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cs/0611113
An Anthological Review of Research Utilizing MontyLingua, a Python-Based End-to-End Text Processor
cs.CL
MontyLingua, an integral part of ConceptNet which is currently the largest commonsense knowledge base, is an English text processor developed using Python programming language in MIT Media Lab. The main feature of MontyLingua is the coverage for all aspects of English text processing from raw input text to semantic meanings and summary generation, yet each component in MontyLingua is loosely-coupled to each other at the architectural and code level, which enabled individual components to be used independently or substituted. However, there has been no review exploring the role of MontyLingua in recent research work utilizing it. This paper aims to review the use of and roles played by MontyLingua and its components in research work published in 19 articles between October 2004 and August 2006. We had observed a diversified use of MontyLingua in many different areas, both generic and domain-specific. Although the use of text summarizing component had not been observe, we are optimistic that it will have a crucial role in managing the current trend of information overload in future research.
cs/0611114
Very Sparse Stable Random Projections, Estimators and Tail Bounds for Stable Random Projections
cs.DS cs.IT cs.LG math.IT
This paper will focus on three different aspects in improving the current practice of stable random projections. Firstly, we propose {\em very sparse stable random projections} to significantly reduce the processing and storage cost, by replacing the $\alpha$-stable distribution with a mixture of a symmetric $\alpha$-Pareto distribution (with probability $\beta$, $0<\beta\leq1$) and a point mass at the origin (with a probability $1-\beta$). This leads to a significant $\frac{1}{\beta}$-fold speedup for small $\beta$. Secondly, we provide an improved estimator for recovering the original $l_\alpha$ norms from the projected data. The standard estimator is based on the (absolute) sample median, while we suggest using the geometric mean. The geometric mean estimator we propose is strictly unbiased and is easier to study. Moreover, the geometric mean estimator is more accurate, especially non-asymptotically. Thirdly, we provide an adequate answer to the basic question of how many projections (samples) are needed for achieving some pre-specified level of accuracy. \cite{Proc:Indyk_FOCS00,Article:Indyk_TKDE03} did not provide a criterion that can be used in practice. The geometric mean estimator we propose allows us to derive sharp tail bounds which can be expressed in exponential forms with constants explicitly given.
cs/0611115
A higher-order active contour model of a `gas of circles' and its application to tree crown extraction
cs.CV
Many image processing problems involve identifying the region in the image domain occupied by a given entity in the scene. Automatic solution of these problems requires models that incorporate significant prior knowledge about the shape of the region. Many methods for including such knowledge run into difficulties when the topology of the region is unknown a priori, for example when the entity is composed of an unknown number of similar objects. Higher-order active contours (HOACs) represent one method for the modelling of non-trivial prior knowledge about shape without necessarily constraining region topology, via the inclusion of non-local interactions between region boundary points in the energy defining the model. The case of an unknown number of circular objects arises in a number of domains, e.g. medical, biological, nanotechnological, and remote sensing imagery. Regions composed of an a priori unknown number of circles may be referred to as a `gas of circles'. In this report, we present a HOAC model of a `gas of circles'. In order to guarantee stable circles, we conduct a stability analysis via a functional Taylor expansion of the HOAC energy around a circular shape. This analysis fixes one of the model parameters in terms of the others and constrains the rest. In conjunction with a suitable likelihood energy, we apply the model to the extraction of tree crowns from aerial imagery, and show that the new model outperforms other techniques.
cs/0611118
A Neutrosophic Description Logic
cs.AI
Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with crisp, well defined concepts. That is, concepts for which the problem whether an individual is an instance of it is yes/no question. More often than not, the concepts encountered in the real world do not have a precisely defined criteria of membership: we may say that an individual is an instance of a concept only to a certain degree, depending on the individual's properties. The DLs that deal with such fuzzy concepts are called fuzzy DLs. In order to deal with fuzzy, incomplete, indeterminate and inconsistent concepts, we need to extend the fuzzy DLs, combining the neutrosophic logic with a classical DL. In particular, concepts become neutrosophic (here neutrosophic means fuzzy, incomplete, indeterminate, and inconsistent), thus reasoning about neutrosophic concepts is supported. We'll define its syntax, its semantics, and describe its properties.
cs/0611120
Wireless Information-Theoretic Security - Part I: Theoretical Aspects
cs.IT math.IT
In this two-part paper, we consider the transmission of confidential data over wireless wiretap channels. The first part presents an information-theoretic problem formulation in which two legitimate partners communicate over a quasi-static fading channel and an eavesdropper observes their transmissions through another independent quasi-static fading channel. We define the secrecy capacity in terms of outage probability and provide a complete characterization of the maximum transmission rate at which the eavesdropper is unable to decode any information. In sharp contrast with known results for Gaussian wiretap channels (without feedback), our contribution shows that in the presence of fading information-theoretic security is achievable even when the eavesdropper has a better average signal-to-noise ratio (SNR) than the legitimate receiver - fading thus turns out to be a friend and not a foe. The issue of imperfect channel state information is also addressed. Practical schemes for wireless information-theoretic security are presented in Part II, which in some cases comes close to the secrecy capacity limits given in this paper.
cs/0611121
Wireless Information-Theoretic Security - Part II: Practical Implementation
cs.IT math.IT
In Part I of this two-part paper on confidential communication over wireless channels, we studied the fundamental security limits of quasi-static fading channels from the point of view of outage secrecy capacity with perfect and imperfect channel state information. In Part II, we develop a practical secret key agreement protocol for Gaussian and quasi-static fading wiretap channels. The protocol uses a four-step procedure to secure communications: establish common randomness via an opportunistic transmission, perform message reconciliation, establish a common key via privacy amplification, and use of the key. We introduce a new reconciliation procedure that uses multilevel coding and optimized low density parity check codes which in some cases comes close to achieving the secrecy capacity limits established in Part I. Finally, we develop new metrics for assessing average secure key generation rates and show that our protocol is effective in secure key renewal.
cs/0611122
Knowledge Representation Concepts for Automated SLA Management
cs.SE cs.AI cs.LO cs.PL
Outsourcing of complex IT infrastructure to IT service providers has increased substantially during the past years. IT service providers must be able to fulfil their service-quality commitments based upon predefined Service Level Agreements (SLAs) with the service customer. They need to manage, execute and maintain thousands of SLAs for different customers and different types of services, which needs new levels of flexibility and automation not available with the current technology. The complexity of contractual logic in SLAs requires new forms of knowledge representation to automatically draw inferences and execute contractual agreements. A logic-based approach provides several advantages including automated rule chaining allowing for compact knowledge representation as well as flexibility to adapt to rapidly changing business requirements. We suggest adequate logical formalisms for representation and enforcement of SLA rules and describe a proof-of-concept implementation. The article describes selected formalisms of the ContractLog KR and their adequacy for automated SLA management and presents results of experiments to demonstrate flexibility and scalability of the approach.
cs/0611123
Functional Bregman Divergence and Bayesian Estimation of Distributions
cs.IT cs.LG math.IT
A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functions or distributions, and generalizes the standard Bregman divergence for vectors and a previous pointwise Bregman divergence that was defined for functions. A recently published result showed that the mean minimizes the expected Bregman divergence. The new functional definition enables the extension of this result to the continuous case to show that the mean minimizes the expected functional Bregman divergence over a set of functions or distributions. It is shown how this theorem applies to the Bayesian estimation of distributions. Estimation of the uniform distribution from independent and identically drawn samples is used as a case study.
cs/0611124
Low-rank matrix factorization with attributes
cs.LG cs.AI cs.IR
We develop a new collaborative filtering (CF) method that combines both previously known users' preferences, i.e. standard CF, as well as product/user attributes, i.e. classical function approximation, to predict a given user's interest in a particular product. Our method is a generalized low rank matrix completion problem, where we learn a function whose inputs are pairs of vectors -- the standard low rank matrix completion problem being a special case where the inputs to the function are the row and column indices of the matrix. We solve this generalized matrix completion problem using tensor product kernels for which we also formally generalize standard kernel properties. Benchmark experiments on movie ratings show the advantages of our generalized matrix completion method over the standard matrix completion one with no information about movies or people, as well as over standard multi-task or single task learning methods.
cs/0611125
Relay Channels with Confidential Messages
cs.IT math.IT
We consider a relay channel where a relay helps the transmission of messages from one sender to one receiver. The relay is considered not only as a sender that helps the message transmission but as a wire-tapper who can obtain some knowledge about the transmitted messages. In this paper we study the coding problem of the relay channel under the situation that some of transmitted messages are confidential to the relay. A security of such confidential messages is measured by the conditional entropy. The rate region is defined by the set of transmission rates for which messages are reliably transmitted and the security of confidential messages is larger than a prescribed level. In this paper we give two definition of the rate region. We first define the rate region in the case of deterministic encoder and call it the deterministic rate region. Next, we define the rate region in the case of stochastic encoder and call it the stochastic rate region. We derive explicit inner and outer bounds for the above two rate regions and present a class of relay channels where two bounds match. Furthermore, we show that stochastic encoder can enlarge the rate region. We also evaluate the deterministic rate region of the Gaussian relay channel with confidential messages.
cs/0611127
Coupling Methodology within the Software Platform Alliances
cs.MS cs.CE
CEA, ANDRA and EDF are jointly developing the software platform ALLIANCES which aim is to produce a tool for the simulation of nuclear waste storage and disposal repository. This type of simulations deals with highly coupled thermo-hydro-mechanical and chemical (T-H-M-C) processes. A key objective of Alliances is to give the capability for coupling algorithms development between existing codes. The aim of this paper is to present coupling methodology use in the context of this software platform.
