagate along links in such a way that linked documents directly influence the words in the linking document. As another main contribution we develop LDA specific boosting of Gibbs samplers resulting in a significant speedup in our experiments. The inferred LDA model can be applied for classification as dimensionality reduction similarly to latent semantic indexing. In addition, the model yields link weights that can be applied in algorithms to process the Web graph; as an example we deploy LDA link weights in stacked graphical learning. By using Weka's BayesNet classifier, in terms of the AUC of classification, we achieve 4% improvement over plain LDA with BayesNet and 18% over tf.idf with SVM. Our Gibbs sampling strategies yield about 5-10 times speedup with less than 1% decrease in accuracy in terms of likelihood and AUC of classification.


Local Termination: theory and practice

Abstract: The characterisation of termination using well-founded monotone algebras has been a milestone on the way to automated termination techniques, of which we have seen an extensive development over the past years. Both the semantic characterisation and most known termination methods are concerned with global termination, uniformly of all the terms of a term rewriting system (TRS). In this paper we consider local termination, of specific sets of terms within a given TRS. The principal goal of this paper is generalising the semantic characterisation of global termination to local termination. This is made possible by admitting the well-founded monotone algebras to be partial. We also extend our approach to local relative termination. The interest in local termination naturally arises in program verification, where one is probably interested only in sensible inputs, or just wants to characterise the set of inputs for which a program terminates. Local termination will be also be of interest when dealing with a specific class of terms within a TRS that is known to be non-terminating, such as combinatory logic (CL) or a TRS encoding recursive program schemes or Turing machines. We show how some of the well-known techniques for proving global termination, such as stepwise removal of rewrite rules and semantic labelling, can be adapted to the local case. We also describe transformations reducing local to global termination problems. The resulting techniques for proving local termination have in some cases already been automated. One of our applications concerns the characterisation of the terminating S-terms in CL as regular language. Previously this language had already been found via a tedious analysis of the reduction behaviour of S-terms. These findings have now been vindicated by a fully automated and verified proof.


Open-Ended Evolutionary Robotics: an Information Theoretic Approach

Abstract: This paper is concerned with designing self-driven fitness functions for Embedded Evolutionary Robotics. The proposed approach considers the entropy of the sensori-motor stream generated by the robot controller. This entropy is computed using unsupervised learning; its maximization, achieved by an on-board evolutionary algorithm, implements a "curiosity instinct", favouring controllers visiting many diverse sensori-motor states (sms). Further, the set of sms discovered by an individual can be transmitted to its offspring, making a cultural evolution mode possible. Cumulative entropy (computed from ancestors and current individual visits to the sms) defines another self-driven fitness; its optimization implements a "discovery instinct", as it favours controllers visiting new or rare sensori-motor states. Empirical results on the benchmark problems proposed by Lehman and Stanley (2008) comparatively demonstrate the merits of the approach.


GraphLab: A New Framework for Parallel Machine Learning

Abstract: Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insufficiently expressive while low-level tools like MPI and Pthreads leave ML experts repeatedly solving the same design challenges. By targeting common patterns in ML, we developed GraphLab, which improves upon abstractions like MapReduce by compactly expressing asynchronous iterative algorithms with sparse computational dependencies while ensuring data consistency and achieving a high degree of parallel performance. We demonstrate the expressiveness of the GraphLab framework by designing and implementing parallel versions of belief propagation, Gibbs sampling, Co-EM, Lasso and Compressed Sensing. We show that using GraphLab we can achieve excellent parallel performance on large scale real-world problems.


A Game Theoretical Analysis of Localization Security in Wireless Sensor Networks with Adversaries

Abstract: Wireless Sensor Networks (WSN) support data collection and distributed data processing by means of very small sensing devices that are easy to tamper and cloning: therefore classical security solutions based on access control and strong authentication are difficult to deploy. In this paper we look at the problem of assessing security of node localization. In particular, we analyze the scenario in which Verifiable Multilateration (VM) is used to localize nodes and a malicious node (i.e., the adversary) try to masquerade as non-malicious. We resort to non-cooperative game theory and we model this scenario as a two-player game. We analyze the optimal players' strategy and we show that the VM is indeed a proper mechanism to reduce fake positions.


