Author-choice open access publishing in the biological and medical literature: a citation analysis

Abstract: In this article, we analyze the citations to articles published in 11 biological and medical journals from 2003 to 2007 that employ author-choice open access models. Controlling for known explanatory predictors of citations, only 2 of the 11 journals show positive and significant open access effects. Analyzing all journals together, we report a small but significant increase in article citations of 17%. In addition, there is strong evidence to suggest that the open access advantage is declining by about 7% per year, from 32% in 2004 to 11% in 2007.


A Simple E-Voting Protocol

Abstract: We propose an e-voting protocol that seems to allow citizens to verify that their vote has been accurately taken into account while preserving its secrecy, without requiring the use of a complex process. The main idea is to give each voter a receipt on which her choice is mixed with the choices of other voters.


On Transformations of Load-Store Maurer Instruction Set Architecture

Abstract: In this paper, we study how certain conditions can affect the transformations on the states of the memory of a strict load-store Maurer ISA, when half of the data memory serves as the part of the operating unit.


Towards Provable Secure Neighbor Discovery in Wireless Networks

Abstract: In wireless systems, neighbor discovery (ND) is a fundamental building block: determining which devices are within direct radio communication is an enabler for networking protocols and a wide range of applications. To thwart abuse of ND and the resultant compromise of the dependent functionality of wireless systems, numerous works proposed solutions to secure ND. Nonetheless, until very recently, there has been no formal analysis of secure ND protocols. We close this gap in \cite{asiaccs08}, but we concentrate primarily on the derivation of an impossibility result for a class of protocols. In this paper, we focus on reasoning about specific protocols. First, we contribute a number of extensions and refinements on the framework of [24]. As we are particularly concerned with the practicality of provably secure ND protocols, we investigate availability and redefine accordingly the ND specification, and also consider composability of ND with other protocols. Then, we propose and analyze two secure ND protocols: We revisit one of the protocols analyzed in [24], and introduce and prove correct a more elaborate challenge-response protocol.


GossiCrypt: Wireless Sensor Network Data Confidentiality Against Parasitic Adversaries

Abstract: Resource and cost constraints remain a challenge for wireless sensor network security. In this paper, we propose a new approach to protect confidentiality against a parasitic adversary, which seeks to exploit sensor networks by obtaining measurements in an unauthorized way. Our low-complexity solution, GossiCrypt, leverages on the large scale of sensor networks to protect confidentiality efficiently and effectively. GossiCrypt protects data by symmetric key encryption at their source nodes and re-encryption at a randomly chosen subset of nodes en route to the sink. Furthermore, it employs key refreshing to mitigate the physical compromise of cryptographic keys. We validate GossiCrypt analytically and with simulations, showing it protects data confidentiality with probability almost one. Moreover, compared with a system that uses public-key data encryption, the energy consumption of GossiCrypt is one to three orders of magnitude lower.


Easily testable logical networks based on a 'widened long flip-flop'

Abstract: The article describes an attempt to solve at once three basic problems arising at testing a complex digital equipment for defects: 1) the problem of an exponential increasing of the complexity of testing the equipment with the complexity of the equipment; 2) the problem of testing of the tester; 3) the problem of a mutual masking of defects. The proposed solution is nothing more than using certain limitations for connections between usual logical gates. Arbitrary multiple stuck-at-faults are supposed as defects.


Report on the "Secure Vehicular Communications: Results and Challenges Ahead" Workshop

Abstract: This is a report and a collection of abstracts from the Feb. 2008 Lausanne Workshop on Secure Vehicular Communication Systems.


Multitask Efficiencies in the Decision Tree Model

Abstract: In Direct Sum problems [KRW], one tries to show that for a given computational model, the complexity of computing a collection of finite functions on independent inputs is approximately the sum of their individual complexities. In this paper, by contrast, we study the diversity of ways in which the joint computational complexity can behave when all the functions are evaluated on a common input. We focus on the deterministic decision tree model, with depth as the complexity measure; in this model we prove a result to the effect that the 'obvious' constraints on joint computational complexity are essentially the only ones. The proof uses an intriguing new type of cryptographic data structure called a `mystery bin' which we construct using a small polynomial separation between deterministic and unambiguous query complexity shown by Savicky. We also pose a variant of the Direct Sum Conjecture of [KRW] which, if proved for a single family of functions, could yield an analogous result for models such as the communication model.


Impact of Vehicular Communications Security on Transportation Safety

Abstract: Transportation safety, one of the main driving forces of the development of vehicular communication (VC) systems, relies on high-rate safety messaging (beaconing). At the same time, there is consensus among authorities, industry, and academia on the need to secure VC systems. With specific proposals in the literature, a critical question must be answered: can secure VC systems be practical and satisfy the requirements of safety applications, in spite of the significant communication and processing overhead and other restrictions security and privacy-enhancing mechanisms impose? To answer this question, we investigate in this paper the following three dimensions for secure and privacy-enhancing VC schemes: the reliability of communication, the processing overhead at each node, and the impact on a safety application. The results indicate that with the appropriate system design, including sufficiently high processing power, applications enabled by secure VC can be in practice as effective as those enabled by unsecured VC.


Secure Neighbor Discovery in Wireless Networks: Formal Investigation of Possibility

Abstract: Wireless communication enables a broad spectrum of applications, ranging from commodity to tactical systems. Neighbor discovery (ND), that is, determining which devices are within direct radio communication, is a building block of network protocols and applications, and its vulnerability can severely compromise their functionalities. A number of proposals to secure ND have been published, but none have analyzed the problem formally. In this paper, we contribute such an analysis: We build a formal model capturing salient characteristics of wireless systems, most notably obstacles and interference, and we provide a specification of a basic variant of the ND problem. Then, we derive an impossibility result for a general class of protocols we term "time-based protocols," to which many of the schemes in the literature belong. We also identify the conditions under which the impossibility result is lifted. Moreover, we explore a second class of protocols we term "time- and location-based protocols," and prove they can secure ND.


Efficient and Robust Secure Aggregation for Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) rely on in-network aggregation for efficiency, however, this comes at a price: A single adversary can severely influence the outcome by contributing an arbitrary partial aggregate value. Secure in-network aggregation can detect such manipulation. But as long as such faults persist, no aggregation result can be obtained. In contrast, the collection of individual sensor node values is robust and solves the problem of availability, yet in an inefficient way. Our work seeks to bridge this gap in secure data collection: We propose a system that enhances availability with an efficiency close to that of in-network aggregation. To achieve this, our scheme relies on costly operations to localize and exclude nodes that manipulate the aggregation, but \emph{only} when a failure is detected. The detection of aggregation disruptions and the removal of faulty nodes provides robustness. At the same time, after removing faulty nodes, the WSN can enjoy low cost (secure) aggregation. Thus, the high exclusion cost is amortized, and efficiency increases.


Accelerating Scientific Computations with Mixed Precision Algorithms

Abstract: On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. The approach presented here can apply not only to conventional processors but also to other technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the STI Cell BE processor. Results on modern processor architectures and the STI Cell BE are presented.


Discretized Multinomial Distributions and Nash Equilibria in Anonymous Games

Abstract: We show that there is a polynomial-time approximation scheme for computing Nash equilibria in anonymous games with any fixed number of strategies (a very broad and important class of games), extending the two-strategy result of Daskalakis and Papadimitriou 2007. The approximation guarantee follows from a probabilistic result of more general interest: The distribution of the sum of n independent unit vectors with values ranging over {e1, e2, ...,ek}, where ei is the unit vector along dimension i of the k-dimensional Euclidean space, can be approximated by the distribution of the sum of another set of independent unit vectors whose probabilities of obtaining each value are multiples of 1/z for some integer z, and so that the variational distance of the two distributions is at most eps, where eps is bounded by an inverse polynomial in z and a function of k, but with no dependence on n. Our probabilistic result specifies the construction of a surprisingly sparse eps-cover -- under the total variation distance -- of the set of distributions of sums of independent unit vectors, which is of interest on its own right.


Fast Intrinsic Mode Decomposition and Filtering of Time Series Data

Abstract: The intrinsic mode function (IMF) provides adaptive function bases for nonlinear and non-stationary time series data. A fast convergent iterative method is introduced in this paper to find the IMF components of the data, the method is faster and more predictable than the Empirical Mode Decomposition method devised by the author of Hilbert Huang Transform. The approach is to iteratively adjust the control points on the data function corresponding to the extrema of the refining IMF, the control points of the residue function are calculated as the median of the straight line segments passing through the data control points, the residue function is then constructed as the cubic spline function of the median points. The initial residue function is simply constructed as the straight line segments passing through the extrema of the first derivative of the data function. The refining IMF is the difference between the data function and the improved residue function. The IMF found reveals all the riding waves in the whole data set. A new data filtering method on frequency and amplitude of IMF is also presented with the similar approach of finding the residue on the part to be filtered out. The program to demonstrate the method is distributed under BSD open source license.


Investigation of the Zipf-plot of the extinct Meroitic language

Abstract: The ancient and extinct language Meroitic is investigated using Zipf's Law. In particular, since Meroitic is still undeciphered, the Zipf law analysis allows us to assess the quality of current texts and possible avenues for future investigation using statistical techniques.