cs/0611129
Shannon's secrecy system with informed receivers and its application to systematic coding for wiretapped channels
cs.IT math.IT
Shannon's secrecy system is studied in a setting, where both the legitimate decoder and the wiretapper have access to side information sequences correlated to the source, but the wiretapper receives both the coded information and the side information via channels that are more noisy than the respective channels of the legitmate decoder, which in turn, also shares a secret key with the encoder. A single--letter characterization is provided for the achievable region in the space of five figures of merit: the equivocation at the wiretapper, the key rate, the distortion of the source reconstruction at the legitimate receiver, the bandwidth expansion factor of the coded channels, and the average transmission cost (generalized power). Beyond the fact that this is an extension of earlier studies, it also provides a framework for studying fundamental performance limits of systematic codes in the presence of a wiretap channel. The best achievable performance of systematic codes is then compared to that of a general code in several respects, and a few examples are given.
cs/0611131
Scatter Networks: A New Approach for Analyzing Information Scatter on the Web
cs.IR
Information on any given topic is often scattered across the web. Previously this scatter has been characterized through the distribution of a set of facts (i.e. pieces of information) across web pages, showing that typically a few pages contain many facts on the topic, while many pages contain just a few. While such approaches have revealed important scatter phenomena, they are lossy in that they conceal how specific facts (e.g. rare facts) occur in specific types of pages (e.g. fact-rich pages). To reveal such regularities, we construct bi-partite networks, consisting of two types of vertices: the facts contained in webpages and the webpages themselves. Such a representation enables the application of a series of network analysis techniques, revealing structural features such as connectivity, robustness, and clustering. We discuss the implications of each of these features to the users' ability to find comprehensive information online. Finally, we compare the bipartite graph structure of webpages and facts with the hyperlink structure between the webpages.
cs/0611132
The specifications making in complex CAD-system of renovation of the enterprises on the basis of modules in the drawing and electronic catalogues
cs.CE
The experience of automation of the specifications making of the projects of renovation of the industrial enterprises is described, being based on the special modules in the drawing containing the visible image and additional parameters, and electronic catalogues
cs/0611133
The modelling of the automation schemes of technological processes in CAD-system of renovation of the enterprises
cs.CE
According to the requirements of the Russian standards, the automation schemes are necessary practically in each project of renovation of industrial buildings and facilities, in which any technological processes are realized. The model representations of the automation schemes in CAD-system TechnoCAD GlassX are described. The models follow a principle "to exclude a repeated input operations"
cs/0611135
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
cs.AI
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed optimization problem; ii) non-linear learning can be brought into linear learning thanks to the kernel trick and the mapping of the initial search space onto a high dimensional feature space. The kernel is designed by the ML expert and it governs the efficiency of the SVM approach. In this paper, a new approach for the automatic design of kernels by Genetic Programming, called the Evolutionary Kernel Machine (EKM), is presented. EKM combines a well-founded fitness function inspired from the margin criterion, and a co-evolution framework ensuring the computational scalability of the approach. Empirical validation on standard ML benchmark demonstrates that EKM is competitive using state-of-the-art SVMs with tuned hyper-parameters.
cs/0611136
Neural Computation with Rings of Quasiperiodic Oscillators
cs.RO
We describe the use of quasiperiodic oscillators for computation and control of robots. We also describe their relationship to central pattern generators in simple organisms and develop a group theory for describing the dynamics of these systems.
cs/0611138
Functional Brain Imaging with Multi-Objective Multi-Modal Evolutionary Optimization
cs.AI
Functional brain imaging is a source of spatio-temporal data mining problems. A new framework hybridizing multi-objective and multi-modal optimization is proposed to formalize these data mining problems, and addressed through Evolutionary Computation (EC). The merits of EC for spatio-temporal data mining are demonstrated as the approach facilitates the modelling of the experts' requirements, and flexibly accommodates their changing goals.
cs/0611140
On the Benefits of Inoculation, an Example in Train Scheduling
cs.AI cs.NE
The local reconstruction of a railway schedule following a small perturbation of the traffic, seeking minimization of the total accumulated delay, is a very difficult and tightly constrained combinatorial problem. Notoriously enough, the railway company's public image degrades proportionally to the amount of daily delays, and the same goes for its profit! This paper describes an inoculation procedure which greatly enhances an evolutionary algorithm for train re-scheduling. The procedure consists in building the initial population around a pre-computed solution based on problem-related information available beforehand. The optimization is performed by adapting times of departure and arrival, as well as allocation of tracks, for each train at each station. This is achieved by a permutation-based evolutionary algorithm that relies on a semi-greedy heuristic scheduler to gradually reconstruct the schedule by inserting trains one after another. Experimental results are presented on various instances of a large real-world case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial math ematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clear-cut success auguring of substantial financial savings.
cs/0611141
A Generic Global Constraint based on MDDs
cs.AI
The paper suggests the use of Multi-Valued Decision Diagrams (MDDs) as the supporting data structure for a generic global constraint. We give an algorithm for maintaining generalized arc consistency (GAC) on this constraint that amortizes the cost of the GAC computation over a root-to-terminal path in the search tree. The technique used is an extension of the GAC algorithm for the regular language constraint on finite length input. Our approach adds support for skipped variables, maintains the reduced property of the MDD dynamically and provides domain entailment detection. Finally we also show how to adapt the approach to constraint types that are closely related to MDDs, such as AOMDDs and Case DAGs.
cs/0611144
Coding Improves the Optimal Delay-Throughput Trade-offs in Mobile Ad-Hoc Networks: Two-Dimensional I.I.D. Mobility Models
cs.NI cs.IT math.IT
In this paper, we investigate the delay-throughput trade-offs in mobile ad-hoc networks under two-dimensional i.i.d. mobility models. We consider two mobility time-scales: (i) Fast mobility where node mobility is at the same time-scale as data transmissions; (ii) Slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions. Given a delay constraint $D,$ the main results are as follows: (1) For the two-dimensional i.i.d. mobility model with fast mobiles, the maximum throughput per source-destination (S-D) pair is shown to be $O(\sqrt{D/n}),$ where $n$ is the number of mobiles. (2) For the two-dimensional i.i.d. mobility model with slow mobiles, the maximum throughput per S-D pair is shown to be $O(\sqrt[3]{D/n}).$ (3) For each case, we propose a joint coding-scheduling algorithm to achieve the optimal delay-throughput trade-offs.
cs/0611145
A Unified View of TD Algorithms; Introducing Full-Gradient TD and Equi-Gradient Descent TD
cs.LG
This paper addresses the issue of policy evaluation in Markov Decision Processes, using linear function approximation. It provides a unified view of algorithms such as TD(lambda), LSTD(lambda), iLSTD, residual-gradient TD. It is asserted that they all consist in minimizing a gradient function and differ by the form of this function and their means of minimizing it. Two new schemes are introduced in that framework: Full-gradient TD which uses a generalization of the principle introduced in iLSTD, and EGD TD, which reduces the gradient by successive equi-gradient descents. These three algorithms form a new intermediate family with the interesting property of making much better use of the samples than TD while keeping a gradient descent scheme, which is useful for complexity issues and optimistic policy iteration.
cs/0611146
Linear-Codes-Based Lossless Joint Source-Channel Coding for Multiple-Access Channels
cs.IT math.IT
A general lossless joint source-channel coding (JSCC) scheme based on linear codes and random interleavers for multiple-access channels (MACs) is presented and then analyzed in this paper. By the information-spectrum approach and the code-spectrum approach, it is shown that a linear code with a good joint spectrum can be used to establish limit-approaching lossless JSCC schemes for correlated general sources and general MACs, where the joint spectrum is a generalization of the input-output weight distribution. Some properties of linear codes with good joint spectra are investigated. A formula on the "distance" property of linear codes with good joint spectra is derived, based on which, it is further proved that, the rate of any systematic codes with good joint spectra cannot be larger than the reciprocal of the corresponding alphabet cardinality, and any sparse generator matrices cannot yield linear codes with good joint spectra. The problem of designing arbitrary rate coding schemes is also discussed. A novel idea called "generalized puncturing" is proposed, which makes it possible that one good low-rate linear code is enough for the design of coding schemes with multiple rates. Finally, various coding problems of MACs are reviewed in a unified framework established by the code-spectrum approach, under which, criteria and candidates of good linear codes in terms of spectrum requirements for such problems are clearly presented.
cs/0611148
Next Generation Language Resources using GRID
cs.DC cs.CL
This paper presents a case study concerning the challenges and requirements posed by next generation language resources, realized as an overall model of open, distributed and collaborative language infrastructure. If a sort of "new paradigm" is required, we think that the emerging and still evolving technology connected to Grid computing is a very interesting and suitable one for a concrete realization of this vision. Given the current limitations of Grid computing, it is very important to test the new environment on basic language analysis tools, in order to get the feeling of what are the potentialities and possible limitations connected to its use in NLP. For this reason, we have done some experiments on a module of Linguistic Miner, i.e. the extraction of linguistic patterns from restricted domain corpora.
cs/0611150
A Novel Bayesian Classifier using Copula Functions
cs.LG cs.AI cs.IR
A useful method for representing Bayesian classifiers is through \emph{discriminant functions}. Here, using copula functions, we propose a new model for discriminants. This model provides a rich and generalized class of decision boundaries. These decision boundaries significantly boost the classification accuracy especially for high dimensional feature spaces. We strengthen our analysis through simulation results.
cs/0611155
Zig-zag and Replacement Product Graphs and LDPC Codes
cs.IT math.IT
The performance of codes defined from graphs depends on the expansion property of the underlying graph in a crucial way. Graph products, such as the zig-zag product and replacement product provide new infinite families of constant degree expander graphs. The paper investigates the use of zig-zag and replacement product graphs for the construction of codes on graphs. A modification of the zig-zag product is also introduced, which can operate on two unbalanced biregular bipartite graphs.