Detecting Danger: The Dendritic Cell Algorithm

Abstract: The Dendritic Cell Algorithm (DCA) is inspired by the function of the dendritic cells of the human immune system. In nature, dendritic cells are the intrusion detection agents of the human body, policing the tissue and organs for potential invaders in the form of pathogens. In this research, and abstract model of DC behaviour is developed and subsequently used to form an algorithm, the DCA. The abstraction process was facilitated through close collaboration with laboratory- based immunologists, who performed bespoke experiments, the results of which are used as an integral part of this algorithm. The DCA is a population based algorithm, with each agent in the system represented as an 'artificial DC'. Each DC has the ability to combine multiple data streams and can add context to data suspected as anomalous. In this chapter the abstraction process and details of the resultant algorithm are given. The algorithm is applied to numerous intrusion detection problems in computer security including the detection of port scans and botnets, where it has produced impressive results with relatively low rates of false positives.


MyUnity: Building Awareness and Fostering Community in the Workplace

Abstract: Successful collaboration depends on effective communication. Ongoing group awareness facilitates communication by enabling workers to be more informed about their collaborators, about their activities, and about the interpersonal dependencies among people working together. In this paper we present MyUnity, a new system that aids workers in building group awareness. The system uses multiple sources, both automatic and user-provided, to report colleagues' location, availability, current tasks, and preferred communication channels. Information is aggregated, fused and presented as a simple presence state for each worker. Workers can each independently control what information is collected by the system, allowing them to participate in the system without compromising their privacy. Results from a four-week field study show MyUnity increased group awareness and fostered an increased sense of community in the workplace. Results provide insights into the utility of awareness systems in the workplace.


Algorithmic Solutions for Several Offline Constrained Resource Processing and Data Transfer Multicriteria Optimization Problems

Abstract: In this paper we present novel algorithmic solutions for several resource processing and data transfer multicriteria optimization problems. The results of most of the presented techniques are strategies which solve the considered problems (almost) optimally. Thus, the developed algorithms construct intelligent strategies which can be implemented by agents in specific situations. All the described solutions make use of the properties of the considered problems and, thus, they are not applicable to a very general class of problems. However, by considering the specific details of each problem, we were able to obtain very efficient results.


The comparison of Wiktionary thesauri transformed into the machine-readable format

Abstract: Wiktionary is a unique, peculiar, valuable and original resource for natural language processing (NLP). The paper describes an open-source Wiktionary parser: its architecture and requirements followed by a description of Wiktionary features to be taken into account, some open problems of Wiktionary and the parser. The current implementation of the parser extracts the definitions, semantic relations, and translations from English and Russian Wiktionaries. The paper's goal is to interest researchers (1) in using the constructed machine-readable dictionary for different NLP tasks, (2) in extending the software to parse 170 still unused Wiktionaries. The comparison of a number and types of semantic relations, a number of definitions, and a number of translations in the English Wiktionary and the Russian Wiktionary has been carried out. It was found that the number of semantic relations in the English Wiktionary is larger by 1.57 times than in Russian (157 and 100 thousands). But the Russian Wiktionary has more "rich" entries (with a big number of semantic relations), e.g. the number of entries with three or more semantic relations is larger by 1.63 times than in the English Wiktionary. Upon comparison, it was found out the methodological shortcomings of the Wiktionary.


GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables

Abstract: Finding the structure of a graphical model has been received much attention in many fields. Recently, it is reported that the non-Gaussianity of data enables us to identify the structure of a directed acyclic graph without any prior knowledge on the structure. In this paper, we propose a novel non-Gaussianity based algorithm for more general type of models; chain graphs. The algorithm finds an ordering of the disjoint subsets of variables by iteratively evaluating the independence between the variable subset and the residuals when the remaining variables are regressed on those. However, its computational cost grows exponentially according to the number of variables. Therefore, we further discuss an efficient approximate approach for applying the algorithm to large sized graphs. We illustrate the algorithm with artificial and real-world datasets.


Cognitive radio ad hoc networks (CRAHNs): Cognitive radio ad hoc networks (CRAHNs): Resource allocation techniques based on Bio-inspired computing

Abstract: Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled spectrum (this is nothing but the "common carrier principle" adopted in oil/gas/electricity pipelines/networks.), since all ad hoc networks share a common pool of channels, exhausting the available channels will force ad hoc networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. CR network proved to next generation wireless communication system that proposed as a way to reuse under-utilised spectrum of licensee user (primary network) in an opportunistic and non-interfering basis. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. Adding this layer of such intelligence to the ad hoc network by looking at the overall geography of the network known as cognitive radio ad hoc networks (CRAHNs). However, CRAHN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilised channels while primary network user arrives. In this paper, channels or resource reallocation technique based on bio-inspired computing algorithm for CRAHN has been proposed.


