REX: Explaining Relationships between Entity Pairs

Abstract: Knowledge bases of entities and relations (either constructed manually or automatically) are behind many real world search engines, including those at Yahoo!, Microsoft, and Google. Those knowledge bases can be viewed as graphs with nodes representing entities and edges representing (primary) relationships, and various studies have been conducted on how to leverage them to answer entity seeking queries. Meanwhile, in a complementary direction, analyses over the query logs have enabled researchers to identify entity pairs that are statistically correlated. Such entity relationships are then presented to search users through the "related searches" feature in modern search engines. However, entity relationships thus discovered can often be "puzzling" to the users because why the entities are connected is often indescribable. In this paper, we propose a novel problem called "entity relationship explanation", which seeks to explain why a pair of entities are connected, and solve this challenging problem by integrating the above two complementary approaches, i.e., we leverage the knowledge base to "explain" the connections discovered between entity pairs. More specifically, we present REX, a system that takes a pair of entities in a given knowledge base as input and efficiently identifies a ranked list of relationship explanations. We formally define relationship explanations and analyze their desirable properties. Furthermore, we design and implement algorithms to efficiently enumerate and rank all relationship explanations based on multiple measures of "interestingness." We perform extensive experiments over real web-scale data gathered from DBpedia and a commercial search engine, demonstrating the efficiency and scalability of REX. We also perform user studies to corroborate the effectiveness of explanations generated by REX.


PASS-JOIN: A Partition-based Method for Similarity Joins

Abstract: As an essential operation in data cleaning, the similarity join has attracted considerable attention from the database community. In this paper, we study string similarity joins with edit-distance constraints, which find similar string pairs from two large sets of strings whose edit distance is within a given threshold. Existing algorithms are efficient either for short strings or for long strings, and there is no algorithm that can efficiently and adaptively support both short strings and long strings. To address this problem, we propose a partition-based method called Pass-Join. Pass-Join partitions a string into a set of segments and creates inverted indices for the segments. Then for each string, Pass-Join selects some of its substrings and uses the selected substrings to find candidate pairs using the inverted indices. We devise efficient techniques to select the substrings and prove that our method can minimize the number of selected substrings. We develop novel pruning techniques to efficiently verify the candidate pairs. Experimental results show that our algorithms are efficient for both short strings and long strings, and outperform state-of-the-art methods on real datasets.


Developing Embodied Multisensory Dialogue Agents

Abstract: A few decades of work in the AI field have focused efforts on developing a new generation of systems which can acquire knowledge via interaction with the world. Yet, until very recently, most such attempts were underpinned by research which predominantly regarded linguistic phenomena as separated from the brain and body. This could lead one into believing that to emulate linguistic behaviour, it suffices to develop 'software' operating on abstract representations that will work on any computational machine. This picture is inaccurate for several reasons, which are elucidated in this paper and extend beyond sensorimotor and semantic resonance. Beginning with a review of research, I list several heterogeneous arguments against disembodied language, in an attempt to draw conclusions for developing embodied multisensory agents which communicate verbally and non-verbally with their environment. Without taking into account both the architecture of the human brain, and embodiment, it is unrealistic to replicate accurately the processes which take place during language acquisition, comprehension, production, or during non-linguistic actions. While robots are far from isomorphic with humans, they could benefit from strengthened associative connections in the optimization of their processes and their reactivity and sensitivity to environmental stimuli, and in situated human-machine interaction. The concept of multisensory integration should be extended to cover linguistic input and the complementary information combined from temporally coincident sensory impressions.


A secure solution on hierarchical access control

Abstract: Hierarchical access control is an important and traditional problem in information security. In 2001, Wu et.al. proposed an elegant solution for hierarchical access control by the secure-filter. Jeng and Wang presented an improvement of Wu et. al.'s method by the ECC cryptosystem. However, secure-filter method is insecure in dynaminc access control. Lie, Hsu and Tripathy, Paul pointed out some secure leaks on the secure-filter and presented some improvements to eliminate these secure flaws. In this paper, we revise the secure-filter in Jeng-Wang method and propose another secure solutions in hierarchical access control problem. CA is a super security class (user) in our proposed method and the secure-filter of $u_i$ in our solutions is a polynomial of degree $n_i+1$ in $\mathbb{Z}_p^*$, $f_i(x)=(x-h_i)(x-a_1)...(x-a_{n_i})+L_{l_i}(K_i)$. Although the degree of our secure-filter is larger than others solutions, our solution is secure and efficient in dynamics access control.


Nested Canalyzing Functions And Their Average Sensitivities

Abstract: In this paper, we obtain complete characterization for nested canalyzing functions (NCFs) by obtaining its unique algebraic normal form (polynomial form). We introduce a new concept, LAYER NUMBER for NCF. Based on this, we obtain explicit formulas for the the following important parameters: 1) Number of all the nested canalyzing functions, 2) Number of all the NCFs with given LAYER NUMBER, 3) Hamming weight of any NCF, 4) The activity number of any variable of any NCF, 5) The average sensitivity of any NCF. Based on these formulas, we show the activity number is greater for those variables in out layer and equal in the same layer. We show the average sensitivity attains minimal value when the NCF has only one layer. We also prove the average sensitivity for any NCF (No matter how many variables it has) is between 0 and 2. Hence, theoretically, we show why NCF is stable since a random Boolean function has average sensitivity $\frac{n}{2}$. Finally we conjecture that the NCF attain the maximal average sensitivity if it has the maximal LAYER NUMBER $n-1$. Hence, we guess the uniform upper bound for the average sensitivity of any NCF can be reduced to 4/3 which is tight.


Towards Designing a Biometric Measure for Enhancing ATM Security in Nigeria E-Banking System

Abstract: Security measures at banks can play a critical, contributory role in preventing attacks on customers. These measures are of paramount importance when considering vulnerabilities and causation in civil litigation. Banks must meet certain standards in order to ensure a safe and secure banking environment for their customers. This paper focuses on vulnerabilities and the increasing wave of criminal activities occurring at Automated Teller Machines (ATMs) where quick cash is the prime target for criminals rather than at banks themselves. A biometric measure as a means of enhancing the security has emerged from the discourse. Keywords-Security, ATM, Biometric, Crime.


Generating Exact- and Ranked Partially-Matched Answers to Questions in Advertisements

Abstract: Taking advantage of the Web, many advertisements (ads for short) websites, which aspire to increase client's transactions and thus profits, offer searching tools which allow users to (i) post keyword queries to capture their information needs or (ii) invoke form-based interfaces to create queries by selecting search options, such as a price range, filled-in entries, check boxes, or drop-down menus. These search mechanisms, however, are inadequate, since they cannot be used to specify a natural-language query with rich syntactic and semantic content, which can only be handled by a question answering (QA) system. Furthermore, existing ads websites are incapable of evaluating arbitrary Boolean queries or retrieving partiallymatched answers that might be of interest to the user whenever a user's search yields only a few or no results at all. In solving these problems, we present a QA system for ads, called CQAds, which (i) allows users to post a natural-language question Q for retrieving relevant ads, if they exist, (ii) identifies ads as answers that partially-match the requested information expressed in Q, if insufficient or no answers to Q can be retrieved, which are ordered using a similarity-ranking approach, and (iii) analyzes incomplete or ambiguous questions to perform the "best guess" in retrieving answers that "best match" the selection criteria specified in Q. CQAds is also equipped with a Boolean model to evaluate Boolean operators that are either explicitly or implicitly specified in Q, i.e., with or without Boolean operators specified by the users, respectively. CQAds is easy to use, scalable to all ads domains, and more powerful than search tools provided by existing ads websites, since its query-processing strategy retrieves relevant ads of higher quality and quantity. We have verified the accuracy of CQAds in retrieving ads on eight ads domains and compared it...[truncated].


Controlling Communication Field of Complex Networks by Transformation Method

Abstract: Controlling the global statuses of a network by its local dynamic parameters is an important issue, and it is difficult to obtain the direct solution for. The transformation method, which is originally used to control physical field by designing material parameters, is proposed to obtain the necessary local dynamic parameters when the global statuses of a network system are prescribed in a space. The feasibility of this transformation method is demonstrated and verified by two examples (a communication field cloak and a communication field bender) in the network system. It is shown that the global system state can be controlled by adjusting the local nodes dynamics with the transformation method. Simulation results also show that the transformation method provides a powerful, intuitive and direct way for the global statuses controlling of network systems.


A New Design for Array Multiplier with Trade off in Power and Area

Abstract: In this paper a low power and low area array multiplier with carry save adder is proposed. The proposed adder eliminates the final addition stage of the multiplier than the conventional parallel array multiplier. The conventional and proposed multiplier both are synthesized with 16-T full adder. Among Transmission Gate, Transmission Function Adder, 14-T, 16-T full adder shows energy efficiency. In the proposed 4x4 multiplier to add carry bits with out using Ripple Carry Adder (RCA) in the final stage, the carries given to the input of the next left column input. Due to this the proposed multiplier shows 56 less transistor count, then cause trade off in power and area. The proposed multiplier has shown 13.91% less power, 34.09% more speed and 59.91% less energy consumption for TSMC 0.18nm technology at a supply voltage 2.0V than the conventional multiplier.


