An Optimal Trade-off between Content Freshness and Refresh Cost

Abstract: Caching is an effective mechanism for reducing bandwidth usage and alleviating server load. However, the use of caching entails a compromise between content freshness and refresh cost. An excessive refresh allows a high degree of content freshness at a greater cost of system resource. Conversely, a deficient refresh inhibits content freshness but saves the cost of resource usages. To address the freshness-cost problem, we formulate the refresh scheduling problem with a generic cost model and use this cost model to determine an optimal refresh frequency that gives the best tradeoff between refresh cost and content freshness. We prove the existence and uniqueness of an optimal refresh frequency under the assumptions that the arrival of content update is Poisson and the age-related cost monotonically increases with decreasing freshness. In addition, we provide an analytic comparison of system performance under fixed refresh scheduling and random refresh scheduling, showing that with the same average refresh frequency two refresh schedulings are mathematically equivalent in terms of the long-run average cost.


On Optimal Deadlock Detection Scheduling

Abstract: Deadlock detection scheduling is an important, yet often overlooked problem that can significantly affect the overall performance of deadlock handling. Excessive initiation of deadlock detection increases overall message usage, resulting in degraded system performance in the absence of deadlocks; while insufficient initiation of deadlock detection increases the deadlock persistence time, resulting in an increased deadlock resolution cost in the presence of deadlocks. The investigation of this performance tradeoff, however, is missing in the literature. This paper studies the impact of deadlock detection scheduling on the overall performance of deadlock handling. In particular, we show that there exists an optimal deadlock detection frequency that yields the minimum long-run mean average cost, which is determined by the message complexities of the deadlock detection and resolution algorithms being used, as well as the rate of deadlock formation, denoted as $\lambda$. For the best known deadlock detection and resolution algorithms, we show that the asymptotically optimal frequency of deadlock detection scheduling that minimizes the overall message overhead is ${\cal O}((\lambda n)^{1/3})$, when the total number $n$ of processes is sufficiently large. Furthermore, we show that in general fully distributed (uncoordinated) deadlock detection scheduling cannot be performed as efficiently as centralized (coordinated) deadlock detection scheduling.


Quasi-Random Rumor Spreading: Reducing Randomness Can Be Costly

Abstract: We give a time-randomness tradeoff for the quasi-random rumor spreading protocol proposed by Doerr, Friedrich and Sauerwald [SODA 2008] on complete graphs. In this protocol, the goal is to spread a piece of information originating from one vertex throughout the network. Each vertex is assumed to have a (cyclic) list of its neighbors. Once a vertex is informed by one of its neighbors, it chooses a position in its list uniformly at random and then informs its neighbors starting from that position and proceeding in order of the list. Angelopoulos, Doerr, Huber and Panagiotou [Electron.~J.~Combin.~2009] showed that after $(1+o(1))(\log_2 n + \ln n)$ rounds, the rumor will have been broadcasted to all nodes with probability $1 - o(1)$. We study the broadcast time when the amount of randomness available at each node is reduced in natural way. In particular, we prove that if each node can only make its initial random selection from every $\ell$-th node on its list, then there exists lists such that $(1-\varepsilon) (\log_2 n + \ln n - \log_2 \ell - \ln \ell)+\ell-1$ steps are needed to inform every vertex with probability at least $1-O\bigl(\exp\bigl(-\frac{n^\varepsilon}{2\ln n}\bigr)\bigr)$. This shows that a further reduction of the amount of randomness used in a simple quasi-random protocol comes at a loss of efficiency.


Fully automatic extraction of salient objects from videos in near real-time

Abstract: Automatic video segmentation plays an important role in a wide range of computer vision and image processing applications. Recently, various methods have been proposed for this purpose. The problem is that most of these methods are far from real-time processing even for low-resolution videos due to the complex procedures. To this end, we propose a new and quite fast method for automatic video segmentation with the help of 1) efficient optimization of Markov random fields with polynomial time of number of pixels by introducing graph cuts, 2) automatic, computationally efficient but stable derivation of segmentation priors using visual saliency and sequential update mechanism, and 3) an implementation strategy in the principle of stream processing with graphics processor units (GPUs). Test results indicates that our method extracts appropriate regions from videos as precisely as and much faster than previous semi-automatic methods even though any supervisions have not been incorporated.


Sensitivity versus block sensitivity of Boolean functions

Abstract: Determining the maximal separation between sensitivity and block sensitivity of Boolean functions is of interest for computational complexity theory. We construct a sequence of Boolean functions with bs(f) = 1/2 s(f)^2 + 1/2 s(f). The best known separation previously was bs(f) = 1/2 s(f)^2 due to Rubinstein. We also report results of computer search for functions with at most 12 variables.


Bounded Coordinate-Descent for Biological Sequence Classification in High Dimensional Predictor Space

Abstract: We present a framework for discriminative sequence classification where the learner works directly in the high dimensional predictor space of all subsequences in the training set. This is possible by employing a new coordinate-descent algorithm coupled with bounding the magnitude of the gradient for selecting discriminative subsequences fast. We characterize the loss functions for which our generic learning algorithm can be applied and present concrete implementations for logistic regression (binomial log-likelihood loss) and support vector machines (squared hinge loss). Application of our algorithm to protein remote homology detection and remote fold recognition results in performance comparable to that of state-of-the-art methods (e.g., kernel support vector machines). Unlike state-of-the-art classifiers, the resulting classification models are simply lists of weighted discriminative subsequences and can thus be interpreted and related to the biological problem.


Strategy iteration is strongly polynomial for 2-player turn-based stochastic games with a constant discount factor

Abstract: Ye showed recently that the simplex method with Dantzig pivoting rule, as well as Howard's policy iteration algorithm, solve discounted Markov decision processes (MDPs), with a constant discount factor, in strongly polynomial time. More precisely, Ye showed that both algorithms terminate after at most $O(\frac{mn}{1-\gamma}\log(\frac{n}{1-\gamma}))$ iterations, where $n$ is the number of states, $m$ is the total number of actions in the MDP, and $0<\gamma<1$ is the discount factor. We improve Ye's analysis in two respects. First, we improve the bound given by Ye and show that Howard's policy iteration algorithm actually terminates after at most $O(\frac{m}{1-\gamma}\log(\frac{n}{1-\gamma}))$ iterations. Second, and more importantly, we show that the same bound applies to the number of iterations performed by the strategy iteration (or strategy improvement) algorithm, a generalization of Howard's policy iteration algorithm used for solving 2-player turn-based stochastic games with discounted zero-sum rewards. This provides the first strongly polynomial algorithm for solving these games, resolving a long standing open problem.


Determinant Sums for Undirected Hamiltonicity

Abstract: We present a Monte Carlo algorithm for Hamiltonicity detection in an $n$-vertex undirected graph running in $O^*(1.657^{n})$ time. To the best of our knowledge, this is the first superpolynomial improvement on the worst case runtime for the problem since the $O^*(2^n)$ bound established for TSP almost fifty years ago (Bellman 1962, Held and Karp 1962). It answers in part the first open problem in Woeginger's 2003 survey on exact algorithms for NP-hard problems. For bipartite graphs, we improve the bound to $O^*(1.414^{n})$ time. Both the bipartite and the general algorithm can be implemented to use space polynomial in $n$. We combine several recently resurrected ideas to get the results. Our main technical contribution is a new reduction inspired by the algebraic sieving method for $k$-Path (Koutis ICALP 2008, Williams IPL 2009). We introduce the Labeled Cycle Cover Sum in which we are set to count weighted arc labeled cycle covers over a finite field of characteristic two. We reduce Hamiltonicity to Labeled Cycle Cover Sum and apply the determinant summation technique for Exact Set Covers (Bj\"orklund STACS 2010) to evaluate it.


LiquidXML: Adaptive XML Content Redistribution

Abstract: We propose to demonstrate LiquidXML, a platform for managing large corpora of XML documents in large-scale P2P networks. All LiquidXML peers may publish XML documents to be shared with all the network peers. The challenge then is to efficiently (re-)distribute the published content in the network, possibly in overlapping, redundant fragments, to support efficient processing of queries at each peer. The novelty of LiquidXML relies in its adaptive method of choosing which data fragments are stored where, to improve performance. The "liquid" aspect of XML management is twofold: XML data flows from many sources towards many consumers, and its distribution in the network continuously adapts to improve query performance.


Row Sampling for Matrix Algorithms via a Non-Commutative Bernstein Bound

Abstract: We focus the use of \emph{row sampling} for approximating matrix algorithms. We give applications to matrix multipication; sparse matrix reconstruction; and, \math{\ell_2} regression. For a matrix \math{\matA\in\R^{m\times d}} which represents \math{m} points in \math{d\ll m} dimensions, all of these tasks can be achieved in \math{O(md^2)} via the singular value decomposition (SVD). For appropriate row-sampling probabilities (which typically depend on the norms of the rows of the \math{m\times d} left singular matrix of \math{\matA} (the \emph{leverage scores}), we give row-sampling algorithms with linear (up to polylog factors) dependence on the stable rank of \math{\matA}. This result is achieved through the application of non-commutative Bernstein bounds. We then give, to our knowledge, the first algorithms for computing approximations to the appropriate row-sampling probabilities without going through the SVD of \math{\matA}. Thus, these are the first \math{o(md^2)} algorithms for row-sampling based approximations to the matrix algorithms which use leverage scores as the sampling probabilities. The techniques we use to approximate sampling according to the leverage scores uses some powerful recent results in the theory of random projections for embedding, and may be of some independent interest. We confess that one may perform all these matrix tasks more efficiently using these same random projection methods, however the resulting algorithms are in terms of a small number of linear combinations of all the rows. In many applications, the actual rows of \math{\matA} have some physical meaning and so methods based on a small number of the actual rows are of interest.