Capacity Planning for Vertical Search Engines

Abstract: Vertical search engines focus on specific slices of content, such as the Web of a single country or the document collection of a large corporation. Despite this, like general open web search engines, they are expensive to maintain, expensive to operate, and hard to design. Because of this, predicting the response time of a vertical search engine is usually done empirically through experimentation, requiring a costly setup. An alternative is to develop a model of the search engine for predicting performance. However, this alternative is of interest only if its predictions are accurate. In this paper we propose a methodology for analyzing the performance of vertical search engines. Applying the proposed methodology, we present a capacity planning model based on a queueing network for search engines with a scale typically suitable for the needs of large corporations. The model is simple and yet reasonably accurate and, in contrast to previous work, considers the imbalance in query service times among homogeneous index servers. We discuss how we tune up the model and how we apply it to predict the impact on the query response time when parameters such as CPU and disk capacities are changed. This allows a manager of a vertical search engine to determine a priori whether a new configuration of the system might keep the query response under specified performance constraints.


PAC learnability of a concept class under non-atomic measures: a problem by Vidyasagar

Abstract: In response to a 1997 problem of M. Vidyasagar, we state a necessary and sufficient condition for distribution-free PAC learnability of a concept class $\mathscr C$ under the family of all non-atomic (diffuse) measures on the domain $\Omega$. Clearly, finiteness of the classical Vapnik-Chervonenkis dimension of $\mathscr C$ is a sufficient, but no longer necessary, condition. Besides, learnability of $\mathscr C$ under non-atomic measures does not imply the uniform Glivenko-Cantelli property with regard to non-atomic measures. Our learnability criterion is stated in terms of a combinatorial parameter $\VC({\mathscr C}\,{\mathrm{mod}}\,\omega_1)$ which we call the VC dimension of $\mathscr C$ modulo countable sets. The new parameter is obtained by ``thickening up'' single points in the definition of VC dimension to uncountable ``clusters''. Equivalently, $\VC(\mathscr C\modd\omega_1)\leq d$ if and only if every countable subclass of $\mathscr C$ has VC dimension $\leq d$ outside a countable subset of $\Omega$. The new parameter can be also expressed as the classical VC dimension of $\mathscr C$ calculated on a suitable subset of a compactification of $\Omega$. We do not make any measurability assumptions on $\mathscr C$, assuming instead the validity of Martin's Axiom (MA).


Approximate Testing Equivalence Based on Time, Probability, and Observed Behavior

Abstract: Several application domains require formal but flexible approaches to the comparison problem. Different process models that cannot be related by behavioral equivalences should be compared via a quantitative notion of similarity, which is usually achieved through approximation of some equivalence. While in the literature the classical equivalence subject to approximation is bisimulation, in this paper we propose a novel approach based on testing equivalence. As a step towards flexibility and usability, we study different relaxations taking into account orthogonal aspects of the process observations: execution time, event probability, and observed behavior. In this unifying framework, both interpretation of the measures and decidability of the verification algorithms are discussed.


Performance Evaluation of Components Using a Granularity-based Interface Between Real-Time Calculus and Timed Automata

Abstract: To analyze complex and heterogeneous real-time embedded systems, recent works have proposed interface techniques between real-time calculus (RTC) and timed automata (TA), in order to take advantage of the strengths of each technique for analyzing various components. But the time to analyze a state-based component modeled by TA may be prohibitively high, due to the state space explosion problem. In this paper, we propose a framework of granularity-based interfacing to speed up the analysis of a TA modeled component. First, we abstract fine models to work with event streams at coarse granularity. We perform analysis of the component at multiple coarse granularities and then based on RTC theory, we derive lower and upper bounds on arrival patterns of the fine output streams using the causality closure algorithm. Our framework can help to achieve tradeoffs between precision and analysis time.


Automatic Probabilistic Program Verification through Random Variable Abstraction

Abstract: The weakest pre-expectation calculus has been proved to be a mature theory to analyze quantitative properties of probabilistic and nondeterministic programs. We present an automatic method for proving quantitative linear properties on any denumerable state space using iterative backwards fixed point calculation in the general framework of abstract interpretation. In order to accomplish this task we present the technique of random variable abstraction (RVA) and we also postulate a sufficient condition to achieve exact fixed point computation in the abstract domain. The feasibility of our approach is shown with two examples, one obtaining the expected running time of a probabilistic program, and the other the expected gain of a gambling strategy. Our method works on general guarded probabilistic and nondeterministic transition systems instead of plain pGCL programs, allowing us to easily model a wide range of systems including distributed ones and unstructured programs. We present the operational and weakest precondition semantics for this programs and prove its equivalence.


