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0912.1016
Refactoring of a Database
cs.DB
The technique of database refactoring is all about applying disciplined and controlled techniques to change an existing database schema. The problem is to successfully create a Database Refactoring Framework for databases. This paper concentrates on the feasibility of adapting this concept to work as a generic template. To retain the constraints regardless of the modifications to the metadata, the paper proposes a MetaData Manipulation Tool to facilitate change. The tool adopts a Template Design Pattern to make it database independent. The paper presents a drawback of using java for constraint extraction and proposes an alternative.
0912.1017
Genetic Programming Framework for Fingerprint Matching
cs.CR cs.CV cs.MM
A fingerprint matching is a very difficult problem. Minutiae based matching is the most popular and widely used technique for fingerprint matching. The minutiae points considered in automatic identification systems are based normally on termination and bifurcation points. In this paper we propose a new technique for fingerprint matching using minutiae points and genetic programming. The goal of this paper is extracting the mathematical formula that defines the minutiae points.
0912.1023
Efficient Relay Beamforming Design with SIC Detection for Dual-Hop MIMO Relay Networks
cs.NI cs.IT math.IT
In this paper, we consider a dual-hop Multiple Input Multiple Output (MIMO) relay wireless network, in which a source-destination pair both equipped with multiple antennas communicates through a large number of half-duplex amplify-and-forward (AF) relay terminals. Two novel linear beamforming schemes based on the matched filter (MF) and regularized zero-forcing (RZF) precoding techniques are proposed for the MIMO relay system. We focus on the linear process at the relay nodes and design the new relay beamformers by utilizing the channel state information (CSI) of both backward channel and forward channel. The proposed beamforming designs are based on the QR decomposition (QRD) filter at the destination node which performs successive interference cancellation (SIC) to achieve the maximum spatial multiplexing gain. Simulation results demonstrate that the proposed beamformers that fulfil both the intranode array gain and distributed array gain outperform other relaying schemes under different system parameters in terms of the ergodic capacity.
0912.1059
Reduced Complexity Angle-Doppler-Range Estimation for MIMO Radar That Employs Compressive Sensing
cs.IT math.IT
The authors recently proposed a MIMO radar system that is implemented by a small wireless network. By applying compressive sensing (CS) at the receive nodes, the MIMO radar super-resolution can be achieved with far fewer observations than conventional approaches. This previous work considered the estimation of direction of arrival and Doppler. Since the targets are sparse in the angle-velocity space, target information can be extracted by solving an l1 minimization problem. In this paper, the range information is exploited by introducing step frequency to MIMO radar with CS. The proposed approach is able to achieve high range resolution and also improve the ambiguous velocity. However, joint angle-Doppler-range estimation requires discretization of the angle-Doppler-range space which causes a sharp rise in the computational burden of the l1 minimization problem. To maintain an acceptable complexity, a technique is proposed to successively estimate angle, Doppler and range in a decoupled fashion. The proposed approach can significantly reduce the complexity without sacrificing performance.
0912.1110
XML Multidimensional Modelling and Querying
cs.DB
As XML becomes ubiquitous and XML storage and processing becomes more efficient, the range of use cases for these technologies widens daily. One promising area is the integration of XML and data warehouses, where an XML-native database stores multidimensional data and processes OLAP queries written in the XQuery interrogation language. This paper explores issues arising in the implementation of such a data warehouse. We first compare approaches for multidimensional data modelling in XML, then describe how typical OLAP queries on these models can be expressed in XQuery. We then show how, regardless of the model, the grouping features of XQuery 1.1 improve performance and readability of these queries. Finally, we evaluate the performance of query evaluation in each modelling choice using the eXist database, which we extended with a grouping clause implementation.
0912.1128
How to Explain Individual Classification Decisions
stat.ML cs.LG
After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to the question what is the most likely label of a given unseen data point. However, most methods will provide no answer why the model predicted the particular label for a single instance and what features were most influential for that particular instance. The only method that is currently able to provide such explanations are decision trees. This paper proposes a procedure which (based on a set of assumptions) allows to explain the decisions of any classification method.
0912.1155
A Learning-Based Approach to Reactive Security
cs.CR cs.GT cs.LG
Despite the conventional wisdom that proactive security is superior to reactive security, we show that reactive security can be competitive with proactive security as long as the reactive defender learns from past attacks instead of myopically overreacting to the last attack. Our game-theoretic model follows common practice in the security literature by making worst-case assumptions about the attacker: we grant the attacker complete knowledge of the defender's strategy and do not require the attacker to act rationally. In this model, we bound the competitive ratio between a reactive defense algorithm (which is inspired by online learning theory) and the best fixed proactive defense. Additionally, we show that, unlike proactive defenses, this reactive strategy is robust to a lack of information about the attacker's incentives and knowledge.