Invariant texture analysis through Local Binary Patterns

Abstract: In many image processing applications, such as segmentation and classification, the selection of robust features descriptors is crucial to improve the discrimination capabilities in real world scenarios. In particular, it is well known that image textures constitute power visual cues for feature extraction and classification. In the past few years the local binary pattern (LBP) approach, a texture descriptor method proposed by Ojala et al., has gained increased acceptance due to its computational simplicity and more importantly for encoding a powerful signature for describing textures. However, the original algorithm presents some limitations such as noise sensitivity and its lack of rotational invariance which have led to many proposals or extensions in order to overcome such limitations. In this paper we performed a quantitative study of the Ojala's original LBP proposal together with other recently proposed LBP extensions in the presence of rotational, illumination and noisy changes. In the experiments we have considered two different databases: Brodatz and CUReT for different sizes of LBP masks. Experimental results demonstrated the effectiveness and robustness of the described texture descriptors for images that are subjected to geometric or radiometric changes.


Achieving Both Valid and Secure Logistic Regression Analysis on Aggregated Data from Different Private Sources

Abstract: Preserving the privacy of individual databases when carrying out statistical calculations has a long history in statistics and had been the focus of much recent attention in machine learning In this paper, we present a protocol for computing logistic regression when the data are held by separate parties without actually combining information sources by exploiting results from the literature on multi-party secure computation. We provide only the final result of the calculation compared with other methods that share intermediate values and thus present an opportunity for compromise of values in the combined database. Our paper has two themes: (1) the development of a secure protocol for computing the logistic parameters, and a demonstration of its performances in practice, and (2) and amended protocol that speeds up the computation of the logistic function. We illustrate the nature of the calculations and their accuracy using an extract of data from the Current Population Survey divided between two parties.


Matroids and Integrality Gaps for Hypergraphic Steiner Tree Relaxations

Abstract: Until recently, LP relaxations have played a limited role in the design of approximation algorithms for the Steiner tree problem. In 2010, Byrka et al. presented a ln(4)+epsilon approximation based on a hypergraphic LP relaxation, but surprisingly, their analysis does not provide a matching bound on the integrality gap. We take a fresh look at hypergraphic LP relaxations for the Steiner tree problem - one that heavily exploits methods and results from the theory of matroids and submodular functions - which leads to stronger integrality gaps, faster algorithms, and a variety of structural insights of independent interest. More precisely, we present a deterministic ln(4)+epsilon approximation that compares against the LP value and therefore proves a matching ln(4) upper bound on the integrality gap. Similarly to Byrka et al., we iteratively fix one component and update the LP solution. However, whereas they solve an LP at every iteration after contracting a component, we show how feasibility can be maintained by a greedy procedure on a well-chosen matroid. Apart from avoiding the expensive step of solving a hypergraphic LP at each iteration, our algorithm can be analyzed using a simple potential function. This gives an easy means to determine stronger approximation guarantees and integrality gaps when considering restricted graph topologies. In particular, this readily leads to a 73/60 bound on the integrality gap for quasi-bipartite graphs. For the case of quasi-bipartite graphs, we present a simple algorithm to transform an optimal solution to the bidirected cut relaxation to an optimal solution of the hypergraphic relaxation, leading to a fast 73/60 approximation for quasi-bipartite graphs. Furthermore, we show how the separation problem of the hypergraphic relaxation can be solved by computing maximum flows, providing a fast independence oracle for our matroids.


A Learning Framework for Self-Tuning Histograms

Abstract: In this paper, we consider the problem of estimating self-tuning histograms using query workloads. To this end, we propose a general learning theoretic formulation. Specifically, we use query feedback from a workload as training data to estimate a histogram with a small memory footprint that minimizes the expected error on future queries. Our formulation provides a framework in which different approaches can be studied and developed. We first study the simple class of equi-width histograms and present a learning algorithm, EquiHist, that is competitive in many settings. We also provide formal guarantees for equi-width histograms that highlight scenarios in which equi-width histograms can be expected to succeed or fail. We then go beyond equi-width histograms and present a novel learning algorithm, SpHist, for estimating general histograms. Here we use Haar wavelets to reduce the problem of learning histograms to that of learning a sparse vector. Both algorithms have multiple advantages over existing methods: 1) simple and scalable extensions to multi-dimensional data, 2) scalability with number of histogram buckets and size of query feedback, 3) natural extensions to incorporate new feedback and handle database updates. We demonstrate these advantages over the current state-of-the-art, ISOMER, through detailed experiments on real and synthetic data. In particular, we show that SpHist obtains up to 50% less error than ISOMER on real-world multi-dimensional datasets.


Les crashs sont rationnels

Abstract: As we show by using notions of equilibrium in infinite sequential games, crashes or financial escalations are rational for economic or environmental agents, who have a vision of an infinite world. This contradicts a picture of a self-regulating, wise and pacific economic world. In other words, in this context, equilibrium is not synonymous of stability. We try to draw, from this statement, methodological consequences and new ways of thinking, especially in economic game theory. Among those new paths, coinduction is the basis of our reasoning in infinite games.


A model of Cross Language Retrieval for IT domain papers through a map of ACM Computing Classification System

Abstract: This article presents a concept model, and the associated tool to help advanced learners to find adapted bibliography. The purpose is the use of an IT representation as educational research software for newcomers in research. We use an ontology based on the ACM's Computing Classification System in order to find scientific articles directly related to the new researcher's domain without any formal request. An ontology translation in French is automatically proposed and can be based on Web 2.0 enhanced by a community of users. A visualization and navigation model is proposed to make it more accessible and examples are given to show the interface of our tool: Ontology Navigator.


Query Optimization Using Genetic Algorithms in the Vector Space Model

Abstract: In information retrieval research; Genetic Algorithms (GA) can be used to find global solutions in many difficult problems. This study used different similarity measures (Dice, Inner Product) in the VSM, for each similarity measure we compared ten different GA approaches based on different fitness functions, different mutations and different crossover strategies to find the best strategy and fitness function that can be used when the data collection is the Arabic language. Our results shows that the GA approach which uses one-point crossover operator, point mutation and Inner Product similarity as a fitness function is the best IR system in VSM.


Improving the User Query for the Boolean Model Using Genetic Algorithms

Abstract: The Use of genetic algorithms in the Information retrieval (IR) area, especially in optimizing a user query in Arabic data collections is presented in this paper. Very little research has been carried out on Arabic text collections. Boolean model have been used in this research. To optimize the query using GA we used different fitness functions, different mutation strategies to find which is the best strategy and fitness function that can be used with Boolean model when the data collection is the Arabic language. Our results show that the best GA strategy for the Boolean model is the GA (M2, Precision) method.


Local Naive Bayes Nearest Neighbor for Image Classification

Abstract: We present Local Naive Bayes Nearest Neighbor, an improvement to the NBNN image classification algorithm that increases classification accuracy and improves its ability to scale to large numbers of object classes. The key observation is that only the classes represented in the local neighborhood of a descriptor contribute significantly and reliably to their posterior probability estimates. Instead of maintaining a separate search structure for each class, we merge all of the reference data together into one search structure, allowing quick identification of a descriptor's local neighborhood. We show an increase in classification accuracy when we ignore adjustments to the more distant classes and show that the run time grows with the log of the number of classes rather than linearly in the number of classes as did the original. This gives a 100 times speed-up over the original method on the Caltech 256 dataset. We also provide the first head-to-head comparison of NBNN against spatial pyramid methods using a common set of input features. We show that local NBNN outperforms all previous NBNN based methods and the original spatial pyramid model. However, we find that local NBNN, while competitive with, does not beat state-of-the-art spatial pyramid methods that use local soft assignment and max-pooling.


1-D Coordinate Based on Local Information for MAC and Routing Issues in WSNs

Abstract: More and more critical Wireless Sensor Networks (WSNs) applications are emerging. Those applications need reliability and respect of time constraints. The underlying mechanisms such as MAC and routing must handle such requirements. Our approach to the time constraint problem is to bound the hop-count between a node and the sink and the time it takes to do a hop so the end-to-end delay can be bounded and the communications are thus real-time. For reliability purpose we propose to select forwarder nodes depending on how they are connected in the direction of the sink. In order to be able to do so we need a coordinate (or a metric) that gives information on hop-count, that allows to strongly differentiate nodes and gives information on the connectivity of each node keeping in mind the intrinsic constraints of WSWs such as energy consumption, autonomy, etc. Due to the efficiency and scalability of greedy routing in WSNs and the financial cost of GPS chips, Virtual Coordinate Systems (VCSs) for WSNs have been proposed. A category of VCSs is based on the hop-count from the sink, this scheme leads to many nodes having the same coordinate. The main advantage of this system is that the hops number of a packet from a source to the sink is known. Nevertheless, it does not allow to differentiate the nodes with the same hop-count. In this report we propose a novel hop-count-based VCS which aims at classifying the nodes having the same hop-count depending on their connectivity and at differentiating nodes in a 2-hop neighborhood. Those properties make the coordinates, which also can be viewed as a local identifier, a very powerful metric which can be used in WSNs mechanisms.


Statistical Sign Language Machine Translation: from English written text to American Sign Language Gloss

Abstract: This works aims to design a statistical machine translation from English text to American Sign Language (ASL). The system is based on Moses tool with some modifications and the results are synthesized through a 3D avatar for interpretation. First, we translate the input text to gloss, a written form of ASL. Second, we pass the output to the WebSign Plug-in to play the sign. Contributions of this work are the use of a new couple of language English/ASL and an improvement of statistical machine translation based on string matching thanks to Jaro-distance.


