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cs/0408031
There Goes the Neighborhood: Relational Algebra for Spatial Data Search
cs.DB
We explored ways of doing spatial search within a relational database: (1) hierarchical triangular mesh (a tessellation of the sphere), (2) a zoned bucketing system, and (3) representing areas as disjunctive-normal form constraints. Each of these approaches has merits. They all allow efficient point-in-region queries. A relational representation for regions allows Boolean operations among them and allows quick tests for point-in-region, regions-containing-point, and region-overlap. The speed of these algorithms is much improved by a zone and multi-scale zone-pyramid scheme. The approach has the virtue that the zone mechanism works well on B-Trees native to all SQL systems and integrates naturally with current query optimizers - rather than requiring a new spatial access method and concomitant query optimizer extensions. Over the last 5 years, we have used these techniques extensively in our work on SkyServer.sdss.org, and SkyQuery.net.
cs/0408036
Consensus on Transaction Commit
cs.DC cs.DB
The distributed transaction commit problem requires reaching agreement on whether a transaction is committed or aborted. The classic Two-Phase Commit protocol blocks if the coordinator fails. Fault-tolerant consensus algorithms also reach agreement, but do not block whenever any majority of the processes are working. Running a Paxos consensus algorithm on the commit/abort decision of each participant yields a transaction commit protocol that uses 2F +1 coordinators and makes progress if at least F +1 of them are working. In the fault-free case, this algorithm requires one extra message delay but has the same stable-storage write delay as Two-Phase Commit. The classic Two-Phase Commit algorithm is obtained as the special F = 0 case of the general Paxos Commit algorithm.
cs/0408037
Multi-dimensional Type Theory: Rules, Categories, and Combinators for Syntax and Semantics
cs.CL cs.AI cs.LO
We investigate the possibility of modelling the syntax and semantics of natural language by constraints, or rules, imposed by the multi-dimensional type theory Nabla. The only multiplicity we explicitly consider is two, namely one dimension for the syntax and one dimension for the semantics, but the general perspective is important. For example, issues of pragmatics could be handled as additional dimensions. One of the main problems addressed is the rather complicated repertoire of operations that exists besides the notion of categories in traditional Montague grammar. For the syntax we use a categorial grammar along the lines of Lambek. For the semantics we use so-called lexical and logical combinators inspired by work in natural logic. Nabla provides a concise interpretation and a sequent calculus as the basis for implementations.
cs/0408038
The Dynamics of Group Codes: Dual Abelian Group Codes and Systems
cs.IT math.IT
Fundamental results concerning the dynamics of abelian group codes (behaviors) and their duals are developed. Duals of sequence spaces over locally compact abelian groups may be defined via Pontryagin duality; dual group codes are orthogonal subgroups of dual sequence spaces. The dual of a complete code or system is finite, and the dual of a Laurent code or system is (anti-)Laurent. If C and C^\perp are dual codes, then the state spaces of C act as the character groups of the state spaces of C^\perp. The controllability properties of C are the observability properties of C^\perp. In particular, C is (strongly) controllable if and only if C^\perp is (strongly) observable, and the controller memory of C is the observer memory of C^\perp. The controller granules of C act as the character groups of the observer granules of C^\perp. Examples of minimal observer-form encoder and syndrome-former constructions are given. Finally, every observer granule of C is an "end-around" controller granule of C.
cs/0408039
Medians and Beyond: New Aggregation Techniques for Sensor Networks
cs.DC cs.DB cs.DS
Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensors, however, have significant power constraint (battery life), making communication very expensive. Another important issue in the context of sensor-based information systems is that individual sensor readings are inherently unreliable. In order to address these two aspects, sensor database systems like TinyDB and Cougar enable in-network data aggregation to reduce the communication cost and improve reliability. The existing data aggregation techniques, however, are limited to relatively simple types of queries such as SUM, COUNT, AVG, and MIN/MAX. In this paper we propose a data aggregation scheme that significantly extends the class of queries that can be answered using sensor networks. These queries include (approximate) quantiles, such as the median, the most frequent data values, such as the consensus value, a histogram of the data distribution, as well as range queries. In our scheme, each sensor aggregates the data it has received from other sensors into a fixed (user specified) size message. We provide strict theoretical guarantees on the approximation quality of the queries in terms of the message size. We evaluate the performance of our aggregation scheme by simulation and demonstrate its accuracy, scalability and low resource utilization for highly variable input data sets.
cs/0408041
Fractal geometry of literature: first attempt to Shakespeare's works
cs.CL cs.CC
It was demonstrated that there is a geometrical order in the structure of literature. Fractal geometry as a modern mathematical approach and a new geometrical viewpoint on natural objects including both processes and structures was employed for analysis of literature. As the first study, the works of William Shakespeare were chosen as the most important items in western literature. By counting the number of letters applied in a manuscript, it is possible to study the whole manuscript statistically. A novel method based on basic assumption of fractal geometry was proposed for the calculation of fractal dimensions of the literature. The results were compared with Zipf's law. Zipf's law was successfully used for letters instead of words. Two new concepts namely Zipf's dimension and Zipf's order were also introduced. It was found that changes of both fractal dimension and Zipf's dimension are similar and dependent on the manuscript length. Interestingly, direct plotting the data obtained in semi-logarithmic and logarithmic forms also led to a power-law.
cs/0408044
FLUX: A Logic Programming Method for Reasoning Agents
cs.AI
FLUX is a programming method for the design of agents that reason logically about their actions and sensor information in the presence of incomplete knowledge. The core of FLUX is a system of Constraint Handling Rules, which enables agents to maintain an internal model of their environment by which they control their own behavior. The general action representation formalism of the fluent calculus provides the formal semantics for the constraint solver. FLUX exhibits excellent computational behavior due to both a carefully restricted expressiveness and the inference paradigm of progression.
cs/0408047
Pervasive Service Architecture for a Digital Business Ecosystem
cs.CE cs.NI
In this paper we present ideas and architectural principles upon which we are basing the development of a distributed, open-source infrastructure that, in turn, will support the expression of business models, the dynamic composition of software services, and the optimisation of service chains through automatic self-organising and evolutionary algorithms derived from biology. The target users are small and medium-sized enterprises (SMEs). We call the collection of the infrastructure, the software services, and the SMEs a Digital Business Ecosystem (DBE).
cs/0408048
Journal of New Democratic Methods: An Introduction
cs.CY cs.LG
This paper describes a new breed of academic journals that use statistical machine learning techniques to make them more democratic. In particular, not only can anyone submit an article, but anyone can also become a reviewer. Machine learning is used to decide which reviewers accurately represent the views of the journal's readers and thus deserve to have their opinions carry more weight. The paper concentrates on describing a specific experimental prototype of a democratic journal called the Journal of New Democratic Methods (JNDM). The paper also mentions the wider implications that machine learning and the techniques used in the JNDM may have for representative democracy in general.
cs/0408049
Using Stochastic Encoders to Discover Structure in Data
cs.NE cs.CV
In this paper a stochastic generalisation of the standard Linde-Buzo-Gray (LBG) approach to vector quantiser (VQ) design is presented, in which the encoder is implemented as the sampling of a vector of code indices from a probability distribution derived from the input vector, and the decoder is implemented as a superposition of reconstruction vectors. This stochastic VQ (SVQ) is optimised using a minimum mean Euclidean reconstruction distortion criterion, as in the LBG case. Numerical simulations are used to demonstrate how this leads to self-organisation of the SVQ, where different stochastically sampled code indices become associated with different input subspaces.
cs/0408050
Invariant Stochastic Encoders
cs.NE cs.CV
The theory of stochastic vector quantisers (SVQ) has been extended to allow the quantiser to develop invariances, so that only "large" degrees of freedom in the input vector are represented in the code. This has been applied to the problem of encoding data vectors which are a superposition of a "large" jammer and a "small" signal, so that only the jammer is represented in the code. This allows the jammer to be subtracted from the total input vector (i.e. the jammer is nulled), leaving a residual that contains only the underlying signal. The main advantage of this approach to jammer nulling is that little prior knowledge of the jammer is assumed, because these properties are automatically discovered by the SVQ as it is trained on examples of input vectors.
cs/0408051
Scalable XSLT Evaluation
cs.DB
XSLT is an increasingly popular language for processing XML data. It is widely supported by application platform software. However, little optimization effort has been made inside the current XSLT processing engines. Evaluating a very simple XSLT program on a large XML document with a simple schema may result in extensive usage of memory. In this paper, we present a novel notion of \emph{Streaming Processing Model} (\emph{SPM}) to evaluate a subset of XSLT programs on XML documents, especially large ones. With SPM, an XSLT processor can transform an XML source document to other formats without extra memory buffers required. Therefore, our approach can not only tackle large source documents, but also produce large results. We demonstrate with a performance study the advantages of the SPM approach. Experimental results clearly confirm that SPM improves XSLT evaluation typically 2 to 10 times better than the existing approaches. Moreover, the SPM approach also features high scalability.
