On Improving the Representation of a Region Achieved by a Sensor Network

Abstract: This report considers the class of applications of sensor networks in which each sensor node makes measurements, such as temperature or humidity, at the precise location of the node. Such spot-sensing applications approximate the physical condition of the entire region of interest by the measurements made at only the points where the sensor nodes are located. Given a certain density of nodes in a region, a more spatially uniform distribution of the nodes leads to a better approximation of the physical condition of the region. This report considers the error in this approximation and seeks to improve the quality of representation of the physical condition of the points in the region in the data collected by the sensor network. We develop two essential metrics which together allow a rigorous quantitative assessment of the quality of representation achieved: the average representation error and the unevenness of representation error, the latter based on a well-accepted measure of inequality used in economics. We present the rationale behind the use of these metrics and derive relevant theoretical bounds on them in the common scenario of a planar region of arbitrary shape covered by a sensor network deployment. A simple new heuristic algorithm is presented for each node to determine if and when it should sense or sleep to conserve energy while also preserving the quality of representation. Simulation results show that it achieves a significant improvement in the quality of representation compared to other related distributed algorithms. Interestingly, our results also show that improved spatial uniformity has the welcome side-effect of a significant increase in the network lifetime.


Machine Learning: When and Where the Horses Went Astray?

Abstract: Machine Learning is usually defined as a subfield of AI, which is busy with information extraction from raw data sets. Despite of its common acceptance and widespread recognition, this definition is wrong and groundless. Meaningful information does not belong to the data that bear it. It belongs to the observers of the data and it is a shared agreement and a convention among them. Therefore, this private information cannot be extracted from the data by any means. Therefore, all further attempts of Machine Learning apologists to justify their funny business are inappropriate.


From Abstract Rewriting Systems to Abstract Proof Systems

Abstract: Some personal recollections on the introduction of `abstract proof systems' as a framework for formulating syntax-independent, general results about rule derivability and admissibility. With a particular eye on the inspiration I owe to Roel de Vrijer: the analogy with abstract rewriting systems.


Co-word Analysis using the Chinese Character Set

Abstract: Until recently, Chinese texts could not be studied using co-word analysis because the words are not separated by spaces in Chinese (and Japanese). A word can be composed of one or more characters. The online availability of programs that separate Chinese texts makes it possible to analyze them using semantic maps. Chinese characters contain not only information, but also meaning. This may enhance the readability of semantic maps. In this study, we analyze 58 words which occur ten or more times in the 1652 journal titles of the China Scientific and Technical Papers and Citations Database. The word occurrence matrix is visualized and factor-analyzed.


Situational Method Engineering: Fundamentals and Experiences

Abstract: The work presented in this paper is related to the area of Situational Method Engineering (SME) which focuses on project-specific method construction. We propose a faceted framework to understand and classify issues in system development SME. The framework identifies four different but complementary viewpoints. Each view allows us to capture a particular aspect of situational methods. Inter-relationships between these views show how they influence each other. In order to study, understand and classify a particular view of SME in its diversity, we associate a set of facets with each view. As a facet allows an in-depth description of one specific aspect of SME, the views show the variety and diversity of these aspects.


Method Chunks Selection by Multicriteria Techniques: an Extension of the Assembly-based Approach

Abstract: The work presented in this paper is related to the area of situational method engineering (SME). In this domain, approaches are developed accordingly to specific project specifications. We propose to adapt an existing method construction process, namely the assembly-based one. One of the particular features of assembly-based SME approach is the selection of method chunks. Our proposal is to offer a better guidance in the retrieval of chunks by the introduction of multicriteria techniques. To use them efficiently, we defined a typology of projects characteristics, in order to identify all their critical aspects, which will offer a priorisation to help the method engineer in the choice between similar chunks.


Improving Software Development Processes with Multicriteria Methods

Abstract: All software development processes include steps where several alternatives induce a choice, a decision-making. Sometimes, methodologies offer a way to make decisions. However, in a lot of cases, the arguments to carry out the decision are very poor and the choice is made in an intuitive and hazardous way. The aim of our work is to offer a scientifically founded way to guide the engineer through tactical choices with the application of multicriteria methods in software development processes. This approach is illustrated with three cases: risks, use cases and tools within Rational Unified Process.


A Round-based Pricing Scheme for Maximizing Service Provider's Revenue in P2PTV Networks

Abstract: In this paper, we analyze a round-based pricing scheme that encourages favorable behavior from users of real-time P2P applications like P2PTV. In the design of pricing schemes, we consider price to be a function of usage and capacity of download/upload streams, and quality of content served. Users are consumers and servers at the same time in such networks, and often exhibit behavior that is unfavorable towards maximization of social benefits. Traditionally, network designers have overcome this difficulty by building-in traffic latencies. However, using simulations, we show that appropriate pricing schemes and usage terms can enable designers to limit required traffic latencies, and be able to earn nearly 30% extra revenue from providing P2PTV services. The service provider adjusts the prices of individual programs incrementally within rounds, while making relatively large-scale adjustments at the end of each round. Through simulations, we show that it is most beneficial for the service provider to carry out 5 such rounds of price adjustments for maximizing his average profit and minimizing the associated standard deviation at the same time.


Throughput Limits of IEEE 802.11 and IEEE 802.15.3

Abstract: IEEE 802.11 and IEEE 802.15.3 are wireless standards originally designed for wireless local area network (WLAN) and wireless personal area network (WPAN). This paper studies MAC throughput analysis of both standards. We present a comparative analysis of both standards in terms of MAC throughput and bandwidth efficiency. Numerical results show that the performance of IEEE 802.15.3 transcends IEEE 802.11 in all cases.


MAC Layer Hurdles in BSNs

Abstract: The last few decades have seen considerable research progress in microelectronics and integrated circuits, system-on-chip design, wireless communication, and sensor technology. This progress has enabled the seamless integration of autonomous wireless sensor nodes around a human body to create a Body Sensor Network (BSN). The development of a proactive and ambulatory BSN induces a number of enormous issues and challenges. This paper presents the technical hurdles during the design and implementation of a low-power Medium Access Control (MAC) protocol for in-body and on-body sensor networks. We analyze the performance of IEEE 802.15.4 protocol for the on-body sensor network. We also provide a comprehensive insight into the heterogeneous characteristics of the in-body sensor network. A low-power technique called Pattern-Based Wake-up Table is proposed to handle the normal traffic in a BSN. The proposed technique provides a reliable solution towards low-power communication in the in-body sensor network.


Performance Analysis of Two-Hop Cooperative MIMO transmission with Relay Selection in Rayleigh Fading Channel

Abstract: Wireless relaying is one of the promising solutions to overcome the channel impairments and provide high data rate coverage that appears for beyond 3G mobile communications. In this paper we present an end to end BER performance analysis of dual hop wireless communication systems equipped with multiple decode and forward relays over the Rayleigh fading channel with relay selection. We select the best relay based on end to end channel conditions. We apply orthogonal space time block coding (OSTBC) at source, and also present how the multiple antennas at the source terminal affects the end to end BER performance. This intermediate relay technique will cover long distance where destination is out of reach from source.


On the Development of Low Power MAC Protocol for WBANs

Abstract: Current advances in wireless communication, microelectronics, semiconductor technologies, and intelligent sensors have contributed to the development of unobtrusive WBANs. These networks provide long term health monitoring of patients without any constraint in their normal activities. Traditional MAC protocols do not accommodate the assorted WBAN traffic requirements in a power efficient manner. In this paper, we present a brief discussion on the development process of a low power MAC protocol for WBANs. We observe the behavior of a beacon-enabled IEEE 802.15.4 for on-body sensor networks. We further propose a low power technique called traffic based wakeup mechanism for a WBAN that exploits the traffic patterns of the BAN Nodes to ensure power efficient and reliable communication.


A Near-Optimal Scheme for TCP ACK Pacing to Maintain Throughput in Wireless Networks

Abstract: The advent of fourth generation technologies in wireless networks and the rapid growth of 3G have heralded an era that will require researchers to find reliable and easily implement-able solutions to the problem of poor TCP performance in the wireless environment. Since a large part of the Internet is TCP-based, solving this problem will be instrumental in determining if the move from wired to wireless will be seamless or not. This paper proposes a scheme that uses the base station's ability to predict the time at which the link may be going down and to estimate the period for which the mobile would be unreachable due to conditions like fading. By using cross-layer and ACK pacing algorithms, the base station prevents the fixed host from timing out while waiting for ACKs from the mobile. This in turn prevents TCP on the fixed host from bringing down the throughput drastically due to temporary network conditions, caused by mobility or the unreliability of wireless links. Experimental results indicate a reasonable increase in throughput when the ACK holding scheme is used.


MIMO Cluster Cooperative Assignment Cross Layer Scheme for Hybrid Wireless Sensor Networks

Abstract: The dual-cross scenario of the hybrid wireless sensor networks (WSNs) is studied and a novel MIMO Cluster Cooperative Assignment Cross Layer Scheduling Scheme (MCCA-CLSS) is proposed in this paper. The comparison and the predominance of the proposed scheme are demonstrated, the clusters are optimized. With the help of the simulations, the relative energy consumption and the end-to-end blocking probability are all improved. The addressing ratio of success in the condition of the unchanged parameters and external information can be increased and the network can tolerate more hops to support reliable transportation by the proposed scheme.