Maximum Matching in Semi-Streaming with Few Passes

Abstract: In the semi-streaming model, an algorithm receives a stream of edges of a graph in arbitrary order and uses a memory of size $O(n \mbox{ polylog } n)$, where $n$ is the number of vertices of a graph. In this work, we present semi-streaming algorithms that perform one or two passes over the input stream for maximum matching with no restrictions on the input graph, and for the important special case of bipartite graphs that we refer to as maximum bipartite matching (MBM). The Greedy matching algorithm performs one pass over the input and outputs a $1/2$ approximation. Whether there is a better one-pass algorithm has been an open question since the appearance of the first paper on streaming algorithms for matching problems in 2005 [Feigenbaum et al., SODA 2005]. We make the following progress on this problem: In the one-pass setting, we show that there is a deterministic semi-streaming algorithm for MBM with expected approximation factor $1/2+0.005$, assuming that edges arrive one by one in (uniform) random order. We extend this algorithm to general graphs, and we obtain a $1/2+0.003$ approximation. In the two-pass setting, we do not require the random arrival order assumption (the edge stream is in arbitrary order). We present a simple randomized two-pass semi-streaming algorithm for MBM with expected approximation factor $1/2 + 0.019$. Furthermore, we discuss a more involved deterministic two-pass semi-streaming algorithm for MBM with approximation factor $1/2 + 0.019$ and a generalization of this algorithm to general graphs with approximation factor $1/2 + 0.0071$.


Digital Ecosystems: Ecosystem-Oriented Architectures

Abstract: We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.


A Framework for Automated and Certified Refinement Steps

Abstract: The refinement calculus provides a methodology for transforming an abstract specification into a concrete implementation, by following a succession of refinement rules. These rules have been mechanized in theorem-provers, thus providing a formal and rigorous way to prove that a given program refines another one. In a previous work, we have extended this mechanization for object-oriented programs, where the memory is represented as a graph, and we have integrated our approach within the rCOS tool, a model-driven software development tool providing a refinement language. Hence, for any refinement step, the tool automatically generates the corresponding proof obligations and the user can manually discharge them, using a provided library of refinement lemmas. In this work, we propose an approach to automate the search of possible refinement rules from a program to another, using the rewriting tool Maude. Each refinement rule in Maude is associated with the corresponding lemma in Isabelle, thus allowing the tool to automatically generate the Isabelle proof when a refinement rule can be automatically found. The user can add a new refinement rule by providing the corresponding Maude rule and Isabelle lemma.


Time and Parallelizability Results for Parity Games with Bounded Tree and DAG Width

Abstract: Parity games are a much researched class of games in NP intersect CoNP that are not known to be in P. Consequently, researchers have considered specialised algorithms for the case where certain graph parameters are small. In this paper, we study parity games on graphs with bounded treewidth, and graphs with bounded DAG width. We show that parity games with bounded DAG width can be solved in O(n^(k+3) k^(k + 2) (d + 1)^(3k + 2)) time, where n, k, and d are the size, treewidth, and number of priorities in the parity game. This is an improvement over the previous best algorithm, given by Berwanger et al., which runs in n^O(k^2) time. We also show that, if a tree decomposition is provided, then parity games with bounded treewidth can be solved in O(n k^(k + 5) (d + 1)^(3k + 5)) time. This improves over previous best algorithm, given by Obdrzalek, which runs in O(n d^(2(k+1)^2)) time. Our techniques can also be adapted to show that the problem of solving parity games with bounded treewidth lies in the complexity class NC^2, which is the class of problems that can be efficiently parallelized. This is in stark contrast to the general parity game problem, which is known to be P-hard, and thus unlikely to be contained in NC.


Simultaneous PQ-Ordering with Applications to Constrained Embedding Problems

Abstract: In this paper, we define and study the new problem Simultaneous PQ-Ordering. Its input consists of a set of PQ-trees, which represent sets of circular orders of their leaves, together with a set of child-parent relations between these PQ-trees, such that the leaves of the child form a subset of the leaves of the parent. Simultaneous PQ-Ordering asks whether orders of the leaves of each of the trees can be chosen simultaneously, that is, for every child-parent relation the order chosen for the parent is an extension of the order chosen for the child. We show that Simultaneous PQ-Ordering is NP-complete in general and that it is efficiently solvable for a special subset of instances, the 2-fixed instances. We then show that several constrained embedding problems can be formulated as such 2-fixed instances. In particular, we obtain a linear-time algorithm for Partially PQ-Constrained Planarity for biconnected graphs, a common generalization of two recently considered embedding problems, and a quadratic-time algorithm for Simultaneous Embedding with Fixed Edges for biconnected graphs with a connected intersection; formerly only the much more restricted case that the intersection is biconnected was known to be efficiently solvable. Both results can be extended to the case where the input graphs are not necessarily biconnected but have the property that each cutvertex is contained in at most two non-trivial blocks. This includes for example the case where both graphs have maximum degree 5. Moreover, we give an optimal linear-time algorithm for recognition of simultaneous interval graphs, improving upon a recent O(n^2 log n)-time algorithm due to Jampani and Lubiw and show that this can be used to also solve the problem of extending partial interval representations of graphs with n vertices and m edges in time O(n + m), improving a recent result of Klav\'ik et al.


Computing on Binary Strings

Abstract: Many problems in Computer Science can be abstracted to the following question: given a set of objects and rules respectively, which new objects can be produced? In the paper, we consider a succinct version of the question: given a set of binary strings and several operations like conjunction and disjunction, which new binary strings can be generated? Although it is a fundamental problem, to the best of our knowledge, the problem hasn't been studied yet. In this paper, an O(m^2n) algorithm is presented to determine whether a string s is representable by a set W, where n is the number of strings in W and each string has the same length m. However, looking for the minimum subset from a set to represent a given string is shown to be NP-hard. Also, finding the smallest subset from a set to represent each string in the original set is NP-hard. We establishes inapproximability results and approximation algorithms for them. In addition, we prove that counting the number of strings representable is #P-complete. We then explore how the problems change when the operator negation is available. For example, if the operator negation can be used, the number is some power of 2. This difference maybe help us understand the problem more profoundly.


Ontological Queries: Rewriting and Optimization (Extended Version)

Abstract: Ontological queries are evaluated against an ontology rather than directly on a database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent query against the underlying relational database. The focus here is on soundness and completeness. We review previous results and present a new rewriting algorithm for rather general types of ontological constraints. In particular, we show how a conjunctive query against an ontology can be compiled into a union of conjunctive queries against the underlying database. Ontological query optimization, in this context, attempts to improve this process so to produce possibly small and cost-effective UCQ rewritings for an input query. We review existing optimization methods, and propose an effective new method that works for linear Datalog+/-, a class of Datalog-based rules that encompasses well-known description logics of the DL-Lite family.


Domain Theory and the Logic of Observable Properties

Abstract: The mathematical framework of Stone duality is used to synthesize a number of hitherto separate developments in Theoretical Computer Science: - Domain Theory, the mathematical theory of computation introduced by Scott as a foundation for denotational semantics. - The theory of concurrency and systems behaviour developed by Milner, Hennessy et al. based on operational semantics. - Logics of programs. Stone duality provides a junction between semantics (spaces of points = denotations of computational processes) and logics (lattices of properties of processes). Moreover, the underlying logic is geometric, which can be computationally interpreted as the logic of observable properties---i.e. properties which can be determined to hold of a process on the basis of a finite amount of information about its execution. These ideas lead to the following programme: 1. A metalanguage is introduced, comprising - types = universes of discourse for various computational situations. - terms = programs = syntactic intensions for models or points. 2. A standard denotational interpretation of the metalanguage is given, assigning domains to types and domain elements to terms. 3. The metalanguage is also given a {\em logical} interpretation, in which types are interpreted as propositional theories and terms are interpreted via a program logic, which axiomatizes the properties they satisfy. 4. The two interpretations are related by showing that they are Stone duals of each other. Hence, semantics and logic are guaranteed to be in harmony with each other, and in fact each determines the other up to isomorphism. This opens the way to a whole range of applications. Given a denotational description of a computational situation in our meta-language, we can turn the handle to obtain a logic for that situation.


Information Spreading in Dynamic Networks

Abstract: We study the fundamental problem of information spreading (also known as gossip) in dynamic networks. In gossip, or more generally, $k$-gossip, there are $k$ pieces of information (or tokens) that are initially present in some nodes and the problem is to disseminate the $k$ tokens to all nodes. The goal is to accomplish the task in as few rounds of distributed computation as possible. The problem is especially challenging in dynamic networks where the network topology can change from round to round and can be controlled by an on-line adversary. The focus of this paper is on the power of token-forwarding algorithms, which do not manipulate tokens in any way other than storing and forwarding them. We first consider a worst-case adversarial model first studied by Kuhn, Lynch, and Oshman~\cite{kuhn+lo:dynamic} in which the communication links for each round are chosen by an adversary, and nodes do not know who their neighbors for the current round are before they broadcast their messages. Our main result is an $\Omega(nk/\log n)$ lower bound on the number of rounds needed for any deterministic token-forwarding algorithm to solve $k$-gossip. This resolves an open problem raised in~\cite{kuhn+lo:dynamic}, improving their lower bound of $\Omega(n \log k)$, and matching their upper bound of $O(nk)$ to within a logarithmic factor. We next show that token-forwarding algorithms can achieve subquadratic time in the offline version of the problem where the adversary has to commit all the topology changes in advance at the beginning of the computation, and present two polynomial-time offline token-forwarding algorithms. Our results are a step towards understanding the power and limitation of token-forwarding algorithms in dynamic networks.