Formaleuros, Formalbitcoins, and Virtual Monies

Abstract: Formalist positions towards money are considered from a perspective of formal methods in computing. The Formaleuro (FEUR) as a dimension for monetary quantities is proposed as well as the Formalbitcoin (FBTC) which represents an item ready for circulation in a model of informational money. An attempt is made to understand the concept of money from scratch. In order to provide a definition of money the need is felt to make use of a tailored theory of definition. To that end a theory of imaginative definitions is presented and its implications for definitions of money are sketched. It is argued that a theory of money may be dependent on the role of its holder. A survey of some roles is given, with the so-called subordinate administrative role (SAR) in a central position. The concepts of virtual memory and virtual machine are taken as the point of departure for a definition of the notion of virtual money. It is argued that from the perspective of a component (division) of a large organization (ORG) its local financial system (LFS) provides a virtual money vm(LFS, ORG) which may well fail to meet the most common general and acknowledged moneyness criteria. Inverse moneyness preference is coined as phrase to assert the tendency of top-management of ORG to make its virtual money deviate from these criteria.


Evaluating and Improving Modern Variable and Revision Ordering Strategies in CSPs

Abstract: A key factor that can dramatically reduce the search space during constraint solving is the criterion under which the variable to be instantiated next is selected. For this purpose numerous heuristics have been proposed. Some of the best of such heuristics exploit information about failures gathered throughout search and recorded in the form of constraint weights, while others measure the importance of variable assignments in reducing the search space. In this work we experimentally evaluate the most recent and powerful variable ordering heuristics, and new variants of them, over a wide range of benchmarks. Results demonstrate that heuristics based on failures are in general more efficient. Based on this, we then derive new revision ordering heuristics that exploit recorded failures to efficiently order the propagation list when arc consistency is maintained during search. Interestingly, in addition to reducing the number of constraint checks and list operations, these heuristics are also able to cut down the size of the explored search tree.


Adaptive Branching for Constraint Satisfaction Problems

Abstract: The two standard branching schemes for CSPs are d-way and 2-way branching. Although it has been shown that in theory the latter can be exponentially more effective than the former, there is a lack of empirical evidence showing such differences. To investigate this, we initially make an experimental comparison of the two branching schemes over a wide range of benchmarks. Experimental results verify the theoretical gap between d-way and 2-way branching as we move from a simple variable ordering heuristic like dom to more sophisticated ones like dom/ddeg. However, perhaps surprisingly, experiments also show that when state-of-the-art variable ordering heuristics like dom/wdeg are used then d-way can be clearly more efficient than 2-way branching in many cases. Motivated by this observation, we develop two generic heuristics that can be applied at certain points during search to decide whether 2-way branching or a restricted version of 2-way branching, which is close to d-way branching, will be followed. The application of these heuristics results in an adaptive branching scheme. Experiments with instantiations of the two generic heuristics confirm that search with adaptive branching outperforms search with a fixed branching scheme on a wide range of problems.


Holographic Algorithms with Matchgates Capture Precisely Tractable Planar #CSP

Abstract: Valiant introduced matchgate computation and holographic algorithms. A number of seemingly exponential time problems can be solved by this novel algorithmic paradigm in polynomial time. We show that, in a very strong sense, matchgate computations and holographic algorithms based on them provide a universal methodology to a broad class of counting problems studied in statistical physics community for decades. They capture precisely those problems which are #P-hard on general graphs but computable in polynomial time on planar graphs. More precisely, we prove complexity dichotomy theorems in the framework of counting CSP problems. The local constraint functions take Boolean inputs, and can be arbitrary real-valued symmetric functions. We prove that, every problem in this class belongs to precisely three categories: (1) those which are tractable (i.e., polynomial time computable) on general graphs, or (2) those which are \#P-hard on general graphs but ractable on planar graphs, or (3) those which are #P-hard even on planar graphs. The classification criteria are explicit. Moreover, problems in category (2) are tractable on planar graphs precisely by holographic algorithms with matchgates.


Cross-Lingual Adaptation using Structural Correspondence Learning

Abstract: Cross-lingual adaptation, a special case of domain adaptation, refers to the transfer of classification knowledge between two languages. In this article we describe an extension of Structural Correspondence Learning (SCL), a recently proposed algorithm for domain adaptation, for cross-lingual adaptation. The proposed method uses unlabeled documents from both languages, along with a word translation oracle, to induce cross-lingual feature correspondences. From these correspondences a cross-lingual representation is created that enables the transfer of classification knowledge from the source to the target language. The main advantages of this approach over other approaches are its resource efficiency and task specificity. We conduct experiments in the area of cross-language topic and sentiment classification involving English as source language and German, French, and Japanese as target languages. The results show a significant improvement of the proposed method over a machine translation baseline, reducing the relative error due to cross-lingual adaptation by an average of 30% (topic classification) and 59% (sentiment classification). We further report on empirical analyses that reveal insights into the use of unlabeled data, the sensitivity with respect to important hyperparameters, and the nature of the induced cross-lingual correspondences.


Web Video Categorization based on Wikipedia Categories and Content-Duplicated Open Resources

Abstract: This paper presents a novel approach for web video categorization by leveraging Wikipedia categories (WikiCs) and open resources describing the same content as the video, i.e., content-duplicated open resources (CDORs). Note that current approaches only col-lect CDORs within one or a few media forms and ignore CDORs of other forms. We explore all these resources by utilizing WikiCs and commercial search engines. Given a web video, its discrimin-ative Wikipedia concepts are first identified and classified. Then a textual query is constructed and from which CDORs are collected. Based on these CDORs, we propose to categorize web videos in the space spanned by WikiCs rather than that spanned by raw tags. Experimental results demonstrate the effectiveness of both the proposed CDOR collection method and the WikiC voting catego-rization algorithm. In addition, the categorization model built based on both WikiCs and CDORs achieves better performance compared with the models built based on only one of them as well as state-of-the-art approach.


Towards Improving the NIST Fingerprint Image Quality (NFIQ) Algorithm (Extended Version)

Abstract: The NIST Fingerprint Image Quality (NFIQ) algorithm has become a standard method to assess fingerprint image quality. However, in many applications a more accurate and reliable assessment is desirable. In this publication, we report on our efforts to optimize the NFIQ algorithm by a re-training of the underlying neural network based on a large fingerprint image database. Although we only achieved a marginal improvement, our work has revealed several areas for potential optimization.


Performance of the Fuzzy Vault for Multiple Fingerprints (Extended Version)

Abstract: The fuzzy vault is an error tolerant authentication method that ensures the privacy of the stored reference data. Several publications have proposed the application of the fuzzy vault to fingerprints, but the results of subsequent analyses indicate that a single finger does not contain sufficient information for a secure implementation. In this contribution, we present an implementation of a fuzzy vault based on minutiae information in several fingerprints aiming at a security level comparable to current cryptographic applications. We analyze and empirically evaluate the security, efficiency, and robustness of the construction and several optimizations. The results allow an assessment of the capacity of the scheme and an appropriate selection of parameters. Finally, we report on a practical simulation conducted with ten users.


A Homogeneous Reaction Rule Language for Complex Event Processing

Abstract: Event-driven automation of reactive functionalities for complex event processing is an urgent need in today's distributed service-oriented architectures and Web-based event-driven environments. An important problem to be addressed is how to correctly and efficiently capture and process the event-based behavioral, reactive logic embodied in reaction rules, and combining this with other conditional decision logic embodied, e.g., in derivation rules. This paper elaborates a homogeneous integration approach that combines derivation rules, reaction rules and other rule types such as integrity constraints into the general framework of logic programming, the industrial-strength version of declarative programming. We describe syntax and semantics of the language, implement a distributed web-based middleware using enterprise service technologies and illustrate its adequacy in terms of expressiveness, efficiency and scalability through examples extracted from industrial use cases. The developed reaction rule language provides expressive features such as modular ID-based updates with support for external imports and self-updates of the intensional and extensional knowledge bases, transactions including integrity testing and roll-backs of update transition paths. It also supports distributed complex event processing, event messaging and event querying via efficient and scalable enterprise middleware technologies and event/action reasoning based on an event/action algebra implemented by an interval-based event calculus variant as a logic inference formalism.


Is submodularity testable?