cs/0611156
D-MG Tradeoff and Optimal Codes for a Class of AF and DF Cooperative Communication Protocols
cs.IT math.IT
We consider cooperative relay communication in a fading channel environment under the Orthogonal Amplify and Forward (OAF) and Orthogonal and Non-Orthogonal Selection Decode and Forward (OSDF and NSDF) protocols. For all these protocols, we compute the Diversity-Multiplexing Gain Tradeoff (DMT). We construct DMT optimal codes for the protocols which are sphere decodable and, in certain cases, incur minimum possible delay. Our results establish that the DMT of the OAF protocol is identical to the DMT of the Non-Orthogonal Amplify and Forward (NAF) protocol. Two variants of the NSDF protocol are considered: fixed-NSDF and variable-NSDF protocol. In the variable-NSDF protocol, the fraction of time duration for which the source alone transmits is allowed to vary with the rate of communication. Among the class of static amplify-and-forward and decode-and-forward protocols, the variable-NSDF protocol is shown to have the best known DMT for any number of relays apart from the two-relay case. When there are two relays, the variable-NSDF protocol is shown to improve on the DMT of the best previously-known protocol for higher values of the multiplexing gain. Our results also establish that the fixed-NSDF protocol has a better DMT than the NAF protocol for any number of relays. Finally, we present a DMT optimal code construction for the NAF protocol.
cs/0611160
Complementary Sets, Generalized Reed-Muller Codes, and Power Control for OFDM
cs.IT math.IT
The use of error-correcting codes for tight control of the peak-to-mean envelope power ratio (PMEPR) in orthogonal frequency-division multiplexing (OFDM) transmission is considered in this correspondence. By generalizing a result by Paterson, it is shown that each q-phase (q is even) sequence of length 2^m lies in a complementary set of size 2^{k+1}, where k is a nonnegative integer that can be easily determined from the generalized Boolean function associated with the sequence. For small k this result provides a reasonably tight bound for the PMEPR of q-phase sequences of length 2^m. A new 2^h-ary generalization of the classical Reed-Muller code is then used together with the result on complementary sets to derive flexible OFDM coding schemes with low PMEPR. These codes include the codes developed by Davis and Jedwab as a special case. In certain situations the codes in the present correspondence are similar to Paterson's code constructions and often outperform them.
cs/0611161
On the Peak-to-Mean Envelope Power Ratio of Phase-Shifted Binary Codes
cs.IT math.IT
The peak-to-mean envelope power ratio (PMEPR) of a code employed in orthogonal frequency-division multiplexing (OFDM) systems can be reduced by permuting its coordinates and by rotating each coordinate by a fixed phase shift. Motivated by some previous designs of phase shifts using suboptimal methods, the following question is considered in this paper. For a given binary code, how much PMEPR reduction can be achieved when the phase shifts are taken from a 2^h-ary phase-shift keying (2^h-PSK) constellation? A lower bound on the achievable PMEPR is established, which is related to the covering radius of the binary code. Generally speaking, the achievable region of the PMEPR shrinks as the covering radius of the binary code decreases. The bound is then applied to some well understood codes, including nonredundant BPSK signaling, BCH codes and their duals, Reed-Muller codes, and convolutional codes. It is demonstrated that most (presumably not optimal) phase-shift designs from the literature attain or approach our bound.
cs/0611162
Quaternary Constant-Amplitude Codes for Multicode CDMA
cs.IT math.IT
A constant-amplitude code is a code that reduces the peak-to-average power ratio (PAPR) in multicode code-division multiple access (MC-CDMA) systems to the favorable value 1. In this paper quaternary constant-amplitude codes (codes over Z_4) of length 2^m with error-correction capabilities are studied. These codes exist for every positive integer m, while binary constant-amplitude codes cannot exist if m is odd. Every word of such a code corresponds to a function from the binary m-tuples to Z_4 having the bent property, i.e., its Fourier transform has magnitudes 2^{m/2}. Several constructions of such functions are presented, which are exploited in connection with algebraic codes over Z_4 (in particular quaternary Reed-Muller, Kerdock, and Delsarte-Goethals codes) to construct families of quaternary constant-amplitude codes. Mappings from binary to quaternary constant-amplitude codes are presented as well.
cs/0611163
On Measuring the Impact of Human Actions in the Machine Learning of a Board Game's Playing Policies
cs.AI cs.GT cs.NE
We investigate systematically the impact of human intervention in the training of computer players in a strategy board game. In that game, computer players utilise reinforcement learning with neural networks for evolving their playing strategies and demonstrate a slow learning speed. Human intervention can significantly enhance learning performance, but carry-ing it out systematically seems to be more of a problem of an integrated game development environment as opposed to automatic evolutionary learning.
cs/0611164
Player co-modelling in a strategy board game: discovering how to play fast
cs.AI cs.LG
In this paper we experiment with a 2-player strategy board game where playing models are evolved using reinforcement learning and neural networks. The models are evolved to speed up automatic game development based on human involvement at varying levels of sophistication and density when compared to fully autonomous playing. The experimental results suggest a clear and measurable association between the ability to win games and the ability to do that fast, while at the same time demonstrating that there is a minimum level of human involvement beyond which no learning really occurs.
cs/0611166
Lossless fitness inheritance in genetic algorithms for decision trees
cs.AI cs.DS cs.NE
When genetic algorithms are used to evolve decision trees, key tree quality parameters can be recursively computed and re-used across generations of partially similar decision trees. Simply storing instance indices at leaves is enough for fitness to be piecewise computed in a lossless fashion. We show the derivation of the (substantial) expected speed-up on two bounding case problems and trace the attractive property of lossless fitness inheritance to the divide-and-conquer nature of decision trees. The theoretical results are supported by experimental evidence.
cs/0612002
Reuse of designs: Desperately seeking an interdisciplinary cognitive approach
cs.HC cs.AI
This text analyses the papers accepted for the workshop "Reuse of designs: an interdisciplinary cognitive approach". Several dimensions and questions considered as important (by the authors and/or by us) are addressed: What about the "interdisciplinary cognitive" character of the approaches adopted by the authors? Is design indeed a domain where the use of CBR is particularly suitable? Are there important distinctions between CBR and other approaches? Which types of knowledge -other than cases- is being, or might be, used in CBR systems? With respect to cases: are there different "types" of case and different types of case use? which formats are adopted for their representation? do cases have "components"? how are cases organised in the case memory? Concerning their retrieval: which types of index are used? on which types of relation is retrieval based? how does one retrieve only a selected number of cases, i.e., how does one retrieve only the "best" cases? which processes and strategies are used, by the system and by its user? Finally, some important aspects of CBR system development are shortly discussed: should CBR systems be assistance or autonomous systems? how can case knowledge be "acquired"? what about the empirical evaluation of CBR systems? The conclusion points out some lacking points: not much attention is paid to the user, and few papers have indeed adopted an interdisciplinary cognitive approach.
cs/0612007
High SNR Analysis for MIMO Broadcast Channels: Dirty Paper Coding vs. Linear Precoding
cs.IT math.IT
We study the MIMO broadcast channel and compare the achievable throughput for the optimal strategy of dirty paper coding to that achieved with sub-optimal and lower complexity linear precoding (e.g., zero-forcing and block diagonalization) transmission. Both strategies utilize all available spatial dimensions and therefore have the same multiplexing gain, but an absolute difference in terms of throughput does exist. The sum rate difference between the two strategies is analytically computed at asymptotically high SNR, and it is seen that this asymptotic statistic provides an accurate characterization at even moderate SNR levels. Furthermore, the difference is not affected by asymmetric channel behavior when each user a has different average SNR. Weighted sum rate maximization is also considered, and a similar quantification of the throughput difference between the two strategies is performed. In the process, it is shown that allocating user powers in direct proportion to user weights asymptotically maximizes weighted sum rate. For multiple antenna users, uniform power allocation across the receive antennas is applied after distributing power proportional to the user weight.
cs/0612011
Estimation of Bit and Frame Error Rates of Low-Density Parity-Check Codes on Binary Symmetric Channels
cs.IT math.IT
A method for estimating the performance of low-density parity-check (LDPC) codes decoded by hard-decision iterative decoding algorithms on binary symmetric channels (BSC) is proposed. Based on the enumeration of the smallest weight error patterns that can not be all corrected by the decoder, this method estimates both the frame error rate (FER) and the bit error rate (BER) of a given LDPC code with very good precision for all crossover probabilities of practical interest. Through a number of examples, we show that the proposed method can be effectively applied to both regular and irregular LDPC codes and to a variety of hard-decision iterative decoding algorithms. Compared with the conventional Monte Carlo simulation, the proposed method has a much smaller computational complexity, particularly for lower error rates.
cs/0612012
Geographic Gossip on Geometric Random Graphs via Affine Combinations
cs.MA cs.IT math.IT
In recent times, a considerable amount of work has been devoted to the development and analysis of gossip algorithms in Geometric Random Graphs. In a recently introduced model termed "Geographic Gossip," each node is aware of its position but possesses no further information. Traditionally, gossip protocols have always used convex linear combinations to achieve averaging. We develop a new protocol for Geographic Gossip, in which counter-intuitively, we use {\it non-convex affine combinations} as updates in addition to convex combinations to accelerate the averaging process. The dependence of the number of transmissions used by our algorithm on the number of sensors $n$ is $n \exp(O(\log \log n)^2) = n^{1 + o(1)}$. For the previous algorithm, this dependence was $\tilde{O}(n^{1.5})$. The exponent 1+ o(1) of our algorithm is asymptotically optimal. Our algorithm involves a hierarchical structure of $\log \log n$ depth and is not completely decentralized. However, the extent of control exercised by a sensor on another is restricted to switching the other on or off.
cs/0612014
Going Stupid with EcoLab
cs.MA
In 2005, Railsback et al. proposed a very simple model ({\em Stupid Model}) that could be implemented within a couple of hours, and later extended to demonstrate the use of common ABM platform functionality. They provided implementations of the model in several agent based modelling platforms, and compared the platforms for ease of implementation of this simple model, and performance. In this paper, I implement Railsback et al's Stupid Model in the EcoLab simulation platform, a C++ based modelling platform, demonstrating that it is a feasible platform for these sorts of models, and compare the performance of the implementation with Repast, Mason and Swarm versions.
cs/0612015
On the intersection of additive perfect codes
cs.IT math.IT
The intersection problem for additive (extended and non-extended) perfect codes, i.e. which are the possibilities for the number of codewords in the intersection of two additive codes C1 and C2 of the same length, is investigated. Lower and upper bounds for the intersection number are computed and, for any value between these bounds, codes which have this given intersection value are constructed. For all these codes the abelian group structure of the intersection is characterized. The parameters of this abelian group structure corresponding to the intersection codes are computed and lower and upper bounds for these parameters are established. Finally, constructions of codes the intersection of which fits any parameters between these bounds are given.