Quantitative Fairness Games

Abstract: We consider two-player games played on finite colored graphs where the goal is the construction of an infinite path with one of the following frequency-related properties: (i) all colors occur with the same asymptotic frequency, (ii) there is a constant that bounds the difference between the occurrences of any two colors for all prefixes of the path, or (iii) all colors occur with a fixed asymptotic frequency. These properties can be viewed as quantitative refinements of the classical notion of fair path in a concurrent system, whose simplest form checks whether all colors occur infinitely often. In particular, the first two properties enforce equal treatment of all the jobs involved in the system, while the third one represents a way to assign a given priority to each job. For all the above goals, we show that the problem of checking whether there exists a winning strategy is CoNP-complete.


Injecting Abstract Interpretations into Linear Cost Models

Abstract: We present a semantics based framework for analysing the quantitative behaviour of programs with regard to resource usage. We start from an operational semantics equipped with costs. The dioid structure of the set of costs allows for defining the quantitative semantics as a linear operator. We then present an abstraction technique inspired from abstract interpretation in order to effectively compute global cost information from the program. Abstraction has to take two distinct notions of order into account: the order on costs and the order on states. We show that our abstraction technique provides a correct approximation of the concrete cost computations.


Testing Reactive Probabilistic Processes

Abstract: We define a testing equivalence in the spirit of De Nicola and Hennessy for reactive probabilistic processes, i.e. for processes where the internal nondeterminism is due to random behaviour. We characterize the testing equivalence in terms of ready-traces. From the characterization it follows that the equivalence is insensitive to the exact moment in time in which an internal probabilistic choice occurs, which is inherent from the original testing equivalence of De Nicola and Hennessy. We also show decidability of the testing equivalence for finite systems for which the complete model may not be known.


Probabilistic Model-Based Safety Analysis

Abstract: Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environment). The advantage of these methods compared to traditional approaches is that the analysis of the whole system gives more precise results. Only few model-based approaches have been applied to answer quantitative questions in safety analysis, often limited to analysis of specific failure propagation models, limited types of failure modes or without system dynamics and behavior, as direct quantitative analysis is uses large amounts of computing resources. New achievements in the domain of (probabilistic) model-checking now allow for overcoming this problem. This paper shows how functional models based on synchronous parallel semantics, which can be used for system design, implementation and qualitative safety analysis, can be directly re-used for (model-based) quantitative safety analysis. Accurate modeling of different types of probabilistic failure occurrence is shown as well as accurate interpretation of the results of the analysis. This allows for reliable and expressive assessment of the safety of a system in early design stages.


An expectation transformer approach to predicate abstraction and data independence for probabilistic programs

Abstract: In this paper we revisit the well-known technique of predicate abstraction to characterise performance attributes of system models incorporating probability. We recast the theory using expectation transformers, and identify transformer properties which correspond to abstractions that yield nevertheless exact bound on the performance of infinite state probabilistic systems. In addition, we extend the developed technique to the special case of "data independent" programs incorporating probability. Finally, we demonstrate the subtleness of the extended technique by using the PRISM model checking tool to analyse an infinite state protocol, obtaining exact bounds on its performance.


Optimal Time-Abstract Schedulers for CTMDPs and Markov Games

Abstract: We study time-bounded reachability in continuous-time Markov decision processes for time-abstract scheduler classes. Such reachability problems play a paramount role in dependability analysis and the modelling of manufacturing and queueing systems. Consequently, their analysis has been studied intensively, and techniques for the approximation of optimal control are well understood. From a mathematical point of view, however, the question of approximation is secondary compared to the fundamental question whether or not optimal control exists. We demonstrate the existence of optimal schedulers for the time-abstract scheduler classes for all CTMDPs. Our proof is constructive: We show how to compute optimal time-abstract strategies with finite memory. It turns out that these optimal schedulers have an amazingly simple structure - they converge to an easy-to-compute memoryless scheduling policy after a finite number of steps. Finally, we show that our argument can easily be lifted to Markov games: We show that both players have a likewise simple optimal strategy in these more general structures.


A new tool for the performance analysis of massively parallel computer systems

Abstract: We present a new tool, GPA, that can generate key performance measures for very large systems. Based on solving systems of ordinary differential equations (ODEs), this method of performance analysis is far more scalable than stochastic simulation. The GPA tool is the first to produce higher moment analysis from differential equation approximation, which is essential, in many cases, to obtain an accurate performance prediction. We identify so-called switch points as the source of error in the ODE approximation. We investigate the switch point behaviour in several large models and observe that as the scale of the model is increased, in general the ODE performance prediction improves in accuracy. In the case of the variance measure, we are able to justify theoretically that in the limit of model scale, the ODE approximation can be expected to tend to the actual variance of the model.