Abstract: We initiate the study of property testing of submodularity on the boolean hypercube. Submodular functions come up in a variety of applications in combinatorial optimization. For a vast range of algorithms, the existence of an oracle to a submodular function is assumed. But how does one check if this oracle indeed represents a submodular function? Consider a function f:{0,1}^n \rightarrow R. The distance to submodularity is the minimum fraction of values of $f$ that need to be modified to make f submodular. If this distance is more than epsilon > 0, then we say that f is epsilon-far from being submodular. The aim is to have an efficient procedure that, given input f that is epsilon-far from being submodular, certifies that f is not submodular. We analyze a very natural tester for this problem, and prove that it runs in subexponential time. This gives the first non-trivial tester for submodularity. On the other hand, we prove an interesting lower bound (that is, unfortunately, quite far from the upper bound) suggesting that this tester cannot be very efficient in terms of epsilon. This involves non-trivial examples of functions which are far from submodular and yet do not exhibit too many local violations. We also provide some constructions indicating the difficulty in designing a tester for submodularity. We construct a partial function defined on exponentially many points that cannot be extended to a submodular function, but any strict subset of these values can be extended to a submodular function.


Associative control processor with a rigid structure

Abstract: The approach of applying associative processor for decision making problem was proposed. It focuses on hardware implementations of fuzzy processing systems, associativity as effective management basis of fuzzy processor. The structural approach is being developed resulting in a quite simple and compact parallel associative memory unit (PAMU). The memory cost and speed comparison of processors with rigid and soft-variable structure is given. Also the example PAMU flashing is considered.


A Heuristic Algorithm for optimizing Page Selection Instructions

Abstract: Page switching is a technique that increases the memory in microcontrollers without extending the address buses. This technique is widely used in the design of 8-bit MCUs. In this paper, we present an algorithm to reduce the overhead of page switching. To pursue small code size, we place the emphasis on the allocation of functions into suitable pages with a heuristic algorithm, thereby the cost-effective placement of page selection instructions. Our experimental results showed the optimization achieved a reduction in code size of 13.2 percent.


A Decidable Dichotomy Theorem on Directed Graph Homomorphisms with Non-negative Weights

Abstract: The complexity of graph homomorphism problems has been the subject of intense study. It is a long standing open problem to give a (decidable) complexity dichotomy theorem for the partition function of directed graph homomorphisms. In this paper, we prove a decidable complexity dichotomy theorem for this problem and our theorem applies to all non-negative weighted form of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function Z_A(G) of directed graph homomorphisms from any directed graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of graph homomorphism problems. The proof of its decidability is algebraic using properties of polynomials.


An Information-Theoretic Analysis of the Security of Communication Systems Employing the Encoding-Encryption Paradigm

Abstract: This paper proposes a generic approach for providing enhanced security to communication systems which encode their data for reliability before encrypting it through a stream cipher for security. We call this counter-intuitive technique the {\em encoding-encryption} paradigm, and use as motivating example the standard for mobile telephony GSM. The enhanced security is based on a dedicated homophonic or wire-tap channel coding that introduces pure randomness, combined with the randomness of the noise occurring over the communication channel. Security evaluation regarding recovery of the secret key employed in the keystream generator is done through an information theoretical approach. We show that with the aid of a dedicated wire-tap encoder, the amount of uncertainty that the adversary must face about the secret key given all the information he could gather during different passive or active attacks he can mount, is a decreasing function of the sample available for cryptanalysis. This means that the wire-tap encoder can indeed provide an information theoretical security level over a period of time, but after a large enough sample is collected the function tends to zero, entering a regime in which a computational security analysis is needed for estimation of the resistance against the secret key recovery.


Faster Shortest Path Algorithm for H-Minor Free Graphs with Negative Edge Weights

Abstract: Let $H$ be a fixed graph and let $G$ be an $H$-minor free $n$-vertex graph with integer edge weights and no negative weight cycles reachable from a given vertex $s$. We present an algorithm that computes a shortest path tree in $G$ rooted at $s$ in $\tilde{O}(n^{4/3}\log L)$ time, where $L$ is the absolute value of the smallest edge weight. The previous best bound was $\tilde{O}(n^{\sqrt{11.5}-2}\log L) = O(n^{1.392}\log L)$. Our running time matches an earlier bound for planar graphs by Henzinger et al.


Witness Gabriel Graphs

Abstract: We consider a generalization of the Gabriel graph, the witness Gabriel graph. Given a set of vertices P and a set of witnesses W in the plane, there is an edge ab between two points of P in the witness Gabriel graph GG-(P,W) if and only if the closed disk with diameter ab does not contain any witness point (besides possibly a and/or b). We study several properties of the witness Gabriel graph, both as a proximity graph and as a new tool in graph drawing.


Witness (Delaunay) Graphs

Abstract: Proximity graphs are used in several areas in which a neighborliness relationship for input data sets is a useful tool in their analysis, and have also received substantial attention from the graph drawing community, as they are a natural way of implicitly representing graphs. However, as a tool for graph representation, proximity graphs have some limitations that may be overcome with suitable generalizations. We introduce a generalization, witness graphs, that encompasses both the goal of more power and flexibility for graph drawing issues and a wider spectrum for neighborhood analysis. We study in detail two concrete examples, both related to Delaunay graphs, and consider as well some problems on stabbing geometric objects and point set discrimination, that can be naturally described in terms of witness graphs.


Computing with Equations

Abstract: The intention of these notes is to give a mathematical account of how I believe students could be taught to think about functional programming languages and to explain how such languages work.


Data visualization in political and social sciences

Abstract: The basic objective of data visualization is to provide an efficient graphical display for summarizing and reasoning about quantitative information. During the last decades, political science has accumulated a large corpus of various kinds of data such as comprehensive factbooks and atlases, characterizing all or most of existing states by multiple and objectively assessed numerical indicators within certain time lapse. As a consequence, there exists a continuous trend for political science to gradually become a more quantitative scientific field and to use quantitative information in the analysis and reasoning. It is believed that any objective analysis in political science must be multidimensional and combine various sources of quantitative information; however, human capabilities for perception of large massifs of numerical information are limited. Hence, methods and approaches for visualization of quantitative and qualitative data (and, especially multivariate data) is an extremely important topic. Data visualization approaches can be classified into several groups, starting from creating informative charts and diagrams (statistical graphics and infographics) and ending with advanced statistical methods for visualizing multidimensional tables containing both quantitative and qualitative information. In this article we provide a short review of existing methods of data visualization methods with applications in political and social science.


Improved Fast Similarity Search in Dictionaries

Abstract: We engineer an algorithm to solve the approximate dictionary matching problem. Given a list of words $\mathcal{W}$, maximum distance $d$ fixed at preprocessing time and a query word $q$, we would like to retrieve all words from $\mathcal{W}$ that can be transformed into $q$ with $d$ or less edit operations. We present data structures that support fault tolerant queries by generating an index. On top of that, we present a generalization of the method that eases memory consumption and preprocessing time significantly. At the same time, running times of queries are virtually unaffected. We are able to match in lists of hundreds of thousands of words and beyond within microseconds for reasonable distances.


Classical Mathematics for a Constructive World

Abstract: Interactive theorem provers based on dependent type theory have the flexibility to support both constructive and classical reasoning. Constructive reasoning is supported natively by dependent type theory and classical reasoning is typically supported by adding additional non-constructive axioms. However, there is another perspective that views constructive logic as an extension of classical logic. This paper will illustrate how classical reasoning can be supported in a practical manner inside dependent type theory without additional axioms. We will see several examples of how classical results can be applied to constructive mathematics. Finally, we will see how to extend this perspective from logic to mathematics by representing classical function spaces using a weak value monad.


Security Weakness of Flexible Group Key Exchange with On-Demand Computation of Subgroup Keys

Abstract: In AFRICACRYPT 2010, Abdalla et al. first proposed a slight modification to the computations steps of the BD protocol, called mBD+P. Then they extended mBD+P protocol into mBD+S protocol. In this paper, we show that both of mBD+P and mBD+S protocols are vulnerable to malicious insiders attack. Further, we propose a simple countermeasure against this attack.


Circle Packing for Origami Design Is Hard

Abstract: We show that deciding whether a given set of circles can be packed into a rectangle, an equilateral triangle, or a unit square are NP-hard problems, settling the complexity of these natural packing problems. On the positive side, we show that any set of circles of total area 1 can be packed into a square of size 4/\sqrt{pi}=2.2567... These results are motivated by problems arising in the context of origami design.


Contributions of PDM Systems in Organizational Technical Data Management

Abstract: Product Data Management (PDM) claims of producing desktop and web based systems to maintain the organizational data to increase the quality of products by improving the process of development, business process flows, change management, product structure management, project tracking and resource planning. Moreover PDM helps in reducing the cost and effort required in engineering. This paper discusses PDM desktop and web based system, needed information and important guidelines for PDM system development, functional requirements, basic components in detail and some already implemented PDM Sys-tems. In the end paper investigates and briefly concludes major currently faced challenges to Product Data Management (PDM) community.