0912.1198
Delay-Optimal Power and Subcarrier Allocation for OFDMA Systems via Stochastic Approximation
cs.LG
In this paper, we consider delay-optimal power and subcarrier allocation design for OFDMA systems with $N_F$ subcarriers, $K$ mobiles and one base station. There are $K$ queues at the base station for the downlink traffic to the $K$ mobiles with heterogeneous packet arrivals and delay requirements. We shall model the problem as a $K$-dimensional infinite horizon average reward Markov Decision Problem (MDP) where the control actions are assumed to be a function of the instantaneous Channel State Information (CSI) as well as the joint Queue State Information (QSI). This problem is challenging because it corresponds to a stochastic Network Utility Maximization (NUM) problem where general solution is still unknown. We propose an {\em online stochastic value iteration} solution using {\em stochastic approximation}. The proposed power control algorithm, which is a function of both the CSI and the QSI, takes the form of multi-level water-filling. We prove that under two mild conditions in Theorem 1 (One is the stepsize condition. The other is the condition on accessibility of the Markov Chain, which can be easily satisfied in most of the cases we are interested.), the proposed solution converges to the optimal solution almost surely (with probability 1) and the proposed framework offers a possible solution to the general stochastic NUM problem. By exploiting the birth-death structure of the queue dynamics, we obtain a reduced complexity decomposed solution with linear $\mathcal{O}(KN_F)$ complexity and $\mathcal{O}(K)$ memory requirement.
0912.1216
Distributive Subband Allocation, Power and Rate Control for Relay-Assisted OFDMA Cellular System with Imperfect System State Knowledge
cs.NI cs.IT math.IT
In this paper, we consider distributive subband, power and rate allocation for a two-hop transmission in an orthogonal frequency-division multiple-access (OFDMA) cellular system with fixed relays which operate in decode-and-forward strategy. We take into account of system fairness by considering weighted sum goodput as our optimization objective. Based on the cluster-based architecture, we obtain a fast-converging distributive solution with only local imperfect CSIT by using decomposition of the optimization problem. To further reduce the signaling overhead and computational complexity, we propose a reduced feedback distributive solution, which can achieve asymptotically optimal performance for large number of users with arbitrarily small feedback overhead per user. We also derive asymptotic average system throughput for the relay-assisted OFDMA system so as to obtain useful design insights.
0912.1224
The university-industry knowledge relationship: Analyzing patents and the science base of technologies
cs.DL cs.CY cs.IR physics.soc-ph
Via the Internet, information scientists can obtain cost-free access to large databases in the hidden or deep web. These databases are often structured far more than the Internet domains themselves. The patent database of the U.S. Patent and Trade Office is used in this study to examine the science base of patents in terms of the literature references in these patents. University-based patents at the global level are compared with results when using the national economy of the Netherlands as a system of reference. Methods for accessing the on-line databases and for the visualization of the results are specified. The conclusion is that 'biotechnology' has historically generated a model for theorizing about university-industry relations that cannot easily be generalized to other sectors and disciplines.
0912.1294
Conception d'un outil d'aide \`a l'indexation de ressources p\'edagogiques - Extraction automatique des th\'ematiques et des mots-clefs de documents UNIT
cs.IR
Indexing learning documents using the Learning Object Metadata (LOM) is often carried out manually by archivists. Filling out the LOM fields is a long and difficult task, requiring a complete reading and a full knowledge on the topic dealt within the document. In this paper, we present an innovative model and method to assist the archivists in finding the important concepts and keywords of a learning document. The application is performed using wikipedia's category links.
0912.1310
Automatic creation of urban velocity fields from aerial video
cs.CV
In this paper, we present a system for modelling vehicle motion in an urban scene from low frame-rate aerial video. In particular, the scene is modelled as a probability distribution over velocities at every pixel in the image. We describe the complete system for acquiring this model. The video is captured from a helicopter and stabilized by warping the images to match an orthorectified image of the area. A pixel classifier is applied to the stabilized images, and the response is segmented to determine car locations and orientations. The results are fed in to a tracking scheme which tracks cars for three frames, creating tracklets. This allows the tracker to use a combination of velocity, direction, appearance, and acceleration cues to keep only tracks likely to be correct. Each tracklet provides a measurement of the car velocity at every point along the tracklet's length, and these are then aggregated to create a histogram of vehicle velocities at every pixel in the image. The results demonstrate that the velocity probability distribution prior can be used to infer a variety of information about road lane directions, speed limits, vehicle speeds and common trajectories, and traffic bottlenecks, as well as providing a means of describing environmental knowledge about traffic rules that can be used in tracking.