Reliable Communication in Wireless Body Area Sensor Network for Health Monitoring

Abstract: Now days, interests in the application of Wireless Body Area Network (WBAN) have grown considerably. A number of tiny wireless sensors, strategically placed on the human body, create a wireless body area network that can monitor various vital signs, providing real-time feedback to the user and medical personnel. This communication needs to be energy efficient and highly reliable while keeping delays low. In this paper we present hardware and software architecture for BAN and also we offer reliable communication and data aggregation.


Grammatical Relations of Myanmar Sentences Augmented by Transformation-Based Learning of Function Tagging

Abstract: In this paper we describe function tagging using Transformation Based Learning (TBL) for Myanmar that is a method of extensions to the previous statistics-based function tagger. Contextual and lexical rules (developed using TBL) were critical in achieving good results. First, we describe a method for expressing lexical relations in function tagging that statistical function tagging are currently unable to express. Function tagging is the preprocessing step to show grammatical relations of the sentences. Then we use the context free grammar technique to clarify the grammatical relations in Myanmar sentences or to output the parse trees. The grammatical relations are the functional structure of a language. They rely very much on the function tag of the tokens. We augment the grammatical relations of Myanmar sentences with transformation-based learning of function tagging.


Publish-Subscribe Systems via Gossip: a Study based on Complex Networks

Abstract: This paper analyzes the adoption of unstructured P2P overlay networks to build publish-subscribe systems. We consider a very simple distributed communication protocol, based on gossip and on the local knowledge each node has about subscriptions made by its neighbours. In particular, upon reception (or generation) of a novel event, a node sends it to those neighbours whose subscriptions match that event. Moreover, the node gossips the event to its "non-interested" neighbours, so that the event can be spread through the overlay. A mathematical analysis is provided to estimate the number of nodes receiving the event, based on the network topology, the amount of subscribers and the gossip probability. These outcomes are compared to those obtained via simulation. Results show even when the amount of subscribers represents a very small (yet non-negligible) portion of network nodes, by tuning the gossip probability the event can percolate through the overlay. Hence, the use of unstructured networks. coupled with simple dissemination protocols, represents a viable approach to build peer-to-peer publish-subscribe applications.


Simple and Effective Dynamic Provisioning for Power-Proportional Data Centers

Abstract: Energy consumption represents a significant cost in data center operation. A large fraction of the energy, however, is used to power idle servers when the workload is low. Dynamic provisioning techniques aim at saving this portion of the energy, by turning off unnecessary servers. In this paper, we explore how much performance gain can knowing future workload information brings to dynamic provisioning. In particular, we study the dynamic provisioning problem under the cost model that a running server consumes a fixed amount energy per unit time, and develop online solutions with and without future workload information available. We first reveal an elegant structure of the off-line dynamic provisioning problem, which allows us to characterize and achieve the optimal solution in a {}"divide-and-conquer" manner. We then exploit this insight to design three online algorithms with competitive ratios $2-\alpha$, $(e-\alpha)/(e-1)\approx1.58-\alpha/(e-1)$ and $e/(e-1+\alpha)$, respectively, where $0\leq\alpha\leq1$ is the fraction of a critical window in which future workload information is available. A fundamental observation is that \emph{future workload information beyond the critical window will not} \emph{improve dynamic provisioning performance}. Our algorithms are decentralized and are simple to implement. We demonstrate their effectiveness in simulations using real-world traces. We also compare their performance with state-of-the-art solutions.


Label Ranking with Abstention: Predicting Partial Orders by Thresholding Probability Distributions (Extended Abstract)

Abstract: We consider an extension of the setting of label ranking, in which the learner is allowed to make predictions in the form of partial instead of total orders. Predictions of that kind are interpreted as a partial abstention: If the learner is not sufficiently certain regarding the relative order of two alternatives, it may abstain from this decision and instead declare these alternatives as being incomparable. We propose a new method for learning to predict partial orders that improves on an existing approach, both theoretically and empirically. Our method is based on the idea of thresholding the probabilities of pairwise preferences between labels as induced by a predicted (parameterized) probability distribution on the set of all rankings.


On the Complexity of Approximate Sum of Sorted List

Abstract: We consider the complexity for computing the approximate sum $a_1+a_2+...+a_n$ of a sorted list of numbers $a_1\le a_2\le ...\le a_n$. We show an algorithm that computes an $(1+\epsilon)$-approximation for the sum of a sorted list of nonnegative numbers in an $O({1\over \epsilon}\min(\log n, {\log ({x_{max}\over x_{min}})})\cdot (\log {1\over \epsilon}+\log\log n))$ time, where $x_{max}$ and $x_{min}$ are the largest and the least positive elements of the input list, respectively. We prove a lower bound $\Omega(\min(\log n,\log ({x_{max}\over x_{min}}))$ time for every O(1)-approximation algorithm for the sum of a sorted list of nonnegative elements. We also show that there is no sublinear time approximation algorithm for the sum of a sorted list that contains at least one negative number.


The interval ordering problem

Abstract: For a given set of intervals on the real line, we consider the problem of ordering the intervals with the goal of minimizing an objective function that depends on the exposed interval pieces (that is, the pieces that are not covered by earlier intervals in the ordering). This problem is motivated by an application in molecular biology that concerns the determination of the structure of the backbone of a protein. We present polynomial-time algorithms for several natural special cases of the problem that cover the situation where the interval boundaries are agreeably ordered and the situation where the interval set is laminar. Also the bottleneck variant of the problem is shown to be solvable in polynomial time. Finally we prove that the general problem is NP-hard, and that the existence of a constant-factor-approximation algorithm is unlikely.


Analysis of Kak's Quantum Cryptography Protocol from the Perspective of Source Strength

Abstract: This paper analyzes the performance of Kak's quantum cryptography protocol when intensity monitoring is used to detect the presence of Eve during transmission. Some difficulties related to interception to obtain useful data from the transmission are discussed. The analysis shows the resilience of the protocol towards the man-in-the-middle attack.


On the Footsteps to Generalized Tower of Hanoi Strategy

Abstract: In this paper, our aim is to prove that our recursive algorithm to solve the "Reve's puzzle" (four- peg Tower of Hanoi) is the optimal solution according to minimum number of moves. Here we used Frame's five step algorithm to solve the "Reve's puzzle", and proved its optimality analyzing all possible strategies to solve the problem. Minimum number of moves is important because no one ever proved that the "presumed optimal" solution, the Frame-Stewart algorithm, always gives the minimum number of moves. The basis of our proof is Bifurcation Theorem. In fact, we can solve generalized "Tower of Hanoi" puzzle for any pegs (three or more pegs) using Bifurcation Theorem. But our scope is limited to the "Reve's puzzle" in this literature, but lately, we would discuss how we can reach our final destination, the Generalized Tower of Hanoi Strategy. Another important point is that we have used only induction method to prove all the results throughout this literature. Moreover, some simple theorems and lemmas are derived through logical perspective or consequence of induction method. Lastly, we will try to answer about uniqueness of solution of this famous puzzle.


How big is BCI fragment of BCK logic

Abstract: We investigate quantitative properties of BCI and BCK logics. The first part of the paper compares the number of formulas provable in BCI versus BCK logics. We consider formulas built on implication and a fixed set of $k$ variables. We investigate the proportion between the number of such formulas of a given length $n$ provable in BCI logic against the number of formulas of length $n$ provable in richer BCK logic. We examine an asymptotic behavior of this fraction when length $n$ of formulas tends to infinity. This limit gives a probability measure that randomly chosen BCK formula is also provable in BCI. We prove that this probability tends to zero as the number of variables tends to infinity. The second part of the paper is devoted to the number of lambda terms representing proofs of BCI and BCK logics. We build a proportion between number of such proofs of the same length $n$ and we investigate asymptotic behavior of this proportion when length of proofs tends to infinity. We demonstrate that with probability 0 a randomly chosen BCK proof is also a proof of a BCI formula.


Analysis and improvement of a strongly secure certificateless key exchange protocol without pairing

Abstract: Recently, Yang and Tan proposed a certificateless key exchange protocol without pairing, and claimed their scheme satisfies forward secrecy, which means no adversary could derive an already-established session key unless the full user secret keys (including a private key and an ephemeral secret key) of both communication parties are compromised. However, in this paper, we point out their protocol is actually not secure as claimed by presenting an attack launched by an adversary who has learned the private key of one party and the ephemeral secret key of the other, but not the full user secret keys of both parties. Furthermore, to make up this flaw, we also provide an improved protocol in which the private key and the ephemeral secret key are closely intertwined with each other for generating the session key, thus above attack can be efficiently resisted.


A Biomimetic Model of the Outer Plexiform Layer by Incorporating Memristive Devices

Abstract: In this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices. The architecture of the proposed network is based on the organisation and functioning of the outer plexiform layer (OPL) in the vertebrate retina. We demonstrate that memristive devices are indeed a valuable building block for neuromorphic architectures, as their highly non-linear and adaptive response could be exploited for establishing ultra-dense networks with similar dynamics to their biological counterparts. We particularly show that hexagonal memristive grids can be employed for faithfully emulating the smoothing-effect occurring at the OPL for enhancing the dynamic range of the system. In addition, we employ a memristor-based thresholding scheme for detecting the edges of grayscale images, while the proposed system is also evaluated for its adaptation and fault tolerance capacity against different light or noise conditions as well as distinct device yields.