A Novel Cross Layer Scheme for Multi-Channel Hybrid Cognitive Ad-hoc Networks

Abstract: A special scenario of the topology in the hybrid Cognitive Ad-hoc networks is studied and a novel cross layer scheme is proposed in this paper. The proposed scheme integrated the attributes both of the new performance evaluation machine check time metric and the topology space in special scenario. The topology and power consumption of each node can all be optimized due to the minimum link occupation with the help of this scheme. Simulation results show that the novel scheme can give schedule guarantee to the multi-channel networks in the variable node loads and transmission powers, and make the node stable to support multi-hops at the same time.


Managing Innovation and Technology in Developing Countries

Abstract: Innovation and technology management is an inevitable issue in the high end technological and innovative organizations. Today, most of the innovations are limited with developed countries like USA, Japan and Europe while developing countries are still behind in the field of innovation and management of technology. But it is also becoming a subject for rapid progress and development in developing countries. Innovation and technology environment in developing countries are by nature, problematic, characterized by poor business models, political instability and governance conditions, low education level and lack of world-class research universities, an underdeveloped and mediocre physical infrastructure, and lack of solid technology based on trained human resources. This paper provides a theoretical and conceptual framework analysis for managing innovation and technology in developing countries like India and China. We present the issues and challenges in innovation and technology management and come up with proposed solutions.


A Discourse-based Approach in Text-based Machine Translation

Abstract: This paper presents a theoretical research based approach to ellipsis resolution in machine translation. The formula of discourse is applied in order to resolve ellipses. The validity of the discourse formula is analyzed by applying it to the real world text, i.e., newspaper fragments. The source text is converted into mono-sentential discourses where complex discourses require further dissection either directly into primitive discourses or first into compound discourses and later into primitive ones. The procedure of dissection needs further improvement, i.e., discovering as many primitive discourse forms as possible. An attempt has been made to investigate new primitive discourses or patterns from the given text.


Resolution of Unidentified Words in Machine Translation

Abstract: This paper presents a mechanism of resolving unidentified lexical units in Text-based Machine Translation (TBMT). In a Machine Translation (MT) system it is unlikely to have a complete lexicon and hence there is intense need of a new mechanism to handle the problem of unidentified words. These unknown words could be abbreviations, names, acronyms and newly introduced terms. We have proposed an algorithm for the resolution of the unidentified words. This algorithm takes discourse unit (primitive discourse) as a unit of analysis and provides real time updates to the lexicon. We have manually applied the algorithm to news paper fragments. Along with anaphora and cataphora resolution, many unknown words especially names and abbreviations were updated to the lexicon.


Applicability of Telemedicine in Bangladesh: Current Status and Future Prospects

Abstract: Telemedicine refers to the use of information and communication technology to provide and support health care mainly for the purpose of providing consultation. It is also a way to provide medical procedures or examinations to remote locations. It has the potential to improve both the quality and the access to health care services delivery while lowering costs even in the scarcity of resources. Understanding the potentiality of telemedicine, many developing countries are implementing telemedicine to provide health care facility to remote area where health care facilities are deficient. Bangladesh is not an exception to this either. In this paper we mention the reasons why Bangladesh has to move for telemedicine. We also present the past and on-going telemedicine activities and projects in Bangladesh. Analyzing these projects we have found out some factors which should be assessed carefully for successful implementation of telemedicine application. Finally we propose a prototype telemedicine network for Bangladesh that can improve health facilities through telemedicine by making a connection between rural health facility providers and special hospitals.


Towards Power Efficient MAC Protocol for In-Body and On-Body Sensor Networks

Abstract: This paper presents an empirical discussion on the design and implementation of a power-efficient Medium Access Control (MAC) protocol for in-body and on-body sensor networks. We analyze the performance of a beacon-enabled IEEE 802.15.4, PB-TDMA, and S-MAC protocols for on-body sensor networks. We further present a Traffic Based Wakeup Mechanism that utilizes the traffic patterns of the BAN Nodes (BNs) to accommodate the entire BSN traffic. To enable a logical connection between different BNs working on different frequency bands, a method called Bridging function is proposed. The Bridging function integrates all BNs working on different bands into a complete BSN.


A Study of Implanted and Wearable Body Sensor Networks

Abstract: Recent advances in intelligent sensors, microelectronics and integrated circuit, system-on-chip design and low power wireless communication introduced the development of miniaturised and autonomous sensor nodes. These tiny sensor nodes can be deployed to develop a proactive Body Sensor Network (BSN). The rapid advancement in ultra low-power RF (radio frequency) technology enables invasive and non-invasive devices to communicate with a remote station. This communication revolutionizes healthcare system by enabling long term health monitoring of a patient and providing real time feedback to the medical experts. In this paper, we present In-body and On-body communication networks with a special focus on the methodologies of wireless communication between implanted medical devices with external monitoring equipment and recent technological growth in both areas. We also discuss open issues and challenges in a BSN.


Manipulating Tournaments in Cup and Round Robin Competitions

Abstract: In sports competitions, teams can manipulate the result by, for instance, throwing games. We show that we can decide how to manipulate round robin and cup competitions, two of the most popular types of sporting competitions in polynomial time. In addition, we show that finding the minimal number of games that need to be thrown to manipulate the result can also be determined in polynomial time. Finally, we show that there are several different variations of standard cup competitions where manipulation remains polynomial.


Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena

Abstract: Microblogging is a form of online communication by which users broadcast brief text updates, also known as tweets, to the public or a selected circle of contacts. A variegated mosaic of microblogging uses has emerged since the launch of Twitter in 2006: daily chatter, conversation, information sharing, and news commentary, among others. Regardless of their content and intended use, tweets often convey pertinent information about their author's mood status. As such, tweets can be regarded as temporally-authentic microscopic instantiations of public mood state. In this article, we perform a sentiment analysis of all public tweets broadcasted by Twitter users between August 1 and December 20, 2008. For every day in the timeline, we extract six dimensions of mood (tension, depression, anger, vigor, fatigue, confusion) using an extended version of the Profile of Mood States (POMS), a well-established psychometric instrument. We compare our results to fluctuations recorded by stock market and crude oil price indices and major events in media and popular culture, such as the U.S. Presidential Election of November 4, 2008 and Thanksgiving Day. We find that events in the social, political, cultural and economic sphere do have a significant, immediate and highly specific effect on the various dimensions of public mood. We speculate that large scale analyses of mood can provide a solid platform to model collective emotive trends in terms of their predictive value with regards to existing social as well as economic indicators.


On the Pricing of Recommendations and Recommending Strategically

Abstract: If you recommend a product to me and I buy it, how much should you be paid by the seller? And if your sole interest is to maximize the amount paid to you by the seller for a sequence of recommendations, how should you recommend optimally if I become more inclined to ignore you with each irrelevant recommendation you make? Finding an answer to these questions is a key challenge in all forms of marketing that rely on and explore social ties; ranging from personal recommendations to viral marketing. In the first part of this paper, we show that there can be no pricing mechanism that is "truthful" with respect to the seller, and we use solution concepts from coalitional game theory, namely the Core, the Shapley Value, and the Nash Bargaining Solution, to derive provably "fair" prices for settings with one or multiple recommenders. We then investigate pricing mechanisms for the setting where recommenders have different "purchase arguments". Here we show that it might be beneficial for the recommenders to withhold some of their arguments, unless anonymity-proof solution concepts, such as the anonymity-proof Shapley value, are used. In the second part of this paper, we analyze the setting where the recommendee loses trust in the recommender for each irrelevant recommendation. Here we prove that even if the recommendee regains her initial trust on each successful recommendation, the expected total profit the recommender can make over an infinite period is bounded. This can only be overcome when the recommendee also incrementally regains trust during periods without any recommendation. Here, we see an interesting connection to "banner blindness", suggesting that showing fewer ads can lead to a higher long-term profit.


Fast Approximation in Subspaces by Doubling Metric Decomposition

Abstract: In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees that need to be constructed for different groups of users. In our model we allow a preprocessing phase, when some information of the input graph $G=(V,E)$ is stored in a limited size data structure. Next, the data structure enables processing queries of the form ``solve problem A for an input $S\subseteq V$''. We consider problems like {\sc Steiner Forest}, {\sc Facility Location}, {\sc $k$-Median}, {\sc $k$-Center} and {\sc TSP} in the case when the graph induces a doubling metric. Our main results are data structures of near-linear size that are able to answer queries in time close to linear in $|S|$. This improves over typical worst case reuniting time of approximation algorithms in the classical setting which is $\Omega(|E|)$ independently of the query size. In most cases, our approximation guarantees are arbitrarily close to those in the classical setting. Additionally, we present the first fully dynamic algorithm for the Steiner tree problem.


An extendible User-Command Framework based on tagging system

Abstract: Memorizing the user commands has been a problem since long. In this study we try to propose solutions to overcome two problems - the problem of selecting appropriate commands names during application development and the problem of memorizing these command names. The proposed solution includes a framework in which the applications can plug into, to get their application commands and corresponding tags in to the new command execution application.We also propose a mechanism where user can generate her own set of tags for a command and share those with peers.