Spatial planning with constraints on translational distances between geometric objects

Abstract: The main constraint on relative position of geometric objects, used in spatial planning for computing the C-space maps (for example, in robotics, CAD, and packaging), is the relative non-overlapping of objects. This is the simplest constraint in which the minimum translational distance between objects is greater than zero, or more generally, than some positive value. We present a technique, based on the Minkowski operations, for generating the translational C-space maps for spatial planning with more general and more complex constraints on the relative position of geometric objects, such as constraints on various types (not only on the minimum) of the translational distances between objects. The developed technique can also be used, respectively, for spatial planning with constraints on translational distances in a given direction, and rotational distances between geometric objects, as well as for spatial planning with given dynamic geometric situation of moving objects.


Declarative Combinatorics: Isomorphisms, Hylomorphisms and Hereditarily Finite Data Types in Haskell

Abstract: This paper is an exploration in a functional programming framework of {\em isomorphisms} between elementary data types (natural numbers, sets, multisets, finite functions, permutations binary decision diagrams, graphs, hypergraphs, parenthesis languages, dyadic rationals, primes, DNA sequences etc.) and their extension to hereditarily finite universes through {\em hylomorphisms} derived from {\em ranking/unranking} and {\em pairing/unpairing} operations. An embedded higher order {\em combinator language} provides any-to-any encodings automatically. Besides applications to experimental mathematics, a few examples of ``free algorithms'' obtained by transferring operations between data types are shown. Other applications range from stream iterators on combinatorial objects to self-delimiting codes, succinct data representations and generation of random instances. The paper covers 59 data types and, through the use of the embedded combinator language, provides 3540 distinct bijective transformations between them. The self-contained source code of the paper, as generated from a literate Haskell program, is available at \url{http://logic.csci.unt.edu/tarau/research/2008/fISO.zip}. {\bf Keywords}: Haskell data representations, data type isomorphisms, declarative combinatorics, computational mathematics, Ackermann encoding, G\"{o}del numberings, arithmetization, ranking/unranking, hereditarily finite sets, functions and permutations, encodings of binary decision diagrams, dyadic rationals, DNA encodings


Building an interpretable fuzzy rule base from data using Orthogonal Least Squares Application to a depollution problem

Abstract: In many fields where human understanding plays a crucial role, such as bioprocesses, the capacity of extracting knowledge from data is of critical importance. Within this framework, fuzzy learning methods, if properly used, can greatly help human experts. Amongst these methods, the aim of orthogonal transformations, which have been proven to be mathematically robust, is to build rules from a set of training data and to select the most important ones by linear regression or rank revealing techniques. The OLS algorithm is a good representative of those methods. However, it was originally designed so that it only cared about numerical performance. Thus, we propose some modifications of the original method to take interpretability into account. After recalling the original algorithm, this paper presents the changes made to the original method, then discusses some results obtained from benchmark problems. Finally, the algorithm is applied to a real-world fault detection depollution problem.


Data Mining Using High Performance Data Clouds: Experimental Studies Using Sector and Sphere

Abstract: We describe the design and implementation of a high performance cloud that we have used to archive, analyze and mine large distributed data sets. By a cloud, we mean an infrastructure that provides resources and/or services over the Internet. A storage cloud provides storage services, while a compute cloud provides compute services. We describe the design of the Sector storage cloud and how it provides the storage services required by the Sphere compute cloud. We also describe the programming paradigm supported by the Sphere compute cloud. Sector and Sphere are designed for analyzing large data sets using computer clusters connected with wide area high performance networks (for example, 10+ Gb/s). We describe a distributed data mining application that we have developed using Sector and Sphere. Finally, we describe some experimental studies comparing Sector/Sphere to Hadoop.


Optimizing Compiler for Engineering Problems

Abstract: New information technologies provide a lot of prospects for performance improvement. One of them is "Dynamic Source Code Generation and Compilation". This article shows how this way provides high performance for engineering problems.


n-ary Fuzzy Logic and Neutrosophic Logic Operators

Abstract: We extend Knuth's 16 Boolean binary logic operators to fuzzy logic and neutrosophic logic binary operators. Then we generalize them to n-ary fuzzy logic and neutrosophic logic operators using the smarandache codification of the Venn diagram and a defined vector neutrosophic law. In such way, new operators in neutrosophic logic/set/probability are built.


On the decidability of semigroup freeness

Abstract: This paper deals with the decidability of semigroup freeness. More precisely, the freeness problem over a semigroup S is defined as: given a finite subset X of S, decide whether each element of S has at most one factorization over X. To date, the decidabilities of two freeness problems have been closely examined. In 1953, Sardinas and Patterson proposed a now famous algorithm for the freeness problem over the free monoid. In 1991, Klarner, Birget and Satterfield proved the undecidability of the freeness problem over three-by-three integer matrices. Both results led to the publication of many subsequent papers. The aim of the present paper is three-fold: (i) to present general results concerning freeness problems, (ii) to study the decidability of freeness problems over various particular semigroups (special attention is devoted to multiplicative matrix semigroups), and (iii) to propose precise, challenging open questions in order to promote the study of the topic.


Privacy Preserving Association Rule Mining Revisited

Abstract: The privacy preserving data mining (PPDM) has been one of the most interesting, yet challenging, research issues. In the PPDM, we seek to outsource our data for data mining tasks to a third party while maintaining its privacy. In this paper, we revise one of the recent PPDM schemes (i.e., FS) which is designed for privacy preserving association rule mining (PP-ARM). Our analysis shows some limitations of the FS scheme in term of its storage requirements guaranteeing a reasonable privacy standard and the high computation as well. On the other hand, we introduce a robust definition of privacy that considers the average case privacy and motivates the study of a weakness in the structure of FS (i.e., fake transactions filtering). In order to overcome this limit, we introduce a hybrid scheme that considers both privacy and resources guidelines. Experimental results show the efficiency of our proposed scheme over the previously introduced one and opens directions for further development.


On the Monotonicity of Work Function in k-Server Conjecture

Abstract: This paper presents a mistake in work function algorithm of k-server conjecture. That is, the monotonicity of the work function is not always true.


Analysis of the postulates produced by Karp's Theorem

Abstract: This is the final article in a series of four articles. Richard Karp has proven that a deterministic polynomial time solution to K-SAT will result in a deterministic polynomial time solution to all NP-Complete problems. However, it is demonstrated that a deterministic polynomial time solution to any NP-Complete problem does not necessarily produce a deterministic polynomial time solution to all NP-Complete problems.


Multi-Instance Multi-Label Learning

Abstract: In this paper, we propose the MIML (Multi-Instance Multi-Label learning) framework where an example is described by multiple instances and associated with multiple class labels. Compared to traditional learning frameworks, the MIML framework is more convenient and natural for representing complicated objects which have multiple semantic meanings. To learn from MIML examples, we propose the MimlBoost and MimlSvm algorithms based on a simple degeneration strategy, and experiments show that solving problems involving complicated objects with multiple semantic meanings in the MIML framework can lead to good performance. Considering that the degeneration process may lose information, we propose the D-MimlSvm algorithm which tackles MIML problems directly in a regularization framework. Moreover, we show that even when we do not have access to the real objects and thus cannot capture more information from real objects by using the MIML representation, MIML is still useful. We propose the InsDif and SubCod algorithms. InsDif works by transforming single-instances into the MIML representation for learning, while SubCod works by transforming single-label examples into the MIML representation for learning. Experiments show that in some tasks they are able to achieve better performance than learning the single-instances or single-label examples directly.


Network Motifs in Object-Oriented Software Systems

Abstract: Nowadays, software has become a complex piece of work that may be beyond our control. Understanding how software evolves over time plays an important role in controlling software development processes. Recently, a few researchers found the quantitative evidence of structural duplication in software systems or web applications, which is similar to the evolutionary trend found in biological systems. To investigate the principles or rules of software evolution, we introduce the relevant theories and methods of complex networks into structural evolution and change of software systems. According to the results of our experiment on network motifs, we find that the stability of a motif shows positive correlation with its abundance and a motif with high Z score tends to have stable structure. These findings imply that the evolution of software systems is based on functional cloning as well as structural duplication and tends to be structurally stable. So, the work presented in this paper will be useful for the analysis of structural changes of software systems in reverse engineering.


Confirmation Bias and the Open Access Advantage: Some Methodological Suggestions for the Davis Citation Study

Abstract: Davis (2008) analyzes citations from 2004-2007 in 11 biomedical journals. 15% of authors paid to make them Open Access (OA). The outcome is a significant OA citation Advantage, but a small one (21%). The author infers that the OA advantage has been shrinking yearly, but the data suggest the opposite. Further analyses are necessary: (1) Not just author-choice (paid) OA but Free OA self-archiving needs to be taken into account rather than being counted as non-OA. (2) proportion of OA articles per journal per year needs to be reported and taken into account. (3) The Journal Impact Factor and the relation between the size of the OA Advantage article 'citation-bracket' need to be taken into account. (4) The sample-size for the highest-impact, largest-sample journal analyzed, PNAS, is restricted and excluded from some of the analyses. The full PNAS dataset is needed. (5) The interaction between OA and time, 2004-2007, is based on retrospective data from a June 2008 total cumulative citation count. The dates of both the cited articles and the citing articles need to be taken into account. The author proposes that author self-selection bias for is the primary cause of the observed OA Advantage, but this study does not test this or of any of the other potential causal factors. The author suggests that paid OA is not worth the cost, per extra citation. But with OA self-archiving both the OA and the extra citations are free.