0912.1333
Spectral Efficiency Optimization for an Interfering Cognitive Radio with Adaptive Modulation and Coding
cs.IT math.IT
In this paper, we consider a primary and a cognitive user transmitting over a wireless fading interference channel. The primary user transmits with a constant power and utilizes an adaptive modulation and coding (AMC) scheme satisfying a bit error rate requirement. We propose a link adaptation scheme to maximize the average spectral efficiency of the cognitive radio, while a minimum required spectral efficiency for the primary user is provisioned. The resulting problem is constrained to also satisfy a bit error rate requirement and a power constraint for the cognitive link. The AMC mode selection and power control at the cognitive transmitter is optimized based on the modified signal to noise plus interference ratio feedback of both links. The problem is then cast as a nonlinear discrete optimization problem for which a fast and efficient suboptimum solution is presented. We also present a scheme with rate adaptive and constant power cognitive radio. An important characteristic of the proposed schemes is that no computation or coordination overhead is imposed on the primary radio due to the cognitive radio activity. Numerical results and comparison with the interweave approach to cognitive radio demonstrate the efficiency of the proposed solutions.
0912.1412
Topological Properties of an Exponential Random Geometric Graph Process
cs.IT cs.DM math.IT math.PR
In this paper, we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential AR(1) process, which may serve as a mobile wireless network model. The transition probability matrix and stationary distribution are derived for the Markov chains in terms of network connectivity and the number of components. We characterize an algorithm for the hitting time regarding disconnectivity. In addition, we also study topological properties for static snapshots. We obtain the degree distributions as well as asymptotic precise bounds and strong law of large numbers for connectivity threshold distance and the largest nearest neighbor distance amongst others. Both closed form results and limit theorems are provided.
0912.1420
Nonlinear Effects in Stiffness Modeling of Robotic Manipulators
cs.RO
The paper focuses on the enhanced stiffness modeling of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the virtual joint technique that describes the compliance of manipulator elements by a set of localized six-dimensional springs separated by rigid links and perfect joints. In contrast to the conventional formulation, which is valid for the unloaded mode and small displacements, the proposed approach implicitly assumes that the loading leads to the non-negligible changes of the manipulator posture and corresponding amendment of the Jacobian. The developed numerical technique allows computing the static equilibrium and relevant force/torque reaction of the manipulator for any given displacement of the end-effector. This enables designer detecting essentially nonlinear effects in elastic behavior of manipulator, similar to the buckling of beam elements. It is also proposed the linearization procedure that is based on the inversion of the dedicated matrix composed of the stiffness parameters of the virtual springs and the Jacobians/Hessians of the active and passive joints. The developed technique is illustrated by an application example that deals with the stiffness analysis of a parallel manipulator of the Orthoglide family.
0912.1421
Context and Keyword Extraction in Plain Text Using a Graph Representation
cs.IR
Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist indexing specialized documents, experience plays an important role. But indexing documents on different topics is much harder. This article proposes an innovative method for an indexing support system. This system takes as input an ontology and a plain text document and provides as output contextualized keywords of the document. The method has been evaluated by exploiting Wikipedia's category links as a termino-ontological resources.
0912.1440
Comment on "New Results on Frame-Proof Codes and Traceability Schemes"
cs.IT math.IT
In the paper "New Results on Frame-Proof Codes and Traceability Schemes" by Reihaneh Safavi-Naini and Yejing Wang [IEEE Trans. Inform. Theory, vol. 47, no. 7, pp. 3029-3033, Nov. 2001], there are lower bounds for the maximal number of codewords in binary frame-proof codes and decoders in traceability schemes. There are also existence proofs using a construction of binary frame-proof codes and traceability schemes. Here it is found that the main results in the referenced paper do not hold.
0912.1534
Evolutionary multi-stage financial scenario tree generation
cs.NE q-fin.CP q-fin.PM
Multi-stage financial decision optimization under uncertainty depends on a careful numerical approximation of the underlying stochastic process, which describes the future returns of the selected assets or asset categories. Various approaches towards an optimal generation of discrete-time, discrete-state approximations (represented as scenario trees) have been suggested in the literature. In this paper, a new evolutionary algorithm to create scenario trees for multi-stage financial optimization models will be presented. Numerical results and implementation details conclude the paper.