cs/0612019
On Finite Memory Universal Data Compression and Classification of Individual Sequences
cs.IT math.IT
Consider the case where consecutive blocks of N letters of a semi-infinite individual sequence X over a finite-alphabet are being compressed into binary sequences by some one-to-one mapping. No a-priori information about X is available at the encoder, which must therefore adopt a universal data-compression algorithm. It is known that if the universal LZ77 data compression algorithm is successively applied to N-blocks then the best error-free compression for the particular individual sequence X is achieved, as $N$ tends to infinity. The best possible compression that may be achieved by any universal data compression algorithm for finite N-blocks is discussed. It is demonstrated that context tree coding essentially achieves it. Next, consider a device called classifier (or discriminator) that observes an individual training sequence X. The classifier's task is to examine individual test sequences of length N and decide whether the test N-sequence has the same features as those that are captured by the training sequence X, or is sufficiently different, according to some appropriatecriterion. Here again, it is demonstrated that a particular universal context classifier with a storage-space complexity that is linear in N, is essentially optimal. This may contribute a theoretical "individual sequence" justification for the Probabilistic Suffix Tree (PST) approach in learning theory and in computational biology.
cs/0612024
On the Maximum Sum-rate Capacity of Cognitive Multiple Access Channel
cs.IT math.IT
We consider the communication scenario where multiple cognitive users wish to communicate to the same receiver, in the presence of primary transmission. The cognitive transmitters are assumed to have the side information about the primary transmission. The capacity region of cognitive users is formulated under the constraint that the capacity of primary transmission is not changed as if no cognitive users exist. Moreover, the maximum sum-rate point of the capacity region is characterized, by optimally allocating the power of each cognitive user to transmit its own information.
cs/0612027
Experimental Information and Statistical Modeling of Physical Laws
cs.IT cs.IR math.IT
Statistical modeling of physical laws connects experiments with mathematical descriptions of natural phenomena. The modeling is based on the probability density of measured variables expressed by experimental data via a kernel estimator. As an objective kernel the scattering function determined by calibration of the instrument is introduced. This function provides for a new definition of experimental information and redundancy of experimentation in terms of information entropy. The redundancy increases with the number of experiments, while the experimental information converges to a value that describes the complexity of the data. The difference between the redundancy and the experimental information is proposed as the model cost function. From its minimum, a proper number of data in the model is estimated. As an optimal, nonparametric estimator of the relation between measured variables the conditional average extracted from the kernel estimator is proposed. The modeling is demonstrated on noisy chaotic data.
cs/0612029
A Classification of 6R Manipulators
cs.RO
This paper presents a classification of generic 6-revolute jointed (6R) manipulators using homotopy class of their critical point manifold. A part of classification is listed in this paper because of the complexity of homotopy class of 4-torus. The results of this classification will serve future research of the classification and topological properties of maniplators joint space and workspace.
cs/0612030
Loop corrections for approximate inference
cs.AI cs.IT cs.LG math.IT
We propose a method for improving approximate inference methods that corrects for the influence of loops in the graphical model. The method is applicable to arbitrary factor graphs, provided that the size of the Markov blankets is not too large. It is an alternative implementation of an idea introduced recently by Montanari and Rizzo (2005). In its simplest form, which amounts to the assumption that no loops are present, the method reduces to the minimal Cluster Variation Method approximation (which uses maximal factors as outer clusters). On the other hand, using estimates of the effect of loops (obtained by some approximate inference algorithm) and applying the Loop Correcting (LC) method usually gives significantly better results than applying the approximate inference algorithm directly without loop corrections. Indeed, we often observe that the loop corrected error is approximately the square of the error of the approximate inference method used to estimate the effect of loops. We compare different variants of the Loop Correcting method with other approximate inference methods on a variety of graphical models, including "real world" networks, and conclude that the LC approach generally obtains the most accurate results.
cs/0612031
Estimating Aggregate Properties on Probabilistic Streams
cs.DS cs.DB
The probabilistic-stream model was introduced by Jayram et al. \cite{JKV07}. It is a generalization of the data stream model that is suited to handling ``probabilistic'' data where each item of the stream represents a probability distribution over a set of possible events. Therefore, a probabilistic stream determines a distribution over potentially a very large number of classical "deterministic" streams where each item is deterministically one of the domain values. The probabilistic model is applicable for not only analyzing streams where the input has uncertainties (such as sensor data streams that measure physical processes) but also where the streams are derived from the input data by post-processing, such as tagging or reconciling inconsistent and poor quality data. We present streaming algorithms for computing commonly used aggregates on a probabilistic stream. We present the first known, one pass streaming algorithm for estimating the \AVG, improving results in \cite{JKV07}. We present the first known streaming algorithms for estimating the number of \DISTINCT items on probabilistic streams. Further, we present extensions to other aggregates such as the repeat rate, quantiles, etc. In all cases, our algorithms work with provable accuracy guarantees and within the space constraints of the data stream model.
cs/0612032
Code Spectrum and Reliability Function: Binary Symmetric Channel
cs.IT math.IT
A new approach for upper bounding the channel reliability function using the code spectrum is described. It allows to treat in a unified way both a low and a high rate cases. In particular, the earlier known upper bounds are improved, and a new derivation of the sphere-packing bound is presented.
cs/0612033
Acronym-Meaning Extraction from Corpora Using Multi-Tape Weighted Finite-State Machines
cs.CL cs.DS cs.SC
The automatic extraction of acronyms and their meaning from corpora is an important sub-task of text mining. It can be seen as a special case of string alignment, where a text chunk is aligned with an acronym. Alternative alignments have different cost, and ideally the least costly one should give the correct meaning of the acronym. We show how this approach can be implemented by means of a 3-tape weighted finite-state machine (3-WFSM) which reads a text chunk on tape 1 and an acronym on tape 2, and generates all alternative alignments on tape 3. The 3-WFSM can be automatically generated from a simple regular expression. No additional algorithms are required at any stage. Our 3-WFSM has a size of 27 states and 64 transitions, and finds the best analysis of an acronym in a few milliseconds.
cs/0612041
Viterbi Algorithm Generalized for n-Tape Best-Path Search
cs.CL cs.DS cs.SC
We present a generalization of the Viterbi algorithm for identifying the path with minimal (resp. maximal) weight in a n-tape weighted finite-state machine (n-WFSM), that accepts a given n-tuple of input strings (s_1,... s_n). It also allows us to compile the best transduction of a given input n-tuple by a weighted (n+m)-WFSM (transducer) with n input and m output tapes. Our algorithm has a worst-case time complexity of O(|s|^n |E| log (|s|^n |Q|)), where n and |s| are the number and average length of the strings in the n-tuple, and |Q| and |E| the number of states and transitions in the n-WFSM, respectively. A straight forward alternative, consisting in intersection followed by classical shortest-distance search, operates in O(|s|^n (|E|+|Q|) log (|s|^n |Q|)) time.
cs/0612042
Decentralized Maximum Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems
cs.DC cs.IT math.IT
In this paper we propose a decentralized sensor network scheme capable to reach a globally optimum maximum likelihood (ML) estimate through self-synchronization of nonlinearly coupled dynamical systems. Each node of the network is composed of a sensor and a first-order dynamical system initialized with the local measurements. Nearby nodes interact with each other exchanging their state value and the final estimate is associated to the state derivative of each dynamical system. We derive the conditions on the coupling mechanism guaranteeing that, if the network observes one common phenomenon, each node converges to the globally optimal ML estimate. We prove that the synchronized state is globally asymptotically stable if the coupling strength exceeds a given threshold. Acting on a single parameter, the coupling strength, we show how, in the case of nonlinear coupling, the network behavior can switch from a global consensus system to a spatial clustering system. Finally, we show the effect of the network topology on the scalability properties of the network and we validate our theoretical findings with simulation results.
cs/0612043
About the Lifespan of Peer to Peer Networks
cs.DC cs.IR
We analyze the ability of peer to peer networks to deliver a complete file among the peers. Early on we motivate a broad generalization of network behavior organizing it into one of two successive phases. According to this view the network has two main states: first centralized - few sources (roots) hold the complete file, and next distributed - peers hold some parts (chunks) of the file such that the entire network has the whole file, but no individual has it. In the distributed state we study two scenarios, first, when the peers are ``patient'', i.e, do not leave the system until they obtain the complete file; second, peers are ``impatient'' and almost always leave the network before obtaining the complete file.
cs/0612044
The Relay-Eavesdropper Channel: Cooperation for Secrecy
cs.IT math.IT
This paper establishes the utility of user cooperation in facilitating secure wireless communications. In particular, the four-terminal relay-eavesdropper channel is introduced and an outer-bound on the optimal rate-equivocation region is derived. Several cooperation strategies are then devised and the corresponding achievable rate-equivocation region are characterized. Of particular interest is the novel Noise-Forwarding (NF) strategy, where the relay node sends codewords independent of the source message to confuse the eavesdropper. This strategy is used to illustrate the deaf helper phenomenon, where the relay is able to facilitate secure communications while being totally ignorant of the transmitted messages. Furthermore, NF is shown to increase the secrecy capacity in the reversely degraded scenario, where the relay node fails to offer performance gains in the classical setting. The gain offered by the proposed cooperation strategies is then proved theoretically and validated numerically in the additive White Gaussian Noise (AWGN) channel.
cs/0612046
Social Networks and Social Information Filtering on Digg
cs.HC cs.AI cs.IR
The new social media sites -- blogs, wikis, Flickr and Digg, among others -- underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide which stories to promote to the front page. Digg users can designate other users as ``friends'' and easily track friends' activities: what new stories they submitted, commented on or read. The friends interface acts as a \emph{social filtering} system, recommending to user stories his or her friends liked or found interesting. By tracking the votes received by newly submitted stories over time, we showed that social filtering is an effective information filtering approach. Specifically, we showed that (a) users tend to like stories submitted by friends and (b) users tend to like stories their friends read and liked. As a byproduct of social filtering, social networks also play a role in promoting stories to Digg's front page, potentially leading to ``tyranny of the minority'' situation where a disproportionate number of front page stories comes from the same small group of interconnected users. Despite this, social filtering is a promising new technology that can be used to personalize and tailor information to individual users: for example, through personal front pages.