Proving Noninterference by a Fully Complete Translation to the Simply Typed lambda-calculus

Abstract: Tse and Zdancewic have formalized the notion of noninterference for Abadi et al.'s DCC in terms of logical relations and given a proof of noninterference by reduction to parametricity of System F. Unfortunately, their proof contains errors in a key lemma that their translation from DCC to System F preserves the logical relations defined for both calculi. In fact, we have found a counterexample for it. In this article, instead of DCC, we prove noninterference for sealing calculus, a new variant of DCC, by reduction to the basic lemma of a logical relation for the simply typed lambda-calculus, using a fully complete translation to the simply typed lambda-calculus. Full completeness plays an important role in showing preservation of the two logical relations through the translation. Also, we investigate relationship among sealing calculus, DCC, and an extension of DCC by Tse and Zdancewic and show that the first and the last of the three are equivalent.


Efficient algorithms for the basis of finite Abelian groups

Abstract: Let $G$ be a finite abelian group $G$ with $N$ elements. In this paper we give a O(N) time algorithm for computing a basis of $G$. Furthermore, we obtain an algorithm for computing a basis from a generating system of $G$ with $M$ elements having time complexity $O(M\sum_{p|N} e(p)\lceil p^{1/2}\rceil^{\mu(p)})$, where $p$ runs over all the prime divisors of $N$, and $p^{e(p)}$, $\mu(p)$ are the exponent and the number of cyclic groups which are direct factors of the $p$-primary component of $G$, respectively. In case where $G$ is a cyclic group having a generating system with $M$ elements, a $O(MN^{\epsilon})$ time algorithm for the computation of a basis of $G$ is obtained.


Linear Programming Formulation of the Boolean Satisfiability Problem

Abstract: In this paper, we present a new, graph-based modeling approach and a polynomial-sized linear programming (LP) formulation of the Boolean satisfiability problem (SAT). The approach is illustrated with a numerical example.


Data Diffusion: Dynamic Resource Provision and Data-Aware Scheduling for Data Intensive Applications

Abstract: Data intensive applications often involve the analysis of large datasets that require large amounts of compute and storage resources. While dedicated compute and/or storage farms offer good task/data throughput, they suffer low resource utilization problem under varying workloads conditions. If we instead move such data to distributed computing resources, then we incur expensive data transfer cost. In this paper, we propose a data diffusion approach that combines dynamic resource provisioning, on-demand data replication and caching, and data locality-aware scheduling to achieve improved resource efficiency under varying workloads. We define an abstract "data diffusion model" that takes into consideration the workload characteristics, data accessing cost, application throughput and resource utilization; we validate the model using a real-world large-scale astronomy application. Our results show that data diffusion can increase the performance index by as much as 34X, and improve application response time by over 506X, while achieving near-optimal throughputs and execution times.


Enabling Loosely-Coupled Serial Job Execution on the IBM BlueGene/P Supercomputer and the SiCortex SC5832

Abstract: Our work addresses the enabling of the execution of highly parallel computations composed of loosely coupled serial jobs with no modifications to the respective applications, on large-scale systems. This approach allows new-and potentially far larger-classes of application to leverage systems such as the IBM Blue Gene/P supercomputer and similar emerging petascale architectures. We present here the challenges of I/O performance encountered in making this model practical, and show results using both micro-benchmarks and real applications on two large-scale systems, the BG/P and the SiCortex SC5832. Our preliminary benchmarks show that we can scale to 4096 processors on the Blue Gene/P and 5832 processors on the SiCortex with high efficiency, and can achieve thousands of tasks/sec sustained execution rates for parallel workloads of ordinary serial applications. We measured applications from two domains, economic energy modeling and molecular dynamics.


Towards Loosely-Coupled Programming on Petascale Systems

Abstract: We have extended the Falkon lightweight task execution framework to make loosely coupled programming on petascale systems a practical and useful programming model. This work studies and measures the performance factors involved in applying this approach to enable the use of petascale systems by a broader user community, and with greater ease. Our work enables the execution of highly parallel computations composed of loosely coupled serial jobs with no modifications to the respective applications. This approach allows a new-and potentially far larger-class of applications to leverage petascale systems, such as the IBM Blue Gene/P supercomputer. We present the challenges of I/O performance encountered in making this model practical, and show results using both microbenchmarks and real applications from two domains: economic energy modeling and molecular dynamics. Our benchmarks show that we can scale up to 160K processor-cores with high efficiency, and can achieve sustained execution rates of thousands of tasks per second.


Scientific Workflow Systems for 21st Century e-Science, New Bottle or New Wine?

Abstract: With the advances in e-Sciences and the growing complexity of scientific analyses, more and more scientists and researchers are relying on workflow systems for process coordination, derivation automation, provenance tracking, and bookkeeping. While workflow systems have been in use for decades, it is unclear whether scientific workflows can or even should build on existing workflow technologies, or they require fundamentally new approaches. In this paper, we analyze the status and challenges of scientific workflows, investigate both existing technologies and emerging languages, platforms and systems, and identify the key challenges that must be addressed by workflow systems for e-science in the 21st century.


Accelerating Large-scale Data Exploration through Data Diffusion

Abstract: Data-intensive applications often require exploratory analysis of large datasets. If analysis is performed on distributed resources, data locality can be crucial to high throughput and performance. We propose a "data diffusion" approach that acquires compute and storage resources dynamically, replicates data in response to demand, and schedules computations close to data. As demand increases, more resources are acquired, thus allowing faster response to subsequent requests that refer to the same data; when demand drops, resources are released. This approach can provide the benefits of dedicated hardware without the associated high costs, depending on workload and resource characteristics. The approach is reminiscent of cooperative caching, web-caching, and peer-to-peer storage systems, but addresses different application demands. Other data-aware scheduling approaches assume dedicated resources, which can be expensive and/or inefficient if load varies significantly. To explore the feasibility of the data diffusion approach, we have extended the Falkon resource provisioning and task scheduling system to support data caching and data-aware scheduling. Performance results from both micro-benchmarks and a large scale astronomy application demonstrate that our approach improves performance relative to alternative approaches, as well as provides improved scalability as aggregated I/O bandwidth scales linearly with the number of data cache nodes.


Realizing Fast, Scalable and Reliable Scientific Computations in Grid Environments

Abstract: The practical realization of managing and executing large scale scientific computations efficiently and reliably is quite challenging. Scientific computations often involve thousands or even millions of tasks operating on large quantities of data, such data are often diversely structured and stored in heterogeneous physical formats, and scientists must specify and run such computations over extended periods on collections of compute, storage and network resources that are heterogeneous, distributed and may change constantly. We present the integration of several advanced systems: Swift, Karajan, and Falkon, to address the challenges in running various large scale scientific applications in Grid environments. Swift is a parallel programming tool for rapid and reliable specification, execution, and management of large-scale science and engineering workflows. Swift consists of a simple scripting language called SwiftScript and a powerful runtime system that is based on the CoG Karajan workflow engine and integrates the Falkon light-weight task execution service that uses multi-level scheduling and a streamlined dispatcher. We showcase the scalability, performance and reliability of the integrated system using application examples drawn from astronomy, cognitive neuroscience and molecular dynamics, which all comprise large number of fine-grained jobs. We show that Swift is able to represent dynamic workflows whose structures can only be determined during runtime and reduce largely the code size of various workflow representations using SwiftScript; schedule the execution of hundreds of thousands of parallel computations via the Karajan engine; and achieve up to 90% reduction in execution time when compared to traditional batch schedulers.


Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities

Abstract: This keynote paper: presents a 21st century vision of computing; identifies various computing paradigms promising to deliver the vision of computing utilities; defines Cloud computing and provides the architecture for creating market-oriented Clouds by leveraging technologies such as VMs; provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; presents some representative Cloud platforms especially those developed in industries along with our current work towards realising market-oriented resource allocation of Clouds by leveraging the 3rd generation Aneka enterprise Grid technology; reveals our early thoughts on interconnecting Clouds for dynamically creating an atmospheric computing environment along with pointers to future community research; and concludes with the need for convergence of competing IT paradigms for delivering our 21st century vision.


What It Feels Like To Hear Voices: Fond Memories of Julian Jaynes

Abstract: Julian Jaynes's profound humanitarian convictions not only prevented him from going to war, but would have prevented him from ever kicking a dog. Yet according to his theory, not only are language-less dogs unconscious, but so too were the speaking/hearing Greeks in the Bicameral Era, when they heard gods' voices telling them what to do rather than thinking for themselves. I argue that to be conscious is to be able to feel, and that all mammals (and probably lower vertebrates and invertebrates too) feel, hence are conscious. Julian Jaynes's brilliant analysis of our concepts of consciousness nevertheless keeps inspiring ever more inquiry and insights into the age-old mind/body problem and its relation to cognition and language.