Instance-based XML data binding for mobile devices

Abstract: XML and XML Schema are widely used in different domains for the definition of standards that enhance the interoperability between parts exchanging information through the Internet. The size and complexity of some standards, and their associated schemas, have been growing with time as new use case scenarios and data models are added to them. The common approach to deal with the complexity of producing XML processing code based on these schemas is the use of XML data binding generators. Unfortunately, these tools do not always produce code that ?ts the limitations of resource-constrained devices, such as mobile phones, in the presence of large schemas. In this paper we present Instance-based XML data binding, an approach to produce compact application-specific XML processing code for mobile devices. The approach utilises information extracted from a set of XML documents about how the application make use of the schemas.


Approximating Low-Dimensional Coverage Problems

Abstract: We study the complexity of the maximum coverage problem, restricted to set systems of bounded VC-dimension. Our main result is a fixed-parameter tractable approximation scheme: an algorithm that outputs a $(1-\eps)$-approximation to the maximum-cardinality union of $k$ sets, in running time $O(f(\eps,k,d)\cdot poly(n))$ where $n$ is the problem size, $d$ is the VC-dimension of the set system, and $f(\eps,k,d)$ is exponential in $(kd/\eps)^c$ for some constant $c$. We complement this positive result by showing that the function $f(\eps,k,d)$ in the running-time bound cannot be replaced by a function depending only on $(\eps,d)$ or on $(k,d)$, under standard complexity assumptions. We also present an improved upper bound on the approximation ratio of the greedy algorithm in special cases of the problem, including when the sets have bounded cardinality and when they are two-dimensional halfspaces. Complementing these positive results, we show that when the sets are four-dimensional halfspaces neither the greedy algorithm nor local search is capable of improving the worst-case approximation ratio of $1-1/e$ that the greedy algorithm achieves on arbitrary instances of maximum coverage.


On the Expected Complexity of Voronoi Diagrams on Terrains

Abstract: We investigate the combinatorial complexity of geodesic Voronoi diagrams on polyhedral terrains using a probabilistic analysis. Aronov etal [ABT08] prove that, if one makes certain realistic input assumptions on the terrain, this complexity is \Theta(n + m \sqrt n) in the worst case, where n denotes the number of triangles that define the terrain and m denotes the number of Voronoi sites. We prove that under a relaxed set of assumptions the Voronoi diagram has expected complexity O(n+m), given that the sites have a uniform distribution on the domain of the terrain(or the surface of the terrain). Furthermore, we present a worst-case construction of a terrain which implies a lower bound of Vmega(n m2/3) on the expected worst-case complexity if these assumptions on the terrain are dropped. As an additional result, we can show that the expected fatness of a cell in a random planar Voronoi diagram is bounded by a constant.


The Traveling Salesman Problem: Low-Dimensionality Implies a Polynomial Time Approximation Scheme

Abstract: The Traveling Salesman Problem (TSP) is among the most famous NP-hard optimization problems. We design for this problem a randomized polynomial-time algorithm that computes a (1+eps)-approximation to the optimal tour, for any fixed eps>0, in TSP instances that form an arbitrary metric space with bounded intrinsic dimension. The celebrated results of Arora (A-98) and Mitchell (M-99) prove that the above result holds in the special case of TSP in a fixed-dimensional Euclidean space. Thus, our algorithm demonstrates that the algorithmic tractability of metric TSP depends on the dimensionality of the space and not on its specific geometry. This result resolves a problem that has been open since the quasi-polynomial time algorithm of Talwar (T-04).


Quantum Cost Efficient Reversible BCD Adder for Nanotechnology Based Systems

Abstract: Reversible logic allows low power dissipating circuit design and founds its application in cryptography, digital signal processing, quantum and optical information processing. This paper presents a novel quantum cost efficient reversible BCD adder for nanotechnology based systems using PFAG gate. It has been demonstrated that the proposed design offers less hardware complexity and requires minimum number of garbage outputs than the existing counterparts. The remarkable property of the proposed designs is that its quantum realization is given in NMR technology.


A New Approach to Incremental Cycle Detection and Related Problems

Abstract: We consider the problem of detecting a cycle in a directed graph that grows by arc insertions, and the related problems of maintaining a topological order and the strong components of such a graph. For these problems, we give two algorithms, one suited to sparse graphs, and the other to dense graphs. The former takes the minimum of O(m^{3/2}) and O(mn^{2/3}) time to insert m arcs into an n-vertex graph; the latter takes O(n^2 log(n)) time. Our sparse algorithm is considerably simpler than a previous O(m^{3/2})-time algorithm; it is also faster on graphs of sufficient density. The time bound of our dense algorithm beats the previously best time bound of O(n^{5/2}) for dense graphs. Our algorithms rely for their efficiency on topologically ordered vertex numberings; bounds on the size of the numbers give bound on running times.


Scaling algorithms for approximate and exact maximum weight matching

Abstract: The {\em maximum cardinality} and {\em maximum weight matching} problems can be solved in time $\tilde{O}(m\sqrt{n})$, a bound that has resisted improvement despite decades of research. (Here $m$ and $n$ are the number of edges and vertices.) In this article we demonstrate that this "$m\sqrt{n}$ barrier" is extremely fragile, in the following sense. For any $\epsilon>0$, we give an algorithm that computes a $(1-\epsilon)$-approximate maximum weight matching in $O(m\epsilon^{-1}\log\epsilon^{-1})$ time, that is, optimal {\em linear time} for any fixed $\epsilon$. Our algorithm is dramatically simpler than the best exact maximum weight matching algorithms on general graphs and should be appealing in all applications that can tolerate a negligible relative error. Our second contribution is a new {\em exact} maximum weight matching algorithm for integer-weighted bipartite graphs that runs in time $O(m\sqrt{n}\log N)$. This improves on the $O(Nm\sqrt{n})$-time and $O(m\sqrt{n}\log(nN))$-time algorithms known since the mid 1980s, for $1\ll \log N \ll \log n$. Here $N$ is the maximum integer edge weight.


Strong Equivalence of Qualitative Optimization Problems

Abstract: We introduce the framework of qualitative optimization problems (or, simply, optimization problems) to represent preference theories. The formalism uses separate modules to describe the space of outcomes to be compared (the generator) and the preferences on outcomes (the selector). We consider two types of optimization problems. They differ in the way the generator, which we model by a propositional theory, is interpreted: by the standard propositional logic semantics, and by the equilibrium-model (answer-set) semantics. Under the latter interpretation of generators, optimization problems directly generalize answer-set optimization programs proposed previously. We study strong equivalence of optimization problems, which guarantees their interchangeability within any larger context. We characterize several versions of strong equivalence obtained by restricting the class of optimization problems that can be used as extensions and establish the complexity of associated reasoning tasks. Understanding strong equivalence is essential for modular representation of optimization problems and rewriting techniques to simplify them without changing their inherent properties.


An Approach to Log Management: Prototyping a Design of Agent for Log Harvesting

Abstract: This paper describes a work in progress implementing a solution for harvesting and transporting information logs from network devices in a e-science environment. The system is composed for servers, agents, active devices and a transporting protocol. This document describes the state of development of agents. Agents capture logs from devices, normalize, reduce and cataloged them by using metadata. Once all these processes are done, they transmit the cataloged data by using Transportation Protocol to a warehouse server. Also an agent use orchestration parameters to transmit modified logs to a data warehouse server. These parameters can be received from orchestration applications such as Taverna. The operation of the agents and the communication protocol solve some of the deficiencies of traditional logs management protocols. Finally, we show some test realized over the new prototype.


Clustering under Perturbation Resilience

Abstract: Motivated by the fact that distances between data points in many real-world clustering instances are often based on heuristic measures, Bilu and Linial~\cite{BL} proposed analyzing objective based clustering problems under the assumption that the optimum clustering to the objective is preserved under small multiplicative perturbations to distances between points. The hope is that by exploiting the structure in such instances, one can overcome worst case hardness results. In this paper, we provide several results within this framework. For center-based objectives, we present an algorithm that can optimally cluster instances resilient to perturbations of factor $(1 + \sqrt{2})$, solving an open problem of Awasthi et al.~\cite{ABS10}. For $k$-median, a center-based objective of special interest, we additionally give algorithms for a more relaxed assumption in which we allow the optimal solution to change in a small $\epsilon$ fraction of the points after perturbation. We give the first bounds known for $k$-median under this more realistic and more general assumption. We also provide positive results for min-sum clustering which is typically a harder objective than center-based objectives from approximability standpoint. Our algorithms are based on new linkage criteria that may be of independent interest. Additionally, we give sublinear-time algorithms, showing algorithms that can return an implicit clustering from only access to a small random sample.


Performance Study on Image Encryption Schemes

Abstract: Image applications have been increasing in recent years.Encryption is used to provide the security needed for image applications. In this paper, we classify various image encryption schemes and analyze them with respect to various parameters like tunability, visual degradation, compression friendliness,format compliance, encryption ratio, speed, and cryptographic security.