Proceedings Eighth Workshop on Quantitative Aspects of Programming Languages

Abstract: This volume contains the proceedings of the Eighth Workshop on Quantitative Aspects of Programming Languages (QAPL 2010), held in Paphos, Cyprus, on March 27-28, 2010. QAPL 2010 is a satellite event of the European Joint Conferences on Theory and Practice of Software (ETAPS 2010). The workshop theme is on quantitative aspects of computation. These aspects are related to the use of physical quantities (storage space, time, bandwidth, etc.) as well as mathematical quantities (e.g. probability and measures for reliability, security and trust), and play an important (sometimes essential) role in characterising the behavior and determining the properties of systems. Such quantities are central to the definition of both the model of systems (architecture, language design, semantics) and the methodologies and tools for the analysis and verification of the systems properties. The aim of this workshop is to discuss the explicit use of quantitative information such as time and probabilities either directly in the model or as a tool for the analysis of systems.


Design of Simple and Efficient Revocation List Distribution in Urban areas for VANET's

Abstract: Vehicular Ad hoc Networks is one of the most challenging research area in the field of Mobile Ad Hoc Networks, in this research we propose a flexible, simple, and scalable design for revocation list distribution in VANET, which will reduce channel overhead and eliminate the use of CRL. Also it will increase the security of the network and helps in identifying the adversary vehicles.


Feature Construction for Relational Sequence Learning

Abstract: We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly each relational sequence is mapped into a feature vector using the result of a feature construction method. Since, the efficacy of sequence learning algorithms strongly depends on the features used to represent the sequences, the second step is to find an optimal subset of the constructed features leading to high classification accuracy. This feature selection task has been solved adopting a wrapper approach that uses a stochastic local search algorithm embedding a naive Bayes classifier. The performance of the proposed method applied to a real-world dataset shows an improvement when compared to other established methods, such as hidden Markov models, Fisher kernels and conditional random fields for relational sequences.


A Framework for Interactive Work Design based on Digital Work Analysis and Simulation

Abstract: Due to the flexibility and adaptability of human, manual handling work is still very important in industry, especially for assembly and maintenance work. Well-designed work operation can improve work efficiency and quality; enhance safety, and lower cost. Most traditional methods for work system analysis need physical mock-up and are time consuming. Digital mockup (DMU) and digital human modeling (DHM) techniques have been developed to assist ergonomic design and evaluation for a specific worker population (e.g. 95 percentile); however, the operation adaptability and adjustability for a specific individual are not considered enough. In this study, a new framework based on motion tracking technique and digital human simulation technique is proposed for motion-time analysis of manual operations. A motion tracking system is used to track a worker's operation while he/she is conducting a manual handling work. The motion data is transferred to a simulation computer for real time digital human simulation. The data is also used for motion type recognition and analysis either online or offline for objective work efficiency evaluation and subjective work task evaluation. Methods for automatic motion recognition and analysis are presented. Constraints and limitations of the proposed method are discussed.


Mining Top-K Frequent Itemsets Through Progressive Sampling

Abstract: We study the use of sampling for efficiently mining the top-K frequent itemsets of cardinality at most w. To this purpose, we define an approximation to the top-K frequent itemsets to be a family of itemsets which includes (resp., excludes) all very frequent (resp., very infrequent) itemsets, together with an estimate of these itemsets' frequencies with a bounded error. Our first result is an upper bound on the sample size which guarantees that the top-K frequent itemsets mined from a random sample of that size approximate the actual top-K frequent itemsets, with probability larger than a specified value. We show that the upper bound is asymptotically tight when w is constant. Our main algorithmic contribution is a progressive sampling approach, combined with suitable stopping conditions, which on appropriate inputs is able to extract approximate top-K frequent itemsets from samples whose sizes are smaller than the general upper bound. In order to test the stopping conditions, this approach maintains the frequency of all itemsets encountered, which is practical only for small w. However, we show how this problem can be mitigated by using a variation of Bloom filters. A number of experiments conducted on both synthetic and real bench- mark datasets show that using samples substantially smaller than the original dataset (i.e., of size defined by the upper bound or reached through the progressive sampling approach) enable to approximate the actual top-K frequent itemsets with accuracy much higher than what analytically proved.