cs/0612047
Social Browsing on Flickr
cs.HC cs.AI
The new social media sites - blogs, wikis, del.icio.us and Flickr, among others - underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. The photo-sharing site Flickr, for example, allows users to upload photographs, view photos created by others, comment on those photos, etc. As is common to other social media sites, Flickr allows users to designate others as ``contacts'' and to track their activities in real time. The contacts (or friends) lists form the social network backbone of social media sites. We claim that these social networks facilitate new ways of interacting with information, e.g., through what we call social browsing. The contacts interface on Flickr enables users to see latest images submitted by their friends. Through an extensive analysis of Flickr data, we show that social browsing through the contacts' photo streams is one of the primary methods by which users find new images on Flickr. This finding has implications for creating personalized recommendation systems based on the user's declared contacts lists.
cs/0612049
Power Control in Distributed Cooperative OFDMA Cellular Networks
cs.IT math.IT
This paper has been withdrawn by the author.
cs/0612051
On the Decoder Error Probability of Bounded Rank-Distance Decoders for Maximum Rank Distance Codes
cs.IT math.IT
In this paper, we first introduce the concept of elementary linear subspace, which has similar properties to those of a set of coordinates. We then use elementary linear subspaces to derive properties of maximum rank distance (MRD) codes that parallel those of maximum distance separable codes. Using these properties, we show that, for MRD codes with error correction capability t, the decoder error probability of bounded rank distance decoders decreases exponentially with t^2 based on the assumption that all errors with the same rank are equally likely.
cs/0612052
Budget Optimization in Search-Based Advertising Auctions
cs.DS cs.CE cs.GT
Internet search companies sell advertisement slots based on users' search queries via an auction. While there has been a lot of attention on the auction process and its game-theoretic aspects, our focus is on the advertisers. In particular, the advertisers have to solve a complex optimization problem of how to place bids on the keywords of their interest so that they can maximize their return (the number of user clicks on their ads) for a given budget. We model the entire process and study this budget optimization problem. While most variants are NP hard, we show, perhaps surprisingly, that simply randomizing between two uniform strategies that bid equally on all the keywords works well. More precisely, this strategy gets at least 1-1/e fraction of the maximum clicks possible. Such uniform strategies are likely to be practical. We also present inapproximability results, and optimal algorithms for variants of the budget optimization problem.
cs/0612053
Deriving Schrodinger Equation From A Soft-Decision Iterative Decoding Algorithm
cs.IT math.IT
The belief propagation algorithm has been recognized in the information theory community as a soft-decision iterative decoding algorithm. It is the most powerful algorithm found so far for attacking hard optimization problems in channel decoding. Quantum mechanics is the foundation of modern physics with the time-independent Schrodinger equation being one of the most important equations. This paper shows that the equation can be derived from a generalized belief propagation algorithm. Such a connection on a mathematical basis might shed new insights into the foundations of quantum mechanics and quantum computing.
cs/0612055
Linear Probing with Constant Independence
cs.DS cs.DB
Hashing with linear probing dates back to the 1950s, and is among the most studied algorithms. In recent years it has become one of the most important hash table organizations since it uses the cache of modern computers very well. Unfortunately, previous analysis rely either on complicated and space consuming hash functions, or on the unrealistic assumption of free access to a truly random hash function. Already Carter and Wegman, in their seminal paper on universal hashing, raised the question of extending their analysis to linear probing. However, we show in this paper that linear probing using a pairwise independent family may have expected {\em logarithmic} cost per operation. On the positive side, we show that 5-wise independence is enough to ensure constant expected time per operation. This resolves the question of finding a space and time efficient hash function that provably ensures good performance for linear probing.
cs/0612056
Conscious Intelligent Systems - Part 1 : I X I
cs.AI
Did natural consciousness and intelligent systems arise out of a path that was co-evolutionary to evolution? Can we explain human self-consciousness as having risen out of such an evolutionary path? If so how could it have been? In this first part of a two-part paper (titled IXI), we take a learning system perspective to the problem of consciousness and intelligent systems, an approach that may look unseasonable in this age of fMRI's and high tech neuroscience. We posit conscious intelligent systems in natural environments and wonder how natural factors influence their design paths. Such a perspective allows us to explain seamlessly a variety of natural factors, factors ranging from the rise and presence of the human mind, man's sense of I, his self-consciousness and his looping thought processes to factors like reproduction, incubation, extinction, sleep, the richness of natural behavior, etc. It even allows us to speculate on a possible human evolution scenario and other natural phenomena.
cs/0612057
Conscious Intelligent Systems - Part II - Mind, Thought, Language and Understanding
cs.AI
This is the second part of a paper on Conscious Intelligent Systems. We use the understanding gained in the first part (Conscious Intelligent Systems Part 1: IXI (arxiv id cs.AI/0612056)) to look at understanding. We see how the presence of mind affects understanding and intelligent systems; we see that the presence of mind necessitates language. The rise of language in turn has important effects on understanding. We discuss the humanoid question and how the question of self-consciousness (and by association mind/thought/language) would affect humanoids too.
cs/0612059
Synchronization recovery and state model reduction for soft decoding of variable length codes
cs.NI cs.IT math.IT
Variable length codes exhibit de-synchronization problems when transmitted over noisy channels. Trellis decoding techniques based on Maximum A Posteriori (MAP) estimators are often used to minimize the error rate on the estimated sequence. If the number of symbols and/or bits transmitted are known by the decoder, termination constraints can be incorporated in the decoding process. All the paths in the trellis which do not lead to a valid sequence length are suppressed. This paper presents an analytic method to assess the expected error resilience of a VLC when trellis decoding with a sequence length constraint is used. The approach is based on the computation, for a given code, of the amount of information brought by the constraint. It is then shown that this quantity as well as the probability that the VLC decoder does not re-synchronize in a strict sense, are not significantly altered by appropriate trellis states aggregation. This proves that the performance obtained by running a length-constrained Viterbi decoder on aggregated state models approaches the one obtained with the bit/symbol trellis, with a significantly reduced complexity. It is then shown that the complexity can be further decreased by projecting the state model on two state models of reduced size.
cs/0612062
Unifying Lexicons in view of a Phonological and Morphological Lexical DB
cs.IR
The present work falls in the line of activities promoted by the European Languguage Resource Association (ELRA) Production Committee (PCom) and raises issues in methods, procedures and tools for the reusability, creation, and management of Language Resources. A two-fold purpose lies behind this experiment. The first aim is to investigate the feasibility, define methods and procedures for combining two Italian lexical resources that have incompatible formats and complementary information into a Unified Lexicon (UL). The adopted strategy and the procedures appointed are described together with the driving criterion of the merging task, where a balance between human and computational efforts is pursued. The coverage of the UL has been maximized, by making use of simple and fast matching procedures. The second aim is to exploit this newly obtained resource for implementing the phonological and morphological layers of the CLIPS lexical database. Implementing these new layers and linking them with the already exisitng syntactic and semantic layers is not a trivial task. The constraints imposed by the model, the impact at the architectural level and the solution adopted in order to make the whole database `speak' efficiently are presented. Advantages vs. disadvantages are discussed.
cs/0612064
Bounds on Key Appearance Equivocation for Substitution Ciphers
cs.IT cs.CR math.IT
The average conditional entropy of the key given the message and its corresponding cryptogram, H(K|M,C), which is reffer as a key appearance equivocation, was proposed as a theoretical measure of the strength of the cipher system under a known-plaintext attack by Dunham in 1980. In the same work (among other things), lower and upper bounds for H(S}_{M}|M^L,C^L) are found and its asymptotic behaviour as a function of cryptogram length L is described for simple substitution ciphers i.e. when the key space S_{M} is the symmetric group acting on a discrete alphabet M. In the present paper we consider the same problem when the key space is an arbitrary subgroup K of S_{M} and generalize Dunham's result.
cs/0612067
Retrieving Reed-Solomon coded data under interpolation-based list decoding
cs.IT math.IT
A transform that enables generator-matrix-based Reed-Solomon (RS) coded data to be recovered under interpolation-based list decoding is presented. The transform matrix needs to be computed only once and the transformation of an element from the output list to the desired RS coded data block incurs $k^{2}$ field multiplications, given a code of dimension $k$.
cs/0612068
Interactive Configuration by Regular String Constraints
cs.AI
A product configurator which is complete, backtrack free and able to compute the valid domains at any state of the configuration can be constructed by building a Binary Decision Diagram (BDD). Despite the fact that the size of the BDD is exponential in the number of variables in the worst case, BDDs have proved to work very well in practice. Current BDD-based techniques can only handle interactive configuration with small finite domains. In this paper we extend the approach to handle string variables constrained by regular expressions. The user is allowed to change the strings by adding letters at the end of the string. We show how to make a data structure that can perform fast valid domain computations given some assignment on the set of string variables. We first show how to do this by using one large DFA. Since this approach is too space consuming to be of practical use, we construct a data structure that simulates the large DFA and in most practical cases are much more space efficient. As an example a configuration problem on $n$ string variables with only one solution in which each string variable is assigned to a value of length of $k$ the former structure will use $\Omega(k^n)$ space whereas the latter only need $O(kn)$. We also show how this framework easily can be combined with the recent BDD techniques to allow both boolean, integer and string variables in the configuration problem.