Design Artifact's, Design Principles, Problems, Goals and Importance

Abstract: Designing human computer interaction interface is an important and a complex task, but it could be simplified by decomposing task into subcomponents and maintaining relationships among those subcomponents. Task decomposition is a structured approach, applicable in both Software Engineering and Human Computer Interaction (HCI) fields depending on specific processes and design artifacts. Using design artifacts applications could be made for analysis and design by making the hand draw sketches to provide high level of logical design based on user requirements, usage scenarios and essential use cases. To design hand draw sketches there are some strategies to be followed .i.e., planning, sequential work flow, and levels of details. In this research paper we are presenting design artifacts, goals, principles, guidelines and currently faced problems to human computer interaction design community. Moreover in the end concluded with assessed observations in a case study.


Statistical Trading Using Target Oriented Trading Agent

Abstract: In this article we briefly present our contributions toward Trading Agent Competition (TAC); an international forum for promotion of research into the trading agent problems. Moreover, we present some strategies proposed and used in the development of our TAC Agent and resultant brief information after its participation in a real time trading environment. In the end we conclude with needed improvements and future recommendations.


Semantic Oriented Agent based Approach towards Engineering Data Management, Web Information Retrieval and User System Communication Problems

Abstract: The four intensive problems to the software rose by the software industry .i.e., User System Communication / Human Machine Interface, Meta Data extraction, Information processing & management and Data representation are discussed in this research paper. To contribute in the field we have proposed and described an intelligent semantic oriented agent based search engine including the concepts of intelligent graphical user interface, natural language based information processing, data management and data reconstruction for the final user end information representation.


Semantic Oriented Intelligent Electronic Learning

Abstract: In this research paper we describe semantic oriented information engineering and knowledge management based solution towards E-Learning systems. We also try to justify the importance of proposed solution with respect to the E-Learning Approaches .i.e., Behavior, Objectivism, Cognitive and Construction. Moreover we briefly describe E-Learning, information engineering, knowledge management and some old and newly available technologies supporting development of E-Learning Systems in this research paper.


Web to Semantic Web & Role of Ontology

Abstract: In this research paper we are briefly presenting current major web problems and introducing semantic web technologies with the claim of solving existing web's problems. Furthermore we are describing Ontology as the main building block of semantic web and focusing on its contributions to semantic web progress and current limitations.


An Agent based Approach towards Metadata Extraction, Modelling and Information Retrieval over the Web

Abstract: Web development is a challenging research area for its creativity and complexity. The existing raised key challenge in web technology technologic development is the presentation of data in machine read and process able format to take advantage in knowledge based information extraction and maintenance. Currently it is not possible to search and extract optimized results using full text queries because there is no such mechanism exists which can fully extract the semantic from full text queries and then look for particular knowledge based information.


How Does Ontology Contribute in Semantic Web Development?

Abstract: This paper investigates and briefly describes the major currently existing problems with World Wide Web .i.e., Information filtration and Security became the main reasons of semantic web's invention. The semantic web claims of providing the semantic based solutions towards current web problems. Semantic web have introduced and relies on a main building block "Ontology" to provide the information in machine processable semantic models and produce semantically modelled knowledge representation systems. This paper also describes the role, construction process and the contributions of ontology in providing some in time proposed and implemented solutions. Furthermore paper concludes with the currently existing limitations in Ontology and the areas which need improvements.


Designing a Dynamic Components and Agent based Approach for Semantic Information Retrieval

Abstract: In this paper based on agent and semantic web technologies we propose an approach .i.e., Semantic Oriented Agent Based Search (SOAS), to cope with currently existing challenges of Meta data extraction, modeling and information retrieval over the web. SOAS is designed by keeping four major requirements .i.e., Automatic user request handling, Dynamic unstructured full text reading, Analysing and modeling, Semantic query generation and optimized result classifier. The architecture of SOAS is consisting of an agent called Personal Agent (PA) and five dynamic components .i.e., Request Processing Unit (RPU), Agent Locator (AL), Agent Communicator (AC), List Builder (LB) and Result Generator (RG). Furthermore, in this paper we briefly discuss Semantic Web and some already existing in time proposed and implemented semantic based approaches.


I-SOAS towards Product Data Management (PDM) based Application's Problems

Abstract: In this research paper we address the importance of Product Data Management (PDM) with respect to the industrial contributional point of view and its major objectives. Moreover we also present some currently available major challenges to the Product Data Management based communities, and targeting those challenges we discuss an already proposed conceptual architectural based helpful approach and briefly describe how this approach can be helpful in solving the PDM communities faced problems.


PDM based I-SOAS Data Warehouse Design

Abstract: This research paper briefly describes the industrial contributions of Product Data Management in any organization's technical and managerial data management. Then focusing on some current major PDM based problems i.e. Static and Unintelligent Search, Platform Independent System and Successful PDM System Implementation, briefly presents a semantic based solution i.e. I-SOAS. Majorly this research paper is about to present and discuss the contributions of I-SOAS in any organization's technical and system data management.


Intelligent Human Machine Interface Design for Advanced Product Life Cycle Management Systems

Abstract: Designing and implementing an intelligent and user friendly human machine interface for any kind of software or hardware oriented application is always be a challenging task for the designers and developers because it is very difficult to understand the psychology of the user, nature of the work and best suit of the environment. This research paper is basically about to propose an intelligent, flexible and user friendly machine interface for Product Life Cycle Management products or PDM Systems since studies show that usability and human computer interaction issues are a major cause of acceptance problems introducing or using such systems. Going into details of the proposition, we present prototype implementations about theme based on design requirements, designed designs and technologies involved for the development of human machine interface.


Removal of Communication Gap

Abstract: This research is about an online forum designed and developed to improve the communication process between alumni, new, old and upcoming students. In this research paper we present targeted problems, designed architecture, used technologies in development and final end product in detail.


Social Networks and Spin Glasses

Abstract: The networks formed from the links between telephones observed in a month's call detail records (CDRs) in the UK are analyzed, looking for the characteristics thought to identify a communications network or a social network. Some novel methods are employed. We find similarities to both types of network. We conclude that, just as analogies to spin glasses have proved fruitful for optimization of large scale practical problems, there will be opportunities to exploit a statistical mechanics of the formation and dynamics of social networks in today's electronically connected world.


Weighted Max-Min Resource Allocation for Frequency Selective Channels

Abstract: In this paper, we discuss the computation of weighted max-min rate allocation using joint TDM/FDM strategies under a PSD mask constraint. We show that the weighted max-min solution allocates the rates according to a predetermined rate ratio defined by the weights, a fact that is very valuable for telecommunication service providers. Furthermore, we show that the problem can be efficiently solved using linear programming. We also discuss the resource allocation problem in the mixed services scenario where certain users have a required rate, while the others have flexible rate requirements. The solution is relevant to many communication systems that are limited by a power spectral density mask constraint such as WiMax, Wi-Fi and UWB.


Towards Design and Implementation of a Language Technology based Information Processor for PDM Systems

Abstract: Product Data Management (PDM) aims to provide 'Systems' contributing in industries by electronically maintaining organizational data, improving data repository system, facilitating with easy access to CAD and providing additional information engineering and management modules to access, store, integrate, secure, recover and manage information. Targeting one of the unresolved issues i.e., provision of natural language based processor for the implementation of an intelligent record search mechanism, an approach is proposed and discussed in detail in this manuscript. Designing an intelligent application capable of reading and analyzing user's structured and unstructured natural language based text requests and then extracting desired concrete and optimized results from knowledge base is still a challenging task for the designers because it is still very difficult to completely extract Meta data out of raw data. Residing within the limited scope of current research and development; we present an approach capable of reading user's natural language based input text, understanding the semantic and extracting results from repositories. To evaluate the effectiveness of implemented prototyped version of proposed approach, it is compared with some existing PDM Systems, in the end the discussion is concluded with an abstract presentation of resultant comparison amongst implemented prototype and some existing PDM Systems.


Semi-Supervised Kernel PCA

Abstract: We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets.


A Simplification of a Real-Time Verification Problem

Abstract: We revisit the problem of real-time verification with dense dynamics using timeout and calendar based models and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timeout Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism.


Actor Model of Computation: Scalable Robust Information Systems

Abstract: The Actor model is a mathematical theory that treats "Actors" as the universal primitives of concurrent digital computation. The model has been used both as a framework for a theoretical understanding of concurrency, and as the theoretical basis for several practical implementations of concurrent systems. Unlike previous models of computation, the Actor model was inspired by physical laws. It was also influenced by the programming languages Lisp, Simula 67 and Smalltalk-72, as well as ideas for Petri Nets, capability-based systems and packet switching. The advent of massive concurrency through client-cloud computing and many-core computer architectures has galvanized interest in the Actor model. Actor technology will see significant application for integrating all kinds of digital information for individuals, groups, and organizations so their information usefully links together. Information integration needs to make use of the following information system principles: * Persistence. Information is collected and indexed. * Concurrency: Work proceeds interactively and concurrently, overlapping in time. * Quasi-commutativity: Information can be used regardless of whether it initiates new work or become relevant to ongoing work. * Sponsorship: Sponsors provide resources for computation, i.e., processing, storage, and communications. * Pluralism: Information is heterogeneous, overlapping and often inconsistent. * Provenance: The provenance of information is carefully tracked and recorded The Actor Model is intended to provide a foundation for inconsistency robust information integration


Fast, precise and dynamic distance queries

Abstract: We present an approximate distance oracle for a point set S with n points and doubling dimension {\lambda}. For every {\epsilon}>0, the oracle supports (1+{\epsilon})-approximate distance queries in (universal) constant time, occupies space [{\epsilon}^{-O({\lambda})} + 2^{O({\lambda} log {\lambda})}]n, and can be constructed in [2^{O({\lambda})} log3 n + {\epsilon}^{-O({\lambda})} + 2^{O({\lambda} log {\lambda})}]n expected time. This improves upon the best previously known constructions, presented by Har-Peled and Mendel. Furthermore, the oracle can be made fully dynamic with expected O(1) query time and only 2^{O({\lambda})} log n + {\epsilon}^{-O({\lambda})} + 2^{O({\lambda} log {\lambda})} update time. This is the first fully dynamic (1+{\epsilon})-distance oracle.