Performance engineering for the Lattice Boltzmann method on GPGPUs: Architectural requirements and performance results

Abstract: GPUs offer several times the floating point performance and memory bandwidth of current standard two socket CPU servers, e.g. NVIDIA C2070 vs. Intel Xeon Westmere X5650. The lattice Boltzmann method has been established as a flow solver in recent years and was one of the first flow solvers to be successfully ported and that performs well on GPUs. We demonstrate advanced optimization strategies for a D3Q19 lattice Boltzmann based incompressible flow solver for GPGPUs and CPUs based on NVIDIA CUDA and OpenCL. Since the implemented algorithm is limited by memory bandwidth, we concentrate on improving memory access. Basic data layout issues for optimal data access are explained and discussed. Furthermore, the algorithmic steps are rearranged to improve scattered access of the GPU memory. The importance of occupancy is discussed as well as optimization strategies to improve overall concurrency. We arrive at a well-optimized GPU kernel, which is integrated into a larger framework that can handle single phase fluid flow simulations as well as particle-laden flows. Our 3D LBM GPU implementation reaches up to 650 MLUPS in single precision and 290 MLUPS in double precision on an NVIDIA Tesla C2070.


I/O efficient bisimulation partitioning on very large directed acyclic graphs

Abstract: In this paper we introduce the first efficient external-memory algorithm to compute the bisimilarity equivalence classes of a directed acyclic graph (DAG). DAGs are commonly used to model data in a wide variety of practical applications, ranging from XML documents and data provenance models, to web taxonomies and scientific workflows. In the study of efficient reasoning over massive graphs, the notion of node bisimilarity plays a central role. For example, grouping together bisimilar nodes in an XML data set is the first step in many sophisticated approaches to building indexing data structures for efficient XPath query evaluation. To date, however, only internal-memory bisimulation algorithms have been investigated. As the size of real-world DAG data sets often exceeds available main memory, storage in external memory becomes necessary. Hence, there is a practical need for an efficient approach to computing bisimulation in external memory. Our general algorithm has a worst-case IO-complexity of O(Sort(|N| + |E|)), where |N| and |E| are the numbers of nodes and edges, resp., in the data graph and Sort(n) is the number of accesses to external memory needed to sort an input of size n. We also study specializations of this algorithm to common variations of bisimulation for tree-structured XML data sets. We empirically verify efficient performance of the algorithms on graphs and XML documents having billions of nodes and edges, and find that the algorithms can process such graphs efficiently even when very limited internal memory is available. The proposed algorithms are simple enough for practical implementation and use, and open the door for further study of external-memory bisimulation algorithms. To this end, the full open-source C++ implementation has been made freely available.


Extending Object-Oriented Languages by Declarative Specifications of Complex Objects using Answer-Set Programming

Abstract: Many applications require complexly structured data objects. Developing new or adapting existing algorithmic solutions for creating such objects can be a non-trivial and costly task if the considered objects are subject to different application-specific constraints. Often, however, it is comparatively easy to declaratively describe the required objects. In this paper, we propose to use answer-set programming (ASP)---a well-established declarative programming paradigm from the area of artificial intelligence---for instantiating objects in standard object-oriented programming languages. In particular, we extend Java with declarative specifications from which the required objects can be automatically generated using available ASP solver technology.


Randomness Quality of CI Chaotic Generators: Applications to Internet Security

Abstract: Due to the rapid development of the Internet in recent years, the need to find new tools to reinforce trust and security through the Internet has became a major concern. The discovery of new pseudo-random number generators with a strong level of security is thus becoming a hot topic, because numerous cryptosystems and data hiding schemes are directly dependent on the quality of these generators. At the conference Internet`09, we have described a generator based on chaotic iterations, which behaves chaotically as defined by Devaney. In this paper, the proposal is to improve the speed and the security of this generator, to make its use more relevant in the Internet security context. To do so, a comparative study between various generators is carried out and statistical results are given. Finally, an application in the information hiding framework is presented, to give an illustrative example of the use of such a generator in the Internet security field.


Class of Trustworthy Pseudo-Random Number Generators

Abstract: With the widespread use of communication technologies, cryptosystems are therefore critical to guarantee security over open networks as the Internet. Pseudo-random number generators (PRNGs) are fundamental in cryptosystems and information hiding schemes. One of the existing chaos-based PRNGs is using chaotic iterations schemes. In prior literature, the iterate function is just the vectorial boolean negation. In this paper, we propose a method using Graph with strongly connected components as a selection criterion for chaotic iterate function. In order to face the challenge of using the proposed chaotic iterate functions in PRNG, these PRNGs are subjected to a statistical battery of tests, which is the well-known NIST in the area of cryptography.


On the design of a family of CI pseudo-random number generators

Abstract: Chaos and its applications in the field of secure communications have attracted a lot of attention. Chaos-based pseudo-random number generators are critical to guarantee security over open networks as the Internet. We have previously demonstrated that it is possible to define such generators with good statistical properties by using a tool called "chaotic iterations", which depends on an iteration function. An approach to find update functions such that the associated generator presents a random-like and chaotic behavior is proposed in this research work. To do so, we use the vectorial Boolean negation as a prototype and explain how to modify this iteration function without deflating the good properties of the associated generator. Simulation results and basic security analysis are then presented to evaluate the randomness of this new family of generators.


Two Squares of Opposition: for Analytic and Synthetic Propositions

Abstract: In the paper I prove that there are two squares of opposition. The unconventional one is built up for synthetic propositions. There a, i are contrary, a, o (resp. e, i) are contradictory, e, o are subcontrary, a, e (resp. i, o) are said to stand in the subalternation.


Small Jump with Negation-UTM Trampoline

Abstract: This paper divide some complexity class by using fixpoint and fixpointless area of Decidable Universal Turing Machine (UTM). Decidable Deterministic Turing Machine (DTM) have fixpointless combinator that add no extra resources (like Negation), but UTM makes some fixpoint in the combinator. This means that we can jump out of the fixpointless combinator system by making more complex problem from diagonalisation argument of UTM. As a concrete example, we proof L is not P . We can make Polynomial time UTM that emulate all Logarithm space DTM (LDTM). LDTM set close under Negation, therefore UTM does not close under LDTM set. (We can proof this theorem like halting problem and time/space hierarchy theorem, and also we can extend this proof to divide time/space limited DTM set.) In the same way, we proof P is not NP. These are new hierarchy that use UTM and Negation.


The Web economy: goods, users, models and policies

Abstract: Web emerged as an antidote to the rapidly increasing quantity of accumulated knowledge and become successful because it facilitates massive participation and communication with minimum costs. Today, its enormous impact, scale and dynamism in time and space make very difficult (and sometimes impossible) to measure and anticipate the effects in human society. In addition to that, we demand from the Web to be fast, secure, reliable, all-inclusive and trustworthy in any transaction. The scope of the present article is to review a part of the Web economy literature that will help us to identify its major participants and their functions. The goal is to understand how the Web economy differs from the traditional setting and what implications have these differences. Secondarily, we attempt to establish a minimal common understanding about the incentives and properties of the Web economy. In this direction the concept of Web Goods and a new classification of Web Users are introduced and analyzed This article, is not, by any means, a thorough review of the economic literature related to the Web. We focus only on its relevant part that models the Web as a standalone economic artifact with native functionality and processes.


Worst-Case Optimal Priority Queues via Extended Regular Counters

Abstract: We consider the classical problem of representing a collection of priority queues under the operations \Findmin{}, \Insert{}, \Decrease{}, \Meld{}, \Delete{}, and \Deletemin{}. In the comparison-based model, if the first four operations are to be supported in constant time, the last two operations must take at least logarithmic time. Brodal showed that his worst-case efficient priority queues achieve these worst-case bounds. Unfortunately, this data structure is involved and the time bounds hide large constants. We describe a new variant of the worst-case efficient priority queues that relies on extended regular counters and provides the same asymptotic time and space bounds as the original. Due to the conceptual separation of the operations on regular counters and all other operations, our data structure is simpler and easier to describe and understand. Also, the constants in the time and space bounds are smaller. In addition, we give an implementation of our structure on a pointer machine. For our pointer-machine implementation, \Decrease{} and \Meld{} are asymptotically slower and require $O(\lg\lg{n})$ worst-case time, where $n$ denotes the number of elements stored in the resulting priority queue.


Yahtzee: An Anonymized Group Level Matching Procedure

Abstract: Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources in order to conduct their research. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects evermore important. However, strict privacy procedures can make joining diverse sources of data that contain information about specific individual behaviors difficult. In this paper we present a procedure to keep information about specific individuals from being "leaked" or shared in either direction between two sources of data. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as expected theoretically when we apply it to data from Facebook and public voter records.


What makes normalized weighted satisfiability tractable

Abstract: We consider the weighted antimonotone and the weighted monotone satisfiability problems on normalized circuits of depth at most $t \geq 2$, abbreviated {\sc wsat$^-[t]$} and {\sc wsat$^+[t]$}, respectively. These problems model the weighted satisfiability of antimonotone and monotone propositional formulas (including weighted anitmonoone/monotone {\sc cnf-sat}) in a natural way, and serve as the canonical problems in the definition of the parameterized complexity hierarchy. We characterize the parameterized complexity of {\sc wsat$^-[t]$} and {\sc wsat$^+[t]$} with respect to the genus of the circuit. For {\sc wsat$^-[t]$}, which is $W[t]$-complete for odd $t$ and $W[t-1]$-complete for even $t$, the characterization is precise: We show that {\sc wsat$^-[t]$} is fixed-parameter tractable (FPT) if the genus of the circuit is $n^{o(1)}$ ($n$ is the number of the variables in the circuit), and that it has the same $W$-hardness as the general {\sc wsat$^-[t]$} problem (i.e., with no restriction on the genus) if the genus is $n^{O(1)}$. For {\sc wsat$^+[2]$} (i.e., weighted monotone {\sc cnf-sat}), which is $W[2]$-complete, the characterization is also precise: We show that {\sc wsat$^+[2]$} is FPT if the genus is $n^{o(1)}$ and $W[2]$-complete if the genus is $n^{O(1)}$. For {\sc wsat$^+[t]$} where $t > 2$, which is $W[t]$-complete for even $t$ and $W[t-1]$-complete for odd $t$, we show that it is FPT if the genus is $O(\sqrt{\log{n}})$, and that it has the same $W$-hardness as the general {\sc wsat$^+[t]$} problem if the genus is $n^{O(1)}$.