cs/0408052
Application of the Double Metaphone Algorithm to Amharic Orthography
cs.CL
The Metaphone algorithm applies the phonetic encoding of orthographic sequences to simplify words prior to comparison. While Metaphone has been highly successful for the English language, for which it was designed, it may not be applied directly to Ethiopian languages. The paper details how the principles of Metaphone can be applied to Ethiopic script and uses Amharic as a case study. Match results improve as specific considerations are made for Amharic writing practices. Results are shown to improve further when common errors from Amharic input methods are considered.
cs/0408054
Providing Authentic Long-term Archival Access to Complex Relational Data
cs.DL cs.DB
We discuss long-term preservation of and access to relational databases. The focus is on national archives and science data archives which have to ingest and integrate data from a broad spectrum of vendor-specific relational database management systems (RDBMS). Furthermore, we present our solution SIARD which analyzes and extracts data and data logic from almost any RDBMS. It enables, to a reasonable level of authenticity, complete detachment of databases from their vendor-specific environment. The user can add archival descriptive metadata according to a customizable schema. A SIARD database archive integrates data, data logic, technical metadata, and archival descriptive information in one archival information package, independent of any specific software and hardware, based upon plain text files and the standardized languages SQL and XML. For usage purposes, a SIARD archive can be reloaded into any current or future RDBMS which supports standard SQL. In addition, SIARD contains a client that enables 'on demand' reload of archives into a target RDBMS, and multi-user remote access for querying and browsing the data together with its technical and descriptive metadata in one graphical user interface.
cs/0408055
Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection Scheme in Evolutionary Algorithms
cs.AI
Boltzmann selection is an important selection mechanism in evolutionary algorithms as it has theoretical properties which help in theoretical analysis. However, Boltzmann selection is not used in practice because a good annealing schedule for the `inverse temperature' parameter is lacking. In this paper we propose a Cauchy annealing schedule for Boltzmann selection scheme based on a hypothesis that selection-strength should increase as evolutionary process goes on and distance between two selection strengths should decrease for the process to converge. To formalize these aspects, we develop formalism for selection mechanisms using fitness distributions and give an appropriate measure for selection-strength. In this paper, we prove an important result, by which we derive an annealing schedule called Cauchy annealing schedule. We demonstrate the novelty of proposed annealing schedule using simulations in the framework of genetic algorithms.
cs/0408056
A CHR-based Implementation of Known Arc-Consistency
cs.LO cs.AI
In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use. For such cases, the Interactive Constraint Satisfaction Problem (ICSP) model has been proposed as an extension of the CSP model, to make it possible to start constraint propagation even when domains are not fully known, performing acquisition of domain elements only when necessary, and without the need for restarting the propagation after every acquisition. In this paper, we show how a solver for the two sorted CLP language, defined in previous work, to express ICSPs, has been implemented in the Constraint Handling Rules (CHR) language, a declarative language particularly suitable for high level implementation of constraint solvers.
cs/0408057
The role of robust semantic analysis in spoken language dialogue systems
cs.CL cs.AI cs.HC
In this paper we summarized a framework for designing grammar-based procedure for the automatic extraction of the semantic content from spoken queries. Starting with a case study and following an approach which combines the notions of fuzziness and robustness in sentence parsing, we showed we built practical domain-dependent rules which can be applied whenever it is possible to superimpose a sentence-level semantic structure to a text without relying on a previous deep syntactical analysis. This kind of procedure can be also profitably used as a pre-processing tool in order to cut out part of the sentence which have been recognized to have no relevance in the understanding process. In the case of particular dialogue applications where there is no need to build a complex semantic structure (e.g. word spotting or excerpting) the presented methodology may represent an efficient alternative solution to a sequential composition of deep linguistic analysis modules. Even if the query generation problem may not seem a critical application it should be held in mind that the sentence processing must be done on-line. Having this kind of constraints we cannot design our system without caring for efficiency and thus provide an immediate response. Another critical issue is related to whole robustness of the system. In our case study we tried to make experiences on how it is possible to deal with an unreliable and noisy input without asking the user for any repetition or clarification. This may correspond to a similar problem one may have when processing text coming from informal writing such as e-mails, news and in many cases Web pages where it is often the case to have irrelevant surrounding information.
cs/0408058
Non-negative matrix factorization with sparseness constraints
cs.LG cs.NE
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been applied in several applications, it does not always result in parts-based representations. In this paper, we show how explicitly incorporating the notion of `sparseness' improves the found decompositions. Additionally, we provide complete MATLAB code both for standard NMF and for our extension. Our hope is that this will further the application of these methods to solving novel data-analysis problems.
cs/0408059
Proofing Tools Technology at Neurosoft S.A.
cs.CL
The aim of this paper is to present the R&D activities carried out at Neurosoft S.A. regarding the development of proofing tools for Modern Greek. Firstly, we focus on infrastructure issues that we faced during our initial steps. Subsequently, we describe the most important insights of three proofing tools developed by Neurosoft, i.e. the spelling checker, the hyphenator and the thesaurus, outlining their efficiencies and inefficiencies. Finally, we discuss some improvement ideas and give our future directions.
cs/0408060
Verbal chunk extraction in French using limited resources
cs.CL
A way of extracting French verbal chunks, inflected and infinitive, is explored and tested on effective corpus. Declarative morphological and local grammar rules specifying chunks and some simple contextual structures are used, relying on limited lexical information and some simple heuristic/statistic properties obtained from restricted corpora. The specific goals, the architecture and the formalism of the system, the linguistic information on which it relies and the obtained results on effective corpus are presented.
cs/0408061
An electronic dictionary as a basis for NLP tools: The Greek case
cs.CL
The existence of a Dictionary in electronic form for Modern Greek (MG) is mandatory if one is to process MG at the morphological and syntactic levels since MG is a highly inflectional language with marked stress and a spelling system with many characteristics carried over from Ancient Greek. Moreover, such a tool becomes necessary if one is to create efficient and sophisticated NLP applications with substantial linguistic backing and coverage. The present paper will focus on the deployment of such an electronic dictionary for Modern Greek, which was built in two phases: first it was constructed to be the basis for a spelling correction schema and then it was reconstructed in order to become the platform for the deployment of a wider spectrum of NLP tools.
cs/0408062
Source Coding With Distortion Side Information At The Encoder
cs.IT math.IT
We consider lossy source coding when side information affecting the distortion measure may be available at the encoder, decoder, both, or neither. For example, such distortion side information can model reliabilities for noisy measurements, sensor calibration information, or perceptual effects like masking and sensitivity to context. When the distortion side information is statistically independent of the source, we show that in many cases (e.g, for additive or multiplicative distortion side information) there is no penalty for knowing the side information only at the encoder, and there is no advantage to knowing it at the decoder. Furthermore, for quadratic distortion measures scaled by the distortion side information, we evaluate the penalty for lack of encoder knowledge and show that it can be arbitrarily large. In this scenario, we also sketch transform based quantizers constructions which efficiently exploit encoder side information in the high-resolution limit.
cs/0408063
Analysis and Visualization of Index Words from Audio Transcripts of Instructional Videos
cs.IR cs.MM
We introduce new techniques for extracting, analyzing, and visualizing textual contents from instructional videos of low production quality. Using Automatic Speech Recognition, approximate transcripts (H75% Word Error Rate) are obtained from the originally highly compressed videos of university courses, each comprising between 10 to 30 lectures. Text material in the form of books or papers that accompany the course are then used to filter meaningful phrases from the seemingly incoherent transcripts. The resulting index into the transcripts is tied together and visualized in 3 experimental graphs that help in understanding the overall course structure and provide a tool for localizing certain topics for indexing. We specifically discuss a Transcript Index Map, which graphically lays out key phrases for a course, a Textbook Chapter to Transcript Match, and finally a Lecture Transcript Similarity graph, which clusters semantically similar lectures. We test our methods and tools on 7 full courses with 230 hours of video and 273 transcripts. We are able to extract up to 98 unique key terms for a given transcript and up to 347 unique key terms for an entire course. The accuracy of the Textbook Chapter to Transcript Match exceeds 70% on average. The methods used can be applied to genres of video in which there are recurrent thematic words (news, sports, meetings,...)
cs/0408064
Proportional Conflict Redistribution Rules for Information Fusion
cs.AI
In this paper we propose five versions of a Proportional Conflict Redistribution rule (PCR) for information fusion together with several examples. From PCR1 to PCR2, PCR3, PCR4, PCR5 one increases the complexity of the rules and also the exactitude of the redistribution of conflicting masses. PCR1 restricted from the hyper-power set to the power set and without degenerate cases gives the same result as the Weighted Average Operator (WAO) proposed recently by J{\o}sang, Daniel and Vannoorenberghe but does not satisfy the neutrality property of vacuous belief assignment. That's why improved PCR rules are proposed in this paper. PCR4 is an improvement of minC and Dempster's rules. The PCR rules redistribute the conflicting mass, after the conjunctive rule has been applied, proportionally with some functions depending on the masses assigned to their corresponding columns in the mass matrix. There are infinitely many ways these functions (weighting factors) can be chosen depending on the complexity one wants to deal with in specific applications and fusion systems. Any fusion combination rule is at some degree ad-hoc.