Data Stream Clustering: Challenges and Issues

Abstract: Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many applications are interesting for researchers. We can identify two main groups of techniques for huge data bases mining. One group refers to streaming data and applies mining techniques whereas second group attempts to solve this problem directly with efficient algorithms. Recently many researchers have focused on data stream as an efficient strategy against huge data base mining instead of mining on entire data base. The main problem in data stream mining means evolving data is more difficult to detect in this techniques therefore unsupervised methods should be applied. However, clustering techniques can lead us to discover hidden information. In this survey, we try to clarify: first, the different problem definitions related to data stream clustering in general; second, the specific difficulties encountered in this field of research; third, the varying assumptions, heuristics, and intuitions forming the basis of different approaches; and how several prominent solutions tackle different problems. Index Terms- Data Stream, Clustering, K-Means, Concept drift


Design specifications of the Human Robotic interface for the biomimetic underwater robot "yellow submarine project"

Abstract: This paper describes the design of a web based multi agent design for a collision avoidance auto navigation biomimetic submarine for submarine hydroelectricity. The paper describes the nature of the map - topology interface for river bodies and the design of interactive agents for the control of the robotic submarine. The agents are migratory on the web and are designed in XML/html interface with both interactive capabilities and visibility on a map. The paper describes mathematically the user interface and the map definition languages used for the multi agent description


Linear Detrending Subsequence Matching in Time-Series Databases

Abstract: Each time-series has its own linear trend, the directionality of a timeseries, and removing the linear trend is crucial to get the more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to a huge number of possible subsequences. In this paper we define this problem the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending), which is obtained as follows: we eliminate the linear trend from a subsequence rather than each window itself and obtain LD-windows by dividing the subsequence into windows. Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and formally prove its correctness. Based on the lower bounding theorem, we next propose the index building and subsequence matching algorithms for linear detrending subsequence matching.We finally show the superiority of our index-based solution through extensive experiments.


A Survey Paper on Recommender Systems

Abstract: Recommender systems apply data mining techniques and prediction algorithms to predict users' interest on information, products and services among the tremendous amount of available items. The vast growth of information on the Internet as well as number of visitors to websites add some key challenges to recommender systems. These are: producing accurate recommendation, handling many recommendations efficiently and coping with the vast growth of number of participants in the system. Therefore, new recommender system technologies are needed that can quickly produce high quality recommendations even for huge data sets. To address these issues we have explored several collaborative filtering techniques such as the item based approach, which identify relationship between items and indirectly compute recommendations for users based on these relationships. The user based approach was also studied, it identifies relationships between users of similar tastes and computes recommendations based on these relationships. In this paper, we introduce the topic of recommender system. It provides ways to evaluate efficiency, scalability and accuracy of recommender system. The paper also analyzes different algorithms of user based and item based techniques for recommendation generation. Moreover, a simple experiment was conducted using a data mining application -Weka- to apply data mining algorithms to recommender system. We conclude by proposing our approach that might enhance the quality of recommender systems.


The F5 Algorithm in Buchberger's Style

Abstract: The famous F5 algorithm for computing \gr basis was presented by Faug\`ere in 2002. The original version of F5 is given in programming codes, so it is a bit difficult to understand. In this paper, the F5 algorithm is simplified as F5B in a Buchberger's style such that it is easy to understand and implement. In order to describe F5B, we introduce F5-reduction, which keeps the signature of labeled polynomials unchanged after reduction. The equivalence between F5 and F5B is also shown. At last, some versions of the F5 algorithm are illustrated.


Data Partitioning for Parallel Entity Matching

Abstract: Entity matching is an important and difficult step for integrating web data. To reduce the typically high execution time for matching we investigate how we can perform entity matching in parallel on a distributed infrastructure. We propose different strategies to partition the input data and generate multiple match tasks that can be independently executed. One of our strategies supports both, blocking to reduce the search space for matching and parallel matching to improve efficiency. Special attention is given to the number and size of data partitions as they impact the overall communication overhead and memory requirements of individual match tasks. We have developed a service-based distributed infrastructure for the parallel execution of match workflows. We evaluate our approach in detail for different match strategies for matching real-world product data of different web shops. We also consider caching of in-put entities and affinity-based scheduling of match tasks.


The Complexity of the Homotopy Method, Equilibrium Selection, and Lemke-Howson Solutions

Abstract: We show that the widely used homotopy method for solving fixpoint problems, as well as the Harsanyi-Selten equilibrium selection process for games, are PSPACE-complete to implement. Extending our result for the Harsanyi-Selten process, we show that several other homotopy-based algorithms for finding equilibria of games are also PSPACE-complete to implement. A further application of our techniques yields the result that it is PSPACE-complete to compute any of the equilibria that could be found via the classical Lemke-Howson algorithm, a complexity-theoretic strengthening of the result in [Savani and von Stengel]. These results show that our techniques can be widely applied and suggest that the PSPACE-completeness of implementing homotopy methods is a general principle.