Offloading Cognition onto Cognitive Technology

Abstract: "Cognizing" (e.g., thinking, understanding, and knowing) is a mental state. Systems without mental states, such as cognitive technology, can sometimes contribute to human cognition, but that does not make them cognizers. Cognizers can offload some of their cognitive functions onto cognitive technology, thereby extending their performance capacity beyond the limits of their own brain power. Language itself is a form of cognitive technology that allows cognizers to offload some of their cognitive functions onto the brains of other cognizers. Language also extends cognizers' individual and joint performance powers, distributing the load through interactive and collaborative cognition. Reading, writing, print, telecommunications and computing further extend cognizers' capacities. And now the web, with its network of cognizers, digital databases and software agents, all accessible anytime, anywhere, has become our 'Cognitive Commons,' in which distributed cognizers and cognitive technology can interoperate globally with a speed, scope and degree of interactivity inconceivable through local individual cognition alone. And as with language, the cognitive tool par excellence, such technological changes are not merely instrumental and quantitative: they can have profound effects on how we think and encode information, on how we communicate with one another, on our mental states, and on our very nature.


Constructing word similarities in Meroitic as an aid to decipherment

Abstract: Meroitic is the still undeciphered language of the ancient civilization of Kush. Over the years, various techniques for decipherment such as finding a bilingual text or cognates from modern or other ancient languages in the Sudan and surrounding areas has not been successful. Using techniques borrowed from information theory and natural language statistics, similar words are paired and attempts are made to use currently defined words to extract at least partial meaning from unknown words.


Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations

Abstract: Strong and weak simulation relations have been proposed for Markov chains, while strong simulation and strong probabilistic simulation relations have been proposed for probabilistic automata. However, decision algorithms for strong and weak simulation over Markov chains, and for strong simulation over probabilistic automata are not efficient, which makes it as yet unclear whether they can be used as effectively as their non-probabilistic counterparts. This paper presents drastically improved algorithms to decide whether some (discrete- or continuous-time) Markov chain strongly or weakly simulates another, or whether a probabilistic automaton strongly simulates another. The key innovation is the use of parametric maximum flow techniques to amortize computations. We also present a novel algorithm for deciding strong probabilistic simulation preorders on probabilistic automata, which has polynomial complexity via a reduction to an LP problem. When extending the algorithms for probabilistic automata to their continuous-time counterpart, we retain the same complexity for both strong and strong probabilistic simulations.


Providing Virtual Execution Environments: A Twofold Illustration

Abstract: Platform virtualization helps solving major grid computing challenges: share resource with flexible, user-controlled and custom execution environments and in the meanwhile, isolate failures and malicious code. Grid resource management tools will evolve to embrace support for virtual resource. We present two open source projects that transparently supply virtual execution environments. Tycoon has been developed at HP Labs to optimise resource usage in creating an economy where users bid to access virtual machines and compete for CPU cycles. SmartDomains provides a peer-to-peer layer that automates virtual machines deployment using a description language and deployment engine from HP Labs. These projects demonstrate both client-server and peer-to-peer approaches to virtual resource management. The first case makes extensive use of virtual machines features for dynamic resource allocation. The second translates virtual machines capabilities into a sophisticated language where resource management components can be plugged in configurations and architectures defined at deployment time. We propose to share our experience at CERN openlab developing SmartDomains and deploying Tycoon to give an illustrative introduction to emerging research in virtual resource management.


Studying Geometric Graph Properties of Road Networks Through an Algorithmic Lens

Abstract: This paper studies real-world road networks from an algorithmic perspective, focusing on empirical studies that yield useful properties of road networks that can be exploited in the design of fast algorithms that deal with geographic data. Unlike previous approaches, our study is not based on the assumption that road networks are planar graphs. Indeed, based on the a number of experiments we have performed on the road networks of the 50 United States and District of Columbia, we provide strong empirical evidence that road networks are quite non-planar. Our approach therefore instead is directed at finding algorithmically-motivated properties of road networks as non-planar geometric graphs, focusing on alternative properties of road networks that can still lead to efficient algorithms for such problems as shortest paths and Voronoi diagrams. In particular, we study road networks as multiscale-dispersed graphs, which is a concept we formalize in terms of disk neighborhood systems. This approach allows us to develop fast algorithms for road networks without making any additional assumptions about the distribution of edge weights. In fact, our algorithms can allow for non-metric weights.


Abstract: Development organizations and International Non-Governmental Organizations have been emphasizing the high potential of Free and Open Source Software for the Less Developed Countries. Cost reduction, less vendor dependency and increased potential for local capacity development have been their main arguments. In spite of its advantages, Free and Open Source Software is not widely adopted at the African continent. In this book the authors will explore the grounds on with these expectations are based. Where do they come from and is there evidence to support these expectations? Over the past years several projects have been initiated and some good results have been achieved, but at the same time many challenges were encountered. What lessons can be drawn from these experiences and do these experiences contain enough evidence to support the high expectations? Several projects and their achievements will be considered. In the final part of the book the future of Free and Open Source Software for Development will be explored. Special attention is given to the African continent since here challenges are highest. What is the role of Free and open Source Software for Development and how do we need to position and explore the potential? What are the threats? The book aims at professionals that are engaged in the design and implementation of ICT for Development (ICT4D) projects and want to improve their understanding of the role Free and Open Source Software can play.


A game-theoretic version of Oakes' example for randomized forecasting

Abstract: Using the game-theoretic framework for probability, Vovk and Shafer. have shown that it is always possible, using randomization, to make sequential probability forecasts that pass any countable set of well-behaved statistical tests. This result generalizes work by other authors, who consider only tests of calbration. We complement this result with a lower bound. We show that Vovk and Shafer's result is valid only when the forecasts are computed with unrestrictedly increasing degree of accuracy. When some level of discreteness is fixed, we present a game-theoretic generalization of Oakes' example for randomized forecasting that is a test failing any given method of deferministic forecasting; originally, this example was presented for deterministic calibration.


Forward Correction and Fountain codes in Delay Tolerant Networks

Abstract: Delay tolerant Ad-hoc Networks make use of mobility of relay nodes to compensate for lack of permanent connectivity and thus enable communication between nodes that are out of range of each other. To decrease delivery delay, the information that needs to be delivered is replicated in the network. Our objective in this paper is to study replication mechanisms that include coding in order to improve the probability of successful delivery within a given time limit. We propose an analytical approach that allows to quantify tradeoffs between resources and performance measures (energy and delay). We study the effect of coding on the performance of the network while optimizing parameters that govern routing. Our results, based on fluid approximations, are compared to simulations which validate the model


Counting Hexagonal Patches and Independent Sets in Circle Graphs

Abstract: A hexagonal patch is a plane graph in which inner faces have length 6, inner vertices have degree 3, and boundary vertices have degree 2 or 3. We consider the following counting problem: given a sequence of twos and threes, how many hexagonal patches exist with this degree sequence along the outer face? This problem is motivated by the study of benzenoid hydrocarbons and fullerenes in computational chemistry. We give the first polynomial time algorithm for this problem. We show that it can be reduced to counting maximum independent sets in circle graphs, and give a simple and fast algorithm for this problem.


The Complexity of Reasoning for Fragments of Default Logic

Abstract: Default logic was introduced by Reiter in 1980. In 1992, Gottlob classified the complexity of the extension existence problem for propositional default logic as $\SigmaPtwo$-complete, and the complexity of the credulous and skeptical reasoning problem as SigmaP2-complete, resp. PiP2-complete. Additionally, he investigated restrictions on the default rules, i.e., semi-normal default rules. Selman made in 1992 a similar approach with disjunction-free and unary default rules. In this paper we systematically restrict the set of allowed propositional connectives. We give a complete complexity classification for all sets of Boolean functions in the meaning of Post's lattice for all three common decision problems for propositional default logic. We show that the complexity is a hexachotomy (SigmaP2-, DeltaP2-, NP-, P-, NL-complete, trivial) for the extension existence problem, while for the credulous and skeptical reasoning problem we obtain similar classifications without trivial cases.


Open architecture for multilingual parallel texts

Abstract: Multilingual parallel texts (abbreviated to parallel texts) are linguistic versions of the same content ("translations"); e.g., the Maastricht Treaty in English and Spanish are parallel texts. This document is about creating an open architecture for the whole Authoring, Translation and Publishing Chain (ATP-chain) for the processing of parallel texts.


Essential arity gap of Boolean functions

Abstract: We investigate the Boolean functions with essential arity gap 2. We use Full Conjunctive Normal Forms instead of Zhegalkin's polynomials, which allow us to simplify the proofs and to obtain several combinatorial results, concerning the Boolean functions with a given arity gap.


On the strength of proof-irrelevant type theories

Abstract: We present a type theory with some proof-irrelevance built into the conversion rule. We argue that this feature is useful when type theory is used as the logical formalism underlying a theorem prover. We also show a close relation with the subset types of the theory of PVS. We show that in these theories, because of the additional extentionality, the axiom of choice implies the decidability of equality, that is, almost classical logic. Finally we describe a simple set-theoretic semantics.