cs/0408066
Robust Locally Testable Codes and Products of Codes
cs.IT cs.CC math.IT
We continue the investigation of locally testable codes, i.e., error-correcting codes for whom membership of a given word in the code can be tested probabilistically by examining it in very few locations. We give two general results on local testability: First, motivated by the recently proposed notion of {\em robust} probabilistically checkable proofs, we introduce the notion of {\em robust} local testability of codes. We relate this notion to a product of codes introduced by Tanner, and show a very simple composition lemma for this notion. Next, we show that codes built by tensor products can be tested robustly and somewhat locally, by applying a variant of a test and proof technique introduced by Raz and Safra in the context of testing low-degree multivariate polynomials (which are a special case of tensor codes). Combining these two results gives us a generic construction of codes of inverse polynomial rate, that are testable with poly-logarithmically many queries. We note these locally testable tensor codes can be obtained from {\em any} linear error correcting code with good distance. Previous results on local testability, albeit much stronger quantitatively, rely heavily on algebraic properties of the underlying codes.
cs/0408069
The Integration of Connectionism and First-Order Knowledge Representation and Reasoning as a Challenge for Artificial Intelligence
cs.AI cs.LO cs.NE
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (also called connectionist systems) on the other, differ substantially. It would be very desirable to combine the robust neural networking machinery with symbolic knowledge representation and reasoning paradigms like logic programming in such a way that the strengths of either paradigm will be retained. Current state-of-the-art research, however, fails by far to achieve this ultimate goal. As one of the main obstacles to be overcome we perceive the question how symbolic knowledge can be encoded by means of connectionist systems: Satisfactory answers to this will naturally lead the way to knowledge extraction algorithms and to integrated neural-symbolic systems.
cs/0409002
Default reasoning over domains and concept hierarchies
cs.AI cs.LO
W.C. Rounds and G.-Q. Zhang (2001) have proposed to study a form of disjunctive logic programming generalized to algebraic domains. This system allows reasoning with information which is hierarchically structured and forms a (suitable) domain. We extend this framework to include reasoning with default negation, giving rise to a new nonmonotonic reasoning framework on hierarchical knowledge which encompasses answer set programming with extended disjunctive logic programs. We also show that the hierarchically structured knowledge on which programming in this paradigm can be done, arises very naturally from formal concept analysis. Together, we obtain a default reasoning paradigm for conceptual knowledge which is in accordance with mainstream developments in nonmonotonic reasoning.
cs/0409003
ScheduleNanny: Using GPS to Learn the User's Significant Locations, Travel Times and Schedule
cs.AI cs.CV cs.HC
As computing technology becomes more pervasive, personal devices such as the PDA, cell-phone, and notebook should use context to determine how to act. Location is one form of context that can be used in many ways. We present a multiple-device system that collects and clusters GPS data into significant locations. These locations are then used to determine travel times and a probabilistic model of the user's schedule, which is used to intelligently alert the user. We evaluate our system and suggest how it should be integrated with a variety of applications.
cs/0409007
The Generalized Pignistic Transformation
cs.AI
This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the complete result obtained by the GPT and its validation drawn from the probability theory.
cs/0409008
A Model for Fine-Grained Alignment of Multilingual Texts
cs.CL
While alignment of texts on the sentential level is often seen as being too coarse, and word alignment as being too fine-grained, bi- or multilingual texts which are aligned on a level in-between are a useful resource for many purposes. Starting from a number of examples of non-literal translations, which tend to make alignment difficult, we describe an alignment model which copes with these cases by explicitly coding them. The model is based on predicate-argument structures and thus covers the middle ground between sentence and word alignment. The model is currently used in a recently initiated project of a parallel English-German treebank (FuSe), which can in principle be extended with additional languages.
cs/0409010
Distance properties of expander codes
cs.IT cs.DM math.IT
We study the minimum distance of codes defined on bipartite graphs. Weight spectrum and the minimum distance of a random ensemble of such codes are computed. It is shown that if the vertex codes have minimum distance $\ge 3$, the overall code is asymptotically good, and sometimes meets the Gilbert-Varshamov bound. Constructive families of expander codes are presented whose minimum distance asymptotically exceeds the product bound for all code rates between 0 and 1.
cs/0409011
Shannon meets Wiener II: On MMSE estimation in successive decoding schemes
cs.IT math.IT
We continue to discuss why MMSE estimation arises in coding schemes that approach the capacity of linear Gaussian channels. Here we consider schemes that involve successive decoding, such as decision-feedback equalization or successive cancellation.
cs/0409019
Outlier Detection by Logic Programming
cs.AI cs.LO
The development of effective knowledge discovery techniques has become in the recent few years a very active research area due to the important impact it has in several relevant application areas. One interesting task thereof is that of singling out anomalous individuals from a given population, e.g., to detect rare events in time-series analysis settings, or to identify objects whose behavior is deviant w.r.t. a codified standard set of "social" rules. Such exceptional individuals are usually referred to as outliers in the literature. Recently, outlier detection has also emerged as a relevant KR&R problem. In this paper, we formally state the concept of outliers by generalizing in several respects an approach recently proposed in the context of default logic, for instance, by having outliers not being restricted to single individuals but, rather, in the more general case, to correspond to entire (sub)theories. We do that within the context of logic programming and, mainly through examples, we discuss its potential practical impact in applications. The formalization we propose is a novel one and helps in shedding some light on the real nature of outliers. Moreover, as a major contribution of this work, we illustrate the exploitation of minimality criteria in outlier detection. The computational complexity of outlier detection problems arising in this novel setting is thoroughly investigated and accounted for in the paper as well. Finally, we also propose a rewriting algorithm that transforms any outlier detection problem into an equivalent inference problem under the stable model semantics, thereby making outlier computation effective and realizable on top of any stable model solver.
cs/0409020
A Generalized Disjunctive Paraconsistent Data Model for Negative and Disjunctive Information
cs.DB
This paper presents a generalization of the disjunctive paraconsistent relational data model in which disjunctive positive and negative information can be represented explicitly and manipulated. There are situations where the closed world assumption to infer negative facts is not valid or undesirable and there is a need to represent and reason with negation explicitly. We consider explicit disjunctive negation in the context of disjunctive databases as there is an interesting interplay between these two types of information. Generalized disjunctive paraconsistent relation is introduced as the main structure in this model. The relational algebra is appropriately generalized to work on generalized disjunctive paraconsistent relations and their correctness is established.
cs/0409026
Capacity-achieving ensembles for the binary erasure channel with bounded complexity
cs.IT math.IT
We present two sequences of ensembles of non-systematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit. This is in contrast to all previous constructions of capacity-achieving sequences of ensembles whose complexity grows at least like the log of the inverse of the gap (in rate) to capacity. The new bounded complexity result is achieved by puncturing bits, and allowing in this way a sufficient number of state nodes in the Tanner graph representing the codes. We also derive an information-theoretic lower bound on the decoding complexity of randomly punctured codes on graphs. The bound holds for every memoryless binary-input output-symmetric channel and is refined for the BEC.
cs/0409027
Bounds on the decoding complexity of punctured codes on graphs
cs.IT math.IT
We present two sequences of ensembles of non-systematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit. This is in contrast to all previous constructions of capacity-achieving sequences of ensembles whose complexity grows at least like the log of the inverse of the gap (in rate) to capacity. The new bounded complexity result is achieved by puncturing bits, and allowing in this way a sufficient number of state nodes in the Tanner graph representing the codes. We also derive an information-theoretic lower bound on the decoding complexity of randomly punctured codes on graphs. The bound holds for every memoryless binary-input output-symmetric channel, and is refined for the BEC.
cs/0409031
Field Geology with a Wearable Computer: First Results of the Cyborg Astrobiologist System
cs.CV astro-ph cs.RO
We present results from the first geological field tests of the `Cyborg Astrobiologist', which is a wearable computer and video camcorder system that we are using to test and train a computer-vision system towards having some of the autonomous decision-making capabilities of a field-geologist. The Cyborg Astrobiologist platform has thus far been used for testing and development of these algorithms and systems: robotic acquisition of quasi-mosaics of images, real-time image segmentation, and real-time determination of interesting points in the image mosaics. The hardware and software systems function reliably, and the computer-vision algorithms are adequate for the first field tests. In addition to the proof-of-concept aspect of these field tests, the main result of these field tests is the enumeration of those issues that we can improve in the future, including: dealing with structural shadow and microtexture, and also, controlling the camera's zoom lens in an intelligent manner. Nonetheless, despite these and other technical inadequacies, this Cyborg Astrobiologist system, consisting of a camera-equipped wearable-computer and its computer-vision algorithms, has demonstrated its ability of finding genuinely interesting points in real-time in the geological scenery, and then gathering more information about these interest points in an automated manner.