A note on communicating between information systems based on including degrees

Abstract: In order to study the communication between information systems, Gong and Xiao [Z. Gong and Z. Xiao, Communicating between information systems based on including degrees, International Journal of General Systems 39 (2010) 189--206] proposed the concept of general relation mappings based on including degrees. Some properties and the extension for fuzzy information systems of the general relation mappings have been investigated there. In this paper, we point out by counterexamples that several assertions (Lemma 3.1, Lemma 3.2, Theorem 4.1, and Theorem 4.3) in the aforementioned work are not true in general.


Free iterative and iteration K-semialgebras

Abstract: We consider algebras of rational power series over an alphabet $\Sigma$ with coefficients in a commutative semiring $K$ and characterize them as the free algebras in various classes of algebraic structures.


The Hitchhiker's Guide to Affiliation Networks: A Game-Theoretic Approach

Abstract: We propose a new class of game-theoretic models for network formation in which strategies are not directly related to edge choices, but instead correspond more generally to the exertion of social effort. The observed social network is thus a byproduct of an expressive strategic interaction, which can more naturally explain the emergence of complex social structures. Within this framework, we present a natural network formation game in which agent utilities are locally defined and that, despite its simplicity, produces a rich class of equilibria that exhibit structural properties commonly observed in social networks - such as triadic closure - that have proved elusive in most existing models. Specifically, we consider a game in which players organize networking events at a cost that grows with the number of attendees. An event's cost is assumed by the organizer but the benefit accrues equally to all attendees: a link is formed between any two players who see each other at more than a certain number r of events per time period. The graph of connections so obtained is the social network of the model. We analyze the Nash equilibria of this game when each player derives a benefit a>0 from all her neighbors in the network and when the costs are linear, i.e., when the cost of an event with L invitees is b+cL, with b>0 and c>0. For a/cr > 1 and b sufficiently small, all Nash equilibria have the complete graph as their social network; for a/cr < 1 the Nash equilibria correspond to a rich class of social networks, all of which have substantial clustering in the sense that the clustering coefficient is bounded below by the inverse of the average degree. Additionally, for any degree sequence with finite mean, and not too many vertices of degree one or two, we can construct a Nash equilibrium producing a social network with the given degree sequence.


The complexity of conservative finite-valued CSPs

Abstract: We study the complexity of valued constraint satisfaction problems (VCSP). A problem from VCSP is characterised by a \emph{constraint language}, a fixed set of cost functions over a finite domain. An instance of the problem is specified by a sum of cost functions from the language and the goal is to minimise the sum. We consider the case of so-called \emph{conservative} languages; that is, languages containing all unary cost functions, thus allowing arbitrary restrictions on the domains of the variables. This problem has been studied by Bulatov [LICS'03] for $\{0,\infty\}$-valued languages (i.e. CSP), by Cohen~\etal\ (AIJ'06) for Boolean domains, by Deineko et al. (JACM'08) for $\{0,1\}$-valued cost functions (i.e. Max-CSP), and by Takhanov (STACS'10) for $\{0,\infty\}$-valued languages containing all finite-valued unary cost functions (i.e. Min-Cost-Hom). We give an elementary proof of a complete complexity classification of conservative finite-valued languages: we show that every conservative finite-valued language is either tractable or NP-hard. This is the \emph{first} dichotomy result for finite-valued VCSPs over non-Boolean domains.


On a game theoretic approach to capacity maximization in wireless networks

Abstract: We consider the capacity problem (or, the single slot scheduling problem) in wireless networks. Our goal is to maximize the number of successful connections in arbitrary wireless networks where a transmission is successful only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. We study a game theoretic approach towards capacity maximization introduced by Andrews and Dinitz (INFOCOM 2009) and Dinitz (INFOCOM 2010). We prove vastly improved bounds for the game theoretic algorithm. In doing so, we achieve the first distributed constant factor approximation algorithm for capacity maximization for the uniform power assignment. When compared to the optimum where links may use an arbitrary power assignment, we prove a $O(\log \Delta)$ approximation, where $\Delta$ is the ratio between the largest and the smallest link in the network. This is an exponential improvement of the approximation factor compared to existing results for distributed algorithms. All our results work for links located in any metric space. In addition, we provide simulation studies clarifying the picture on distributed algorithms for capacity maximization.


Separate Training for Conditional Random Fields Using Co-occurrence Rate Factorization

Abstract: The standard training method of Conditional Random Fields (CRFs) is very slow for large-scale applications. As an alternative, piecewise training divides the full graph into pieces, trains them independently, and combines the learned weights at test time. In this paper, we present \emph{separate} training for undirected models based on the novel Co-occurrence Rate Factorization (CR-F). Separate training is a local training method. In contrast to MEMMs, separate training is unaffected by the label bias problem. Experiments show that separate training (i) is unaffected by the label bias problem; (ii) reduces the training time from weeks to seconds; and (iii) obtains competitive results to the standard and piecewise training on linear-chain CRFs.


Scaling Turbo Boost to a 1000 cores

Abstract: The Intel Core i7 processor code named Nehalem provides a feature named Turbo Boost which opportunistically varies the frequencies of the processor's cores. The frequency of a core is determined by core temperature, the number of active cores, the estimated power consumption, the estimated current consumption, and operating system frequency scaling requests. For a chip multi-processor(CMP) that has a small number of physical cores and a small set of performance states, deciding the Turbo Boost frequency to use on a given core might not be difficult. However, we do not know the complexity of this decision making process in the context of a large number of cores, scaling to the 100s, as predicted by researchers in the field.


Bootstrap Markov chain Monte Carlo and optimal solutions for the Law of Categorical Judgment (Corrected)

Abstract: A novel procedure is described for accelerating the convergence of Markov chain Monte Carlo computations. The algorithm uses an adaptive bootstrap technique to generate candidate steps in the Markov Chain. It is efficient for symmetric, convex probability distributions, similar to multivariate Gaussians, and it can be used for Bayesian estimation or for obtaining maximum likelihood solutions with confidence limits. As a test case, the Law of Categorical Judgment (Corrected) was fitted with the algorithm to data sets from simulated rating scale experiments. The correct parameters were recovered from practical-sized data sets simulated for Full Signal Detection Theory and its special cases of standard Signal Detection Theory and Complementary Signal Detection Theory.


Approximation Schemes for Sequential Posted Pricing in Multi-Unit Auctions

Abstract: We design algorithms for computing approximately revenue-maximizing {\em sequential posted-pricing mechanisms (SPM)} in $K$-unit auctions, in a standard Bayesian model. A seller has $K$ copies of an item to sell, and there are $n$ buyers, each interested in only one copy, who have some value for the item. The seller must post a price for each buyer, the buyers arrive in a sequence enforced by the seller, and a buyer buys the item if its value exceeds the price posted to it. The seller does not know the values of the buyers, but have Bayesian information about them. An SPM specifies the ordering of buyers and the posted prices, and may be {\em adaptive} or {\em non-adaptive} in its behavior. The goal is to design SPM in polynomial time to maximize expected revenue. We compare against the expected revenue of optimal SPM, and provide a polynomial time approximation scheme (PTAS) for both non-adaptive and adaptive SPMs. This is achieved by two algorithms: an efficient algorithm that gives a $(1-\frac{1}{\sqrt{2\pi K}})$-approximation (and hence a PTAS for sufficiently large $K$), and another that is a PTAS for constant $K$. The first algorithm yields a non-adaptive SPM that yields its approximation guarantees against an optimal adaptive SPM -- this implies that the {\em adaptivity gap} in SPMs vanishes as $K$ becomes larger.


Performance Analysis of Markov Modulated 1-Persistent CSMA/CA Protocols with Exponential Backoff Scheduling

Abstract: This paper proposes a Markovian model of 1-persistent CSMA/CA protocols with K-Exponential Backoff scheduling algorithms. The input buffer of each access node is modeled as a Geo/G/1 queue, and the service time distribution of each individual head-of-line packet is derived from the Markov chain of the underlying scheduling algorithm. From the queuing model, we derive the characteristic equation of network throughput and obtain the stable throughput and bounded delay regions with respect to the retransmission factor. Our results show that the stable throughput region of the exponential backoff scheme exists even for an infinite population. Moreover, we find that the bounded delay region of exponential backoff is only a sub-set of its stable throughput region due to the large variance of the service time of input packets caused by the capture effect. All analytical results presented in this paper are verified by simulations.