Stabilization of Branching Queueing Networks

Abstract: Queueing networks are gaining attraction for the performance analysis of parallel computer systems. A Jackson network is a set of interconnected servers, where the completion of a job at server i may result in the creation of a new job for server j. We propose to extend Jackson networks by "branching" and by "control" features. Both extensions are new and substantially expand the modelling power of Jackson networks. On the other hand, the extensions raise computational questions, particularly concerning the stability of the networks, i.e, the ergodicity of the underlying Markov chain. We show for our extended model that it is decidable in polynomial time if there exists a controller that achieves stability. Moreover, if such a controller exists, one can efficiently compute a static randomized controller which stabilizes the network in a very strong sense; in particular, all moments of the queue sizes are finite.


Non-Malleable Extractors, Two-Source Extractors and Privacy Amplification

Abstract: Dodis and Wichs introduced the notion of a non-malleable extractor to study the problem of privacy amplification with an active adversary. A non-malleable extractor is a much stronger version of a strong extractor. Previously, there are only two known constructions of non-malleable extractors. Both constructions only work for (n, k)-sources with k>n/2. Interestingly, both constructions are also two-source extractors. In this paper, we present a strong connection between non-malleable extractors and two-source extractors. The first part of the connection shows that non-malleable extractors can be used to construct two-source extractors. With appropriate parameters the resulted two-source extractor beats the best known construction of two-source extractors. This partially explains why previous constructions of non-malleable extractors only work for sources with entropy rate >1/2, and why explicit non-malleable extractors for small min-entropy may be hard to get. The second part of the connection shows that certain two-source extractors can be used to construct non-malleable extractors. Using this connection, we obtain the first construction of non-malleable extractors for k < n/2. Specifically, we give an unconditional construction for min-entropy k=(1/2-\delta)n for some constant \delta>0, and a conditional (semi-explicit) construction that can potentially achieve k=\alpha n for any constant \alpha>0. Finally, despite the lack of explicit non-malleable extractors for arbitrarily linear entropy, we give the first 2-round privacy amplification protocol with asymptotically optimal entropy loss and communication complexity for (n, k) sources with k=\alpha n for any constant \alpha>0. This dramatically improves previous results and answers an open problem in \cite{DLWZ11}.


Using Quasigroups for Generating Pseudorandom Numbers

Abstract: This paper presents an algorithm for generating pseudorandom numbers using quasigroups. Random numbers have several applications in the area of secure communication. The proposed algorithm uses a matrix of size n x n which is pre-generated and stored. The quality of random numbers generated is compared with other pseudorandom number generator using Marsaglia's Diehard battery of tests.


Quantitative Analysis for Authentication of Low-cost RFID Tags

Abstract: Formal analysis techniques are widely used today in order to verify and analyze communication protocols. In this work, we launch a quantitative verification analysis for the low- cost Radio Frequency Identification (RFID) protocol proposed by Song and Mitchell. The analysis exploits a Discrete-Time Markov Chain (DTMC) using the well-known PRISM model checker. We have managed to represent up to 100 RFID tags communicating with a reader and quantify each RFID session according to the protocol's computation and transmission cost requirements. As a consequence, not only does the proposed analysis provide quantitative verification results, but also it constitutes a methodology for RFID designers who want to validate their products under specific cost requirements.


Approximating the Diameter of Planar Graphs in Near Linear Time

Abstract: We present a $(1+\epsilon)$-approximation algorithm running in $O(f(\epsilon)\cdot n \log^4 n)$ time for finding the diameter of an undirected planar graph with non-negative edge lengths.


Finding Heavy Paths in Graphs: A Rank Join Approach

Abstract: Graphs have been commonly used to model many applications. A natural problem which abstracts applications such as itinerary planning, playlist recommendation, and flow analysis in information networks is that of finding the heaviest path(s) in a graph. More precisely, we can model these applications as a graph with non-negative edge weights, along with a monotone function such as sum, which aggregates edge weights into a path weight, capturing some notion of quality. We are then interested in finding the top-k heaviest simple paths, i.e., the $k$ simple (cycle-free) paths with the greatest weight, whose length equals a given parameter $\ell$. We call this the \emph{Heavy Path Problem} (HPP). It is easy to show that the problem is NP-Hard. In this work, we develop a practical approach to solve the Heavy Path problem by leveraging a strong connection with the well-known Rank Join paradigm. We first present an algorithm by adapting the Rank Join algorithm. We identify its limitations and develop a new exact algorithm called HeavyPath and a scalable heuristic algorithm. We conduct a comprehensive set of experiments on three real data sets and show that HeavyPath outperforms the baseline algorithms significantly, with respect to both $\ell$ and $k$. Further, our heuristic algorithm scales to longer lengths, finding paths that are empirically within 50% of the optimum solution or better under various settings, and takes only a fraction of the running time compared to the exact algorithm.


Minimum Convex Partitions and Maximum Empty Polytopes

Abstract: Let $S$ be a set of $n$ points in $\mathbb{R}^d$. A Steiner convex partition is a tiling of ${\rm conv}(S)$ with empty convex bodies. For every integer $d$, we show that $S$ admits a Steiner convex partition with at most $\lceil (n-1)/d\rceil$ tiles. This bound is the best possible for points in general position in the plane, and it is best possible apart from constant factors in every fixed dimension $d\geq 3$. We also give the first constant-factor approximation algorithm for computing a minimum Steiner convex partition of a planar point set in general position. Establishing a tight lower bound for the maximum volume of a tile in a Steiner convex partition of any $n$ points in the unit cube is equivalent to a famous problem of Danzer and Rogers. It is conjectured that the volume of the largest tile is $\omega(1/n)$. Here we give a $(1-\varepsilon)$-approximation algorithm for computing the maximum volume of an empty convex body amidst $n$ given points in the $d$-dimensional unit box $[0,1]^d$.


Learning in embodied action-perception loops through exploration

Abstract: Although exploratory behaviors are ubiquitous in the animal kingdom, their computational underpinnings are still largely unknown. Behavioral Psychology has identified learning as a primary drive underlying many exploratory behaviors. Exploration is seen as a means for an animal to gather sensory data useful for reducing its ignorance about the environment. While related problems have been addressed in Data Mining and Reinforcement Learning, the computational modeling of learning-driven exploration by embodied agents is largely unrepresented. Here, we propose a computational theory for learning-driven exploration based on the concept of missing information that allows an agent to identify informative actions using Bayesian inference. We demonstrate that when embodiment constraints are high, agents must actively coordinate their actions to learn efficiently. Compared to earlier approaches, our exploration policy yields more efficient learning across a range of worlds with diverse structures. The improved learning in turn affords greater success in general tasks including navigation and reward gathering. We conclude by discussing how the proposed theory relates to previous information-theoretic objectives of behavior, such as predictive information and the free energy principle, and how it might contribute to a general theory of exploratory behavior.


Multi-timescale Nexting in a Reinforcement Learning Robot

Abstract: The term "nexting" has been used by psychologists to refer to the propensity of people and many other animals to continually predict what will happen next in an immediate, local, and personal sense. The ability to "next" constitutes a basic kind of awareness and knowledge of one's environment. In this paper we present results with a robot that learns to next in real time, predicting thousands of features of the world's state, including all sensory inputs, at timescales from 0.1 to 8 seconds. This was achieved by treating each state feature as a reward-like target and applying temporal-difference methods to learn a corresponding value function with a discount rate corresponding to the timescale. We show that two thousand predictions, each dependent on six thousand state features, can be learned and updated online at better than 10Hz on a laptop computer, using the standard TD(lambda) algorithm with linear function approximation. We show that this approach is efficient enough to be practical, with most of the learning complete within 30 minutes. We also show that a single tile-coded feature representation suffices to accurately predict many different signals at a significant range of timescales. Finally, we show that the accuracy of our learned predictions compares favorably with the optimal off-line solution.


Secretary Problems with Convex Costs

Abstract: We consider online resource allocation problems where given a set of requests our goal is to select a subset that maximizes a value minus cost type of objective function. Requests are presented online in random order, and each request possesses an adversarial value and an adversarial size. The online algorithm must make an irrevocable accept/reject decision as soon as it sees each request. The "profit" of a set of accepted requests is its total value minus a convex cost function of its total size. This problem falls within the framework of secretary problems. Unlike previous work in that area, one of the main challenges we face is that the objective function can be positive or negative and we must guard against accepting requests that look good early on but cause the solution to have an arbitrarily large cost as more requests are accepted. This requires designing new techniques. We study this problem under various feasibility constraints and present online algorithms with competitive ratios only a constant factor worse than those known in the absence of costs for the same feasibility constraints. We also consider a multi-dimensional version of the problem that generalizes multi-dimensional knapsack within a secretary framework. In the absence of any feasibility constraints, we present an O(l) competitive algorithm where l is the number of dimensions; this matches within constant factors the best known ratio for multi-dimensional knapsack secretary.