cs/0409035
Parallel Computing Environments and Methods for Power Distribution System Simulation
cs.DC cs.CE cs.MA cs.PF
The development of cost-effective highperformance parallel computing on multi-processor supercomputers makes it attractive to port excessively time consuming simulation software from personal computers (PC) to super computes. The power distribution system simulator (PDSS) takes a bottom-up approach and simulates load at the appliance level, where detailed thermal models for appliances are used. This approach works well for a small power distribution system consisting of a few thousand appliances. When the number of appliances increases, the simulation uses up the PC memory and its runtime increases to a point where the approach is no longer feasible to model a practical large power distribution system. This paper presents an effort made to port a PC-based power distribution system simulator to a 128-processor shared-memory supercomputer. The paper offers an overview of the parallel computing environment and a description of the modification made to the PDSS model. The performance of the PDSS running on a standalone PC and on the supercomputer is compared. Future research direction of utilizing parallel computing in the power distribution system simulation is also addressed.
cs/0409040
Unification of Fusion Theories
cs.AI
Since no fusion theory neither rule fully satisfy all needed applications, the author proposes a Unification of Fusion Theories and a combination of fusion rules in solving problems/applications. For each particular application, one selects the most appropriate model, rule(s), and algorithm of implementation. We are working in the unification of the fusion theories and rules, which looks like a cooking recipe, better we'd say like a logical chart for a computer programmer, but we don't see another method to comprise/unify all things. The unification scenario presented herein, which is now in an incipient form, should periodically be updated incorporating new discoveries from the fusion and engineering research.
cs/0409042
A new architecture for making highly scalable applications
cs.HC cs.CL
An application is a logical image of the world on a computer. A scalable application is an application that allows one to update that logical image at run time. To put it in operational terms: an application is scalable if a client can change between time T1 and time T2 - the logic of the application as expressed by language L; - the structure and volume of the stored knowledge; - the user interface of the application; while clients working with the application at time T1 will work with the changed application at time T2 without performing any special action between T1 and T2. In order to realize such a scalable application a new architecture has been developed that fully orbits around language. In order to verify the soundness of that architecture a program has been build. Both architecture and program are called CommunSENS. The main purpose of this paper is: - to list the relevant elements of the architecture; - to give a visual presentation of how the program and its image of the world look like; - to give a visual presentation of how the image can be updated. Some relevant philosophical and practical backgrounds are included in the appendixes.
cs/0409044
Some Applications of Coding Theory in Computational Complexity
cs.CC cs.IT math.IT
Error-correcting codes and related combinatorial constructs play an important role in several recent (and old) results in computational complexity theory. In this paper we survey results on locally-testable and locally-decodable error-correcting codes, and their applications to complexity theory and to cryptography. Locally decodable codes are error-correcting codes with sub-linear time error-correcting algorithms. They are related to private information retrieval (a type of cryptographic protocol), and they are used in average-case complexity and to construct ``hard-core predicates'' for one-way permutations. Locally testable codes are error-correcting codes with sub-linear time error-detection algorithms, and they are the combinatorial core of probabilistically checkable proofs.
cs/0409045
Augmenting ALC(D) (atemporal) roles and (aspatial) concrete domain with temporal roles and a spatial concrete domain -first results
cs.AI cs.LO
We consider the well-known family ALC(D) of description logics with a concrete domain, and provide first results on a framework obtained by augmenting ALC(D) atemporal roles and aspatial concrete domain with temporal roles and a spatial concrete domain.
cs/0409046
A TCSP-like decidable constraint language generalising existing cardinal direction relations
cs.AI cs.LO
We define a quantitative constraint language subsuming two calculi well-known in QSR (Qualitative Spatial Reasoning): Frank's cone-shaped and projection-based calculi of cardinal direction relations. We show how to solve a CSP (Constraint Satisfaction Problem) expressed in the language.
cs/0409047
An ALC(D)-based combination of temporal constraints and spatial constraints suitable for continuous (spatial) change
cs.AI cs.LO
We present a family of spatio-temporal theories suitable for continuous spatial change in general, and for continuous motion of spatial scenes in particular. The family is obtained by spatio-temporalising the well-known ALC(D) family of Description Logics (DLs) with a concrete domain D, as follows, where TCSPs denotes "Temporal Constraint Satisfaction Problems", a well-known constraint-based framework: (1) temporalisation of the roles, so that they consist of TCSP constraints (specifically, of an adaptation of TCSP constraints to interval variables); and (2) spatialisation of the concrete domain D: the concrete domain is now $D_x$, and is generated by a spatial Relation Algebra (RA) $x$, in the style of the Region-Connection Calculus RCC8. We assume durative truth (i.e., holding during a durative interval). We also assume the homogeneity property (if a truth holds during a given interval, it holds during all of its subintervals). Among other things, these assumptions raise the "conflicting" problem of overlapping truths, which the work solves with the use of a specific partition of the 13 atomic relations of Allen's interval algebra.
cs/0409053
On the role of MMSE estimation in approaching the information-theoretic limits of linear Gaussian channels: Shannon meets Wiener
cs.IT math.IT
We discuss why MMSE estimation arises in lattice-based schemes for approaching the capacity of linear Gaussian channels, and comment on its properties.
cs/0409056
Using sparse matrices and splines-based interpolation in computational fluid dynamics simulations
cs.NA cs.CE physics.comp-ph
In this relation I present a technique of construction and fast evaluation of a family of cubic polynomials for analytic smoothing and graphical rendering of particles trajectories for flows in a generic geometry. The principal result of the work was implementation and test of a method for interpolating 3D points by regular parametric curves and their fast and efficient evaluation for a good resolution of rendering. For the purpose a parallel environment using a multiprocessor cluster architecture has been used. This work has been developed for the Research and Development Department of my company for planning advanced customized models of industrial burners.
cs/0409058
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
cs.CL
Sentiment analysis seeks to identify the viewpoint(s) underlying a text span; an example application is classifying a movie review as "thumbs up" or "thumbs down". To determine this sentiment polarity, we propose a novel machine-learning method that applies text-categorization techniques to just the subjective portions of the document. Extracting these portions can be implemented using efficient techniques for finding minimum cuts in graphs; this greatly facilitates incorporation of cross-sentence contextual constraints.
cs/0410001
The Infati Data
cs.DB
The ability to perform meaningful empirical studies is of essence in research in spatio-temporal query processing. Such studies are often necessary to gain detailed insight into the functional and performance characteristics of proposals for new query processing techniques. We present a collection of spatio-temporal data, collected during an intelligent speed adaptation project, termed INFATI, in which some two dozen cars equipped with GPS receivers and logging equipment took part. We describe how the data was collected and how it was "modified" to afford the drivers some degree of anonymity. We also present the road network in which the cars were moving during data collection. The GPS data is publicly available for non-commercial purposes. It is our hope that this resource will help the spatio-temporal research community in its efforts to develop new and better query processing techniques.
cs/0410002
Shannon Information and Kolmogorov Complexity
cs.IT math.IT
We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and where they are fundamentally different. We discuss and relate the basic notions of both theories: Shannon entropy versus Kolmogorov complexity, the relation of both to universal coding, Shannon mutual information versus Kolmogorov (`algorithmic') mutual information, probabilistic sufficient statistic versus algorithmic sufficient statistic (related to lossy compression in the Shannon theory versus meaningful information in the Kolmogorov theory), and rate distortion theory versus Kolmogorov's structure function. Part of the material has appeared in print before, scattered through various publications, but this is the first comprehensive systematic comparison. The last mentioned relations are new.
cs/0410003
Capacity and Random-Coding Exponents for Channel Coding with Side Information
cs.IT math.IT
Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is to be reliably transmitted through a noisy channel with finite input and output alphabets and random state sequence, and the channel is selected by a hypothetical adversary. Partial information about the state sequence is available to the encoder, adversary, and decoder. The design of the transmitter is subject to a cost constraint. Two families of channels are considered: 1) compound discrete memoryless channels (CDMC), and 2) channels with arbitrary memory, subject to an additive cost constraint, or more generally to a hard constraint on the conditional type of the channel output given the input. Both problems are closely connected. The random-coding exponent is achieved using a stacked binning scheme and a maximum penalized mutual information decoder, which may be thought of as an empirical generalized Maximum a Posteriori decoder. For channels with arbitrary memory, the random-coding exponents are larger than their CDMC counterparts. Applications of this study include watermarking, data hiding, communication in presence of partially known interferers, and problems such as broadcast channels, all of which involve the fundamental idea of binning.