Survey of Search and Replication Schemes in Unstructured P2P Networks

Abstract: P2P computing lifts taxing issues in various areas of computer science. The largely used decentralized unstructured P2P systems are ad hoc in nature and present a number of research challenges. In this paper, we provide a comprehensive theoretical survey of various state-of-the-art search and replication schemes in unstructured P2P networks for file-sharing applications. The classifications of search and replication techniques and their advantages and disadvantages are briefly explained. Finally, the various issues on searching and replication for unstructured P2P networks are discussed.


A Learning Algorithm based on High School Teaching Wisdom

Abstract: A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate a student and to give them training on the examples for which they repeatedly fail, until, they can correctly answer all types of questions. This incremental learning procedure produces better learning curves by demanding the student to optimally dedicate their learning time on the failed examples. When used in machine learning, the algorithm is found to train a machine on a data with maximum variance in the feature space so that the generalization ability of the network improves. The algorithm has interesting applications in data mining, model evaluations and rare objects discovery.


State Complexity of Catenation Combined with Star and Reversal

Abstract: This paper is a continuation of our research work on state complexity of combined operations. Motivated by applications, we study the state complexities of two particular combined operations: catenation combined with star and catenation combined with reversal. We show that the state complexities of both of these combined operations are considerably less than the compositions of the state complexities of their individual participating operations.


Accepting Hybrid Networks of Evolutionary Processors with Special Topologies and Small Communication

Abstract: Starting from the fact that complete Accepting Hybrid Networks of Evolutionary Processors allow much communication between the nodes and are far from network structures used in practice, we propose in this paper three network topologies that restrict the communication: star networks, ring networks, and grid networks. We show that ring-AHNEPs can simulate 2-tag systems, thus we deduce the existence of a universal ring-AHNEP. For star networks or grid networks, we show a more general result; that is, each recursively enumerable language can be accepted efficiently by a star- or grid-AHNEP. We also present bounds for the size of these star and grid networks. As a consequence we get that each recursively enumerable can be accepted by networks with at most 13 communication channels and by networks where each node communicates with at most three other nodes.


Representing Small Ordinals by Finite Automata

Abstract: It is known that an ordinal is the order type of the lexicographic ordering of a regular language if and only if it is less than omega^omega. We design a polynomial time algorithm that constructs, for each well-ordered regular language L with respect to the lexicographic ordering, given by a deterministic finite automaton, the Cantor Normal Form of its order type. It follows that there is a polynomial time algorithm to decide whether two deterministic finite automata accepting well-ordered regular languages accept isomorphic languages. We also give estimates on the size of the smallest automaton representing an ordinal less than omega^omega, together with an algorithm that translates each such ordinal to an automaton.


Graph-Controlled Insertion-Deletion Systems

Abstract: In this article, we consider the operations of insertion and deletion working in a graph-controlled manner. We show that like in the case of context-free productions, the computational power is strictly increased when using a control graph: computational completeness can be obtained by systems with insertion or deletion rules involving at most two symbols in a contextual or in a context-free manner and with the control graph having only four nodes.


Transition Complexity of Incomplete DFAs

Abstract: In this paper, we consider the transition complexity of regular languages based on the incomplete deterministic finite automata. A number of results on Boolean operations have been obtained. It is shown that the transition complexity results for union and complementation are very different from the state complexity results for the same operations. However, for intersection, the transition complexity result is similar to that of state complexity.


Ciliate Gene Unscrambling with Fewer Templates

Abstract: One of the theoretical models proposed for the mechanism of gene unscrambling in some species of ciliates is the template-guided recombination (TGR) system by Prescott, Ehrenfeucht and Rozenberg which has been generalized by Daley and McQuillan from a formal language theory perspective. In this paper, we propose a refinement of this model that generates regular languages using the iterated TGR system with a finite initial language and a finite set of templates, using fewer templates and a smaller alphabet compared to that of the Daley-McQuillan model. To achieve Turing completeness using only finite components, i.e., a finite initial language and a finite set of templates, we also propose an extension of the contextual template-guided recombination system (CTGR system) by Daley and McQuillan, by adding an extra control called permitting contexts on the usage of templates.


Descriptional Complexity of the Languages KaL: Automata, Monoids and Varieties

Abstract: The first step when forming the polynomial hierarchies of languages is to consider languages of the form KaL where K and L are over a finite alphabet A and from a given variety V of languages, a being a letter from A. All such KaL's generate the variety of languages BPol1(V). We estimate the numerical parameters of the language KaL in terms of their values for K and L. These parameters include the state complexity of the minimal complete DFA and the size of the syntactic monoids. We also estimate the cardinality of the image of A* in the Schuetzenberger product of the syntactic monoids of K and L. In these three cases we obtain the optimal bounds. Finally, we also consider estimates for the cardinalities of free monoids in the variety of monoids corresponding to BPol1(V) in terms of sizes of the free monoids in the variety of monoids corresponding to V.


State Elimination Ordering Strategies: Some Experimental Results

Abstract: Recently, the problem of obtaining a short regular expression equivalent to a given finite automaton has been intensively investigated. Algorithms for converting finite automata to regular expressions have an exponential blow-up in the worst-case. To overcome this, simple heuristic methods have been proposed. In this paper we analyse some of the heuristics presented in the literature and propose new ones. We also present some experimental comparative results based on uniform random generated deterministic finite automata.


Operational State Complexity of Deterministic Unranked Tree Automata

Abstract: We consider the state complexity of basic operations on tree languages recognized by deterministic unranked tree automata. For the operations of union and intersection the upper and lower bounds of both weakly and strongly deterministic tree automata are obtained. For tree concatenation we establish a tight upper bound that is of a different order than the known state complexity of concatenation of regular string languages. We show that (n+1) ( (m+1)2^n-2^(n-1) )-1 vertical states are sufficient, and necessary in the worst case, to recognize the concatenation of tree languages recognized by (strongly or weakly) deterministic automata with, respectively, m and n vertical states.


Transformations Between Different Types of Unranked Bottom-Up Tree Automata

Abstract: We consider the representational state complexity of unranked tree automata. The bottom-up computation of an unranked tree automaton may be either deterministic or nondeterministic, and further variants arise depending on whether the horizontal string languages defining the transitions are represented by a DFA or an NFA. Also, we consider for unranked tree automata the alternative syntactic definition of determinism introduced by Cristau et al. (FCT'05, Lect. Notes Comput. Sci. 3623, pp. 68-79). We establish upper and lower bounds for the state complexity of conversions between different types of unranked tree automata.


On the Descriptional Complexity of Limited Propagating Lindenmayer Systems

Abstract: We investigate the descriptional complexity of limited propagating Lindenmayer systems and their deterministic and tabled variants with respect to the number of rules and the number of symbols. We determine the decrease of complexity when the generative capacity is increased. For incomparable families, we give languages that can be described more efficiently in either of these families than in the other.


Nondeterministic State Complexity for Suffix-Free Regular Languages

Abstract: We investigate the nondeterministic state complexity of basic operations for suffix-free regular languages. The nondeterministic state complexity of an operation is the number of states that are necessary and sufficient in the worst-case for a minimal nondeterministic finite-state automaton that accepts the language obtained from the operation. We consider basic operations (catenation, union, intersection, Kleene star, reversal and complementation) and establish matching upper and lower bounds for each operation. In the case of complementation the upper and lower bounds differ by an additive constant of two.


Complexity in Prefix-Free Regular Languages

Abstract: We examine deterministic and nondeterministic state complexities of regular operations on prefix-free languages. We strengthen several results by providing witness languages over smaller alphabets, usually as small as possible. We next provide the tight bounds on state complexity of symmetric difference, and deterministic and nondeterministic state complexity of difference and cyclic shift of prefix-free languages.


Learning Residual Finite-State Automata Using Observation Tables

Abstract: We define a two-step learner for RFSAs based on an observation table by using an algorithm for minimal DFAs to build a table for the reversal of the language in question and showing that we can derive the minimal RFSA from it after some simple modifications. We compare the algorithm to two other table-based ones of which one (by Bollig et al. 2009) infers a RFSA directly, and the other is another two-step learner proposed by the author. We focus on the criterion of query complexity.


L-systems in Geometric Modeling

Abstract: We show that parametric context-sensitive L-systems with affine geometry interpretation provide a succinct description of some of the most fundamental algorithms of geometric modeling of curves. Examples include the Lane-Riesenfeld algorithm for generating B-splines, the de Casteljau algorithm for generating Bezier curves, and their extensions to rational curves. Our results generalize the previously reported geometric-modeling applications of L-systems, which were limited to subdivision curves.


Remembering Chandra Kintala

Abstract: With this contribution we would like to remember Chandra M. R. Kintala who passed away in November 2009. We will give short overviews of his CV and his contributions to the field of theoretical and applied computer science and, given the opportunity, will attempt to present the current state of limited nondeterminism and limited resources for machines. Finally, we will briefly touch on some research topics which hopefully will be addressed in the not so distant future.