Industrial-Strength Formally Certified SAT Solving

Abstract: Boolean Satisfiability (SAT) solvers are now routinely used in the verification of large industrial problems. However, their application in safety-critical domains such as the railways, avionics, and automotive industries requires some form of assurance for the results, as the solvers can (and sometimes do) have bugs. Unfortunately, the complexity of modern, highly optimized SAT solvers renders impractical the development of direct formal proofs of their correctness. This paper presents an alternative approach where an untrusted, industrial-strength, SAT solver is plugged into a trusted, formally certified, SAT proof checker to provide industrial-strength certified SAT solving. The key novelties and characteristics of our approach are (i) that the checker is automatically extracted from the formal development, (ii), that the combined system can be used as a standalone executable program independent of any supporting theorem prover, and (iii) that the checker certifies any SAT solver respecting the agreed format for satisfiability and unsatisfiability claims. The core of the system is a certified checker for unsatisfiability claims that is formally designed and verified in Coq. We present its formal design and outline the correctness proofs. The actual standalone checker is automatically extracted from the the Coq development. An evaluation of the certified checker on a representative set of industrial benchmarks from the SAT Race Competition shows that, albeit it is slower than uncertified SAT checkers, it is significantly faster than certified checkers implemented on top of an interactive theorem prover.


Applications of UWB Technology

Abstract: Recent advances in wideband impulse technology, low power communication along with unlicensed band have enabled ultra wide band (UWB) as a leading technology for future wireless applications. This paper outlines the applications of emerging UWB technology in a private and commercial sector. We further talk about UWB technology for a wireless body area network (WBAN).


Multi-Objective Optimisation Method for Posture Prediction and Analysis with Consideration of Fatigue Effect and its Application Case

Abstract: Automation technique has been widely used in manufacturing industry, but there are still manual handling operations required in assembly and maintenance work in industry. Inappropriate posture and physical fatigue might result in musculoskeletal disorders (MSDs) in such physical jobs. In ergonomics and occupational biomechanics, virtual human modelling techniques have been employed to design and optimize the manual operations in design stage so as to avoid or decrease potential MSD risks. In these methods, physical fatigue is only considered as minimizing the muscle or joint stress, and the fatigue effect along time for the posture is not considered enough. In this study, based on the existing methods and multiple objective optimisation method (MOO), a new posture prediction and analysis method is proposed for predicting the optimal posture and evaluating the physical fatigue in the manual handling operation. The posture prediction and analysis problem is mathematically described and a special application case is demonstrated for analyzing a drilling assembly operation in European Aeronautic Defence & Space Company (EADS) in this paper.


Vertical partitioning of relational OLTP databases using integer programming

Abstract: A way to optimize performance of relational row store databases is to reduce the row widths by vertically partitioning tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This paper considers vertical partitioning algorithms for relational row-store OLTP databases with an H-store-like architecture, meaning that we would like to maximize the number of single-sited transactions. We present a model for the vertical partitioning problem that, given a schema together with a vertical partitioning and a workload, estimates the costs (bytes read/written by storage layer access methods and bytes transferred between sites) of evaluating the workload on the given partitioning. The cost model allows for arbitrarily prioritizing load balancing of sites vs. total cost minimization. We show that finding a minimum-cost vertical partitioning in this model is NP-hard and present two algorithms returning solutions in which single-sitedness of read queries is preserved while allowing column replication (which may allow a drastically reduced cost compared to disjoint partitioning). The first algorithm is a quadratic integer program that finds optimal minimum-cost solutions with respect to the model, and the second algorithm is a more scalable heuristic based on simulated annealing. Experiments show that the algorithms can reduce the cost of the model objective by 37% when applied to the TPC-C benchmark and the heuristic is shown to obtain solutions with cost close to the ones found using the quadratic program.


Graph isomorphism and volumes of convex bodies

Abstract: We show that a nontrivial graph isomorphism problem of two undirected graphs, and more generally, the permutation similarity of two given $n\times n$ matrices, is equivalent to equalities of volumes of the induced three convex bounded polytopes intersected with a given sequence of balls, centered at the origin with radii $t_i\in (0,\sqrt{n-1})$, where $\{t_i\}$ is an increasing sequence converging to $\sqrt{n-1}$. These polytopes are characterized by $n^2$ inequalities in at most $n^2$ variables. The existence of fpras for computing volumes of convex bodies gives rise to a semi-frpas of order $O^*(n^{14})$ at most to find if given two undirected graphs are isomorphic.


GEDI: Scalable Algorithms for Genotype Error Detection and Imputation

Abstract: Genome-wide association studies generate very large datasets that require scalable analysis algorithms. In this report we describe the GEDI software package, which implements efficient algorithms for performing several common tasks in the analysis of population genotype data, including genotype error detection and correction, imputation of both randomly missing and untyped genotypes, and genotype phasing. Experimental results show that GEDI achieves high accuracy with a runtime scaling linearly with the number of markers and samples. The open source C++ code of GEDI, released under the GNU General Public License, is available for download at http://dna.engr.uconn.edu/software/GEDI/


A Natural Dynamics for Bargaining on Exchange Networks

Abstract: Bargaining networks model the behavior of a set of players that need to reach pairwise agreements for making profits. Nash bargaining solutions are special outcomes of such games that are both stable and balanced. Kleinberg and Tardos proved a sharp algorithmic characterization of such outcomes, but left open the problem of how the actual bargaining process converges to them. A partial answer was provided by Azar et al. who proposed a distributed algorithm for constructing Nash bargaining solutions, but without polynomial bounds on its convergence rate. In this paper, we introduce a simple and natural model for this process, and study its convergence rate to Nash bargaining solutions. At each time step, each player proposes a deal to each of her neighbors. The proposal consists of a share of the potential profit in case of agreement. The share is chosen to be balanced in Nash's sense as far as this is feasible (with respect to the current best alternatives for both players). We prove that, whenever the Nash bargaining solution is unique (and satisfies a positive gap condition) this dynamics converges to it in polynomial time. Our analysis is based on an approximate decoupling phenomenon between the dynamics on different substructures of the network. This approach may be of general interest for the analysis of local algorithms on networks.


Big Macs and Eigenfactor Scores: Don't Let Correlation Coefficients Fool You

Abstract: The Eigenfactor Metrics provide an alternative way of evaluating scholarly journals based on an iterative ranking procedure analogous to Google's PageRank algorithm. These metrics have recently been adopted by Thomson-Reuters and are listed alongside the Impact Factor in the Journal Citation Reports. But do these metrics differ sufficiently so as to be a useful addition to the bibliometric toolbox? Davis (2008) has argued otherwise, based on his finding of a 0.95 correlation coefficient between Eigenfactor score and Total Citations for a sample of journals in the field of medicine. This conclusion is mistaken; here we illustrate the basic statistical fallacy to which Davis succumbed. We provide a complete analysis of the 2006 Journal Citation Reports and demonstrate that there are statistically and economically significant differences between the information provided by the Eigenfactor Metrics and that provided by Impact Factor and Total Citations.


Interactive Privacy via the Median Mechanism

Abstract: We define a new interactive differentially private mechanism -- the median mechanism -- for answering arbitrary predicate queries that arrive online. Relative to fixed accuracy and privacy constraints, this mechanism can answer exponentially more queries than the previously best known interactive privacy mechanism (the Laplace mechanism, which independently perturbs each query result). Our guarantee is almost the best possible, even for non-interactive privacy mechanisms. Conceptually, the median mechanism is the first privacy mechanism capable of identifying and exploiting correlations among queries in an interactive setting. We also give an efficient implementation of the median mechanism, with running time polynomial in the number of queries, the database size, and the domain size. This efficient implementation guarantees privacy for all input databases, and accurate query results for almost all input databases. The dependence of the privacy on the number of queries in this mechanism improves over that of the best previously known efficient mechanism by a super-polynomial factor, even in the non-interactive setting.


Standards for Language Resources

Abstract: The goal of this paper is two-fold: to present an abstract data model for linguistic annotations and its implementation using XML, RDF and related standards; and to outline the work of a newly formed committee of the International Standards Organization (ISO), ISO/TC 37/SC 4 Language Resource Management, which will use this work as its starting point.


Functional units for natural numbers

Abstract: Interaction with services provided by an execution environment forms part of the behaviours exhibited by instruction sequences under execution. Mechanisms related to the kind of interaction in question have been proposed in the setting of thread algebra. Like thread, service is an abstract behavioural concept. The concept of a functional unit is similar to the concept of a service, but more concrete. A state space is inherent in the concept of a functional unit, whereas it is not inherent in the concept of a service. In this paper, we establish the existence of a universal computable functional unit for natural numbers and related results.


Characteristic Formulae for Fixed-Point Semantics: A General Framework

Abstract: The literature on concurrency theory offers a wealth of examples of characteristic-formula constructions for various behavioural relations over finite labelled transition systems and Kripke structures that are defined in terms of fixed points of suitable functions. Such constructions and their proofs of correctness have been developed independently, but have a common underlying structure. This study provides a general view of characteristic formulae that are expressed in terms of logics with a facility for the recursive definition of formulae. It is shown how several examples of characteristic-formula constructions from the literature can be recovered as instances of the proposed general framework, and how the framework can be used to yield novel constructions.