0912.1588
Self-organizing urban transportation systems
nlin.AO cs.MA
Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete solutions, as the problem changes before it can be optimized. An alternative lies in seeking adaptive solutions. This adaptation can be achieved with self-organization. In a self-organizing transportation system, the elements of the system follow local rules to achieve a global solution. Like this, when the problem changes the system can adapt by itself to the new configuration. In this chapter, I will review recent, current, and future work on self-organizing transportation systems. Self-organizing traffic lights have proven to improve traffic flow considerably over traditional methods. In public transportation systems, simple rules are being explored to prevent the "equal headway instability" phenomenon. The methods we have used can be also applied to other urban transportation systems and their generality is discussed.
0912.1628
KF-CS: Compressive Sensing on Kalman Filtered Residual
cs.IT math.IT stat.ME
We consider the problem of recursively reconstructing time sequences of sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear incoherent measurements with additive noise. The idea of our proposed solution, KF CS-residual (KF-CS) is to replace compressed sensing (CS) on the observation by CS on the Kalman filtered (KF) observation residual computed using the previous estimate of the support. KF-CS error stability over time is studied. Simulation comparisons with CS and LS-CS are shown.
0912.1655
Maximum-likelihood co-channel interference cancellation with power control for cellular OFDM networks
cs.IT math.IT
In cellular Orthogonal Frequency Division Multiplexing (OFDM) networks, Co-Channel Interference (CCI) leads to severe degradation in the BER performance. To solve this problem, Maximum-Likelihood Estimation (MLE) CCI cancellation scheme has been proposed in the literature. MLE CCI cancellation scheme generates weighted replicas of the transmitted signals and selects replica with the smallest Euclidean distance from the received signal. When the received power of the desired and interference signals are nearly the same, the BER performance is degraded. In this paper, we propose an improved MLE CCI canceler with closed-loop Power Control (PC) scheme capable of detecting and combating against the equal received power situation at the Mobile Station (MS) receiver by using the newly introduced parameter Power Ratio (PR). At cell edge where Signal to Interferer Ratio (SIR) is considered to have average value between -5 and 10 dB, computer simulations show that the proposed closed-loop PC scheme has a gain of 7 dB at 28 km/h and about 2 dB at 120 km/h.
0912.1658
On the achievable improvement by the linear minimum mean square error detector
cs.IT math.IT
Linear minimum mean square error (MMSE) detector has been shown to alleviate the noise amplification problem, resulting in the conventional zero-forcing (ZF) detector. In this paper, we analyze the performance improvement by the MMSE detector in terms of the condition number of its filtering matrix, and in terms of the post-precessing signal to noise ratio (SNR) improvement. To this end, we derive explicit formulas for the condition numbers of the filtering matrices and the post-processing SNRs. Analytical and simulation results demonstrate that the improvement achieved by the MMSE detector over the ZF detector is not only dependent on the noise variance and the condition number of the channel matrix, but also on how close the smallest singular values are to the noise variance.
0912.1661
Fixed-complexity vector perturbation with Block diagonalization for MU-MIMO systems
cs.IT math.IT
Block diagonalization (BD) is an attractive technique that transforms the multi-user multiple-input multiple-output (MU-MIMO) channel into parallel single-user MIMO (SU-MIMO) channels with zero inter-user interference (IUI). In this paper, we combine the BD technique with two deterministic vector perturbation (VP) algorithms that reduce the transmit power in MU-MIMO systems with linear precoding. These techniques are the fixed-complexity sphere encoder (FSE) and the QR-decomposition with M-algorithm encoder (QRDM-E). In contrast to the conventional BD VP technique, which is based on the sphere encoder (SE), the proposed techniques have fixed complexity and a tradeoff between performance and complexity can be achieved by controlling the size of the set of candidates for the perturbation vector. Simulation results and analysis demonstrate the properness of the proposed techniques for the next generation mobile communications systems which are latency and computational complexity limited. In MU-MIMO system with 4 users each equipped with 2 receive antennas, simulation results show that the proposed BD-FSE and BD-QRDM-E outperforms the conventional BD-THP (Tomlinson Harashima precoding) by 5.5 and 7.4dB, respectively, at a target BER of 10^{-4}.