cs/0410004
Applying Policy Iteration for Training Recurrent Neural Networks
cs.AI cs.LG cs.NE
Recurrent neural networks are often used for learning time-series data. Based on a few assumptions we model this learning task as a minimization problem of a nonlinear least-squares cost function. The special structure of the cost function allows us to build a connection to reinforcement learning. We exploit this connection and derive a convergent, policy iteration-based algorithm. Furthermore, we argue that RNN training can be fit naturally into the reinforcement learning framework.
cs/0410005
A dynamical model of a GRID market
cs.MA cond-mat.other cs.CE
We discuss potential market mechanisms for the GRID. A complete dynamical model of a GRID market is defined with three types of agents. Providers, middlemen and users exchange universal GRID computing units (GCUs) at varying prices. Providers and middlemen have strategies aimed at maximizing profit while users are 'satisficing' agents, and only change their behavior if the service they receive is sufficiently poor or overpriced. Preliminary results from a multi-agent numerical simulation of the market model shows that the distribution of price changes has a power law tail.
cs/0410008
Source Coding with Fixed Lag Side Information
cs.IT math.IT
We consider source coding with fixed lag side information at the decoder. We focus on the special case of perfect side information with unit lag corresponding to source coding with feedforward (the dual of channel coding with feedback) introduced by Pradhan. We use this duality to develop a linear complexity algorithm which achieves the rate-distortion bound for any memoryless finite alphabet source and distortion measure.
cs/0410014
Normal forms for Answer Sets Programming
cs.AI
Normal forms for logic programs under stable/answer set semantics are introduced. We argue that these forms can simplify the study of program properties, mainly consistency. The first normal form, called the {\em kernel} of the program, is useful for studying existence and number of answer sets. A kernel program is composed of the atoms which are undefined in the Well-founded semantics, which are those that directly affect the existence of answer sets. The body of rules is composed of negative literals only. Thus, the kernel form tends to be significantly more compact than other formulations. Also, it is possible to check consistency of kernel programs in terms of colorings of the Extended Dependency Graph program representation which we previously developed. The second normal form is called {\em 3-kernel.} A 3-kernel program is composed of the atoms which are undefined in the Well-founded semantics. Rules in 3-kernel programs have at most two conditions, and each rule either belongs to a cycle, or defines a connection between cycles. 3-kernel programs may have positive conditions. The 3-kernel normal form is very useful for the static analysis of program consistency, i.e., the syntactic characterization of existence of answer sets. This result can be obtained thanks to a novel graph-like representation of programs, called Cycle Graph which presented in the companion article \cite{Cos04b}.
cs/0410015
L1 regularization is better than L2 for learning and predicting chaotic systems
cs.LG cs.AI
Emergent behaviors are in the focus of recent research interest. It is then of considerable importance to investigate what optimizations suit the learning and prediction of chaotic systems, the putative candidates for emergence. We have compared L1 and L2 regularizations on predicting chaotic time series using linear recurrent neural networks. The internal representation and the weights of the networks were optimized in a unifying framework. Computational tests on different problems indicate considerable advantages for the L1 regularization: It had considerably better learning time and better interpolating capabilities. We shall argue that optimization viewed as a maximum likelihood estimation justifies our results, because L1 regularization fits heavy-tailed distributions -- an apparently general feature of emergent systems -- better.
cs/0410017
Automated Pattern Detection--An Algorithm for Constructing Optimally Synchronizing Multi-Regular Language Filters
cs.CV cond-mat.stat-mech cs.CL cs.DS cs.IR cs.LG nlin.AO nlin.CG nlin.PS physics.comp-ph q-bio.GN
In the computational-mechanics structural analysis of one-dimensional cellular automata the following automata-theoretic analogue of the \emph{change-point problem} from time series analysis arises: \emph{Given a string $\sigma$ and a collection $\{\mc{D}_i\}$ of finite automata, identify the regions of $\sigma$ that belong to each $\mc{D}_i$ and, in particular, the boundaries separating them.} We present two methods for solving this \emph{multi-regular language filtering problem}. The first, although providing the ideal solution, requires a stack, has a worst-case compute time that grows quadratically in $\sigma$'s length and conditions its output at any point on arbitrarily long windows of future input. The second method is to algorithmically construct a transducer that approximates the first algorithm. In contrast to the stack-based algorithm, however, the transducer requires only a finite amount of memory, runs in linear time, and gives immediate output for each letter read; it is, moreover, the best possible finite-state approximation with these three features.
cs/0410019
Finite-Length Scaling and Finite-Length Shift for Low-Density Parity-Check Codes
cs.IT cond-mat.dis-nn math.IT
Consider communication over the binary erasure channel BEC using random low-density parity-check codes with finite-blocklength n from `standard' ensembles. We show that large error events is conveniently described within a scaling theory, and explain how to estimate heuristically their effect. Among other quantities, we consider the finite length threshold e(n), defined by requiring a block error probability P_B = 1/2. For ensembles with minimum variable degree larger than two, the following expression is argued to hold e(n) = e -e_1 n^{-2/3} +\Theta(n^{-1}) with a calculable shift} parameter e_1>0.
cs/0410020
Adaptive Cluster Expansion (ACE): A Hierarchical Bayesian Network
cs.NE cs.CV
Using the maximum entropy method, we derive the "adaptive cluster expansion" (ACE), which can be trained to estimate probability density functions in high dimensional spaces. The main advantage of ACE over other Bayesian networks is its ability to capture high order statistics after short training times, which it achieves by making use of a hierarchical vector quantisation of the input data. We derive a scheme for representing the state of an ACE network as a "probability image", which allows us to identify statistically anomalous regions in an otherwise statistically homogeneous image, for instance. Finally, we present some probability images that we obtained after training ACE on some Brodatz texture images - these demonstrate the ability of ACE to detect subtle textural anomalies.
cs/0410022
RRL: A Rich Representation Language for the Description of Agent Behaviour in NECA
cs.MM cs.MA
In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is an XML compliant framework for representing the information that is exchanged at the interfaces between the various NECA system modules. The full XML Schemas for the RRL are available at http://www.ai.univie.ac.at/NECA/RRL
cs/0410027
Detecting User Engagement in Everyday Conversations
cs.SD cs.CL cs.HC
This paper presents a novel application of speech emotion recognition: estimation of the level of conversational engagement between users of a voice communication system. We begin by using machine learning techniques, such as the support vector machine (SVM), to classify users' emotions as expressed in individual utterances. However, this alone fails to model the temporal and interactive aspects of conversational engagement. We therefore propose the use of a multilevel structure based on coupled hidden Markov models (HMM) to estimate engagement levels in continuous natural speech. The first level is comprised of SVM-based classifiers that recognize emotional states, which could be (e.g.) discrete emotion types or arousal/valence levels. A high-level HMM then uses these emotional states as input, estimating users' engagement in conversation by decoding the internal states of the HMM. We report experimental results obtained by applying our algorithms to the LDC Emotional Prosody and CallFriend speech corpora.
cs/0410028
Life Above Threshold: From List Decoding to Area Theorem and MSE
cs.IT cond-mat.dis-nn math.IT
We consider communication over memoryless channels using low-density parity-check code ensembles above the iterative (belief propagation) threshold. What is the computational complexity of decoding (i.e., of reconstructing all the typical input codewords for a given channel output) in this regime? We define an algorithm accomplishing this task and analyze its typical performance. The behavior of the new algorithm can be expressed in purely information-theoretical terms. Its analysis provides an alternative proof of the area theorem for the binary erasure channel. Finally, we explain how the area theorem is generalized to arbitrary memoryless channels. We note that the recently discovered relation between mutual information and minimal square error is an instance of the area theorem in the setting of Gaussian channels.
cs/0410033
An In-Depth Look at Information Fusion Rules & the Unification of Fusion Theories
cs.AI
This paper may look like a glossary of the fusion rules and we also introduce new ones presenting their formulas and examples: Conjunctive, Disjunctive, Exclusive Disjunctive, Mixed Conjunctive-Disjunctive rules, Conditional rule, Dempster's, Yager's, Smets' TBM rule, Dubois-Prade's, Dezert-Smarandache classical and hybrid rules, Murphy's average rule, Inagaki-Lefevre-Colot-Vannoorenberghe Unified Combination rules [and, as particular cases: Iganaki's parameterized rule, Weighting Average Operator, minC (M. Daniel), and newly Proportional Conflict Redistribution rules (Smarandache-Dezert) among which PCR5 is the most exact way of redistribution of the conflicting mass to non-empty sets following the path of the conjunctive rule], Zhang's Center Combination rule, Convolutive x-Averaging, Consensus Operator (Josang), Cautious Rule (Smets), ?-junctions rules (Smets), etc. and three new T-norm & T-conorm rules adjusted from fuzzy and neutrosophic sets to information fusion (Tchamova-Smarandache). Introducing the degree of union and degree of inclusion with respect to the cardinal of sets not with the fuzzy set point of view, besides that of intersection, many fusion rules can be improved. There are corner cases where each rule might have difficulties working or may not get an expected result.