Resource Allocation using Virtual Clusters

Abstract: In this report we demonstrate the potential utility of resource allocation management systems that use virtual machine technology for sharing parallel computing resources among competing jobs. We formalize the resource allocation problem with a number of underlying assumptions, determine its complexity, propose several heuristic algorithms to find near-optimal solutions, and evaluate these algorithms in simulation. We find that among our algorithms one is very efficient and also leads to the best resource allocations. We then describe how our approach can be made more general by removing several of the underlying assumptions.


Cresterea securitatii sistemelor informatice si de comunicatii prin criptografia cuantica

Abstract: Catch 22 of cryptography - "Before two parties can communicate in secret, they must first communicate in secret". The weakness of classical cryptographic communication systems is that secret communication can only take place after a key is communicated in secret over a totally secure communication channel. Here comes quantum key distribution which takes advantage of certain phenomena that occur at the subatomic level, so that any attempt by an enemy to obtain the bits in a key not only fails, but gets detected as well.


From Encounters to Plausible Mobility

Abstract: Inferring plausible node mobility based only on information from wireless contact traces is a difficult problem. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure. On the other hand, contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. In this paper, we propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.


Merging Two Arima Models for Energy Optimization in WSN

Abstract: Use of ARIMA model in Sensor network The basic idea of our energy efficient information collection scheme is to suppress data transmission if the data sampled by sensor nodes are predictable by the sink node. This is done in two phases 1) Preliminary Data Collection- During this phase sink node collects enough data so that it can build up ARIMA model for each node. Then sink node selects a model for the particular node and sends back the corresponding model parameters to the node and also keeps them with it. Selecting the model for a node there is a tradeoff between energy consumption and accuracy of prediction. So we choose the model according to C = {\alpha} xMAE + (1 - {\alpha}) x rtran 0=< {\alpha} =<1 where the model should minimize C. Here MAE is Mean Absolute Error which is normalized by some predefined error tolerance and rtran is the ratio of number of samples transmitted over total number of samples. 2) Adaptive Data Collection- After the sensor node has received the model parameters it checks each actual data value with the data value calculated from the parameters received. If there is deviation beyond some predefined error tolerance then only it sends the original data value to the sink node.


Listing All Maximal Cliques in Sparse Graphs in Near-optimal Time

Abstract: The degeneracy of an $n$-vertex graph $G$ is the smallest number $d$ such that every subgraph of $G$ contains a vertex of degree at most $d$. We show that there exists a nearly-optimal fixed-parameter tractable algorithm for enumerating all maximal cliques, parametrized by degeneracy. To achieve this result, we modify the classic Bron--Kerbosch algorithm and show that it runs in time $O(dn3^{d/3})$. We also provide matching upper and lower bounds showing that the largest possible number of maximal cliques in an $n$-vertex graph with degeneracy $d$ (when $d$ is a multiple of 3 and $n\ge d+3$) is $(n-d)3^{d/3}$. Therefore, our algorithm matches the $\Theta(d(n-d)3^{d/3})$ worst-case output size of the problem whenever $n-d=\Omega(n)$.


Static and Dynamic Quality Assurance by Aspect Oriented Techniques

Abstract: The overall goal of the described research project was to create applicable quality assurance patterns for Java software systems using the aspect-oriented programming language extension AspectJ 5. We tried to develop aspects to check static quality criteria as a variable mutator convention and architectural layering rules. We successfully developed aspects for automating the following dynamic quality criteria: Parameterized Exception Chaining, Comfortable Declaration of Parameterized Exceptions, Not-Null Checking of Reference Variables.


A Game Theoretical Approach to Modeling Information Dissemination in Social Networks

Abstract: One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the information forwarding and feedback mechanisms in a social network that take into account the personalities of the sender and the receiver (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network.


Mirage: Mitigating Illicit Inventorying in a RFID Enabled Retail Environment

Abstract: Given its low dollar and maintenance cost, RFID is poised to become the enabling technology for inventory control and supply chain management. However, as an outcome of its low cost, RFID based inventory control is susceptible to pernicious security and privacy threats. A deleterious attack on such a system is corporate espionage, where attackers through illicit inventorying infer sales and restocking trends for products. In this paper, we first present plausible aftermaths of corporate espionage using real data from online sources. Second, to mitigate corporate espionage in a retail store environment, we present a simple lowcost system called Mirage. Mirage uses additional programmable low cost passive RFID tags called honeytokens to inject noise in retail store inven-torying. Using a simple history based algorithm that controls activation and de-activation of honeytokens, Mirage randomizes sales and restocking trends. We evaluate Mirage in a real warehouse environment using a commercial off-the-shelf Motorola MC9090 handheld RFID reader and over 450 Gen2 low cost RFID tags. We show that Mirage successfully flattens and randomizes sales and restocking trends while adding minimal cost to inventory control.