A note on conjugacy search and racks

Abstract: We show that for every effective left conjugacy closed left quasigroup, there is an induced rack that retains the conjugation structure of the left translations. This means that cryptographic protocols relying on conjugacy search can be secure only if conjugacy search of left translations is infeasible in the induced rack. We note that, in fact, protocols based on conjugacy search could be simply implemented using a rack. We give an exposition of the Anshel-Anshel-Goldfeld protocol in such a case.


A Faster Exact Algorithm for the Directed Maximum Leaf Spanning Tree Problem

Abstract: Given a directed graph $G=(V,A)$, the Directed Maximum Leaf Spanning Tree problem asks to compute a directed spanning tree (i.e., an out-branching) with as many leaves as possible. By designing a Branch-and-Reduced algorithm combined with the Measure & Conquer technique for running time analysis, we show that the problem can be solved in time $\Oh^*(1.9043^n)$ using polynomial space. Hitherto, there have been only few examples. Provided exponential space this run time upper bound can be lowered to $\Oh^*(1.8139^n)$.


Active Learning for Mention Detection: A Comparison of Sentence Selection Strategies

Abstract: We propose and compare various sentence selection strategies for active learning for the task of detecting mentions of entities. The best strategy employs the sum of confidences of two statistical classifiers trained on different views of the data. Our experimental results show that, compared to the random selection strategy, this strategy reduces the amount of required labeled training data by over 50% while achieving the same performance. The effect is even more significant when only named mentions are considered: the system achieves the same performance by using only 42% of the training data required by the random selection strategy.


People-Sensing Spatial Characteristics of RF Sensor Networks

Abstract: An "RF sensor" network can monitor RSS values on links in the network and perform device-free localization, i.e., locating a person or object moving in the area in which the network is deployed. This paper provides a statistical model for the RSS variance as a function of the person's position w.r.t. the transmitter (TX) and receiver (RX). We show that the ensemble mean of the RSS variance has an approximately linear relationship with the expected total affected power (ETAP). We then use analysis to derive approximate expressions for the ETAP as a function of the person's position, for both scattering and reflection. Counterintuitively, we show that reflection, not scattering, causes the RSS variance contours to be shaped like Cassini ovals. Experimental tests reported here and in past literature are shown to validate the analysis.


Almost Linear B\"uchi Automata

Abstract: We introduce a new fragment of Linear temporal logic (LTL) called LIO and a new class of Buechi automata (BA) called Almost linear Buechi automata (ALBA). We provide effective translations between LIO and ALBA showing that the two formalisms are expressively equivalent. While standard translations of LTL into BA use some intermediate formalisms, the presented translation of LIO into ALBA is direct. As we expect applications of ALBA in model checking, we compare the expressiveness of ALBA with other classes of Buechi automata studied in this context and we indicate possible applications.


Expressing the Behavior of Three Very Different Concurrent Systems by Using Natural Extensions of Separation Logic

Abstract: Separation Logic is a non-classical logic used to verify pointer-intensive code. In this paper, however, we show that Separation Logic, along with its natural extensions, can also be used as a specification language for concurrent-system design. To do so, we express the behavior of three very different concurrent systems: a Subway, a Stopwatch, and a 2x2 Switch. The Subway is originally implemented in LUSTRE, the Stopwatch in Esterel, and the 2x2 Switch in Bluespec.


Modal Logic and the Approximation Induction Principle

Abstract: We prove a compactness theorem in the context of Hennessy-Milner logic. It is used to derive a sufficient condition on modal characterizations for the Approximation Induction Principle to be sound modulo the corresponding process equivalence. We show that this condition is necessary when the equivalence in question is compositional with respect to the projection operators.


Security Theorems via Model Theory

Abstract: A model-theoretic approach can establish security theorems for cryptographic protocols. Formulas expressing authentication and non-disclosure properties of protocols have a special form. They are quantified implications for all xs . (phi implies for some ys . psi). Models (interpretations) for these formulas are *skeletons*, partially ordered structures consisting of a number of local protocol behaviors. Realized skeletons contain enough local sessions to explain all the behavior, when combined with some possible adversary behaviors. We show two results. (1) If phi is the antecedent of a security goal, then there is a skeleton A_phi such that, for every skeleton B, phi is satisfied in B iff there is a homomorphism from A_phi to B. (2) A protocol enforces for all xs . (phi implies for some ys . psi) iff every realized homomorphic image of A_phi satisfies psi. Hence, to verify a security goal, one can use the Cryptographic Protocol Shapes Analyzer CPSA (TACAS, 2007) to identify minimal realized skeletons, or "shapes," that are homomorphic images of A_phi. If psi holds in each of these shapes, then the goal holds.


A scientific understanding of network designing

Abstract: As the Internet becomes severely overburdened with exponentially growing traffic demand, it becomes a general belief that a new generation data network is in urgent need today. However, standing at this crossroad, we find that we are in a situation that lacks a theory of network designing. This issue becomes even more serious as the recent progress of network measurement and modeling challenges the foundation of network research in the past decades. This paper tries to set up a scientific foundation for network designing by formalizing it as a multi-objective optimization process and quantifying the way different designing choices independently and collectively influence these objectives. A cartesian coordinate system is introduced to map the effect of each designing scheme to a coordinate. We investigated the achievable area of the network designing space and proved some boundary conditions. It is shown that different kind of networks display different shapes of achievable areas in the cartesian coordinate and exhibit different abilities to achieve cost-effective and scalable designing. In particular, we found that the philosophy underlying current empirical network designing and engineering fails to meet the cost-effective and evolvable requirements of network designing. We demonstrated that the efficient routing combined with effective betweenness based link bandwidth allocation scheme is a cost-effective and scalable design for BA-like scale-free networks, whereas if other designing choices cannot be determined beforehand, ER network is a markedly good candidate for cost-effective and scalable design.


Feeds as Query Result Serializations

Abstract: Many Web-based data sources and services are available as feeds, a model that provides consumers with a loosely coupled way of interacting with providers. The current feed model is limited in its capabilities, however. Though it is simple to implement and scales well, it cannot be transferred to a wider range of application scenarios. This paper conceptualizes feeds as a way to serialize query results, describes the current hardcoded query semantics of such a perspective, and surveys the ways in which extensions of this hardcoded model have been proposed or implemented. Our generalized view of feeds as query result serializations has implications for the applicability of feeds as a generic Web service for any collection that is providing access to individual information items. As one interesting and compelling class of applications, we describe a simple way in which a query-based approach to feeds can be used to support location-based services.


Approximation Schemes for the Betweenness Problem in Tournaments and Related Ranking Problems

Abstract: We design the first polynomial time approximation schemes (PTASs) for the Minimum Betweenness problem in tournaments and some related higher arity ranking problems. This settles the approximation status of the Betweenness problem in tournaments along with other ranking problems which were open for some time now. The results depend on a new technique of dealing with fragile ranking constraints and could be of independent interest.


Pseudo-Power Avoidance

Abstract: Repetition avoidance has been studied since Thue's work. In this paper, we considered another type of repetition, which is called pseudo-power. This concept is inspired by Watson-Crick complementarity in DNA sequence and is defined over an antimorphic involution $\phi$. We first classify the alphabet $\Sigma$ and the antimorphic involution $\phi$, under which there exists sufficiently long pseudo-$k$th-power-free words. Then we present algorithms to test whether a finite word $w$ is pseudo-$k$th-power-free.


An Iteratively Reweighted Algorithm for Sparse Reconstruction of Subsurface Flow Properties from Nonlinear Dynamic Data

Abstract: In this paper, we present a practical algorithm based on sparsity regularization to effectively solve nonlinear dynamic inverse problems that are encountered in subsurface model calibration. We use an iteratively reweighted algorithm that is widely used to solve linear inverse problems with sparsity constraint known as compressed sensing to estimate permeability fields from nonlinear dynamic flow data.


PageRank Optimization by Edge Selection

Abstract: The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts - including ranking websites - and can be interpreted as the average portion of time spent at the node by an infinite random walk. We consider the problem of maximizing the PageRank of a node by selecting some of the edges from a set of edges that are under our control. By applying results from Markov decision theory, we show that an optimal solution to this problem can be found in polynomial time. Our core solution results in a linear programming formulation, but we also provide an alternative greedy algorithm, a variant of policy iteration, which runs in polynomial time, as well. Finally, we show that, under the slight modification for which we are given mutually exclusive pairs of edges, the problem of PageRank optimization becomes NP-hard.


A New Look at the Classical Entropy of Written English

Abstract: A simple method for finding the entropy and redundancy of a reasonable long sample of English text by direct computer processing and from first principles according to Shannon theory is presented. As an example, results on the entropy of the English language have been obtained based on a total of 20.3 million characters of written English, considering symbols from one to five hundred characters in length. Besides a more realistic value of the entropy of English, a new perspective on some classic entropy-related concepts is presented. This method can also be extended to other Latin languages. Some implications for practical applications such as plagiarism-detection software, and the minimum number of words that should be used in social Internet network messaging, are discussed.