cs/0410036
Self-Organised Factorial Encoding of a Toroidal Manifold
cs.LG cs.CV
It is shown analytically how a neural network can be used optimally to encode input data that is derived from a toroidal manifold. The case of a 2-layer network is considered, where the output is assumed to be a set of discrete neural firing events. The network objective function measures the average Euclidean error that occurs when the network attempts to reconstruct its input from its output. This optimisation problem is solved analytically for a toroidal input manifold, and two types of solution are obtained: a joint encoder in which the network acts as a soft vector quantiser, and a factorial encoder in which the network acts as a pair of soft vector quantisers (one for each of the circular subspaces of the torus). The factorial encoder is favoured for small network sizes when the number of observed firing events is large. Such self-organised factorial encoding may be used to restrict the size of network that is required to perform a given encoding task, and will decompose an input manifold into its constituent submanifolds.
cs/0410038
Frequent Knot Discovery
cs.DB
We explore the possibility of applying the framework of frequent pattern mining to a class of continuous objects appearing in nature, namely knots. We introduce the frequent knot mining problem and present a solution. The key observation is that a database consisting of knots can be transformed into a transactional database. This observation is based on the Prime Decomposition Theorem of knots.
cs/0410040
Two Methods for Decreasing the Computational Complexity of the MIMO ML Decoder
cs.IT math.IT
We propose use of QR factorization with sort and Dijkstra's algorithm for decreasing the computational complexity of the sphere decoder that is used for ML detection of signals on the multi-antenna fading channel. QR factorization with sort decreases the complexity of searching part of the decoder with small increase in the complexity required for preprocessing part of the decoder. Dijkstra's algorithm decreases the complexity of searching part of the decoder with increase in the storage complexity. The computer simulation demonstrates that the complexity of the decoder is reduced by the proposed methods significantly.
cs/0410041
Maximum Mutual Information of Space-Time Block Codes with Symbolwise Decodability
cs.IT math.IT
In this paper, we analyze the performance of space-time block codes which enable symbolwise maximum likelihood decoding. We derive an upper bound of maximum mutual information (MMI) on space-time block codes that enable symbolwise maximum likelihood decoding for a frequency non-selective quasi-static fading channel. MMI is an upper bound on how much one can send information with vanishing error probability by using the target code.
cs/0410042
Neural Architectures for Robot Intelligence
cs.RO cs.CV cs.HC cs.LG cs.NE q-bio.NC
We argue that the direct experimental approaches to elucidate the architecture of higher brains may benefit from insights gained from exploring the possibilities and limits of artificial control architectures for robot systems. We present some of our recent work that has been motivated by that view and that is centered around the study of various aspects of hand actions since these are intimately linked with many higher cognitive abilities. As examples, we report on the development of a modular system for the recognition of continuous hand postures based on neural nets, the use of vision and tactile sensing for guiding prehensile movements of a multifingered hand, and the recognition and use of hand gestures for robot teaching. Regarding the issue of learning, we propose to view real-world learning from the perspective of data mining and to focus more strongly on the imitation of observed actions instead of purely reinforcement-based exploration. As a concrete example of such an effort we report on the status of an ongoing project in our lab in which a robot equipped with an attention system with a neurally inspired architecture is taught actions by using hand gestures in conjunction with speech commands. We point out some of the lessons learnt from this system, and discuss how systems of this kind can contribute to the study of issues at the junction between natural and artificial cognitive systems.
cs/0410043
Strategy in Ulam's Game and Tree Code Give Error-Resistant Protocols
cs.DC cs.IT math.IT
We present a new approach to construction of protocols which are proof against communication errors. The construction is based on a generalization of the well known Ulam's game. We show equivalence between winning strategies in this game and robust protocols for multi-party computation. We do not give any complete theory. We want rather to describe a new fresh idea. We use a tree code defined by Schulman. The tree code is the most important part of the interactive version of Shannon's Coding Theorem proved by Schulman. He uses probabilistic argument for the existence of a tree code without giving any effective construction. We show another proof yielding a randomized construction which in contrary to his proof almost surely gives a good code. Moreover our construction uses much smaller alphabet.
cs/0410049
Intransitivity and Vagueness
cs.AI
There are many examples in the literature that suggest that indistinguishability is intransitive, despite the fact that the indistinguishability relation is typically taken to be an equivalence relation (and thus transitive). It is shown that if the uncertainty perception and the question of when an agent reports that two things are indistinguishable are both carefully modeled, the problems disappear, and indistinguishability can indeed be taken to be an equivalence relation. Moreover, this model also suggests a logic of vagueness that seems to solve many of the problems related to vagueness discussed in the philosophical literature. In particular, it is shown here how the logic can handle the sorites paradox.
cs/0410050
Sleeping Beauty Reconsidered: Conditioning and Reflection in Asynchronous Systems
cs.AI
A careful analysis of conditioning in the Sleeping Beauty problem is done, using the formal model for reasoning about knowledge and probability developed by Halpern and Tuttle. While the Sleeping Beauty problem has been viewed as revealing problems with conditioning in the presence of imperfect recall, the analysis done here reveals that the problems are not so much due to imperfect recall as to asynchrony. The implications of this analysis for van Fraassen's Reflection Principle and Savage's Sure-Thing Principle are considered.
cs/0410053
An Extended Generalized Disjunctive Paraconsistent Data Model for Disjunctive Information
cs.DB
This paper presents an extension of generalized disjunctive paraconsistent relational data model in which pure disjunctive positive and negative information as well as mixed disjunctive positive and negative information can be represented explicitly and manipulated. We consider explicit mixed disjunctive information in the context of disjunctive databases as there is an interesting interplay between these two types of information. Extended generalized disjunctive paraconsistent relation is introduced as the main structure in this model. The relational algebra is appropriately generalized to work on extended generalized disjunctive paraconsistent relations and their correctness is established.
cs/0410054
Paraconsistent Intuitionistic Fuzzy Relational Data Model
cs.DB
In this paper, we present a generalization of the relational data model based on paraconsistent intuitionistic fuzzy sets. Our data model is capable of manipulating incomplete as well as inconsistent information. Fuzzy relation or intuitionistic fuzzy relation can only handle incomplete information. Associated with each relation are two membership functions one is called truth-membership function $T$ which keeps track of the extent to which we believe the tuple is in the relation, another is called false-membership function which keeps track of the extent to which we believe that it is not in the relation. A paraconsistent intuitionistic fuzzy relation is inconsistent if there exists one tuple $a$ such that $T(a) + F(a) > 1$. In order to handle inconsistent situation, we propose an operator called split to transform inconsistent paraconsistent intuitionistic fuzzy relations into pseudo-consistent paraconsistent intuitionistic fuzzy relations and do the set-theoretic and relation-theoretic operations on them and finally use another operator called combine to transform the result back to paraconsistent intuitionistic fuzzy relation. For this model, we define algebraic operators that are generalisations of the usual operators such as union, selection, join on fuzzy relations. Our data model can underlie any database and knowledge-base management system that deals with incomplete and inconsistent information.
cs/0410055
Mathematical knowledge management is needed
cs.IR
In this lecture I discuss some aspects of MKM, Mathematical Knowledge Management, with particuar emphasis on information storage and information retrieval.
cs/0410058
Robust Dialogue Understanding in HERALD
cs.CL cs.AI cs.HC cs.MA cs.SE
We tackle the problem of robust dialogue processing from the perspective of language engineering. We propose an agent-oriented architecture that allows us a flexible way of composing robust processors. Our approach is based on Shoham's Agent Oriented Programming (AOP) paradigm. We will show how the AOP agent model can be enriched with special features and components that allow us to deal with classical problems of dialogue understanding.
cs/0410059
A knowledge-based approach to semi-automatic annotation of multimedia documents via user adaptation
cs.DL cs.CL cs.IR
Current approaches to the annotation process focus on annotation schemas, languages for annotation, or are very application driven. In this paper it is proposed that a more flexible architecture for annotation requires a knowledge component to allow for flexible search and navigation of the annotated material. In particular, it is claimed that a general approach must take into account the needs, competencies, and goals of the producers, annotators, and consumers of the annotated material. We propose that a user-model based approach is, therefore, necessary.