cs/0612073
On the Fingerprinting Capacity Under the Marking Assumption
cs.IT cs.CR math.IT
We address the maximum attainable rate of fingerprinting codes under the marking assumption, studying lower and upper bounds on the value of the rate for various sizes of the attacker coalition. Lower bounds are obtained by considering typical coalitions, which represents a new idea in the area of fingerprinting and enables us to improve the previously known lower bounds for coalitions of size two and three. For upper bounds, the fingerprinting problem is modelled as a communications problem. It is shown that the maximum code rate is bounded above by the capacity of a certain class of channels, which are similar to the multiple-access channel. Converse coding theorems proved in the paper provide new upper bounds on fingerprinting capacity. It is proved that capacity for fingerprinting against coalitions of size two and three over the binary alphabet satisfies $0.25 \leq C_{2,2} \leq 0.322$ and $0.083 \leq C_{3,2} \leq 0.199$ respectively. For coalitions of an arbitrary fixed size $t,$ we derive an upper bound $(t\ln2)^{-1}$ on fingerprinting capacity in the binary case. Finally, for general alphabets, we establish upper bounds on the fingerprinting capacity involving only single-letter mutual information quantities.
cs/0612075
Intermediate Performance of Rateless Codes
cs.IT math.IT
Rateless/fountain codes are designed so that all input symbols can be recovered from a slightly larger number of coded symbols, with high probability using an iterative decoder. In this paper we investigate the number of input symbols that can be recovered by the same decoder, but when the number of coded symbols available is less than the total number of input symbols. Of course recovery of all inputs is not possible, and the fraction that can be recovered will depend on the output degree distribution of the code. In this paper we (a) outer bound the fraction of inputs that can be recovered for any output degree distribution of the code, and (b) design degree distributions which meet/perform close to this bound. Our results are of interest for real-time systems using rateless codes, and for Raptor-type two-stage designs.
cs/0612076
A New Approach for Capacity Analysis of Large Dimensional Multi-Antenna Channels
cs.IT math.IT math.PR
This paper adresses the behaviour of the mutual information of correlated MIMO Rayleigh channels when the numbers of transmit and receive antennas converge to infinity at the same rate. Using a new and simple approach based on Poincar\'{e}-Nash inequality and on an integration by parts formula, it is rigorously established that the mutual information converges to a Gaussian random variable whose mean and variance are evaluated. These results confirm previous evaluations based on the powerful but non rigorous replica method. It is believed that the tools that are used in this paper are simple, robust, and of interest for the communications engineering community.
cs/0612077
Algebraic Signal Processing Theory
cs.IT math.IT
This paper presents an algebraic theory of linear signal processing. At the core of algebraic signal processing is the concept of a linear signal model defined as a triple (A, M, phi), where familiar concepts like the filter space and the signal space are cast as an algebra A and a module M, respectively, and phi generalizes the concept of the z-transform to bijective linear mappings from a vector space of, e.g., signal samples, into the module M. A signal model provides the structure for a particular linear signal processing application, such as infinite and finite discrete time, or infinite or finite discrete space, or the various forms of multidimensional linear signal processing. As soon as a signal model is chosen, basic ingredients follow, including the associated notions of filtering, spectrum, and Fourier transform. The shift operator is a key concept in the algebraic theory: it is the generator of the algebra of filters A. Once the shift is chosen, a well-defined methodology leads to the associated signal model. Different shifts correspond to infinite and finite time models with associated infinite and finite z-transforms, and to infinite and finite space models with associated infinite and finite C-transforms (that we introduce). In particular, we show that the 16 discrete cosine and sine transforms are Fourier transforms for the finite space models. Other definitions of the shift naturally lead to new signal models and to new transforms as associated Fourier transforms in one and higher dimensions, separable and non-separable. We explain in algebraic terms shift-invariance (the algebra of filters A is commutative), the role of boundary conditions and signal extensions, the connections between linear transforms and linear finite Gauss-Markov fields, and several other concepts and connections.
cs/0612078
Effect of Finite Rate Feedback on CDMA Signature Optimization and MIMO Beamforming Vector Selection
cs.IT math.IT
We analyze the effect of finite rate feedback on CDMA (code-division multiple access) signature optimization and MIMO (multi-input-multi-output) beamforming vector selection. In CDMA signature optimization, for a particular user, the receiver selects a signature vector from a codebook to best avoid interference from other users, and then feeds the corresponding index back to the specified user. For MIMO beamforming vector selection, the receiver chooses a beamforming vector from a given codebook to maximize throughput, and feeds back the corresponding index to the transmitter. These two problems are dual: both can be modeled as selecting a unit norm vector from a finite size codebook to "match" a randomly generated Gaussian matrix. In signature optimization, the least match is required while the maximum match is preferred for beamforming selection. Assuming that the feedback link is rate limited, our main result is an exact asymptotic performance formulae where the length of the signature/beamforming vector, the dimensions of interference/channel matrix, and the feedback rate approach infinity with constant ratios. The proof rests on a large deviation principle over a random matrix ensemble. Further, we show that random codebooks generated from the isotropic distritution are asymptotically optimal not only on average, but also with probability one.
cs/0612080
On the Decrease Rate of the Non-Gaussianness of the Sum of Independent Random Variables
cs.IT math.IT
Several proofs of the monotonicity of the non-Gaussianness (divergence with respect to a Gaussian random variable with identical second order statistics) of the sum of n independent and identically distributed (i.i.d.) random variables were published. We give an upper bound on the decrease rate of the non-Gaussianness which is proportional to the inverse of n, for large n. The proof is based on the relationship between non-Gaussianness and minimum mean-square error (MMSE) and causal minimum mean-square error (CMMSE) in the time-continuous Gaussian channel.
cs/0612083
A Byzantine Fault Tolerant Distributed Commit Protocol
cs.DC cs.DB
In this paper, we present a Byzantine fault tolerant distributed commit protocol for transactions running over untrusted networks. The traditional two-phase commit protocol is enhanced by replicating the coordinator and by running a Byzantine agreement algorithm among the coordinator replicas. Our protocol can tolerate Byzantine faults at the coordinator replicas and a subset of malicious faults at the participants. A decision certificate, which includes a set of registration records and a set of votes from participants, is used to facilitate the coordinator replicas to reach a Byzantine agreement on the outcome of each transaction. The certificate also limits the ways a faulty replica can use towards non-atomic termination of transactions, or semantically incorrect transaction outcomes.
cs/0612084
Achievable Rates for the General Gaussian Multiple Access Wire-Tap Channel with Collective Secrecy
cs.IT cs.CR math.IT
We consider the General Gaussian Multiple Access Wire-Tap Channel (GGMAC-WT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed eavesdropper who is as capable as the intended receiver, but has different channel parameters. We aim to provide perfect secrecy for the transmitters in this multi-access environment. Using Gaussian codebooks, an achievable secrecy region is determined and the power allocation that maximizes the achievable sum-rate is found. Numerical results showing the new rate region are presented. It is shown that the multiple-access nature of the channel may be utilized to allow users with zero single-user secrecy capacity to be able to transmit in perfect secrecy. In addition, a new collaborative scheme is shown that may increase the achievable sum-rate. In this scheme, a user who would not transmit to maximize the sum rate can help another user who (i) has positive secrecy capacity to increase its rate, or (ii) has zero secrecy capacity to achieve a positive secrecy capacity.
cs/0612086
An asynchronous, decentralised commitment protocol for semantic optimistic replication
cs.DB cs.NI
We study large-scale distributed cooperative systems that use optimistic replication. We represent a system as a graph of actions (operations) connected by edges that reify semantic constraints between actions. Constraint types include conflict, execution order, dependence, and atomicity. The local state is some schedule that conforms to the constraints; because of conflicts, client state is only tentative. For consistency, site schedules should converge; we designed a decentralised, asynchronous commitment protocol. Each client makes a proposal, reflecting its tentative and{\slash}or preferred schedules. Our protocol distributes the proposals, which it decomposes into semantically-meaningful units called candidates, and runs an election between comparable candidates. A candidate wins when it receives a majority or a plurality. The protocol is fully asynchronous: each site executes its tentative schedule independently, and determines locally when a candidate has won an election. The committed schedule is as close as possible to the preferences expressed by clients.
cs/0612087
Statistical mechanics of neocortical interactions: Portfolio of Physiological Indicators
cs.CE cs.IT cs.NE math.IT q-bio.QM
There are several kinds of non-invasive imaging methods that are used to collect data from the brain, e.g., EEG, MEG, PET, SPECT, fMRI, etc. It is difficult to get resolution of information processing using any one of these methods. Approaches to integrate data sources may help to get better resolution of data and better correlations to behavioral phenomena ranging from attention to diagnoses of disease. The approach taken here is to use algorithms developed for the author's Trading in Risk Dimensions (TRD) code using modern methods of copula portfolio risk management, with joint probability distributions derived from the author's model of statistical mechanics of neocortical interactions (SMNI). The author's Adaptive Simulated Annealing (ASA) code is for optimizations of training sets, as well as for importance-sampling. Marginal distributions will be evolved to determine their expected duration and stability using algorithms developed by the author, i.e., PATHTREE and PATHINT codes.
cs/0612095
Approximation of the Two-Part MDL Code
cs.LG cs.AI cs.IT math.IT
Approximation of the optimal two-part MDL code for given data, through successive monotonically length-decreasing two-part MDL codes, has the following properties: (i) computation of each step may take arbitrarily long; (ii) we may not know when we reach the optimum, or whether we will reach the optimum at all; (iii) the sequence of models generated may not monotonically improve the goodness of fit; but (iv) the model associated with the optimum has (almost) the best goodness of fit. To express the practically interesting goodness of fit of individual models for individual data sets we have to rely on Kolmogorov complexity.