Understanding Fairness and its Impact on Quality of Service in IEEE 802.11

Abstract: The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on quality of service in mind. In this paper we provide an accurate model for the fairness of the DCF. Given M greedy stations we assume fairness if a tagged station contributes a share of 1/M to the overall number of packets transmitted. We derive the probability distribution of fairness deviations and support our analytical results by an extensive set of measurements. We find a closed-form expression for the improvement of long-term over short-term fairness. Regarding the random countdown values we quantify the significance of their distribution whereas we discover that fairness is largely insensitive to the distribution parameters. Based on our findings we view the DCF as emulating an ideal fair queuing system to quantify the deviations from a fair rate allocation. We deduce a stochastic service curve model for the DCF to predict packet delays in IEEE 802.11. We show how a station can estimate its fair bandwidth share from passive measurements of its traffic arrivals and departures.


Adaptive Dynamic Congestion Avoidance with Master Equation

Abstract: This paper proposes an adaptive variant of Random Early Detection (RED) gateway queue management for packet-switched networks via a discrete state analog of the non-stationary Master Equation i.e. Markov process. The computation of average queue size, which appeared in the original RED algorithm, is altered by introducing a probability $P(l,t)$, which defines the probability of having $l$ number of packets in the queue at the given time $t$, and depends upon the previous state of the queue. This brings the advantage of eliminating a free parameter: queue weight, completely. Computation of transition rates and probabilities are carried out on the fly, and determined by the algorithm automatically. Simulations with unstructured packets illustrate the method, the performance of the adaptive variant of RED algorithm, and the comparison with the standard RED.


TrustMAS: Trusted Communication Platform for Multi-Agent Systems

Abstract: The paper presents TrustMAS - Trusted Communication Platform for Multi-Agent Systems, which provides trust and anonymity for mobile agents. The platform includes anonymous technique based on random-walk algorithm for providing general purpose anonymous communication for agents. All agents, which take part in the proposed platform, benefit from trust and anonymity that is provided for their interactions. Moreover, in TrustMAS there are StegAgents (SA) that are able to perform various steganographic communication. To achieve that goal, SAs may use methods in different layers of TCP/IP model or specialized middleware enabling steganography that allows hidden communication through all layers of mentioned model. In TrustMAS steganographic channels are used to exchange routing tables between StegAgents. Thus all StegAgents in TrustMAS with their ability to exchange information by using hidden channels form distributed steganographic router (Stegrouter).


From Altruism to Non-Cooperation in Routing Games

Abstract: The paper studies the routing in the network shared by several users. Each user seeks to optimize either its own performance or some combination between its own performance and that of other users, by controlling the routing of its given flow demand. We parameterize the degree of cooperation which allows to cover the fully non-cooperative behavior, the fully cooperative behavior, and even more, the fully altruistic behavior, all these as special cases of the parameter's choice. A large part of the work consists in exploring the impact of the degree of cooperation on the equilibrium. Our first finding is to identify multiple Nash equilibria with cooperative behavior that do not occur in the non-cooperative case under the same conditions (cost, demand and topology). We then identify Braess like paradox (in which adding capacity or adding a link to a network results in worse performance to all users) and study the impact of the degree of cooperation on it. We identify another type of paradox in cooperation scenario. We identify that when we increase the degree of cooperation of a user while other users keep unchanged their degree of cooperation, leads to an improvement in performance of that user. We then pursue the exploration and carry it on to the setting of Mixed equilibrium (i.e. some users are non atomic-they have infinitesimally small demand, and other have finite fixed demand). We finally obtain some theoretical results that show that for low degree of cooperation the equilibrium is unique, confirming the results of our numerical study.


Flow-level Characteristics of Spam and Ham

Abstract: Despite a large amount of effort devoted in the past years trying to limit unsolicited mail, spam is still a major global concern. Content-analysis techniques and blacklists, the most popular methods used to identify and block spam, are beginning to lose their edge in the battle. We argue here that one not only needs to look into the network-related characteristics of spam traffic, as has been recently suggested, but also to look deeper into the network core, in order to counter the increasing sophistication of spam-ing methods. Yet, at the same time, local knowledge available at a given server can often be irreplaceable in identifying specific spammers. To this end, in this paper we show how the local intelligence of mail servers can be gathered and correlated pas- sively at the ISP-level providing valuable network-wide information. Specifically, we use first a large network flow trace from a medium size, national ISP, to demonstrate that the pre-filtering decisions of individual mail servers can be tracked and combined at the flow level. Then, we argue that such aggregated knowledge not only can allow ISPs to develop and evaluate powerful new methods for fighting spam, but also to monitor remotely what their own servers are doing.


Swapping Lemmas for Regular and Context-Free Languages

Abstract: In formal language theory, one of the most fundamental tools, known as pumping lemmas, is extremely useful for regular and context-free languages. However, there are natural properties for which the pumping lemmas are of little use. One of such examples concerns a notion of advice, which depends only on the size of an underlying input. A standard pumping lemma encounters difficulty in proving that a given language is not regular in the presence of advice. We develop its substitution, called a swapping lemma for regular languages, to demonstrate the non-regularity of a target language with advice. For context-free languages, we also present a similar form of swapping lemma, which serves as a technical tool to show that certain languages are not context-free with advice.


Tableau-based decision procedure for the multi-agent epistemic logic with operators of common and distributed knowledge

Abstract: We develop an incremental-tableau-based decision procedure for the multi-agent epistemic logic MAEL(CD) (aka S5_n (CD)), whose language contains operators of individual knowledge for a finite set Ag of agents, as well as operators of distributed and common knowledge among all agents in Ag. Our tableau procedure works in (deterministic) exponential time, thus establishing an upper bound for MAEL(CD)-satisfiability that matches the (implicit) lower-bound known from earlier results, which implies ExpTime-completeness of MAEL(CD)-satisfiability. Therefore, our procedure provides a complexity-optimal algorithm for checking MAEL(CD)-satisfiability, which, however, in most cases is much more efficient. We prove soundness and completeness of the procedure, and illustrate it with an example.


Spectral Sparsification of Graphs

Abstract: We introduce a new notion of graph sparsificaiton based on spectral similarity of graph Laplacians: spectral sparsification requires that the Laplacian quadratic form of the sparsifier approximate that of the original. This is equivalent to saying that the Laplacian of the sparsifier is a good preconditioner for the Laplacian of the original. We prove that every graph has a spectral sparsifier of nearly linear size. Moreover, we present an algorithm that produces spectral sparsifiers in time $\softO{m}$, where $m$ is the number of edges in the original graph. This construction is a key component of a nearly-linear time algorithm for solving linear equations in diagonally-dominant matrcies. Our sparsification algorithm makes use of a nearly-linear time algorithm for graph partitioning that satisfies a strong guarantee: if the partition it outputs is very unbalanced, then the larger part is contained in a subgraph of high conductance.


Game Theory with Costly Computation

Abstract: We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer hold. Nevertheless, we can use the framework to provide psychologically appealing explanations to observed behavior in well-studied games (such as finitely repeated prisoner's dilemma and rock-paper-scissors). Furthermore, we provide natural conditions on games sufficient to guarantee that equilibria exist. As an application of this framework, we consider a notion of game-theoretic implementation of mediators in computational games. We show that a special case of this notion is equivalent to a variant of the traditional cryptographic definition of protocol security; this result shows that, when taking computation into account, the two approaches used for dealing with "deviating" players in two different communities -- Nash equilibrium in game theory and zero-knowledge "simulation" in cryptography -- are intimately related.


Model Checking Probabilistic Timed Automata with One or Two Clocks

Abstract: Probabilistic timed automata are an extension of timed automata with discrete probability distributions. We consider model-checking algorithms for the subclasses of probabilistic timed automata which have one or two clocks. Firstly, we show that PCTL probabilistic model-checking problems (such as determining whether a set of target states can be reached with probability at least 0.99 regardless of how nondeterminism is resolved) are PTIME-complete for one-clock probabilistic timed automata, and are EXPTIME-complete for probabilistic timed automata with two clocks. Secondly, we show that, for one-clock probabilistic timed automata, the model-checking problem for the probabilistic timed temporal logic PCTL is EXPTIME-complete. However, the model-checking problem for the subclass of PCTL which does not permit both punctual timing bounds, which require the occurrence of an event at an exact time point, and comparisons with probability bounds other than 0 or 1, is PTIME-complete for one-clock probabilistic timed automata.


The Stochastic Logarithmic Norm for Stability Analysis of Stochastic Differential Equations

Abstract: To analyze the stability of It\^o stochastic differential equations with multiplicative noise, we introduce the stochastic logarithmic norm. The logarithmic norm was originally introduced by G. Dahlquist in 1958 as a tool to study the growth of solutions to ordinary differential equations and for estimating the error growth in discretization methods for their approximate solutions. We extend the concept to the stability analysis of It\^o stochastic differential equations with multiplicative noise. Stability estimates for linear It\^o SDEs using the one, two and $\infty$-norms in the $l$-th mean, where $1 \leq l < \infty $, are derived and the application of the stochastic logarithmic norm is illustrated with examples.