cs/0410060
Semantic filtering by inference on domain knowledge in spoken dialogue systems
cs.CL cs.AI cs.HC cs.IR
General natural dialogue processing requires large amounts of domain knowledge as well as linguistic knowledge in order to ensure acceptable coverage and understanding. There are several ways of integrating lexical resources (e.g. dictionaries, thesauri) and knowledge bases or ontologies at different levels of dialogue processing. We concentrate in this paper on how to exploit domain knowledge for filtering interpretation hypotheses generated by a robust semantic parser. We use domain knowledge to semantically constrain the hypothesis space. Moreover, adding an inference mechanism allows us to complete the interpretation when information is not explicitly available. Further, we discuss briefly how this can be generalized towards a predictive natural interactive system.
cs/0410061
An argumentative annotation schema for meeting discussions
cs.CL cs.DL cs.IR
In this article, we are interested in the annotation of transcriptions of human-human dialogue taken from meeting records. We first propose a meeting content model where conversational acts are interpreted with respect to their argumentative force and their role in building the argumentative structure of the meeting discussion. Argumentation in dialogue describes the way participants take part in the discussion and argue their standpoints. Then, we propose an annotation scheme based on such an argumentative dialogue model as well as the evaluation of its adequacy. The obtained higher-level semantic annotations are exploited in the conceptual indexing of the information contained in meeting discussions.
cs/0410062
Automatic Keyword Extraction from Spoken Text. A Comparison of two Lexical Resources: the EDR and WordNet
cs.CL cs.DL cs.IR
Lexical resources such as WordNet and the EDR electronic dictionary have been used in several NLP tasks. Probably, partly due to the fact that the EDR is not freely available, WordNet has been used far more often than the EDR. We have used both resources on the same task in order to make a comparison possible. The task is automatic assignment of keywords to multi-party dialogue episodes (i.e. thematically coherent stretches of spoken text). We show that the use of lexical resources in such a task results in slightly higher performances than the use of a purely statistically based method.
cs/0410063
INSPIRE: Evaluation of a Smart-Home System for Infotainment Management and Device Control
cs.HC cs.CL
This paper gives an overview of the assessment and evaluation methods which have been used to determine the quality of the INSPIRE smart home system. The system allows different home appliances to be controlled via speech, and consists of speech and speaker recognition, speech understanding, dialogue management, and speech output components. The performance of these components is first assessed individually, and then the entire system is evaluated in an interaction experiment with test users. Initial results of the assessment and evaluation are given, in particular with respect to the transmission channel impact on speech and speaker recognition, and the assessment of speech output for different system metaphors.
cs/0410064
Intelligent Computer Numerical Control unit for machine tools
cs.CE
The paper describes a new CNC control unit for machining centres with learning ability and automatic intelligent generating of NC programs on the bases of a neural network, which is built-in into a CNC unit as special device. The device performs intelligent and completely automatically the NC part programs only on the bases of 2D, 2,5D or 3D computer model of prismatic part. Intervention of the operator is not needed. The neural network for milling, drilling, reaming, threading and operations alike has learned to generate NC programs in the learning module, which is a part of intelligent CAD/CAM system.
cs/0410068
Analyzing and Improving Performance of a Class of Anomaly-based Intrusion Detectors
cs.CR cs.AI
Anomaly-based intrusion detection (AID) techniques are useful for detecting novel intrusions into computing resources. One of the most successful AID detectors proposed to date is stide, which is based on analysis of system call sequences. In this paper, we present a detailed formal framework to analyze, understand and improve the performance of stide and similar AID techniques. Several important properties of stide-like detectors are established through formal proofs, and validated by carefully conducted experiments using test datasets. Finally, the framework is utilized to design two applications to improve the cost and performance of stide-like detectors which are based on sequence analysis. The first application reduces the cost of developing AID detectors by identifying the critical sections in the training dataset, and the second application identifies the intrusion context in the intrusive dataset, that helps to fine-tune the detectors. Such fine-tuning in turn helps to improve detection rate and reduce false alarm rate, thereby increasing the effectiveness and efficiency of the intrusion detectors.
cs/0410070
Using image partitions in 4th Dimension
cs.DB
I have plotted an image by using mathematical functions in the Database "4th Dimension". I'm going to show an alternative method to: detect which sector has been clicked; highlight it and combine it with other sectors already highlighted; store the graph information in an efficient way; load and splat image layers to reconstruct the stored graph.
cs/0410071
The Cyborg Astrobiologist: First Field Experience
cs.CV astro-ph cs.AI cs.CE cs.HC cs.RO cs.SE q-bio.NC
We present results from the first geological field tests of the `Cyborg Astrobiologist', which is a wearable computer and video camcorder system that we are using to test and train a computer-vision system towards having some of the autonomous decision-making capabilities of a field-geologist and field-astrobiologist. The Cyborg Astrobiologist platform has thus far been used for testing and development of these algorithms and systems: robotic acquisition of quasi-mosaics of images, real-time image segmentation, and real-time determination of interesting points in the image mosaics. The hardware and software systems function reliably, and the computer-vision algorithms are adequate for the first field tests. In addition to the proof-of-concept aspect of these field tests, the main result of these field tests is the enumeration of those issues that we can improve in the future, including: first, detection and accounting for shadows caused by 3D jagged edges in the outcrop; second, reincorporation of more sophisticated texture-analysis algorithms into the system; third, creation of hardware and software capabilities to control the camera's zoom lens in an intelligent manner; and fourth, development of algorithms for interpretation of complex geological scenery. Nonetheless, despite these technical inadequacies, this Cyborg Astrobiologist system, consisting of a camera-equipped wearable-computer and its computer-vision algorithms, has demonstrated its ability of finding genuinely interesting points in real-time in the geological scenery, and then gathering more information about these interest points in an automated manner.
cs/0410072
Temporal logic with predicate abstraction
cs.LO cs.CL
A predicate linear temporal logic LTL_{\lambda,=} without quantifiers but with predicate abstraction mechanism and equality is considered. The models of LTL_{\lambda,=} can be naturally seen as the systems of pebbles (flexible constants) moving over the elements of some (possibly infinite) domain. This allows to use LTL_{\lambda,=} for the specification of dynamic systems using some resources, such as processes using memory locations, mobile agents occupying some sites, etc. On the other hand we show that LTL_{\lambda,=} is not recursively axiomatizable and, therefore, fully automated verification of LTL_{\lambda,=} specifications is not, in general, possible.
cs/0411003
Applications of LDPC Codes to the Wiretap Channel
cs.IT cs.CR math.IT
With the advent of quantum key distribution (QKD) systems, perfect (i.e. information-theoretic) security can now be achieved for distribution of a cryptographic key. QKD systems and similar protocols use classical error-correcting codes for both error correction (for the honest parties to correct errors) and privacy amplification (to make an eavesdropper fully ignorant). From a coding perspective, a good model that corresponds to such a setting is the wire tap channel introduced by Wyner in 1975. In this paper, we study fundamental limits and coding methods for wire tap channels. We provide an alternative view of the proof for secrecy capacity of wire tap channels and show how capacity achieving codes can be used to achieve the secrecy capacity for any wiretap channel. We also consider binary erasure channel and binary symmetric channel special cases for the wiretap channel and propose specific practical codes. In some cases our designs achieve the secrecy capacity and in others the codes provide security at rates below secrecy capacity. For the special case of a noiseless main channel and binary erasure channel, we consider encoder and decoder design for codes achieving secrecy on the wiretap channel; we show that it is possible to construct linear-time decodable secrecy codes based on LDPC codes that achieve secrecy.
cs/0411006
Capacity Achieving Code Constructions for Two Classes of (d,k) Constraints
cs.IT math.IT
In this paper, we present two low complexity algorithms that achieve capacity for the noiseless (d,k) constrained channel when k=2d+1, or when k-d+1 is not prime. The first algorithm, called symbol sliding, is a generalized version of the bit flipping algorithm introduced by Aviran et al. [1]. In addition to achieving capacity for (d,2d+1) constraints, it comes close to capacity in other cases. The second algorithm is based on interleaving, and is a generalized version of the bit stuffing algorithm introduced by Bender and Wolf [2]. This method uses fewer than k-d biased bit streams to achieve capacity for (d,k) constraints with k-d+1 not prime. In particular, the encoder for (d,d+2^m-1) constraints, 1\le m<\infty, requires only m biased bit streams.