cs/0612096
Using state space differential geometry for nonlinear blind source separation
cs.LG cs.SD
Given a time series of multicomponent measurements of an evolving stimulus, nonlinear blind source separation (BSS) seeks to find a "source" time series, comprised of statistically independent combinations of the measured components. In this paper, we seek a source time series with local velocity cross correlations that vanish everywhere in stimulus state space. However, in an earlier paper the local velocity correlation matrix was shown to constitute a metric on state space. Therefore, nonlinear BSS maps onto a problem of differential geometry: given the metric observed in the measurement coordinate system, find another coordinate system in which the metric is diagonal everywhere. We show how to determine if the observed data are separable in this way, and, if they are, we show how to construct the required transformation to the source coordinate system, which is essentially unique except for an unknown rotation that can be found by applying the methods of linear BSS. Thus, the proposed technique solves nonlinear BSS in many situations or, at least, reduces it to linear BSS, without the use of probabilistic, parametric, or iterative procedures. This paper also describes a generalization of this methodology that performs nonlinear independent subspace separation. In every case, the resulting decomposition of the observed data is an intrinsic property of the stimulus' evolution in the sense that it does not depend on the way the observer chooses to view it (e.g., the choice of the observing machine's sensors). In other words, the decomposition is a property of the evolution of the "real" stimulus that is "out there" broadcasting energy to the observer. The technique is illustrated with analytic and numerical examples.
cs/0612097
Error Exponents for Variable-length Block Codes with Feedback and Cost Constraints
cs.IT math.IT
Variable-length block-coding schemes are investigated for discrete memoryless channels with ideal feedback under cost constraints. Upper and lower bounds are found for the minimum achievable probability of decoding error $P_{e,\min}$ as a function of constraints $R, \AV$, and $\bar \tau$ on the transmission rate, average cost, and average block length respectively. For given $R$ and $\AV$, the lower and upper bounds to the exponent $-(\ln P_{e,\min})/\bar \tau$ are asymptotically equal as $\bar \tau \to \infty$. The resulting reliability function, $\lim_{\bar \tau\to \infty} (-\ln P_{e,\min})/\bar \tau$, as a function of $R$ and $\AV$, is concave in the pair $(R, \AV)$ and generalizes the linear reliability function of Burnashev to include cost constraints. The results are generalized to a class of discrete-time memoryless channels with arbitrary alphabets, including additive Gaussian noise channels with amplitude and power constraints.
cs/0612099
Network Information Flow in Small World Networks
cs.IT cs.DM math.IT
Recent results from statistical physics show that large classes of complex networks, both man-made and of natural origin, are characterized by high clustering properties yet strikingly short path lengths between pairs of nodes. This class of networks are said to have a small-world topology. In the context of communication networks, navigable small-world topologies, i.e. those which admit efficient distributed routing algorithms, are deemed particularly effective, for example in resource discovery tasks and peer-to-peer applications. Breaking with the traditional approach to small-world topologies that privileges graph parameters pertaining to connectivity, and intrigued by the fundamental limits of communication in networks that exploit this type of topology, we investigate the capacity of these networks from the perspective of network information flow. Our contribution includes upper and lower bounds for the capacity of standard and navigable small-world models, and the somewhat surprising result that, with high probability, random rewiring does not alter the capacity of a small-world network.
cs/0612101
Maximum Entropy MIMO Wireless Channel Models
cs.IT math.IT
In this contribution, models of wireless channels are derived from the maximum entropy principle, for several cases where only limited information about the propagation environment is available. First, analytical models are derived for the cases where certain parameters (channel energy, average energy, spatial correlation matrix) are known deterministically. Frequently, these parameters are unknown (typically because the received energy or the spatial correlation varies with the user position), but still known to represent meaningful system characteristics. In these cases, analytical channel models are derived by assigning entropy-maximizing distributions to these parameters, and marginalizing them out. For the MIMO case with spatial correlation, we show that the distribution of the covariance matrices is conveniently handled through its eigenvalues. The entropy-maximizing distribution of the covariance matrix is shown to be a Wishart distribution. Furthermore, the corresponding probability density function of the channel matrix is shown to be described analytically by a function of the channel Frobenius norm. This technique can provide channel models incorporating the effect of shadow fading and spatial correlation between antennas without the need to assume explicit values for these parameters. The results are compared in terms of mutual information to the classical i.i.d. Gaussian model.
cs/0612102
The Dichotomy of Conjunctive Queries on Probabilistic Structures
cs.DB
We show that for every conjunctive query, the complexity of evaluating it on a probabilistic database is either \PTIME or #\P-complete, and we give an algorithm for deciding whether a given conjunctive query is \PTIME or #\P-complete. The dichotomy property is a fundamental result on query evaluation on probabilistic databases and it gives a complete classification of the complexity of conjunctive queries.
cs/0612103
The Boundary Between Privacy and Utility in Data Anonymization
cs.DB
We consider the privacy problem in data publishing: given a relation I containing sensitive information 'anonymize' it to obtain a view V such that, on one hand attackers cannot learn any sensitive information from V, and on the other hand legitimate users can use V to compute useful statistics on I. These are conflicting goals. We use a definition of privacy that is derived from existing ones in the literature, which relates the a priori probability of a given tuple t, Pr(t), with the a posteriori probability, Pr(t | V), and propose a novel and quite practical definition for utility. Our main result is the following. Denoting n the size of I and m the size of the domain from which I was drawn (i.e. n < m) then: when the a priori probability is Pr(t) = Omega(n/sqrt(m)) for some t, there exists no useful anonymization algorithm, while when Pr(t) = O(n/m) for all tuples t, then we give a concrete anonymization algorithm that is both private and useful. Our algorithm is quite different from the k-anonymization algorithm studied intensively in the literature, and is based on random deletions and insertions to I.
cs/0612104
Sufficient Conditions for Coarse-Graining Evolutionary Dynamics
cs.NE cs.AI
It is commonly assumed that the ability to track the frequencies of a set of schemata in the evolving population of an infinite population genetic algorithm (IPGA) under different fitness functions will advance efforts to obtain a theory of adaptation for the simple GA. Unfortunately, for IPGAs with long genomes and non-trivial fitness functions there do not currently exist theoretical results that allow such a study. We develop a simple framework for analyzing the dynamics of an infinite population evolutionary algorithm (IPEA). This framework derives its simplicity from its abstract nature. In particular we make no commitment to the data-structure of the genomes, the kind of variation performed, or the number of parents involved in a variation operation. We use this framework to derive abstract conditions under which the dynamics of an IPEA can be coarse-grained. We then use this result to derive concrete conditions under which it becomes computationally feasible to closely approximate the frequencies of a family of schemata of relatively low order over multiple generations, even when the bitstsrings in the evolving population of the IPGA are long.
cs/0612109
Truncating the loop series expansion for Belief Propagation
cs.AI
Recently, M. Chertkov and V.Y. Chernyak derived an exact expression for the partition sum (normalization constant) corresponding to a graphical model, which is an expansion around the Belief Propagation solution. By adding correction terms to the BP free energy, one for each "generalized loop" in the factor graph, the exact partition sum is obtained. However, the usually enormous number of generalized loops generally prohibits summation over all correction terms. In this article we introduce Truncated Loop Series BP (TLSBP), a particular way of truncating the loop series of M. Chertkov and V.Y. Chernyak by considering generalized loops as compositions of simple loops. We analyze the performance of TLSBP in different scenarios, including the Ising model, regular random graphs and on Promedas, a large probabilistic medical diagnostic system. We show that TLSBP often improves upon the accuracy of the BP solution, at the expense of increased computation time. We also show that the performance of TLSBP strongly depends on the degree of interaction between the variables. For weak interactions, truncating the series leads to significant improvements, whereas for strong interactions it can be ineffective, even if a high number of terms is considered.
cs/0612110
Architecture for Modular Data Centers
cs.DB
Several factors are driving high-scale deployments of large data centers built upon commodity components. These commodity clusters are far cheaper than mainframe systems of the past but they bring serious heat and power density issues. Also the high failure rate of the individual components drives significant administrative costs. This proposal outlines an architecture for data center design based upon 20'x8'x8' modules that substantially changes how these systems are acquired, administered, and then later recycled.
cs/0612111
Fragmentation in Large Object Repositories
cs.DB
Fragmentation leads to unpredictable and degraded application performance. While these problems have been studied in detail for desktop filesystem workloads, this study examines newer systems such as scalable object stores and multimedia repositories. Such systems use a get/put interface to store objects. In principle, databases and filesystems can support such applications efficiently, allowing system designers to focus on complexity, deployment cost and manageability. Although theoretical work proves that certain storage policies behave optimally for some workloads, these policies often behave poorly in practice. Most storage benchmarks focus on short-term behavior or do not measure fragmentation. We compare SQL Server to NTFS and find that fragmentation dominates performance when object sizes exceed 256KB-1MB. NTFS handles fragmentation better than SQL Server. Although the performance curves will vary with other systems and workloads, we expect the same interactions between fragmentation and free space to apply. It is well-known that fragmentation is related to the percentage free space. We found that the ratio of free space to object size also impacts performance. Surprisingly, in both systems, storing objects of a single size causes fragmentation, and changing the size of write requests affects fragmentation. These problems could be addressed with simple changes to the filesystem and database interfaces. It is our hope that an improved understanding of fragmentation will lead to predictable storage systems that require less maintenance after deployment.
cs/0612112
Managing Query Compilation Memory Consumption to Improve DBMS Throughput
cs.DB
While there are known performance trade-offs between database page buffer pool and query execution memory allocation policies, little has been written on the impact of query compilation memory use on overall throughput of the database management system (DBMS). We present a new aspect of the query optimization problem and offer a solution implemented in Microsoft SQL Server 2005. The solution provides stable throughput for a range of workloads even when memory requests outstrip the ability of the hardware to service those requests.
cs/0612113
Isolation Support for Service-based Applications: A Position Paper
cs.DB
In this paper, we propose an approach to providing the benefits of isolation in service-oriented applications where it is not feasible to hold traditional locks for ACID transactions. Our technique, called "Promises", provides an uniform view for clients which covers a wide range of implementation techniques on the service side, all allowing the client to check a condition and then later rely on that condition still holding.
cs/0612114
Demaq: A Foundation for Declarative XML Message Processing
cs.DB
This paper gives an overview of Demaq, an XML message processing system operating on the foundation of transactional XML message queues. We focus on the syntax and semantics of its fully declarative, rule-based application language and demonstrate our message-based programming paradigm in the context of a case study. Further, we discuss optimization opportunities for executing Demaq programs.