A Robust Control Framework for Malware Filtering

Abstract: We study and develop a robust control framework for malware filtering and network security. We investigate the malware filtering problem by capturing the tradeoff between increased security on one hand and continued usability of the network on the other. We analyze the problem using a linear control system model with a quadratic cost structure and develop algorithms based on H infinity-optimal control theory. A dynamic feedback filter is derived and shown via numerical analysis to be an improvement over various heuristic approaches to malware filtering. The results are verified and demonstrated with packet level simulations on the Ns-2 network simulator.


Algorithms for Quantum Branching Programs Based on Fingerprinting

Abstract: In the paper we develop a method for constructing quantum algorithms for computing Boolean functions by quantum ordered read-once branching programs (quantum OBDDs). Our method is based on fingerprinting technique and representation of Boolean functions by their characteristic polynomials. We use circuit notation for branching programs for desired algorithms presentation. For several known functions our approach provides optimal QOBDDs. Namely we consider such functions as Equality, Palindrome, and Permutation Matrix Test. We also propose a generalization of our method and apply it to the Boolean variant of the Hidden Subgroup Problem.


Orthomodular Lattices Induced by the Concurrency Relation

Abstract: We apply to locally finite partially ordered sets a construction which associates a complete lattice to a given poset; the elements of the lattice are the closed subsets of a closure operator, defined starting from the concurrency relation. We show that, if the partially ordered set satisfies a property of local density, i.e.: N-density, then the associated lattice is also orthomodular. We then consider occurrence nets, introduced by C.A. Petri as models of concurrent computations, and define a family of subsets of the elements of an occurrence net; we call those subsets "causally closed" because they can be seen as subprocesses of the whole net which are, intuitively, closed with respect to the forward and backward local state changes. We show that, when the net is K-dense, the causally closed sets coincide with the closed sets induced by the closure operator defined starting from the concurrency relation. K-density is a property of partially ordered sets introduced by Petri, on the basis of former axiomatizations of special relativity theory.


Circular Languages Generated by Complete Splicing Systems and Pure Unitary Languages

Abstract: Circular splicing systems are a formal model of a generative mechanism of circular words, inspired by a recombinant behaviour of circular DNA. Some unanswered questions are related to the computational power of such systems, and finding a characterization of the class of circular languages generated by circular splicing systems is still an open problem. In this paper we solve this problem for complete systems, which are special finite circular splicing systems. We show that a circular language L is generated by a complete system if and only if the set Lin(L) of all words corresponding to L is a pure unitary language generated by a set closed under the conjugacy relation. The class of pure unitary languages was introduced by A. Ehrenfeucht, D. Haussler, G. Rozenberg in 1983, as a subclass of the class of context-free languages, together with a characterization of regular pure unitary languages by means of a decidable property. As a direct consequence, we characterize (regular) circular languages generated by complete systems. We can also decide whether the language generated by a complete system is regular. Finally, we point out that complete systems have the same computational power as finite simple systems, an easy type of circular splicing system defined in the literature from the very beginning, when only one rule is allowed. From our results on complete systems, it follows that finite simple systems generate a class of context-free languages containing non-regular languages, showing the incorrectness of a longstanding result on simple systems.


Random Constraint Satisfaction Problems

Abstract: Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with probability close to one due to non-constructive arguments. However, no algorithms are known to find solutions efficiently with a non-vanishing probability at even much lower densities. This fact appears to be related to a phase transition in the set of all solutions. The goal of this extended abstract is to provide a perspective on this phenomenon, and on the computational challenge that it poses.


A Type System for Required/Excluded Elements in CLS

Abstract: The calculus of looping sequences is a formalism for describing the evolution of biological systems by means of term rewriting rules. We enrich this calculus with a type discipline to guarantee the soundness of reduction rules with respect to some biological properties deriving from the requirement of certain elements, and the repellency of others. As an example, we model a toy system where the repellency of a certain element is captured by our type system and forbids another element to exit a compartment.


Deterministic Autopoietic Automata

Abstract: This paper studies two issues related to the paper on Computing by Self-reproduction: Autopoietic Automata by Jiri Wiedermann. It is shown that all results presented there extend to deterministic computations. In particular, nondeterminism is not needed for a lineage to generate all autopoietic automata.


Characterizing Polynomial Time Computability of Rational and Real Functions

Abstract: Recursive analysis was introduced by A. Turing [1936], A. Grzegorczyk [1955], and D. Lacombe [1955]. It is based on a discrete mechanical framework that can be used to model computation over the real numbers. In this context the computational complexity of real functions defined over compact domains has been extensively studied. However, much less have been done for other kinds of real functions. This article is divided into two main parts. The first part investigates polynomial time computability of rational functions and the role of continuity in such computation. On the one hand this is interesting for its own sake. On the other hand it provides insights into polynomial time computability of real functions for the latter, in the sense of recursive analysis, is modeled as approximations of rational computations. The main conclusion of this part is that continuity does not play any role in the efficiency of computing rational functions. The second part defines polynomial time computability of arbitrary real functions, characterizes it, and compares it with the corresponding notion over rational functions. Assuming continuity, the main conclusion is that there is a conceptual difference between polynomial time computation over the rationals and the reals manifested by the fact that there are polynomial time computable rational functions whose extensions to the reals are not polynomial time computable and vice versa.


Emotion: Appraisal-coping model for the "Cascades" problem

Abstract: Modelling emotion has become a challenge nowadays. Therefore, several models have been produced in order to express human emotional activity. However, only a few of them are currently able to express the close relationship existing between emotion and cognition. An appraisal-coping model is presented here, with the aim to simulate the emotional impact caused by the evaluation of a particular situation (appraisal), along with the consequent cognitive reaction intended to face the situation (coping). This model is applied to the "Cascades" problem, a small arithmetical exercise designed for ten-year-old pupils. The goal is to create a model corresponding to a child's behaviour when solving the problem using his own strategies.


Towards a Number Theoretic Discrete Hilbert Transform

Abstract: This paper presents an approach for the development of a number theoretic discrete Hilbert transform. The forward transformation has been applied by taking the odd reciprocals that occur in the DHT matrix with respect to a power of 2. Specifically, the expression for a 16-point transform is provided and results of a few representative signals are provided. The inverse transform is the inverse of the forward 16-point matrix. But at this time the inverse transform is not identical to the forward transform and, therefore, our proposed number theoretic transform must be taken as a provisional result.


Memoryless Routing in Convex Subdivisions: Random Walks are Optimal

Abstract: A memoryless routing algorithm is one in which the decision about the next edge on the route to a vertex t for a packet currently located at vertex v is made based only on the coordinates of v, t, and the neighbourhood, N(v), of v. The current paper explores the limitations of such algorithms by showing that, for any (randomized) memoryless routing algorithm A, there exists a convex subdivision on which A takes Omega(n^2) expected time to route a message between some pair of vertices. Since this lower bound is matched by a random walk, this result implies that the geometric information available in convex subdivisions is not helpful for this class of routing algorithms. The current paper also shows the existence of triangulations for which the Random-Compass algorithm proposed by Bose etal (2002,2004) requires 2^{\Omega(n)} time to route between some pair of vertices.


Emotion : mod\`ele d'appraisal-coping pour le probl\`eme des Cascades

Abstract: Modeling emotion has become a challenge nowadays. Therefore, several models have been produced in order to express human emotional activity. However, only a few of them are currently able to express the close relationship existing between emotion and cognition. An appraisal-coping model is presented here, with the aim to simulate the emotional impact caused by the evaluation of a particular situation (appraisal), along with the consequent cognitive reaction intended to face the situation (coping). This model is applied to the ?Cascades? problem, a small arithmetical exercise designed for ten-year-old pupils. The goal is to create a model corresponding to a child's behavior when solving the problem using his own strategies.


Rule-based Modelling and Tunable Resolution

Abstract: We investigate the use of an extension of rule-based modelling for cellular signalling to create a structured space of model variants. This enables the incremental development of rule sets that start from simple mechanisms and which, by a gradual increase in agent and rule resolution, evolve into more detailed descriptions.


Euclidean versus hyperbolic congestion in idealized versus experimental networks

Abstract: This paper proposes a mathematical justification of the phenomenon of extreme congestion at a very limited number of nodes in very large networks. It is argued that this phenomenon occurs as a combination of the negative curvature property of the network together with minimum length routing. More specifically, it is shown that, in a large n-dimensional hyperbolic ball B of radius R viewed as a roughly similar model of a Gromov hyperbolic network, the proportion of traffic paths transiting through a small ball near the center is independent of the radius R whereas, in a Euclidean ball, the same proportion scales as 1/R^{n-1}. This discrepancy persists for the traffic load, which at the center of the hyperbolic ball scales as the square of the volume, whereas the same traffic load scales as the volume to the power (n+1)/n in the Euclidean ball. This provides a theoretical justification of the experimental exponent discrepancy observed by Narayan and Saniee between traffic loads in Gromov-hyperbolic networks from the Rocketfuel data base and synthetic Euclidean lattice networks. It is further conjectured that for networks that do not enjoy the obvious symmetry of hyperbolic and Euclidean balls, the point of maximum traffic is near the center of mass of the network.