Toward Expressive and Scalable Sponsored Search Auctions

Abstract: Internet search results are a growing and highly profitable advertising platform. Search providers auction advertising slots to advertisers on their search result pages. Due to the high volume of searches and the users' low tolerance for search result latency, it is imperative to resolve these auctions fast. Current approaches restrict the expressiveness of bids in order to achieve fast winner determination, which is the problem of allocating slots to advertisers so as to maximize the expected revenue given the advertisers' bids. The goal of our work is to permit more expressive bidding, thus allowing advertisers to achieve complex advertising goals, while still providing fast and scalable techniques for winner determination.


A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations

Abstract: Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semantic phenomena, and we cannot afford to create ad hoc algorithms for each semantic phenomenon; we need to seek a unified approach. We propose to subsume a broad range of phenomena under analogies. To limit the scope of this paper, we restrict our attention to the subsumption of synonyms, antonyms, and associations. We introduce a supervised corpus-based machine learning algorithm for classifying analogous word pairs, and we show that it can solve multiple-choice SAT analogy questions, TOEFL synonym questions, ESL synonym-antonym questions, and similar-associated-both questions from cognitive psychology.


Improved Approximations for Guarding 1.5-Dimensional Terrains

Abstract: We present a 4-approximation algorithm for the problem of placing a fewest guards on a 1.5D terrain so that every point of the terrain is seen by at least one guard. This improves on the currently best approximation factor of 5. Our method is based on rounding the linear programming relaxation of the corresponding covering problem. Besides the simplicity of the analysis, which mainly relies on decomposing the constraint matrix of the LP into totally balanced matrices, our algorithm, unlike previous work, generalizes to the weighted and partial versions of the basic problem.


Approximating Transitivity in Directed Networks

Abstract: We study the problem of computing a minimum equivalent digraph (also known as the problem of computing a strong transitive reduction) and its maximum objective function variant, with two types of extensions. First, we allow to declare a set $D\subset E$ and require that a valid solution $A$ satisfies $D\subset A$ (it is sometimes called transitive reduction problem). In the second extension (called $p$-ary transitive reduction), we have integer edge labeling and we view two paths as equivalent if they have the same beginning, ending and the sum of labels modulo $p$. A solution $A\subseteq E$ is valid if it gives an equivalent path for every original path. For all problems we establish the following: polynomial time minimization of $|A|$ within ratio 1.5, maximization of $|E-A|$ within ratio 2, MAX-SNP hardness even of the length of simple cycles is limited to 5. Furthermore, we believe that the combinatorial technique behind the approximation algorithm for the minimization version might be of interest to other graph connectivity problems as well.


Light Logics and the Call-by-Value Lambda Calculus

Abstract: The so-called light logics have been introduced as logical systems enjoying quite remarkable normalization properties. Designing a type assignment system for pure lambda calculus from these logics, however, is problematic. In this paper we show that shifting from usual call-by-name to call-by-value lambda calculus allows regaining strong connections with the underlying logic. This will be done in the context of Elementary Affine Logic (EAL), designing a type system in natural deduction style assigning EAL formulae to lambda terms.


Colliding Message Pairs for 23 and 24-step SHA-512

Abstract: Recently, Indesteege et al. [1] had described attacks against 23 and 24-step SHA-512 at SAC '08. Their attacks are based on the differential path by Nikolic and Biryukov [2]. The reported complexities are $2^{44.9}$ and $2^{53}$ calls to the respective step reduced SHA-512 hash function. They provided colliding message pairs for 23-step SHA-512 but did not provide a colliding message pair for 24-step SHA-512. In this note we provide a colliding message pair for 23-step SHA-512 and the first colliding message pair for 24-step SHA-512. Our attacks use the differential path first described by Sanadhya and Sarkar at ACISP '08 [3]. The complexities of our attacks are $2^{16.5}$ and $2^{34.5}$ calls to the respective step reduced SHA-512 hash function. Complete details of the attacks will be provided in an extended version of this note.


Linear Kernelizations for Restricted 3-Hitting Set Problems

Abstract: The 3-\textsc{Hitting Set} problem is also called the \textsc{Vertex Cover} problem on 3-uniform hypergraphs. In this paper, we address kernelizations of the \textsc{Vertex Cover} problem on 3-uniform hypergraphs. We show that this problem admits a linear kernel in three classes of 3-uniform hypergraphs. We also obtain lower and upper bounds on the kernel size for them by the parametric duality.


Randomised Variable Neighbourhood Search for Multi Objective Optimisation

Abstract: Various local search approaches have recently been applied to machine scheduling problems under multiple objectives. Their foremost consideration is the identification of the set of Pareto optimal alternatives. An important aspect of successfully solving these problems lies in the definition of an appropriate neighbourhood structure. Unclear in this context remains, how interdependencies within the fitness landscape affect the resolution of the problem. The paper presents a study of neighbourhood search operators for multiple objective flow shop scheduling. Experiments have been carried out with twelve different combinations of criteria. To derive exact conclusions, small problem instances, for which the optimal solutions are known, have been chosen. Statistical tests show that no single neighbourhood operator is able to equally identify all Pareto optimal alternatives. Significant improvements however have been obtained by hybridising the solution algorithm using a randomised variable neighbourhood search technique.


Instruction sequences and non-uniform complexity theory

Abstract: We develop theory concerning non-uniform complexity in a setting in which the notion of single-pass instruction sequence considered in program algebra is the central notion. We define counterparts of the complexity classes P/poly and NP/poly and formulate a counterpart of the complexity theoretic conjecture that NP is not included in P/poly. In addition, we define a notion of completeness for the counterpart of NP/poly using a non-uniform reducibility relation and formulate complexity hypotheses which concern restrictions on the instruction sequences used for computation. We think that the theory developed opens up an additional way of investigating issues concerning non-uniform complexity.


Simulations between triangular and hexagonal number-conserving cellular automata

Abstract: A number-conserving cellular automaton is a cellular automaton whose states are integers and whose transition function keeps the sum of all cells constant throughout its evolution. It can be seen as a kind of modelization of the physical conservation laws of mass or energy. In this paper, we first propose a necessary condition for triangular and hexagonal cellular automata to be number-conserving. The local transition function is expressed by the sum of arity two functions which can be regarded as 'flows' of numbers. The sufficiency is obtained through general results on number-conserving cellular automata. Then, using the previous flow functions, we can construct effective number-conserving simulations between hexagonal cellular automata and triangular cellular automata.


The Complexity of Enriched Mu-Calculi

Abstract: The fully enriched μ-calculus is the extension of the propositional μ-calculus with inverse programs, graded modalities, and nominals. While satisfiability in several expressive fragments of the fully enriched μ-calculus is known to be decidable and ExpTime-complete, it has recently been proved that the full calculus is undecidable. In this paper, we study the fragments of the fully enriched μ-calculus that are obtained by dropping at least one of the additional constructs. We show that, in all fragments obtained in this way, satisfiability is decidable and ExpTime-complete. Thus, we identify a family of decidable logics that are maximal (and incomparable) in expressive power. Our results are obtained by introducing two new automata models, showing that their emptiness problems are ExpTime-complete, and then reducing satisfiability in the relevant logics to these problems. The automata models we introduce are two-way graded alternating parity automata over infinite trees (2GAPTs) and fully enriched automata (FEAs) over infinite forests. The former are a common generalization of two incomparable automata models from the literature. The latter extend alternating automata in a similar way as the fully enriched μ-calculus extends the standard μ-calculus.


Canonical Coin Systems for Change-Making Problems

Abstract: The Change-Making Problem is to represent a given value with the fewest coins under a given coin system. As a variation of the knapsack problem, it is known to be NP-hard. Nevertheless, in most real money systems, the greedy algorithm yields optimal solutions. In this paper, we study what type of coin systems that guarantee the optimality of the greedy algorithm. We provide new proofs for a sufficient and necessary condition for the so-called \emph{canonical} coin systems with four or five types of coins, and a sufficient condition for non-canonical coin systems, respectively. Moreover, we present an $O(m^2)$ algorithm that decides whether a tight coin system is canonical.


Foundations of the Pareto Iterated Local Search Metaheuristic

Abstract: The paper describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow shop scheduling problems under multiple objectives. While the obtained results are encouraging in terms of their quality, another positive attribute of the approach is its' simplicity as it does require the setting of only very few parameters. The implementation of the Pareto Iterated Local Search metaheuristic is based on the MOOPPS computer system of local search heuristics for multi-objective scheduling which has been awarded the European Academic Software Award 2002 in Ronneby, Sweden (http://www.easa-award.net/, http://www.bth.se/llab/easa_2002.nsf)


A Computational Study of Genetic Crossover Operators for Multi-Objective Vehicle Routing Problem with Soft Time Windows

Abstract: The article describes an investigation of the effectiveness of genetic algorithms for multi-objective combinatorial optimization (MOCO) by presenting an application for the vehicle routing problem with soft time windows. The work is motivated by the question, if and how the problem structure influences the effectiveness of different configurations of the genetic algorithm. Computational results are presented for different classes of vehicle routing problems, varying in their coverage with time windows, time window size, distribution and number of customers. The results are compared with a simple, but effective local search approach for multi-objective combinatorial optimization problems.