cs/0612115
Consistent Streaming Through Time: A Vision for Event Stream Processing
cs.DB
Event processing will play an increasingly important role in constructing enterprise applications that can immediately react to business critical events. Various technologies have been proposed in recent years, such as event processing, data streams and asynchronous messaging (e.g. pub/sub). We believe these technologies share a common processing model and differ only in target workload, including query language features and consistency requirements. We argue that integrating these technologies is the next step in a natural progression. In this paper, we present an overview and discuss the foundations of CEDR, an event streaming system that embraces a temporal stream model to unify and further enrich query language features, handle imperfections in event delivery and define correctness guarantees. We describe specific contributions made so far and outline next steps in developing the CEDR system.
cs/0612117
Statistical Mechanics of On-line Learning when a Moving Teacher Goes around an Unlearnable True Teacher
cs.LG cond-mat.dis-nn
In the framework of on-line learning, a learning machine might move around a teacher due to the differences in structures or output functions between the teacher and the learning machine. In this paper we analyze the generalization performance of a new student supervised by a moving machine. A model composed of a fixed true teacher, a moving teacher, and a student is treated theoretically using statistical mechanics, where the true teacher is a nonmonotonic perceptron and the others are simple perceptrons. Calculating the generalization errors numerically, we show that the generalization errors of a student can temporarily become smaller than that of a moving teacher, even if the student only uses examples from the moving teacher. However, the generalization error of the student eventually becomes the same value with that of the moving teacher. This behavior is qualitatively different from that of a linear model.
cs/0612118
Gossiping with Multiple Messages
cs.NI cs.IT math.IT
This paper investigates the dissemination of multiple pieces of information in large networks where users contact each other in a random uncoordinated manner, and users upload one piece per unit time. The underlying motivation is the design and analysis of piece selection protocols for peer-to-peer networks which disseminate files by dividing them into pieces. We first investigate one-sided protocols, where piece selection is based on the states of either the transmitter or the receiver. We show that any such protocol relying only on pushes, or alternatively only on pulls, is inefficient in disseminating all pieces to all users. We propose a hybrid one-sided piece selection protocol -- INTERLEAVE -- and show that by using both pushes and pulls it disseminates $k$ pieces from a single source to $n$ users in $10(k+\log n)$ time, while obeying the constraint that each user can upload at most one piece in one unit of time, with high probability for large $n$. An optimal, unrealistic centralized protocol would take $k+\log_2 n$ time in this setting. Moreover, efficient dissemination is also possible if the source implements forward erasure coding, and users push the latest-released coded pieces (but do not pull). We also investigate two-sided protocols where piece selection is based on the states of both the transmitter and the receiver. We show that it is possible to disseminate $n$ pieces to $n$ users in $n+O(\log n)$ time, starting from an initial state where each user has a unique piece.
cs/0612122
Large N Analysis of Amplify-and-Forward MIMO Relay Channels with Correlated Rayleigh Fading
cs.IT math.IT
In this correspondence the cumulants of the mutual information of the flat Rayleigh fading amplify-and-forward MIMO relay channel without direct link between source and destination are derived in the large array limit. The analysis is based on the replica trick and covers both spatially independent and correlated fading in the first and the second hop, while beamforming at all terminals is restricted to deterministic weight matrices. Expressions for mean and variance of the mutual information are obtained. Their parameters are determined by a nonlinear equation system. All higher cumulants are shown to vanish as the number of antennas n goes to infinity. In conclusion the distribution of the mutual information I becomes Gaussian in the large n limit and is completely characterized by the expressions obtained for mean and variance of I. Comparisons with simulation results show that the asymptotic results serve as excellent approximations for systems with only few antennas at each node. The derivation of the results follows the technique formalized by Moustakas et al. in [1]. Although the evaluations are more involved for the MIMO relay channel compared to point-to-point MIMO channels, the structure of the results is surprisingly simple again. In particular an elegant formula for the mean of the mutual information is obtained, i.e., the ergodic capacity of the two-hop amplify-and-forward MIMO relay channel without direct link.
cs/0612123
Electronic Laboratory Notebook Assisting Reflectance Spectrometry in Legal Medicine
cs.DB cs.DL cs.IR
Reflectance spectrometry is a fast and reliable method for the characterisation of human skin if the spectra are analysed with respect to a physical model describing the optical properties of human skin. For a field study performed at the Institute of Legal Medicine and the Freiburg Materials Research Center of the University of Freiburg an electronic laboratory notebook has been developed, which assists in the recording, management, and analysis of reflectance spectra. The core of the electronic laboratory notebook is a MySQL database. It is filled with primary data via a web interface programmed in Java, which also enables the user to browse the database and access the results of data analysis. These are carried out by Matlab, Tcl and Python scripts, which retrieve the primary data from the electronic laboratory notebook, perform the analysis, and store the results in the database for further usage.
cs/0612124
Highly robust error correction by convex programming
cs.IT math.IT math.PR math.ST stat.TH
This paper discusses a stylized communications problem where one wishes to transmit a real-valued signal x in R^n (a block of n pieces of information) to a remote receiver. We ask whether it is possible to transmit this information reliably when a fraction of the transmitted codeword is corrupted by arbitrary gross errors, and when in addition, all the entries of the codeword are contaminated by smaller errors (e.g. quantization errors). We show that if one encodes the information as Ax where A is a suitable m by n coding matrix (m >= n), there are two decoding schemes that allow the recovery of the block of n pieces of information x with nearly the same accuracy as if no gross errors occur upon transmission (or equivalently as if one has an oracle supplying perfect information about the sites and amplitudes of the gross errors). Moreover, both decoding strategies are very concrete and only involve solving simple convex optimization programs, either a linear program or a second-order cone program. We complement our study with numerical simulations showing that the encoder/decoder pair performs remarkably well.
cs/0612126
The virtual reality framework for engineering objects
cs.CE cs.MS
A framework for virtual reality of engineering objects has been developed. This framework may simulate different equipment related to virtual reality. Framework supports 6D dynamics, ordinary differential equations, finite formulas, vector and matrix operations. The framework also supports embedding of external software.
cs/0612127
bdbms -- A Database Management System for Biological Data
cs.DB
Biologists are increasingly using databases for storing and managing their data. Biological databases typically consist of a mixture of raw data, metadata, sequences, annotations, and related data obtained from various sources. Current database technology lacks several functionalities that are needed by biological databases. In this paper, we introduce bdbms, an extensible prototype database management system for supporting biological data. bdbms extends the functionalities of current DBMSs to include: (1) Annotation and provenance management including storage, indexing, manipulation, and querying of annotation and provenance as first class objects in bdbms, (2) Local dependency tracking to track the dependencies and derivations among data items, (3) Update authorization to support data curation via content-based authorization, in contrast to identity-based authorization, and (4) New access methods and their supporting operators that support pattern matching on various types of compressed biological data types. This paper presents the design of bdbms along with the techniques proposed to support these functionalities including an extension to SQL. We also outline some open issues in building bdbms.
cs/0612128
SASE: Complex Event Processing over Streams
cs.DB
RFID technology is gaining adoption on an increasing scale for tracking and monitoring purposes. Wide deployments of RFID devices will soon generate an unprecedented volume of data. Emerging applications require the RFID data to be filtered and correlated for complex pattern detection and transformed to events that provide meaningful, actionable information to end applications. In this work, we design and develop SASE, a com-plex event processing system that performs such data-information transformation over real-time streams. We design a complex event language for specifying application logic for such transformation, devise new query processing techniques to effi-ciently implement the language, and develop a comprehensive system that collects, cleans, and processes RFID data for deliv-ery of relevant, timely information as well as storing necessary data for future querying. We demonstrate an initial prototype of SASE through a real-world retail management scenario.
cs/0612129
Impliance: A Next Generation Information Management Appliance
cs.DB
ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from scratch, based upon today's requirements and hardware capabilities, would it look anything like today's database systems?" In this paper, we introduce Impliance, a next-generation information management system consisting of hardware and software components integrated to form an easy-to-administer appliance that can store, retrieve, and analyze all types of structured, semi-structured, and unstructured information. We first summarize the trends that will shape information management for the foreseeable future. Those trends imply three major requirements for Impliance: (1) to be able to store, manage, and uniformly query all data, not just structured records; (2) to be able to scale out as the volume of this data grows; and (3) to be simple and robust in operation. We then describe four key ideas that are uniquely combined in Impliance to address these requirements, namely the ideas of: (a) integrating software and off-the-shelf hardware into a generic information appliance; (b) automatically discovering, organizing, and managing all data - unstructured as well as structured - in a uniform way; (c) achieving scale-out by exploiting simple, massive parallel processing, and (d) virtualizing compute and storage resources to unify, simplify, and streamline the management of Impliance. Impliance is an ambitious, long-term effort to define simpler, more robust, and more scalable information systems for tomorrow's enterprises.
cs/0612132
A New Era in Citation and Bibliometric Analyses: Web of Science, Scopus, and Google Scholar
cs.DL cs.IR
Academic institutions, federal agencies, publishers, editors, authors, and librarians increasingly rely on citation analysis for making hiring, promotion, tenure, funding, and/or reviewer and journal evaluation and selection decisions. The Institute for Scientific Information's (ISI) citation databases have been used for decades as a starting point and often as the only tools for locating citations and/or conducting citation analyses. ISI databases (or Web of Science), however, may no longer be adequate as the only or even the main sources of citations because new databases and tools that allow citation searching are now available. Whether these new databases and tools complement or represent alternatives to Web of Science (WoS) is important to explore. Using a group of 15 library and information science faculty members as a case study, this paper examines the effects of using Scopus and Google Scholar (GS) on the citation counts and rankings of scholars as measured by WoS. The paper discusses the strengths and weaknesses of WoS, Scopus, and GS, their overlap and uniqueness, quality and language of the citations, and the implications of the findings for citation analysis. The project involved citation searching for approximately 1,100 scholarly works published by the study group and over 200 works by a test group (an additional 10 faculty members). Overall, more than 10,000 citing and purportedly citing documents were examined. WoS data took about 100 hours of collecting and processing time, Scopus consumed 200 hours, and GS a grueling 3,000 hours.