Tile Packing Tomography is NP-hard

Abstract: Discrete tomography deals with reconstructing finite spatial objects from lower dimensional projections and has applications for example in timetable design. In this paper we consider the problem of reconstructing a tile packing from its row and column projections. It consists of disjoint copies of a fixed tile, all contained in some rectangular grid. The projections tell how many cells are covered by a tile in each row and column. How difficult is it to construct a tile packing satisfying given projections? It was known to be solvable by a greedy algorithm for bars (tiles of width or height 1), and NP-hardness results were known for some specific tiles. This paper shows that the problem is NP-hard whenever the tile is not a bar.


Cybermatter

Abstract: In this paper we examine several aspects of the impact of Cyberworld onto our Reality conceptions, and their social implications.


Active Flows in Diagnostic of Troubleshooting on Backbone Links

Abstract: This paper aims to identify the operational region of a link in terms of its utilization and alert operators at the point where the link becomes overloaded and requires a capacity upgrade. The number of active flows is considered the real network state and is proposed to use a proxy for utilization. The Gaussian approximation gives the expression for the confidence interval on an operational region. The easy rule has been formulated to display the network defects by means of measurements of router loading and number of active flows. Mean flow performance is considered as the basic universal index characterized quality of network services provided to single user.


Performance Analysis of MANET Routing Protocols Using An Elegant Visual Simulation Tool

Abstract: The task of simulation is often complicated for which many naive users often seek for relatively easier solutions. In many cases, simulations are done without any visual output which makes them non-attractive. In this paper, we present ViSim; a new simulation tool that has a user-friendly graphical interface. ViSim could be useful for researchers, students, teachers in their works, and for the demonstration of various wireless network scenarios on computer screen. It could make the task of simulation more exciting and enhance the interest of the users without going into complex command-only text interface. ViSim is not a simulation engine rather it calls ns-2 simulations in the background and makes the task easy for the users to visualize the simulation in Windows environment. Though ViSim is mainly a simulation demonstration tool, any user with the knowledge of ns-2 and Tcl scripting is also allowed to do necessary modifications and quick configurations for any other MANET routing scenario. Using our simulation tool, we measured the performances of several Mobile Ad-hoc Network (MANET) routing protocols. In this paper, we present the performance analysis of three prominent MANET routing protocols; DSDV, DSR, and AODV using our tool. The details of various features of ViSim, brief descriptions of the selected routing protocols and their comparisons, details about the performed experiments, and the gained results are presented in this work.


Measuring contextual citation impact of scientific journals

Abstract: This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject field, especially the frequency at which authors cite other papers in their reference lists, the rapidity of maturing of citation impact, and the extent to which a database used for the assessment covers the field's literature. It further develops Eugene Garfield's notions of a field's 'citation potential' defined as the average length of references lists in a field and determining the probability of being cited, and the need in fair performance assessments to correct for differences between subject fields. A journal's subject field is defined as the set of papers citing that journal. SNIP is defined as the ratio of the journal's citation count per paper and the citation potential in its subject field. It aims to allow direct comparison of sources in different subject fields. Citation potential is shown to vary not only between journal subject categories - groupings of journals sharing a research field - or disciplines (e.g., journals in mathematics, engineering and social sciences tend to have lower values than titles in life sciences), but also between journals within the same subject category. For instance, basic journals tend to show higher citation potentials than applied or clinical journals, and journals covering emerging topics higher than periodicals in classical subjects or more general journals. SNIP corrects for such differences. Its strengths and limitations are critically discussed, and suggestions are made for further research. All empirical results are derived from Elsevier's Scopus.


Robustness of a bisimulation-type faster-than preorder

Abstract: TACS is an extension of CCS where upper time bounds for delays can be specified. Luettgen and Vogler defined three variants of bismulation-type faster-than relations and showed that they all three lead to the same preorder, demonstrating the robustness of their approach. In the present paper, the operational semantics of TACS is extended; it is shown that two of the variants still give the same preorder as before, underlining robustness. An explanation is given why this result fails for the third variant. It is also shown that another variant, which mixes old and new operational semantics, can lead to smaller relations that prove the same preorder.


NP Datalog: a Logic Language for Expressing NP Search and Optimization Problems

Abstract: This paper presents a logic language for expressing NP search and optimization problems. Specifically, first a language obtained by extending (positive) Datalog with intuitive and efficient constructs (namely, stratified negation, constraints and exclusive disjunction) is introduced. Next, a further restricted language only using a restricted form of disjunction to define (non-deterministically) subsets (or partitions) of relations is investigated. This language, called NP Datalog, captures the power of Datalog with unstratified negation in expressing search and optimization problems. A system prototype implementing NP Datalog is presented. The system translates NP Datalog queries into OPL programs which are executed by the ILOG OPL Development Studio. Our proposal combines easy formulation of problems, expressed by means of a declarative logic language, with the efficiency of the ILOG System. Several experiments show the effectiveness of this approach.


On the Minimum Size of a Contraction-Universal Tree

Abstract: A tree T_uni is m-universal for the class of trees if for every tree T of size m, T can be obtained from T_uni by successive contractions of edges. We prove that a m-universal tree for the class of trees has at least mln(m) + (gamma-1)m + O(1) edges where is the Euler's constant and we build such a tree with less than mc edges for a fixed constant c = 1.984...


Proceedings Fifth Workshop on Developments in Computational Models--Computational Models From Nature

Abstract: The special theme of DCM 2009, co-located with ICALP 2009, concerned Computational Models From Nature, with a particular emphasis on computational models derived from physics and biology. The intention was to bring together different approaches - in a community with a strong foundational background as proffered by the ICALP attendees - to create inspirational cross-boundary exchanges, and to lead to innovative further research. Specifically DCM 2009 sought contributions in quantum computation and information, probabilistic models, chemical, biological and bio-inspired ones, including spatial models, growth models and models of self-assembly. Contributions putting to the test logical or algorithmic aspects of computing (e.g., continuous computing with dynamical systems, or solid state computing models) were also very much welcomed.


Neural Networks for Dynamic Shortest Path Routing Problems - A Survey

Abstract: This paper reviews the overview of the dynamic shortest path routing problem and the various neural networks to solve it. Different shortest path optimization problems can be solved by using various neural networks algorithms. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The survey shows that the neural networks are the best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other softcomputing and metaheuristics algorithms


Global communications in multiprocessor simulations of flames

Abstract: In this paper we investigate performance of global communications in a particular parallel code. The code simulates dynamics of expansion of premixed spherical flames using an asymptotic model of Sivashinsky type and a spectral numerical algorithm. As a result, the code heavily relies on global all-to-all interprocessor communications implementing transposition of the distributed data array in which numerical solution to the problem is stored. This global data interdependence makes interprocessor connectivity of the HPC system as important as the floating-point power of the processors of which the system is built. Our experiments show that efficient numerical simulation of this particular model, with global data interdependence, on modern HPC systems is possible. Prospects of performance of more sophisticated models of flame dynamics are analysed as well.


Coding Guidelines for Prolog

Abstract: Coding standards and good practices are fundamental to a disciplined approach to software projects, whatever programming languages they employ. Prolog programming can benefit from such an approach, perhaps more than programming in other languages. Despite this, no widely accepted standards and practices seem to have emerged up to now. The present paper is a first step towards filling this void: it provides immediate guidelines for code layout, naming conventions, documentation, proper use of Prolog features, program development, debugging and testing. Presented with each guideline is its rationale and, where sensible options exist, illustrations of the relative pros and cons for each alternative. A coding standard should always be selected on a per-project basis, based on a host of issues pertinent to any given programming project; for this reason the paper goes beyond the mere provision of normative guidelines by discussing key factors and important criteria that should be taken into account when deciding on a fully-fledged coding standard for the project.


Simulation of Pedestrians Crossing a Street

Abstract: The simulation of vehicular traffic as well as pedestrian dynamics meanwhile both have a decades long history. The success of this conference series, PED and others show that the interest in these topics is still strongly increasing. This contribution deals with a combination of both systems: pedestrians crossing a street. In a VISSIM simulation for varying demand jam sizes of vehicles as well as pedestrians and the travel times of the pedestrians are measured and compared. The study is considered as a study of VISSIM's con ict area functionality as such, as there is no empirical data available to use for calibration issues. Above a vehicle demand threshold the results show a non-monotonic dependence of pedestrians' travel time on pedestrian demand.


Sequential anomaly detection in the presence of noise and limited feedback

Abstract: This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) {\em filtering}, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations, and (2) {\em hedging}, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed approach lie exponential-family models which can be used in a wide variety of contexts and applications, and which yield methods that achieve sublinear per-round regret against both static and slowly varying product distributions with marginals drawn from the same exponential family. Moreover, the regret against static distributions coincides with the minimax value of the corresponding online strongly convex game. We also prove bounds on the number of mistakes made during the hedging step relative to the best offline choice of the threshold with access to all estimated beliefs and feedback signals. We validate the theory on synthetic data drawn from a time-varying distribution over binary vectors of high dimensionality, as well as on the Enron email dataset.