On the Complexity of the Evaluation of Transient Extensions of Boolean Functions

Abstract: Transient algebra is a multi-valued algebra for hazard detection in gate circuits. Sequences of alternating 0's and 1's, called transients, represent signal values, and gates are modeled by extensions of boolean functions to transients. Formulas for computing the output transient of a gate from the input transients are known for NOT, AND, OR} and XOR gates and their complements, but, in general, even the problem of deciding whether the length of the output transient exceeds a given bound is NP-complete. We propose a method of evaluating extensions of general boolean functions. We introduce and study a class of functions with the following property: Instead of evaluating an extension of a boolean function on a given set of transients, it is possible to get the same value by using transients derived from the given ones, but having length at most 3. We prove that all functions of three variables, as well as certain other functions, have this property, and can be efficiently evaluated.


Finite-State Complexity and the Size of Transducers

Abstract: Finite-state complexity is a variant of algorithmic information theory obtained by replacing Turing machines with finite transducers. We consider the state-size of transducers needed for minimal descriptions of arbitrary strings and, as our main result, we show that the state-size hierarchy with respect to a standard encoding is infinite. We consider also hierarchies yielded by more general computable encodings.


State Complexity of Testing Divisibility

Abstract: Under some mild assumptions, we study the state complexity of the trim minimal automaton accepting the greedy representations of the multiples of m >= 2 for a wide class of linear numeration systems. As an example, the number of states of the trim minimal automaton accepting the greedy representations of the multiples of m in the Fibonacci system is exactly 2m^2.


Interoperability, Trust Based Information Sharing Protocol and Security: Digital Government Key Issues

Abstract: Improved interoperability between public and private organizations is of key significance to make digital government newest triumphant. Digital Government interoperability, information sharing protocol and security are measured the key issue for achieving a refined stage of digital government. Flawless interoperability is essential to share the information between diverse and merely dispersed organisations in several network environments by using computer based tools. Digital government must ensure security for its information systems, including computers and networks for providing better service to the citizens. Governments around the world are increasingly revolving to information sharing and integration for solving problems in programs and policy areas. Evils of global worry such as syndrome discovery and manage, terror campaign, immigration and border control, prohibited drug trafficking, and more demand information sharing, harmonization and cooperation amid government agencies within a country and across national borders. A number of daunting challenges survive to the progress of an efficient information sharing protocol. A secure and trusted information-sharing protocol is required to enable users to interact and share information easily and perfectly across many diverse networks and databases globally.


A Parsing Scheme for Finding the Design Pattern and Reducing the Development Cost of Reusable Object Oriented Software

Abstract: Because of the importance of object oriented methodologies, the research in developing new measure for object oriented system development is getting increased focus. The most of the metrics need to find the interactions between the objects and modules for developing necessary metric and an influential software measure that is attracting the software developers, designers and researchers. In this paper a new interactions are defined for object oriented system. Using these interactions, a parser is developed to analyze the existing architecture of the software. Within the design model, it is necessary for design classes to collaborate with one another. However, collaboration should be kept to an acceptable minimum i.e. better designing practice will introduce low coupling. If a design model is highly coupled, the system is difficult to implement, to test and to maintain overtime. In case of enhancing software, we need to introduce or remove module and in that case coupling is the most important factor to be considered because unnecessary coupling may make the system unstable and may cause reduction in the system's performance. So coupling is thought to be a desirable goal in software construction, leading to better values for external software qualities such as maintainability, reusability and so on. To test this hypothesis, a good measure of class coupling is needed. In this paper, based on the developed tool called Design Analyzer we propose a methodology to reuse an existing system with the objective of enhancing an existing Object oriented system keeping the coupling as low as possible.


Space and the Synchronic A-Ram

Abstract: Space is a circuit oriented, spatial programming language designed to exploit the massive parallelism available in a novel formal model of computation called the Synchronic A-Ram, and physically related FPGA and reconfigurable architectures. Space expresses variable grained MIMD parallelism, is modular, strictly typed, and deterministic. Barring operations associated with memory allocation and compilation, modules cannot access global variables, and are referentially transparent. At a high level of abstraction, modules exhibit a small, sequential state transition system, aiding verification. Space deals with communication, scheduling, and resource contention issues in parallel computing, by resolving them explicitly in an incremental manner, module by module, whilst ascending the ladder of abstraction. Whilst the Synchronic A-Ram model was inspired by linguistic considerations, it is also put forward as a formal model for reconfigurable digital circuits. A programming environment has been developed, that incorporates a simulator and compiler that transform Space programs into Synchronic A-Ram machine code, consisting of only three bit-level instructions, and a marking instruction. Space and the Synchronic A-Ram point to novel routes out of the parallel computing crisis.


A Deterministic Polynomial-time Approximation Scheme for Counting Knapsack Solutions

Abstract: Given n elements with nonnegative integer weights w1,..., wn and an integer capacity C, we consider the counting version of the classic knapsack problem: find the number of distinct subsets whose weights add up to at most the given capacity. We give a deterministic algorithm that estimates the number of solutions to within relative error 1+-eps in time polynomial in n and 1/eps (fully polynomial approximation scheme). More precisely, our algorithm takes time O(n^3 (1/eps) log (n/eps)). Our algorithm is based on dynamic programming. Previously, randomized polynomial time approximation schemes were known first by Morris and Sinclair via Markov chain Monte Carlo techniques, and subsequently by Dyer via dynamic programming and rejection sampling.


Biometric Authentication using Nonparametric Methods

Abstract: The physiological and behavioral trait is employed to develop biometric authentication systems. The proposed work deals with the authentication of iris and signature based on minimum variance criteria. The iris patterns are preprocessed based on area of the connected components. The segmented image used for authentication consists of the region with large variations in the gray level values. The image region is split into quadtree components. The components with minimum variance are determined from the training samples. Hu moments are applied on the components. The summation of moment values corresponding to minimum variance components are provided as input vector to k-means and fuzzy k-means classifiers. The best performance was obtained for MMU database consisting of 45 subjects. The number of subjects with zero False Rejection Rate [FRR] was 44 and number of subjects with zero False Acceptance Rate [FAR] was 45. This paper addresses the computational load reduction in off-line signature verification based on minimal features using k-means, fuzzy k-means, k-nn, fuzzy k-nn and novel average-max approaches. FRR of 8.13% and FAR of 10% was achieved using k-nn classifier. The signature is a biometric, where variations in a genuine case, is a natural expectation. In the genuine signature, certain parts of signature vary from one instance to another. The system aims to provide simple, fast and robust system using less number of features when compared to state of art works.


A domain decomposing parallel sparse linear system solver

Abstract: The solution of large sparse linear systems is often the most time-consuming part of many science and engineering applications. Computational fluid dynamics, circuit simulation, power network analysis, and material science are just a few examples of the application areas in which large sparse linear systems need to be solved effectively. In this paper we introduce a new parallel hybrid sparse linear system solver for distributed memory architectures that contains both direct and iterative components. We show that by using our solver one can alleviate the drawbacks of direct and iterative solvers, achieving better scalability than with direct solvers and more robustness than with classical preconditioned iterative solvers. Comparisons to well-known direct and iterative solvers on a parallel architecture are provided.


Introduction to the 26th International Conference on Logic Programming Special Issue

Abstract: This is the preface to the 26th International Conference on Logic Programming Special Issue


The universality of iterated hashing over variable-length strings

Abstract: Iterated hash functions process strings recursively, one character at a time. At each iteration, they compute a new hash value from the preceding hash value and the next character. We prove that iterated hashing can be pairwise independent, but never 3-wise independent. We show that it can be almost universal over strings much longer than the number of hash values; we bound the maximal string length given the collision probability.


Role of Ontology in Semantic Web Development

Abstract: World Wide Web (WWW) is the most popular global information sharing and communication system consisting of three standards .i.e., Uniform Resource Identifier (URL), Hypertext Transfer Protocol (HTTP) and Hypertext Mark-up Language (HTML). Information is provided in text, image, audio and video formats over the web by using HTML which is considered to be unconventional in defining and formalizing the meaning of the context...


Minimization of Handoff latency by co-ordinate evaluation method using GPS based map

Abstract: Handoff has become an essential criterion in mobile communication system, specially in urban areas, owing to the limited coverage area of Access Points (AP). Handover of calls between two Base Stations (BSs) is encountered frequently and it is essentially required to minimize the delay of the process. Many solutions attempting to improve this process have been proposed but only a few use geo-location systems in the management of the handover. Here we propose to minimize the handoff latency by minimizing the number of APs scanned by the Mobile Node (MN) during each handoff procedure. We consider the whole topographical area as a two dimensional plane. By GPS, we can note down the co-ordinates of the MN at any instant. The average rate of change of its latitudinal distance and longitudinal distance with a specific time period is evaluated at the end of the given time period. With the knowledge of the given parameter, it is possible to determine the latitude and longitude of the MN after a particular instant of time. Hence, the direction of motion of the MN can be determined, which in turns gives the AP towards which the MN is headings. This reduces the number of APs to be scanned. Thus, on an overall basis, the handoff latency can be reduced by almost half to one third of its value.