cs/0411008
Intuitionistic computability logic
cs.LO cs.AI math.LO
Computability logic (CL) is a systematic formal theory of computational tasks and resources, which, in a sense, can be seen as a semantics-based alternative to (the syntactically introduced) linear logic. With its expressive and flexible language, where formulas represent computational problems and "truth" is understood as algorithmic solvability, CL potentially offers a comprehensive logical basis for constructive applied theories and computing systems inherently requiring constructive and computationally meaningful underlying logics. Among the best known constructivistic logics is Heyting's intuitionistic calculus INT, whose language can be seen as a special fragment of that of CL. The constructivistic philosophy of INT, however, has never really found an intuitively convincing and mathematically strict semantical justification. CL has good claims to provide such a justification and hence a materialization of Kolmogorov's known thesis "INT = logic of problems". The present paper contains a soundness proof for INT with respect to the CL semantics. A comprehensive online source on CL is available at http://www.cis.upenn.edu/~giorgi/cl.html
cs/0411011
Capacity Analysis for Continuous Alphabet Channels with Side Information, Part I: A General Framework
cs.IT math.IT
Capacity analysis for channels with side information at the receiver has been an active area of interest. This problem is well investigated for the case of finite alphabet channels. However, the results are not easily generalizable to the case of continuous alphabet channels due to analytic difficulties inherent with continuous alphabets. In the first part of this two-part paper, we address an analytical framework for capacity analysis of continuous alphabet channels with side information at the receiver. For this purpose, we establish novel necessary and sufficient conditions for weak* continuity and strict concavity of the mutual information. These conditions are used in investigating the existence and uniqueness of the capacity-achieving measures. Furthermore, we derive necessary and sufficient conditions that characterize the capacity value and the capacity-achieving measure for continuous alphabet channels with side information at the receiver.
cs/0411012
Capacity Analysis for Continuous Alphabet Channels with Side Information, Part II: MIMO Channels
cs.IT math.IT
In this part, we consider the capacity analysis for wireless mobile systems with multiple antenna architectures. We apply the results of the first part to a commonly known baseband, discrete-time multiple antenna system where both the transmitter and receiver know the channel's statistical law. We analyze the capacity for additive white Gaussian noise (AWGN) channels, fading channels with full channel state information (CSI) at the receiver, fading channels with no CSI, and fading channels with partial CSI at the receiver. For each type of channels, we study the capacity value as well as issues such as the existence, uniqueness, and characterization of the capacity-achieving measures for different types of moment constraints. The results are applicable to both Rayleigh and Rician fading channels in the presence of arbitrary line-of-sight and correlation profiles.
cs/0411014
Rate Distortion and Denoising of Individual Data Using Kolmogorov complexity
cs.IT math.IT
We examine the structure of families of distortion balls from the perspective of Kolmogorov complexity. Special attention is paid to the canonical rate-distortion function of a source word which returns the minimal Kolmogorov complexity of all distortion balls containing that word subject to a bound on their cardinality. This canonical rate-distortion function is related to the more standard algorithmic rate-distortion function for the given distortion measure. Examples are given of list distortion, Hamming distortion, and Euclidean distortion. The algorithmic rate-distortion function can behave differently from Shannon's rate-distortion function. To this end, we show that the canonical rate-distortion function can and does assume a wide class of shapes (unlike Shannon's); we relate low algorithmic mutual information to low Kolmogorov complexity (and consequently suggest that certain aspects of the mutual information formulation of Shannon's rate-distortion function behave differently than would an analogous formulation using algorithmic mutual information); we explore the notion that low Kolmogorov complexity distortion balls containing a given word capture the interesting properties of that word (which is hard to formalize in Shannon's theory) and this suggests an approach to denoising; and, finally, we show that the different behavior of the rate-distortion curves of individual source words to some extent disappears after averaging over the source words.
cs/0411015
Bounded Input Bounded Predefined Control Bounded Output
cs.AI
The paper is an attempt to generalize a methodology, which is similar to the bounded-input bounded-output method currently widely used for the system stability studies. The presented earlier methodology allows decomposition of input space into bounded subspaces and defining for each subspace its bounding surface. It also defines a corresponding predefined control, which maps any point of a bounded input into a desired bounded output subspace. This methodology was improved by providing a mechanism for the fast defining a bounded surface. This paper presents enhanced bounded-input bounded-predefined-control bounded-output approach, which provides adaptability feature to the control and allows transferring of a controlled system along a suboptimal trajectory.
cs/0411016
Intelligent search strategies based on adaptive Constraint Handling Rules
cs.AI cs.PL
The most advanced implementation of adaptive constraint processing with Constraint Handling Rules (CHR) allows the application of intelligent search strategies to solve Constraint Satisfaction Problems (CSP). This presentation compares an improved version of conflict-directed backjumping and two variants of dynamic backtracking with respect to chronological backtracking on some of the AIM instances which are a benchmark set of random 3-SAT problems. A CHR implementation of a Boolean constraint solver combined with these different search strategies in Java is thus being compared with a CHR implementation of the same Boolean constraint solver combined with chronological backtracking in SICStus Prolog. This comparison shows that the addition of ``intelligence'' to the search process may reduce the number of search steps dramatically. Furthermore, the runtime of their Java implementations is in most cases faster than the implementations of chronological backtracking. More specifically, conflict-directed backjumping is even faster than the SICStus Prolog implementation of chronological backtracking, although our Java implementation of CHR lacks the optimisations made in the SICStus Prolog system. To appear in Theory and Practice of Logic Programming (TPLP).
cs/0411018
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
cs.RO cs.AI
This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams.
cs/0411020
Dynamic Modelling and Adaptive Traction Control for Mobile Robots
cs.RO
Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as Low level controller. The second level is developed to take care of path planning and trajectory generation.
cs/0411021
Coevolution Based Adaptive Monte Carlo Localization (CEAMCL)
cs.RO
An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robots pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robots pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL). Experiments have been carried out to prove the efficiency of the new localization algorithm.
cs/0411022
Topological Navigation of Simulated Robots using Occupancy Grid
cs.RO cs.AI
Formerly I presented a metric navigation method in the Webots mobile robot simulator. The navigating Khepera-like robot builds an occupancy grid of the environment and explores the square-shaped room around with a value iteration algorithm. Now I created a topological navigation procedure based on the occupancy grid process. The extension by a skeletonization algorithm results a graph of important places and the connecting routes among them. I also show the significant time profit gained during the process.
cs/0411023
Design and Implementation of a General Decision-making Model in RoboCup Simulation
cs.RO
The study of the collaboration, coordination and negotiation among different agents in a multi-agent system (MAS) has always been the most challenging yet popular in the research of distributed artificial intelligence. In this paper, we will suggest for RoboCup simulation, a typical MAS, a general decision-making model, rather than define a different algorithm for each tactic (e.g. ball handling, pass, shoot and interception, etc.) in soccer games as most RoboCup simulation teams did. The general decision-making model is based on two critical factors in soccer games: the vertical distance to the goal line and the visual angle for the goalpost. We have used these two parameters to formalize the defensive and offensive decisions in RoboCup simulation and the results mentioned above had been applied in NOVAURO, original name is UJDB, a RoboCup simulation team of Jiangsu University, whose decision-making model, compared with that of Tsinghua University, the world champion team in 2001, is a universal model and easier to be implemented.
cs/0411024
Space Robotics Part 2: Space-based Manipulators
cs.RO
In this second of three short papers, I introduce some of the basic concepts of space robotics with an emphasis on some specific challenging areas of research that are peculiar to the application of robotics to space infrastructure development. The style of these short papers is pedagogical and the concepts in this paper are developed from fundamental manipulator robotics. This second paper considers the application of space manipulators to on-orbit servicing (OOS), an application which has considerable commercial application. I provide some background to the notion of robotic on-orbit servicing and explore how manipulator control algorithms may be modified to accommodate space manipulators which operate in the micro-gravity of space.
cs/0411025
Bionic Humans Using EAP as Artificial Muscles Reality and Challenges
cs.RO cs.AI
For many years, the idea of a human with bionic muscles immediately conjures up science fiction images of a TV series superhuman character that was implanted with bionic muscles and portrayed with strength and speed far superior to any normal human. As fantastic as this idea may seem, recent developments in electroactive polymers (EAP) may one day make such bionics possible. Polymers that exhibit large displacement in response to stimulation that is other than electrical signal were known for many years. Initially, EAP received relatively little attention due to their limited actuation capability. However, in the recent years, the view of the EAP materials has changed due to the introduction of effective new materials that significantly surpassed the capability of the widely used piezoelectric polymer, PVDF. As this technology continues to evolve, novel mechanisms that are biologically inspired are expected to emerge. EAP materials can potentially provide actuation with lifelike response and more flexible configurations. While further improvements in performance and robustness are still needed, there already have been several reported successes. In recognition of the need for cooperation in this multidisciplinary field, the author initiated and organized a series of international forums that are leading to a growing number of research and development projects and to great advances in the field. In 1999, he challenged the worldwide science and engineering community of EAP experts to develop a robotic arm that is actuated by artificial muscles to win a wrestling match against a human opponent. In this paper, the field of EAP as artificial muscles will be reviewed covering the state of the art, the challenges and the vision for the progress in future years.
cs/0411026
A Search Relevancy Tuning Method Using Expert Results Content Evaluation
cs.IR
The article presents an online relevancy tuning method using explicit user feedback. The author developed and tested a method of words' weights modification based on search result evaluation by user. User decides whether the result is useful or not after inspecting the full result content. The experiment proved that the constantly accumulated words weights base leads to better search quality in a specified data domain. The author also suggested future improvements of the method.