A Recursive Definition of the Holographic Standard Signature

Abstract: We provide a recursive description of the signatures realizable on the standard basis by a holographic algorithm. The description allows us to prove tight bounds on the size of planar matchgates and efficiently test for standard signatures. Over finite fields, it allows us to count the number of n-bit standard signatures and calculate their expected sparsity.


Synthesizing Minimal Tile Sets for Patterned DNA Self-Assembly

Abstract: The Pattern self-Assembly Tile set Synthesis (PATS) problem is to determine a set of coloured tiles that self-assemble to implement a given rectangular colour pattern. We give an exhaustive branch-and-bound algorithm to find tile sets of minimum cardinality for the PATS problem. Our algorithm makes use of a search tree in the lattice of partitions of the ambient rectangular grid, and an efficient bounding function to prune this search tree. Empirical data on the performance of the algorithm shows that it compares favourably to previously presented heuristic solutions to the problem.


Breaching Euclidean Distance-Preserving Data Perturbation Using Few Known Inputs

Abstract: We examine Euclidean distance-preserving data perturbation as a tool for privacy-preserving data mining. Such perturbations allow many important data mining algorithms e.g. hierarchical and k-means clustering), with only minor modification, to be applied to the perturbed data and produce exactly the same results as if applied to the original data. However, the issue of how well the privacy of the original data is preserved needs careful study. We engage in this study by assuming the role of an attacker armed with a small set of known original data tuples (inputs). Little work has been done examining this kind of attack when the number of known original tuples is less than the number of data dimensions. We focus on this important case, develop and rigorously analyze an attack that utilizes any number of known original tuples. The approach allows the attacker to estimate the original data tuple associated with each perturbed tuple and calculate the probability that the estimation results in a privacy breach. On a real 16-dimensional dataset, we show that the attacker, with 4 known original tuples, can estimate an original unknown tuple with less than 7% error with probability exceeding 0.8.


A Dynamic Near-Optimal Algorithm for Online Linear Programming

Abstract: A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) in which the constraint matrix is revealed column by column along with the corresponding objective coefficient. In such a model, a decision variable has to be set each time a column is revealed without observing the future inputs and the goal is to maximize the overall objective function. In this paper, we provide a near-optimal algorithm for this general class of online problems under the assumption of random order of arrival and some mild conditions on the size of the LP right-hand-side input. Specifically, our learning-based algorithm works by dynamically updating a threshold price vector at geometric time intervals, where the dual prices learned from the revealed columns in the previous period are used to determine the sequential decisions in the current period. Due to the feature of dynamic learning, the competitiveness of our algorithm improves over the past study of the same problem. We also present a worst-case example showing that the performance of our algorithm is near-optimal.


A two-level logic approach to reasoning about computations

Abstract: Relational descriptions have been used in formalizing diverse computational notions, including, for example, operational semantics, typing, and acceptance by non-deterministic machines. We therefore propose a (restricted) logical theory over relations as a language for specifying such notions. Our specification logic is further characterized by an ability to explicitly treat binding in object languages. Once such a logic is fixed, a natural next question is how we might prove theorems about specifications written in it. We propose to use a second logic, called a reasoning logic, for this purpose. A satisfactory reasoning logic should be able to completely encode the specification logic. Associated with the specification logic are various notions of binding: for quantifiers within formulas, for eigenvariables within sequents, and for abstractions within terms. To provide a natural treatment of these aspects, the reasoning logic must encode binding structures as well as their associated notions of scope, free and bound variables, and capture-avoiding substitution. Further, to support arguments about provability, the reasoning logic should possess strong mechanisms for constructing proofs by induction and co-induction. We provide these capabilities here by using a logic called G which represents relations over lambda-terms via definitions of atomic judgments, contains inference rules for induction and co-induction, and includes a special generic quantifier. We show how provability in the specification logic can be transparently encoded in G. We also describe an interactive theorem prover called Abella that implements G and this two-level logic approach and we present several examples that demonstrate the efficacy of Abella in reasoning about computations.


The hardness of routing two pairs on one face

Abstract: We prove the NP-completeness of the integer multiflow problem in planar graphs, with the following restrictions: there are only two demand edges, both lying on the infinite face of the routing graph. This was one of the open challenges concerning disjoint paths, explicitly asked by M\"uller. It also strengthens Schw\"arzler's recent proof of one of the open problems of Schrijver's book, about the complexity of the edge-disjoint paths problem with terminals on the outer boundary of a planar graph. We also give a directed acyclic reduction. This proves that the arc-disjoint paths problem is NP-complete in directed acyclic graphs, even with only two demand arcs.


Fault-Tolerance through Message-logging and Check-pointing: Disaster Recovery for CORBA-based Distributed Bank Servers

Abstract: This report presents results of our endeavor towards developing a failure-recovery variant of a CORBA-based bank server that provides fault tolerance features through message logging and checkpoint logging. In this group of projects, three components were developed to satisfy the requirements: 1) a message-logging protocol for the branch servers of the distributed banking system to log required information; 2) a recovery module that restarts the bank server using the message log to help the restarted bank server process subsequent requests for various operations; 3) a monitor module that periodically checks whether the bank server is down and helps the recovery module restart the bank server if the latter has crashed.


Faster exponentials of power series

Abstract: We describe a new algorithm for computing exp(f) where f is a power series in C[[x]]. If M(n) denotes the cost of multiplying polynomials of degree n, the new algorithm costs (2.1666... + o(1)) M(n) to compute exp(f) to order n. This improves on the previous best result, namely (2.333... + o(1)) M(n).


A computational model of the bottlenose dolphin sonar: Feature-extracting method

Abstract: The data describing a process of echo-image formation in bottlenose dolphin sonar perception were accumulated in our experimental explorations. These data were formalized mathematically and used in the computational model, comparative testing of which in echo-discrimination tasks revealed no less capabilities then those of bottlenose dolphins.


Bounding Rationality by Discounting Time

Abstract: Consider a game where Alice generates an integer and Bob wins if he can factor that integer. Traditional game theory tells us that Bob will always win this game even though in practice Alice will win given our usual assumptions about the hardness of factoring. We define a new notion of bounded rationality, where the payoffs of players are discounted by the computation time they take to produce their actions. We use this notion to give a direct correspondence between the existence of equilibria where Alice has a winning strategy and the hardness of factoring. Namely, under a natural assumption on the discount rates, there is an equilibriumwhere Alice has a winning strategy iff there is a linear-time samplable distribution with respect to which Factoring is hard on average. We also give general results for discounted games over countable action spaces, including showing that any game with bounded and computable payoffs has an equilibrium in our model, even if each player is allowed a countable number of actions. It follows, for example, that the Largest Integer game has an equilibrium in our model though it has no Nash equilibria or epsilon-Nash equilibria.


Proceedings 16th International Workshop on Expressiveness in Concurrency

Abstract: This volume contains the proceedings of the 16th International Workshop on Expressiveness in Concurrency (EXPRESS'09), which took place on 5th September 2009 in Bologna, co-located with CONCUR'09. The EXPRESS workshop series aim at bringing together researchers who are interested in the expressiveness and comparison of formal models that broadly relate to concurrency. In particular, this also includes emergent fields such as logic and interaction, game-theoretic models, and service-oriented computing.


Efficient Distributed Random Walks with Applications

Abstract: We focus on the problem of performing random walks efficiently in a distributed network. Given bandwidth constraints, the goal is to minimize the number of rounds required to obtain a random walk sample. We first present a fast sublinear time distributed algorithm for performing random walks whose time complexity is sublinear in the length of the walk. Our algorithm performs a random walk of length $\ell$ in $\tilde{O}(\sqrt{\ell D})$ rounds (with high probability) on an undirected network, where $D$ is the diameter of the network. This improves over the previous best algorithm that ran in $\tilde{O}(\ell^{2/3}D^{1/3})$ rounds (Das Sarma et al., PODC 2009). We further extend our algorithms to efficiently perform $k$ independent random walks in $\tilde{O}(\sqrt{k\ell D} + k)$ rounds. We then show that there is a fundamental difficulty in improving the dependence on $\ell$ any further by proving a lower bound of $\Omega(\sqrt{\frac{\ell}{\log \ell}} + D)$ under a general model of distributed random walk algorithms. Our random walk algorithms are useful in speeding up distributed algorithms for a variety of applications that use random walks as a subroutine. We present two main applications. First, we give a fast distributed algorithm for computing a random spanning tree (RST) in an arbitrary (undirected) network which runs in $\tilde{O}(\sqrt{m}D)$ rounds (with high probability; here $m$ is the number of edges). Our second application is a fast decentralized algorithm for estimating mixing time and related parameters of the underlying network. Our algorithm is fully decentralized and can serve as a building block in the design of topologically-aware networks.