Soft Approximations and uni-int Decision Making

Abstract: Notions of core, support and inversion of a soft set have been defined and studied. Soft approximations are soft sets developed through core and support, and are used for granulating the soft space. Membership structure of a soft set has been probed in and many interesting properties presented. The mathematical apparatus developed so far in this paper yields a detailed analysis of two works viz. [N. Cagman, S. Enginoglu, Soft set theory and uni-int decision making, European Jr. of Operational Research (article in press, available online 12 May 2010)] and [N. Cagman, S. Enginoglu, Soft matrix theory and its decision making, Computers and Mathematics with Applications 59 (2010) 3308 - 3314.]. We prove (Theorem 8.1) that uni-int method of Cagman is equivalent to a core-support expression which is computationally far less expansive than uni-int. This also highlights some shortcomings in Cagman's uni-int method and thus motivates us to improve the method. We first suggest an improvement in uni-int method and then present a new conjecture to solve the optimum choice problem given by Cagman and Enginoglu. Our Example 8.6 presents a case where the optimum choice is intuitively clear yet both uni-int methods (Cagman's and our improved one) give wrong answer but the new conjecture solves the problem correctly.


Rewriting Preserving Recognizability of Finite Tree Languages

Abstract: We show that left-linear generalized semi-monadic TRSs effectively preserving recognizability of finite tree languages (are EPRF-TRSs). We show that reachability, joinability, and local confluence are decidable for EPRF-TRSs.


Domain Representable Spaces Defined by Strictly Positive Induction

Abstract: Recursive domain equations have natural solutions. In particular there are domains defined by strictly positive induction. The class of countably based domains gives a computability theory for possibly non-countably based topological spaces. A $ qcb_{0} $ space is a topological space characterized by its strong representability over domains. In this paper, we study strictly positive inductive definitions for $ qcb_{0} $ spaces by means of domain representations, i.e. we show that there exists a canonical fixed point of every strictly positive operation on $qcb_{0} $ spaces.


A Multi-Core Processor Platform for Open Embedded Systems

Abstract: Recent proliferation of embedded systems has generated a bold new paradigm, known as open embedded systems. While traditional embedded systems provide only closed base applications (natively-installed software) to users, open embedded systems allow the users to freely execute open applications (additionally-installed software) in order to meet various user requirements, such as user personalization and device coordination. Key to the success of platforms required for open embedded systems is the achievement of both the scalable extension of base applications and the secure execution of open applications. Most existing platforms, however, have focused on either scalable or secure execution, limiting their applicability. This dissertation presents a new secure platform using multi-core processors, which achieves both scalability and security. Four techniques feature the new platform: (1) seamless communication, by which legacy applications designed for a single processor make it possible to be executed on multiple processors without any software modifications; (2) secure processor partitioning with hardware support, by which Operating Systems (OSs) required for base and open applications are securely executed on separate processors; (3) asymmetric virtualization, by which many OSs over the number of processors are securely executed under secure processor partitioning; and (4) secure dynamic partitioning, by which the number of processors allocated to individual OSs makes it possible to be dynamically changed under secure processor partitioning.


Better algorithms for satisfiability problems for formulas of bounded rank-width

Abstract: We provide a parameterized polynomial algorithm for the propositional model counting problem #SAT, the runtime of which is single-exponential in the rank-width of a formula. Previously, analogous algorithms have been known -- e.g.~[Fischer, Makowsky, and Ravve] -- with a single-exponential dependency on the clique-width of a formula. Our algorithm thus presents an exponential runtime improvement (since clique-width reaches up to exponentially higher values than rank-width), and can be of practical interest for small values of rank-width. We also provide an algorithm for the MAX-SAT problem along the same lines.


A Reflective Approach to Providing Flexibility in Application Distribution

Abstract: Current middleware systems suffer from drawbacks. Often one is forced to make decisions early in the design process about which classes may participate in inter-machine communication. Further, application level and middleware specific semantics cannot be separated forcing an unnatural design. The RAFDA project proposes to adress these deficiencies by creating an adaptive, reflective framework that enables the transformation of non-distributed applications into isomorphic applications whose distribution architecture is flexible. This paper describes the code transformation techniques that have been developed as part of the project. The system enables the distribution of a program according to a flexible configuration without user intervention. Proxy objects can then be substituted, permitting cross-address space communication. The distributed program can adapt to its environment by dynamically altering its distribution boundaries.