Genetic Algorithms for multiple objective vehicle routing

Abstract: The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic algorithm to adress even problems with efficient, but convex-dominated alternatives. The algorithm is implemented in a multilingual computer program, solving vehicle routing problems with time windows under multiple objectives. The graphical user interface of the program shows the progress of the genetic algorithm and the main parameters of the approach can be easily modified. In addition to that, the program provides powerful decision support to the decision maker. The software has proved it's excellence at the finals of the European Academic Software Award EASA, held at the Keble college/ University of Oxford/ Great Britain.


Agent Models of Political Interactions

Abstract: Looks at state interactions from an agent based AI perspective to see state interactions as an example of emergent intelligent behavior. Exposes basic principles of game theory.


Stochastic Combinatorial Optimization under Probabilistic Constraints

Abstract: In this paper, we present approximation algorithms for combinatorial optimization problems under probabilistic constraints. Specifically, we focus on stochastic variants of two important combinatorial optimization problems: the k-center problem and the set cover problem, with uncertainty characterized by a probability distribution over set of points or elements to be covered. We consider these problems under adaptive and non-adaptive settings, and present efficient approximation algorithms for the case when underlying distribution is a product distribution. In contrast to the expected cost model prevalent in stochastic optimization literature, our problem definitions support restrictions on the probability distributions of the total costs, via incorporating constraints that bound the probability with which the incurred costs may exceed a given threshold.


The Semiotic Machine

Abstract: A semiotic model of the user interface in human-computer interaction. Algorithmic sign, semotics, algorithmic art.


Interaction Grammars

Abstract: Interaction Grammar (IG) is a grammatical formalism based on the notion of polarity. Polarities express the resource sensitivity of natural languages by modelling the distinction between saturated and unsaturated syntactic structures. Syntactic composition is represented as a chemical reaction guided by the saturation of polarities. It is expressed in a model-theoretic framework where grammars are constraint systems using the notion of tree description and parsing appears as a process of building tree description models satisfying criteria of saturation and minimality.


Complexity of comparison of influence of players in simple games

Abstract: Coalitional voting games appear in different forms in multi-agent systems, social choice and threshold logic. In this paper, the complexity of comparison of influence between players in coalitional voting games is characterized. The possible representations of simple games considered are simple games represented by winning coalitions, minimal winning coalitions, weighted voting game or a multiple weighted voting game. The influence of players is gauged from the viewpoint of basic player types, desirability relations and classical power indices such as Shapley-Shubik index, Banzhaf index, Holler index, Deegan-Packel index and Chow parameters. Among other results, it is shown that for a simple game represented by minimal winning coalitions, although it is easy to verify whether a player has zero or one voting power, computing the Banzhaf value of the player is #P-complete. Moreover, it is proved that multiple weighted voting games are the only representations for which it is NP-hard to verify whether the game is linear or not. For a simple game with a set W^m of minimal winning coalitions and n players, a O(n.|W^m|+(n^2)log(n)) algorithm is presented which returns `no' if the game is non-linear and returns the strict desirability ordering otherwise. The complexity of transforming simple games into compact representations is also examined.


Computer Art in the Former Soviet Bloc

Abstract: Documents early computer art in the Soviet bloc and describes Marxist art theory.


Power Control in Cognitive Radio Networks: How to Cross a Multi-Lane Highway

Abstract: We consider power control in cognitive radio networks where secondary users identify and exploit instantaneous and local spectrum opportunities without causing unacceptable interference to primary users. We qualitatively characterize the impact of the transmission power of secondary users on the occurrence of spectrum opportunities and the reliability of opportunity detection. Based on a Poisson model of the primary network, we quantify these impacts by showing that (i) the probability of spectrum opportunity decreases exponentially with respect to the transmission power of secondary users, where the exponential decay constant is given by the traffic load of primary users; (ii) reliable opportunity detection is achieved in the two extreme regimes in terms of the ratio between the transmission power of secondary users and that of primary users. Such analytical characterizations allow us to study power control for optimal transport throughput under constraints on the interference to primary users. Furthermore, we reveal the difference between detecting primary signals and detecting spectrum opportunities, and demonstrate the complex relationship between physical layer spectrum sensing and MAC layer throughput. The dependency of this PHY-MAC interaction on the application type and the use of handshake signaling such as RTS/CTS is illustrated.


A framework for the interactive resolution of multi-objective vehicle routing problems

Abstract: The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.


Improving Local Search for Fuzzy Scheduling Problems

Abstract: The integration of fuzzy set theory and fuzzy logic into scheduling is a rather new aspect with growing importance for manufacturing applications, resulting in various unsolved aspects. In the current paper, we investigate an improved local search technique for fuzzy scheduling problems with fitness plateaus, using a multi criteria formulation of the problem. We especially address the problem of changing job priorities over time as studied at the Sherwood Press Ltd, a Nottingham based printing company, who is a collaborator on the project.


Binary Random Sequences Obtained From Decimal Sequences

Abstract: This paper presents a twist to the generation of binary random sequences by starting with decimal sequences. Rather than representing the prime reciprocal sequence directly in base 2, we first right the prime reciprocal in base 10 and then convert it into the binary form. The autocorrelation and cross-correlation properties of these binary random (BRD) sequences are discussed.


The Prolog Interface to the Unstructured Information Management Architecture

Abstract: In this paper we describe the design and implementation of the Prolog interface to the Unstructured Information Management Architecture (UIMA) and some of its applications in natural language processing. The UIMA Prolog interface translates unstructured data and the UIMA Common Analysis Structure (CAS) into a Prolog knowledge base, over which, the developers write rules and use resolution theorem proving to search and generate new annotations over the unstructured data. These rules can explore all the previous UIMA annotations (such as, the syntactic structure, parsing statistics) and external Prolog knowledge bases (such as, Prolog WordNet and Extended WordNet) to implement a variety of tasks for the natural language analysis. We also describe applications of this logic programming interface in question analysis (such as, focus detection, answer-type and other constraints detection), shallow parsing (such as, relations in the syntactic structure), and answer selection.


A Simple Mechanism for Focused Web-harvesting

Abstract: The focused web-harvesting is deployed to realize an automated and comprehensive index databases as an alternative way for virtual topical data integration. The web-harvesting has been implemented and extended by not only specifying the targeted URLs, but also predefining human-edited harvesting parameters to improve the speed and accuracy. The harvesting parameter set comprises three main components. First, the depth-scale of being harvested final pages containing desired information counted from the first page at the targeted URLs. Secondly, the focus-point number to determine the exact box containing relevant information. Lastly, the combination of keywords to recognize encountered hyperlinks of relevant images or full-texts embedded in those final pages. All parameters are accessible and fully customizable for each target by the administrators of participating institutions over an integrated web interface. A real implementation to the Indonesian Scientific Index which covers all scientific information across Indonesia is also briefly introduced.


Microcontroller-based System for Modular Networked Robot

Abstract: A prototype of modular networked robot for autonomous monitoring works with full control over web through wireless connection has been developed. The robot is equipped with a particular set of built-in analyzing tools and appropriate censors, depending on its main purposes, to enable self-independent and real-time data acquisition and processing. The paper is focused on the microcontroller-based system to realize the modularity. The whole system is divided into three modules : main unit, data acquisition and data processing, while the analyzed results and all aspects of control and monitoring systems are fully accessible over an integrated web-interface. This concept leads to some unique features : enhancing flexibility due to enabling partial replacement of the modules according to user needs, easy access over web for remote users, and low development and maintenance cost due to software dominated components.


Proposition of the Interactive Pareto Iterated Local Search Procedure - Elements and Initial Experiments

Abstract: The article presents an approach to interactively solve multi-objective optimization problems. While the identification of efficient solutions is supported by computational intelligence techniques on the basis of local search, the search is directed by partial preference information obtained from the decision maker. An application of the approach to biobjective portfolio optimization, modeled as the well-known knapsack problem, is reported, and experimental results are reported for benchmark instances taken from the literature. In brief, we obtain encouraging results that show the applicability of the approach to the described problem.


Bin Packing Under Multiple Objectives - a Heuristic Approximation Approach

Abstract: The article proposes a heuristic approximation approach to the bin packing problem under multiple objectives. In addition to the traditional objective of minimizing the number of bins, the heterogeneousness of the elements in each bin is minimized, leading to a biobjective formulation of the problem with a tradeoff between the number of bins and their heterogeneousness. An extension of the Best-Fit approximation algorithm is presented to solve the problem. Experimental investigations have been carried out on benchmark instances of different size, ranging from 100 to 1000 items. Encouraging results have been obtained, showing the applicability of the heuristic approach to the described problem.


An application of the Threshold Accepting metaheuristic for curriculum based course timetabling

Abstract: The article presents a local search approach for the solution of timetabling problems in general, with a particular implementation for competition track 3 of the International Timetabling Competition 2007 (ITC 2007). The heuristic search procedure is based on Threshold Accepting to overcome local optima. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution. The overall concept has been incrementally obtained from a series of experiments, which we describe in each (sub)section of the paper. In result, we successfully derived a potential candidate solution approach for the finals of track 3 of the ITC 2007.


Peek Arc Consistency

Abstract: This paper studies peek arc consistency, a reasoning technique that extends the well-known arc consistency technique for constraint satisfaction. In contrast to other more costly extensions of arc consistency that have been studied in the literature, peek arc consistency requires only linear space and quadratic time and can be parallelized in a straightforward way such that it runs in linear time with a linear number of processors. We demonstrate that for various constraint languages, peek arc consistency gives a polynomial-time decision procedure for the constraint satisfaction problem. We also present an algebraic characterization of those constraint languages that can be solved by peek arc consistency, and study the robustness of the algorithm.