Understanding Space in Proof Complexity: Separations and Trade-offs via Substitutions

Abstract: For current state-of-the-art DPLL SAT-solvers the two main bottlenecks are the amounts of time and memory used. In proof complexity, these resources correspond to the length and space of resolution proofs. There has been a long line of research investigating these proof complexity measures, but while strong results have been established for length, our understanding of space and how it relates to length has remained quite poor. In particular, the question whether resolution proofs can be optimized for length and space simultaneously, or whether there are trade-offs between these two measures, has remained essentially open. In this paper, we remedy this situation by proving a host of length-space trade-off results for resolution. Our collection of trade-offs cover almost the whole range of values for the space complexity of formulas, and most of the trade-offs are superpolynomial or even exponential and essentially tight. Using similar techniques, we show that these trade-offs in fact extend to the exponentially stronger k-DNF resolution proof systems, which operate with formulas in disjunctive normal form with terms of bounded arity k. We also answer the open question whether the k-DNF resolution systems form a strict hierarchy with respect to space in the affirmative. Our key technical contribution is the following, somewhat surprising, theorem: Any CNF formula F can be transformed by simple variable substitution into a new formula F' such that if F has the right properties, F' can be proven in essentially the same length as F, whereas on the other hand the minimal number of lines one needs to keep in memory simultaneously in any proof of F' is lower-bounded by the minimal number of variables needed simultaneously in any proof of F. Applying this theorem to so-called pebbling formulas defined in terms of pebble games on directed acyclic graphs, we obtain our results.


Symmetry-breaking Answer Set Solving

Abstract: In the context of Answer Set Programming, this paper investigates symmetry-breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We propose a reduction of disjunctive logic programs to a coloured digraph such that permutational symmetries can be constructed from graph automorphisms. Symmetries are then broken by introducing symmetry-breaking constraints. For this purpose, we formulate a preprocessor that integrates a graph automorphism system. Experiments demonstrate its computational impact.


Breaking the Legend: Maxmin Fairness notion is no longer effective

Abstract: In this paper we analytically propose an alternative approach to achieve better fairness in scheduling mechanisms which could provide better quality of service particularly for real time application. Our proposal oppose the allocation of the bandwidth which adopted by all previous scheduling mechanism. It rather adopt the opposition approach be proposing the notion of Maxmin-charge which fairly distribute the congestion. Furthermore, analytical proposition of novel mechanism named as Just Queueing is been demonstrated.


Nash Equilibria in Perturbation Resilient Games

Abstract: Motivated by the fact that in many game-theoretic settings, the game analyzed is only an approximation to the game being played, in this work we analyze equilibrium computation for the broad and natural class of bimatrix games that are stable to perturbations. We specifically focus on games with the property that small changes in the payoff matrices do not cause the Nash equilibria of the game to fluctuate wildly. For such games we show how one can compute approximate Nash equilibria more efficiently than the general result of Lipton et al. \cite{LMM03}, by an amount that depends on the degree of stability of the game and that reduces to their bound in the worst case. Furthermore, we show that for stable games the approximate equilibria found will be close in variation distance to true equilibria, and moreover this holds even if we are given as input only a perturbation of the actual underlying stable game. For uniformly-stable games, where the equilibria fluctuate at most quasi-linearly in the extent of the perturbation, we get a particularly dramatic improvement. Here, we achieve a fully quasi-polynomial-time approximation scheme: that is, we can find $1/\poly(n)$-approximate equilibria in quasi-polynomial time. This is in marked contrast to the general class of bimatrix games for which finding such approximate equilibria is PPAD-hard. In particular, under the (widely believed) assumption that PPAD is not contained in quasi-polynomial time, our results imply that such uniformly stable games are inherently easier for computation of approximate equilibria than general bimatrix games.


Scheduling with Rate Adaptation under Incomplete Knowledge of Channel/Estimator Statistics

Abstract: In time-varying wireless networks, the states of the communication channels are subject to random variations, and hence need to be estimated for efficient rate adaptation and scheduling. The estimation mechanism possesses inaccuracies that need to be tackled in a probabilistic framework. In this work, we study scheduling with rate adaptation in single-hop queueing networks under two levels of channel uncertainty: when the channel estimates are inaccurate but complete knowledge of the channel/estimator joint statistics is available at the scheduler; and when the knowledge of the joint statistics is incomplete. In the former case, we characterize the network stability region and show that a maximum-weight type scheduling policy is throughput-optimal. In the latter case, we propose a joint channel statistics learning - scheduling policy. With an associated trade-off in average packet delay and convergence time, the proposed policy has a stability region arbitrarily close to the stability region of the network under full knowledge of channel/estimator joint statistics.


An Efficient Network Coding based Retransmission Algorithm for Wireless Multicasts

Abstract: Retransmission based on packet acknowledgement (ACK/NAK) is a fundamental error control technique employed in IEEE 802.11-2007 unicast network. However the 802.11-2007 standard falls short of proposing a reliable MAC-level recovery protocol for multicast frames. In this paper we propose a latency and bandwidth efficient coding algorithm based on the principles of network coding for retransmitting lost packets in a singlehop wireless multicast network and demonstrate its effectiveness over previously proposed network coding based retransmission algorithms.


Mechanism Design via Correlation Gap

Abstract: For revenue and welfare maximization in single-dimensional Bayesian settings, Chawla et al. (STOC10) recently showed that sequential posted-price mechanisms (SPMs), though simple in form, can perform surprisingly well compared to the optimal mechanisms. In this paper, we give a theoretical explanation of this fact, based on a connection to the notion of correlation gap. Loosely speaking, for auction environments with matroid constraints, we can relate the performance of a mechanism to the expectation of a monotone submodular function over a random set. This random set corresponds to the winner set for the optimal mechanism, which is highly correlated, and corresponds to certain demand set for SPMs, which is independent. The notion of correlation gap of Agrawal et al.\ (SODA10) quantifies how much we {}"lose" in the expectation of the function by ignoring correlation in the random set, and hence bounds our loss in using certain SPM instead of the optimal mechanism. Furthermore, the correlation gap of a monotone and submodular function is known to be small, and it follows that certain SPM can approximate the optimal mechanism by a good constant factor. Exploiting this connection, we give tight analysis of a greedy-based SPM of Chawla et al.\ for several environments. In particular, we show that it gives an $e/(e-1)$-approximation for matroid environments, gives asymptotically a $1/(1-1/\sqrt{2\pi k})$-approximation for the important sub-case of $k$-unit auctions, and gives a $(p+1)$-approximation for environments with $p$-independent set system constraints.


Enhancing QOS and QOE in IMS enabled next generation networks

Abstract: Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks - all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to "achieve more, for less." The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user's access agnosticism, service agility, and global mobility.


Design and Modeling Billing solution to Next Generation Networks

Abstract: Next generation networks (NGN) services are assumed to be a new revenue stream for both network operators and service providers. New services especially focused on a mobile telecommunications that would be used not only as a communication de vice but also as a personal gateway to order or consume a variety of services and products [1]. This type of advanced services can be accomplished when the adaptability of the packet-networks (Internet) and the quality of service of the circuit switched networks are combined into one network [2]. New challenges appear in the billing of this heterogeneous multi services network. Some examples of such a services and possible solutions about charging and billing are examined in this paper. The first steps of mathematical model for billing are also considered.


The Cloud Adoption Toolkit: Supporting Cloud Adoption Decisions in the Enterprise

Abstract: Cloud computing promises a radical shift in the provisioning of computing resource within the enterprise. This paper describes the challenges that decision makers face when assessing the feasibility of the adoption of cloud computing in their organisations, and describes our Cloud Adoption Toolkit, which has been developed to support this process. The toolkit provides a framework to support decision makers in identifying their concerns, and matching these concerns to appropriate tools/techniques that can be used to address them. Cost Modeling is the most mature tool in the toolkit, and this paper shows its effectiveness by demonstrating how practitioners can use it to examine the costs of deploying their IT systems on the cloud. The Cost Modeling tool is evaluated using a case study of an organization that is considering the migration of some of its IT systems to the cloud. The case study shows that running systems on the cloud using a traditional "always on" approach can be less cost effective, and the elastic nature of the cloud has to be used to reduce costs. Therefore, decision makers have to be able to model the variations in resource usage and their systems deployment options to obtain accurate cost estimates.


Optimization over Geodesics for Exact Principal Geodesic Analysis

Abstract: In fields ranging from computer vision to signal processing and statistics, increasing computational power allows a move from classical linear models to models that incorporate non-linear phenomena. This shift has created interest in computational aspects of differential geometry, and solving optimization problems that incorporate non-linear geometry constitutes an important computational task. In this paper, we develop methods for numerically solving optimization problems over spaces of geodesics using numerical integration of Jacobi fields and second order derivatives of geodesic families. As an important application of this optimization strategy, we compute exact Principal Geodesic Analysis (PGA), a non-linear version of the PCA dimensionality reduction procedure. By applying the exact PGA algorithm to synthetic data, we exemplify the differences between the linearized and exact algorithms caused by the non-linear geometry. In addition, we use the numerically integrated Jacobi fields to determine sectional curvatures and provide upper bounds for injectivity radii.