Highly-Concurrent Doubly-Linked Lists

Abstract: As file systems are increasingly being deployed on ever larger systems with many cores and multi-gigabytes of memory, scaling the internal data structures of file systems has taken greater importance and urgency. A doubly-linked list is a simple and very commonly used data structure in file systems but it is not very friendly to multi-threaded use. While special cases of lists, such as queues and stacks, have lock-free versions that scale reasonably well, the general form of a doubly-linked list offers no such solution. Using a mutex to serialize all operations remains the de-facto method of maintaining a doubly linked list. This severely limits the scalability of the list and developers must resort to ad-hoc workarounds that involve using multiple smaller lists (with individual locks) and deal with the resulting complexity of the system. In this paper, we present an approach to building highly concurrent data structures, with special focus on the implementation of highly concurrent doubly-linked lists. Dubbed "advanced doubly-linked list" or "adlist" for short, our list allows iteration in any direction, and insert/delete operations over non-overlapping nodes to execute in parallel. Operations with common nodes get serialized so as to always present a locally consistent view to the callers. An adlist node needs an additional 8 bytes of space for keeping synchronization information. The Data Domain File System makes extensive use of adlists which has allowed for significant scaling of the system without sacrificing simplicity.


The Dimension of Spline Spaces with Highest Order Smoothness over Hierarchical T-meshes

Abstract: This paper discusses the dimension of spline spaces with highest order smoothness over hierarchical T-meshes over certain type of hierarchical T-meshes. The major step is to set up a bijection between the spline space with highest order smoothness over a hierarchical T-mesh and a univariate spline space whose definition depends on the l-edges of the extended T-mesh. We decompose the univariate spline space into direct sums in the sense of isomorphism using the theory of the short exact sequence in homological algebra. According to the decomposition of the univariate spline space, the dimension formula of the spline space with highest order smoothness over certain type of hierarchical T-mesh is presented. A set of basis functions of the spline space is also constructed.


Knightian Auctions

Abstract: We study single-good auctions in a setting where each player knows his own valuation only within a constant multiplicative factor \delta{} in (0,1), and the mechanism designer knows \delta. The classical notions of implementation in dominant strategies and implementation in undominated strategies are naturally extended to this setting, but their power is vastly different. On the negative side, we prove that no dominant-strategy mechanism can guarantee social welfare that is significantly better than that achievable by assigning the good to a random player. On the positive side, we provide tight upper and lower bounds for the fraction of the maximum social welfare achievable in undominated strategies, whether deterministically or probabilistically.


Wireless Communications and Networking Technologies for Smart Grid: Paradigms and Challenges

Abstract: Smart grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this work we present our vision on smart grid from the perspective of wireless communications and networking technologies. We present wireless communication and networking paradigms for four typical scenarios in the future smart grid and also point out the research challenges of the wireless communication and networking technologies used in smart grid


Rationality and Escalation in Infinite Extensive Games

Abstract: The aim of this of this paper is to study infinite games and to prove formally some properties in this framework. As a consequence we show that the behavior (the madness) of people which leads to speculative crashes or escalation can be fully rational. Indeed it proceeds from the statement that resources are infinite. The reasoning is based on the concept of coinduction conceived by computer scientists to model infinite computations and used by economic agents unknowingly. When used consciously, this concept is not as simple as induction and we could paraphrase Newton: "Modeling the madness of people is more difficult than modeling the motion of planets".


A multi-feature tracking algorithm enabling adaptation to context variations

Abstract: We propose in this paper a tracking algorithm which is able to adapt itself to different scene contexts. A feature pool is used to compute the matching score between two detected objects. This feature pool includes 2D, 3D displacement distances, 2D sizes, color histogram, histogram of oriented gradient (HOG), color covariance and dominant color. An offline learning process is proposed to search for useful features and to estimate their weights for each context. In the online tracking process, a temporal window is defined to establish the links between the detected objects. This enables to find the object trajectories even if the objects are misdetected in some frames. A trajectory filter is proposed to remove noisy trajectories. Experimentation on different contexts is shown. The proposed tracker has been tested in videos belonging to three public datasets and to the Caretaker European project. The experimental results prove the effect of the proposed feature weight learning, and the robustness of the proposed tracker compared to some methods in the state of the art. The contributions of our approach over the state of the art trackers are: (i) a robust tracking algorithm based on a feature pool, (ii) a supervised learning scheme to learn feature weights for each context, (iii) a new method to quantify the reliability of HOG descriptor, (iv) a combination of color covariance and dominant color features with spatial pyramid distance to manage the case of object occlusion.


Evaluating Quality of Chaotic Pseudo-Random Generators: Application to Information Hiding

Abstract: Guaranteeing the security of information transmitted through the Internet, against passive or active attacks, is a major concern. The discovery of new pseudo-random number generators with a strong level of security is a field of research in full expansion, due to the fact that numerous cryptosystems and data hiding schemes are directly dependent on the quality of these generators. At the conference Internet`09, we described a generator based on chaotic iterations which behaves chaotically as defined by Devaney. In this paper which is an extension of the work presented at the conference Internet`10, the proposal is to improve the speed, the security, and the evaluation of this generator, to make its use more relevant in the Internet security context. In order to do so, a comparative study between various generators is carried out and statistical results are improved. Finally, an application in the information hiding framework is presented with details, to give an illustrative example of the use of such a generator in the Internet security field.


Efficient Computation of Distance Sketches in Distributed Networks

Abstract: Distance computation is one of the most fundamental primitives used in communication networks. The cost of effectively and accurately computing pairwise network distances can become prohibitive in large-scale networks such as the Internet and Peer-to-Peer (P2P) networks. To negotiate the rising need for very efficient distance computation, approximation techniques for numerous variants of this question have recently received significant attention in the literature. The goal is to preprocess the graph and store a small amount of information such that whenever a query for any pairwise distance is issued, the distance can be well approximated (i.e., with small stretch) very quickly in an online fashion. Specifically, the pre-processing (usually) involves storing a small sketch with each node, such that at query time only the sketches of the concerned nodes need to be looked up to compute the approximate distance. In this paper, we present the first theoretical study of distance sketches derived from distance oracles in a distributed network. We first present a fast distributed algorithm for computing approximate distance sketches, based on a distributed implementation of the distance oracle scheme of [Thorup-Zwick, JACM 2005]. We also show how to modify this basic construction to achieve different tradeoffs between the number of pairs for which the distance estimate is accurate and other parameters. These tradeoffs can then be combined to give an efficient construction of small sketches with provable average-case as well as worst-case performance. Our algorithms use only small-sized messages and hence are suitable for bandwidth-constrained networks, and can be used in various networking applications such as topology discovery and construction, token management, load balancing, monitoring overlays, and several other problems in distributed algorithms.


Steganography: a class of secure and robust algorithms

Abstract: This research work presents a new class of non-blind information hiding algorithms that are stego-secure and robust. They are based on some finite domains iterations having the Devaney's topological chaos property. Thanks to a complete formalization of the approach we prove security against watermark-only attacks of a large class of steganographic algorithms. Finally a complete study of robustness is given in frequency DWT and DCT domains.


Performance Analysis of a Keyed Hash Function based on Discrete and Chaotic Proven Iterations

Abstract: Security of information transmitted through the Internet is an international concern. This security is guaranteed by tools like hash functions. However, as security flaws have been recently identified in the current standard in this domain, new ways to hash digital media must be investigated. In this document an original keyed hash function is evaluated. It is based on chaotic iterations and thus possesses various topological properties as uniform repartition and sensibility to its initial condition. These properties make our hash function satisfy the requirements in this field. This claim is verified qualitatively and experimentally in this research work, among other things by realizing simulations of diffusion and confusion.


Additive schemes (splitting schemes) for some systems of evolutionary equations

Abstract: On the basis of additive schemes (splitting schemes) we construct efficient numerical algorithms to solve approximately the initial-boundary value problems for systems of time-dependent partial differential equations (PDEs). In many applied problems the individual components of the vector of unknowns are coupled together and then splitting schemes are applied in order to get a simple problem for evaluating components at a new time level. Typically, the additive operator-difference schemes for systems of evolutionary equations are constructed for operators coupled in space. In this paper we investigate more general problems where coupling of derivatives in time for components of the solution vector takes place. Splitting schemes are developed using an additive representation for both the primary operator of the problem and the operator at the time derivative. Splitting schemes are based on a triangular two-component representation of the operators.


Small Private Circuits

Abstract: Ishai, Sahai, and Wagner initiated in 2003 the theoretical study of securing a circuit against an adversary who can probe its wires. They presented a universal way of transforming an arbitrary boolean circuit of size s into a circuit of size linear in s and quadratic in t, with perfect security against an adversary who can read up to t wires of the circuit. We present a new method for securing circuits against such an adversary with circuit size linear in s and polylogarithmic in t, while meeting the original privacy requirements from Ishai et al. Our solution works for arithmetic circuits over arbitrary fields of positive characteristic. The improvement from quadratic to quasilinear complexity (in t) comes from using the DFT instead of naive multiplication.


Generic Environments in Coq

Abstract: We introduce a library which provides an abstract data type of environments, as a functor parameterized by a module defining variables, and a function which builds environments for such variables with any Type of type. Usual operations over environments are defined, along with an extensive set of basic and more advanced properties. Moreover, we give an implementation using lists satisfying all the required properties.