The stable configuration in acyclic preference-based systems

Abstract: Acyclic preferences recently appeared as an elegant way to model many distributed systems. An acyclic instance admits a unique stable configuration, which can reveal the performance of the system. In this paper, we give the statistical properties of the stable configuration for three classes of acyclic preferences: node-based preferences, distance-based preferences, and random acyclic systems. Using random overlay graphs, we prove using mean-field and fluid-limit techniques that these systems have an asymptotically continuous independent rank distribution for a proper scaling, and the analytical solution is compared to simulations. These results provide a theoretical ground for validating the performance of bandwidth-based or proximity-based unstructured systems.


Approximating the volume of unions and intersections of high-dimensional geometric objects

Abstract: We consider the computation of the volume of the union of high-dimensional geometric objects. While showing that this problem is #P-hard already for very simple bodies (i.e., axis-parallel boxes), we give a fast FPRAS for all objects where one can: (1) test whether a given point lies inside the object, (2) sample a point uniformly, (3) calculate the volume of the object in polynomial time. All three oracles can be weak, that is, just approximate. This implies that Klee's measure problem and the hypervolume indicator can be approximated efficiently even though they are #P-hard and hence cannot be solved exactly in time polynomial in the number of dimensions unless P=NP. Our algorithm also allows to approximate efficiently the volume of the union of convex bodies given by weak membership oracles. For the analogous problem of the intersection of high-dimensional geometric objects we prove #P-hardness for boxes and show that there is no multiplicative polynomial-time $2^{d^{1-\epsilon}}$-approximation for certain boxes unless NP=BPP, but give a simple additive polynomial-time $\epsilon$-approximation.


Between the Information Economy and Student Recruitment: Present Conjuncture and Future Prospects

Abstract: In university programs and curricula, in general we react to the need to meet market needs. We respond to market stimulus, or at least try to do so. Consider now an inverted view. Consider our data and perspectives in university programs as reflecting and indeed presaging economic trends. In this article I pursue this line of thinking. I show how various past events fit very well into this new view. I provide explanation for why some technology trends happened as they did, and why some current developments are important now.


On the role of metaphor in information visualization

Abstract: The concept of metaphor, in particular graphical (or visual) metaphor, is central to the field of information visualization. Information graphics and interactive information visualization systems employ a variety of metaphorical devices to make abstract, complex, voluminous, or otherwise difficult-to-comprehend information understandable in graphical terms. This paper explores the use of metaphor in information visualization, advancing the theory previously argued by Johnson, Lakoff, Tversky et al. that many information graphics are metaphorically understood in terms of cognitively entrenched spatial patterns known as image schemas. These patterns serve to structure and constrain abstract reasoning processes via metaphorical projection operations that are grounded in everyday perceptual experiences with phenomena such as containment, movement, and force dynamics. Building on previous research, I argue that information graphics promote comprehension of their target information through the use of graphical patterns that invoke these preexisting schematic structures. I further theorize that the degree of structural alignment of a particular graphic with one or more corresponding image schemas accounts for its perceived degree of intuitiveness. Accordingly, image schema theory can provide a powerful explanatory and predictive framework for visualization research. I review relevant theories of analogy and metaphor, and discuss the image schematic properties of several common types of information graphic. I conclude with the proposal that the inventory of image schemas culled from linguistic studies can serve as the basis for an inventory of design elements suitable for developing intuitive and effective new information visualization techniques.


Superposition for Fixed Domains

Abstract: Superposition is an established decision procedure for a variety of first-order logic theories represented by sets of clauses. A satisfiable theory, saturated by superposition, implicitly defines a minimal term-generated model for the theory. Proving universal properties with respect to a saturated theory directly leads to a modification of the minimal model's term-generated domain, as new Skolem functions are introduced. For many applications, this is not desired. Therefore, we propose the first superposition calculus that can explicitly represent existentially quantified variables and can thus compute with respect to a given domain. This calculus is sound and refutationally complete in the limit for a first-order fixed domain semantics. For saturated Horn theories and classes of positive formulas, we can even employ the calculus to prove properties of the minimal model itself, going beyond the scope of known superposition-based approaches.


MOOPPS: An Optimization System for Multi Objective Scheduling

Abstract: In the current paper, we present an optimization system solving multi objective production scheduling problems (MOOPPS). The identification of Pareto optimal alternatives or at least a close approximation of them is possible by a set of implemented metaheuristics. Necessary control parameters can easily be adjusted by the decision maker as the whole software is fully menu driven. This allows the comparison of different metaheuristic algorithms for the considered problem instances. Results are visualized by a graphical user interface showing the distribution of solutions in outcome space as well as their corresponding Gantt chart representation. The identification of a most preferred solution from the set of efficient solutions is supported by a module based on the aspiration interactive method (AIM). The decision maker successively defines aspiration levels until a single solution is chosen. After successfully competing in the finals in Ronneby, Sweden, the MOOPPS software has been awarded the European Academic Software Award 2002 (http://www.bth.se/llab/easa_2002.nsf)


Moving and resizing of the screen objects

Abstract: The shape and size of the objects, which we see on the screen, when the application is running, are defined at the design time. By using some sort of adaptive interface, developers give users a chance to resize these objects or on rare occasion even change, but all these changes are predetermined by a developer; user can't go out of the designer's scenario. Making each and all elements moveable / resizable and giving users the full control of these processes, changes the whole idea of applications; programs become user-driven and significantly increase the effectiveness of users' work. This article is about the instrument to turn any screen object into moveable / resizable.


A Novel Proportional Fairness Criterion for Throughput Allocation in Multirate IEEE 802.11

Abstract: This paper focuses on multirate IEEE 802.11 Wireless LAN employing the mandatory Distributed Coordination Function (DCF) option. Its aim is threefold. Upon starting from the multi-dimensional Markovian state transition model proposed by Malone \textit{et.al.} for characterizing the behavior of the IEEE 802.11 protocol at the Medium Access Control layer, it presents an extension accounting for packet transmission failures due to channel errors. Second, it establishes the conditions under which a network constituted by $N$ stations, each station transmitting with its own bit rate, $R^{(s)}_d$, and packet rate, $\lambda_s$, can be assumed loaded. Finally, it proposes a modified Proportional Fairness (PF) criterion, suitable for mitigating the \textit{rate anomaly} problem of multirate loaded IEEE 802.11 Wireless LANs, employing the mandatory DCF option. Compared to the widely adopted assumption of saturated network, the proposed fairness criterion can be applied to general loaded networks. The throughput allocation resulting from the proposed algorithm is able to greatly increase the aggregate throughput of the DCF, while ensuring fairness levels among the stations of the same order as the ones guaranteed by the classical PF criterion. Simulation results are presented for some sample scenarios, confirming the effectiveness of the proposed criterion for optimized throughput allocation.


Variable Neighborhood Search for the University Lecturer-Student Assignment Problem

Abstract: The paper presents a study of local search heuristics in general and variable neighborhood search in particular for the resolution of an assignment problem studied in the practical work of universities. Here, students have to be assigned to scientific topics which are proposed and supported by members of staff. The problem involves the optimization under given preferences of students which may be expressed when applying for certain topics. It is possible to observe that variable neighborhood search leads to superior results for the tested problem instances. One instance is taken from an actual case, while others have been generated based on the real world data to support the analysis with a deeper analysis. An extension of the problem has been formulated by integrating a second objective function that simultaneously balances the workload of the members of staff while maximizing utility of the students. The algorithmic approach has been prototypically implemented in a computer system. One important aspect in this context is the application of the research work to problems of other scientific institutions, and therefore the provision of decision support functionalities.


Managing Varying Worst Case Execution Times on DVS Platforms

Abstract: Energy efficient real-time task scheduling attracted a lot of attention in the past decade. Most of the time, deterministic execution lengths for tasks were considered, but this model fits less and less with the reality, especially with the increasing number of multimedia applications. It's why a lot of research is starting to consider stochastic models, where execution times are only known stochastically. However, authors consider that they have a pretty much precise knowledge about the properties of the system, especially regarding to the worst case execution time (or worst case execution cycles, WCEC). In this work, we try to relax this hypothesis, and assume that the WCEC can vary. We propose miscellaneous methods to react to such a situation, and give many simulation results attesting that with a small effort, we can provide very good results, allowing to keep a low deadline miss rate as well as an energy consumption similar to clairvoyant algorithms.


Minkowski Sum Selection and Finding

Abstract: For the \textsc{Minkowski Sum Selection} problem with linear objective functions, we obtain the following results: (1) optimal $O(n\log n)$ time algorithms for $\lambda=1$; (2) $O(n\log^2 n)$ time deterministic algorithms and expected $O(n\log n)$ time randomized algorithms for any fixed $\lambda>1$. For the \textsc{Minkowski Sum Finding} problem with linear objective functions or objective functions of the form $f(x,y)=\frac{by}{ax}$, we construct optimal $O(n\log n)$ time algorithms for any fixed $\lambda\geq 1$.