Apply Ant Colony Algorithm to Search All Extreme Points of Function

Abstract: To find all extreme points of multimodal functions is called extremum problem, which is a well known difficult issue in optimization fields. Applying ant colony optimization (ACO) to solve this problem is rarely reported. The method of applying ACO to solve extremum problem is explored in this paper. Experiment shows that the solution error of the method presented in this paper is less than 10^-8. keywords: Extremum Problem; Ant Colony Optimization (ACO)


Bifinite Chu Spaces

Abstract: This paper studies colimits of sequences of finite Chu spaces and their ramifications. Besides generic Chu spaces, we consider extensional and biextensional variants. In the corresponding categories we first characterize the monics and then the existence (or the lack thereof) of the desired colimits. In each case, we provide a characterization of the finite objects in terms of monomorphisms/injections. Bifinite Chu spaces are then expressed with respect to the monics of generic Chu spaces, and universal, homogeneous Chu spaces are shown to exist in this category. Unanticipated results driving this development include the fact that while for generic Chu spaces monics consist of an injective first and a surjective second component, in the extensional and biextensional cases the surjectivity requirement can be dropped. Furthermore, the desired colimits are only guaranteed to exist in the extensional case. Finally, not all finite Chu spaces (considered set-theoretically) are finite objects in their categories. This study opens up opportunities for further investigations into recursively defined Chu spaces, as well as constructive models of linear logic.


A Tighter Bound for the Determinization of Visibly Pushdown Automata

Abstract: Visibly pushdown automata (VPA), introduced by Alur and Madhusuan in 2004, is a subclass of pushdown automata whose stack behavior is completely determined by the input symbol according to a fixed partition of the input alphabet. Since its introduce, VPAs have been shown to be useful in various context, e.g., as specification formalism for verification and as automaton model for processing XML streams. Due to high complexity, however, implementation of formal verification based on VPA framework is a challenge. In this paper we consider the problem of implementing VPA-based model checking algorithms. For doing so, we first present an improvement on upper bound for determinization of VPA. Next, we propose simple on-the-fly algorithms to check universality and inclusion problems of this automata class. Then, we implement the proposed algorithms in a prototype tool. Finally, we conduct experiments on randomly generated VPAs. The experimental results show that the proposed algorithms are considerably faster than the standard ones.


An Inverse Method for Policy-Iteration Based Algorithms

Abstract: We present an extension of two policy-iteration based algorithms on weighted graphs (viz., Markov Decision Problems and Max-Plus Algebras). This extension allows us to solve the following inverse problem: considering the weights of the graph to be unknown constants or parameters, we suppose that a reference instantiation of those weights is given, and we aim at computing a constraint on the parameters under which an optimal policy for the reference instantiation is still optimal. The original algorithm is thus guaranteed to behave well around the reference instantiation, which provides us with some criteria of robustness. We present an application of both methods to simple examples. A prototype implementation has been done.


Automated Predicate Abstraction for Real-Time Models

Abstract: We present a technique designed to automatically compute predicate abstractions for dense real-timed models represented as networks of timed automata. We use the CIPM algorithm in our previous work which computes new invariants for timed automata control locations and prunes the model, to compute a predicate abstraction of the model. We do so by taking information regarding control locations and their newly computed invariants into account.


On external presentations of infinite graphs

Abstract: The vertices of a finite state system are usually a subset of the natural numbers. Most algorithms relative to these systems only use this fact to select vertices. For infinite state systems, however, the situation is different: in particular, for such systems having a finite description, each state of the system is a configuration of some machine. Then most algorithmic approaches rely on the structure of these configurations. Such characterisations are said internal. In order to apply algorithms detecting a structural property (like identifying connected components) one may have first to transform the system in order to fit the description needed for the algorithm. The problem of internal characterisation is that it hides structural properties, and each solution becomes ad hoc relatively to the form of the configurations. On the contrary, external characterisations avoid explicit naming of the vertices. Such characterisation are mostly defined via graph transformations. In this paper we present two kind of external characterisations: deterministic graph rewriting, which in turn characterise regular graphs, deterministic context-free languages, and rational graphs. Inverse substitution from a generator (like the complete binary tree) provides characterisation for prefix-recognizable graphs, the Caucal Hierarchy and rational graphs. We illustrate how these characterisation provide an efficient tool for the representation of infinite state systems.


Recognizing well-parenthesized expressions in the streaming model

Abstract: Motivated by a concrete problem and with the goal of understanding the sense in which the complexity of streaming algorithms is related to the complexity of formal languages, we investigate the problem Dyck(s) of checking matching parentheses, with $s$ different types of parenthesis. We present a one-pass randomized streaming algorithm for Dyck(2) with space $\Order(\sqrt{n}\log n)$, time per letter $\polylog (n)$, and one-sided error. We prove that this one-pass algorithm is optimal, up to a $\polylog n$ factor, even when two-sided error is allowed. For the lower bound, we prove a direct sum result on hard instances by following the "information cost" approach, but with a few twists. Indeed, we play a subtle game between public and private coins. This mixture between public and private coins results from a balancing act between the direct sum result and a combinatorial lower bound for the base case. Surprisingly, the space requirement shrinks drastically if we have access to the input stream in reverse. We present a two-pass randomized streaming algorithm for Dyck(2) with space $\Order((\log n)^2)$, time $\polylog (n)$ and one-sided error, where the second pass is in the reverse direction. Both algorithms can be extended to Dyck(s) since this problem is reducible to Dyck(2) for a suitable notion of reduction in the streaming model.


Understanding the Principles of Recursive Neural networks: A Generative Approach to Tackle Model Complexity

Abstract: Recursive Neural Networks are non-linear adaptive models that are able to learn deep structured information. However, these models have not yet been broadly accepted. This fact is mainly due to its inherent complexity. In particular, not only for being extremely complex information processing models, but also because of a computational expensive learning phase. The most popular training method for these models is back-propagation through the structure. This algorithm has been revealed not to be the most appropriate for structured processing due to problems of convergence, while more sophisticated training methods enhance the speed of convergence at the expense of increasing significantly the computational cost. In this paper, we firstly perform an analysis of the underlying principles behind these models aimed at understanding their computational power. Secondly, we propose an approximate second order stochastic learning algorithm. The proposed algorithm dynamically adapts the learning rate throughout the training phase of the network without incurring excessively expensive computational effort. The algorithm operates in both on-line and batch modes. Furthermore, the resulting learning scheme is robust against the vanishing gradients problem. The advantages of the proposed algorithm are demonstrated with a real-world application example.


Some Models and Tools for Open Systems

Abstract: In computer science, there is a distinction between closed systems, whose behavior is totally determined in advance, and open systems, that are systems maintaining a constant interaction with an unspecified environment. Closed systems are naturally modeled by transitions systems. Open systems have been modeled in various ways, including process algebras, I/O automata, ``modules'', and interfaces. Games provide a uniform setting in which all these models can be cast and compared. In this paper, we discuss the features and costs related to the game-based approach to open systems, referring to some of the existing models. Finally, we describe a new model of interface, called sociable interface, which is geared towards easier specification, improved reusability of models, and efficient symbolic implementation.


Le travail coop\'eratif comme vecteur d'\'evolution de nos syst\`emes d'information

Abstract: This article focuses on presenting the cooperative tool DIMS, it is a platform that can manage the participants's daily life, by providing flexibility and speed in the organization's tasks. The main interest lies in the possibility of organizing information system in a logical network, across multiple physical sites, incorporating a specific protocol to making possible the inter-server communication. This protocol, based on the Jabber standard, that meets the needs of working everyday matters, allowing the distribution of research and access to resources of the WAN. The technological objective concerns the evolution of an information system architectures, where the application may be a comprehensive set of tools and services on a distributed network of remote sites. The challenge for users is the perception of a collective role to each individual who cooperates in compliance with safety rules and unlimited access to technical information.


Keystroke Dynamics Authentication For Collaborative Systems

Abstract: We present in this paper a study on the ability and the benefits of using a keystroke dynamics authentication method for collaborative systems. Authentication is a challenging issue in order to guarantee the security of use of collaborative systems during the access control step. Many solutions exist in the state of the art such as the use of one time passwords or smart-cards. We focus in this paper on biometric based solutions that do not necessitate any additional sensor. Keystroke dynamics is an interesting solution as it uses only the keyboard and is invisible for users. Many methods have been published in this field. We make a comparative study of many of them considering the operational constraints of use for collaborative systems.


Software Engineering Education by Example

Abstract: Based on the old but famous distinction between "in the small" and "in the large" software development, at Nancy Universit\'e, UHP Nancy 1, we experience for a while software engineering education thanks to actual project engineering. This education method has the merit to enable students to discover and to overcome actual problems when faced to a large project which may be conducted by a large development team. The mode of education is a simulation of an actual software engineering project as encountered in "real life\'e" activities.


Re-Pair Compression of Inverted Lists

Abstract: Compression of inverted lists with methods that support fast intersection operations is an active research topic. Most compression schemes rely on encoding differences between consecutive positions with techniques that favor small numbers. In this paper we explore a completely different alternative: We use Re-Pair compression of those differences. While Re-Pair by itself offers fast decompression at arbitrary positions in main and secondary memory, we introduce variants that in addition speed up the operations required for inverted list intersection. We compare the resulting data structures with several recent proposals under various list intersection algorithms, to conclude that our Re-Pair variants offer an interesting time/space tradeoff for this problem, yet further improvements are required for it to improve upon the state of the art.


Final Architecture Specification of security, privacy, and incentive mechanisms

Abstract: In this document, we define the NADA security architecture based on refined use case scenarios, a derived high level model and security analysis. For the architecure design and verification we are applying the well known STRIDE model.