0912.1767
An evaluation of Flickrs distributed classification system, from the perspective of its members, and as an image retrieval tool in comparison with a controlled vocabulary
cs.DL cs.IT math.IT
The profusion of online digital images presents new challenges for image indexing. Images have always been problematic to describe and catalogue due to lack of inherent textual data and ambiguity of meaning. An alternative to time-consuming professionally-applied metadata has been sought in the form of tags, simple keywords that form a flat structure known as distributed classification, or more popularly as a folksonomy. This research aims to increase understanding of why people tag and how effective they find it for searching, using as the focus. Open-ended questionnaires were sent out to members of the photo-sharing website Flickr, with the opportunity to post comments to an online discussion space. There is also a systematic comparison between a tag-based system and a more traditional controlled vocabulary, to test out the claims made regarding the suitability of tagging for searching and browsing. For this purpose Flickr has been compared with Getty Images using a series of test themes. The small number of people who replied to the questionnaire gave detailed answers that confirmed several assertions made about tags: they are accepted despite their flaws (sloppiness and potential for inaccuracy) because they serve their purpose to a satisfactory level. Some answers challenged the assumption that tagging is only done for personal benefit. The search comparison found that while Getty allows highly specific queries and logical semantic links, Flickr is more flexible and better placed to deal with subtle concepts. The overall conclusion is that tags achieve most when used in conjunction with groupings of people with a shared interest.
0912.1768
Frequency of Occurrence and Information Entropy of American Sign Language
cs.IT math.IT
American Sign Language (ASL) uses a series of hand based gestures as a replacement for words to allow the deaf to communicate. Previous work has shown that although it takes longer to make signs than to say the equivalent words, on average sentences can be completed in about the same time. This leaves unresolved, however, precisely why that should be the case. This paper reports a determination of the empirical entropy and redundancy in the set of handshapes of ASL. In this context, the entropy refers to the average information content in a unit of data. It is found that the handshapes, as fundamental units of ASL, are less redundant than phonemes, the equivalent fundamental units of spoken English, and that their entropy is much closer to the maximum possible information content. This explains why the slower signs can produce sentences in the same time as speaking; the low redundancy compensates for the slow rate of sign production. In addition to this precise quantification, this work is also novel in its approach towards quantifying an aspect of the ASL alphabet. Unlike spoken and written languages, frequency analysis of ASL is difficult due to the fact that every sign is composed of phonemes that are created through a combination of manual and a relatively large and imprecise set of bodily features. Focusing on handshapes as the ubiquitous and universal feature of all sign languages permits a precise quantitative analysis. As interest in visual electronic communication explodes within the deaf community, this work also paves the way for more precise automated sign recognition and synthesis.
0912.1790
A Note on the Injection Distance
cs.IT math.IT
Koetter and Kschischang showed in [R. Koetter and F.R. Kschischang, "Coding for Errors and Erasures in Random Network Coding," IEEE Trans. Inform. Theory, {54(8), 2008] that the network coding counterpart of Gabidulin codes performs asymptotically optimal with respect to the subspace distance. Recently, Silva and Kschischang introduced in [D. Silva and F.R. Kschischang, "On Metrics for Error Correction in Network Coding," To appear in IEEE Trans. Inform. Theory, ArXiv: 0805.3824v4[cs.IT], 2009] the injection distance to give a detailed picture of what happens in noncoherent network coding. We show that the above codes are also asymptotically optimal with respect to this distance.
0912.1815
Detection of Denial of Service Attacks against Domain Name System Using Neural Networks
cs.CR cs.NE
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against Domain Name System (DNS). Our system architecture consists of two most important parts: a statistical preprocessor and a neural network classifier. The preprocessor extracts required statistical features in a shorttime frame from traffic received by the target name server. We compared three different neural networks for detecting and classifying different types of DoS attacks. The proposed system is evaluated in a simulated network and showed that the best performed neural network is a feed-forward backpropagation with an accuracy of 99%.
0912.1820
Parsing of part-of-speech tagged Assamese Texts
cs.CL
A natural language (or ordinary language) is a language that is spoken, written, or signed by humans for general-purpose communication, as distinguished from formal languages (such as computer-programming languages or the "languages" used in the study of formal logic). The computational activities required for enabling a computer to carry out information processing using natural language is called natural language processing. We have taken Assamese language to check the grammars of the input sentence. Our aim is to produce a technique to check the grammatical structures of the sentences in Assamese text. We have made grammar rules by analyzing the structures of Assamese sentences. Our parsing program finds the grammatical errors, if any, in the Assamese sentence. If there is no error, the program will generate the parse tree for the Assamese sentence
0912.1822
Association Rule Pruning based on Interestingness Measures with Clustering
cs.LG
Association rule mining plays vital part in knowledge mining. The difficult task is discovering knowledge or useful rules from the large number of rules generated for reduced support. For pruning or grouping rules, several techniques are used such as rule structure cover methods, informative cover methods, rule clustering, etc. Another way of selecting association rules is based on interestingness measures such as support, confidence, correlation, and so on. In this paper, we study how rule clusters of the pattern Xi - Y are distributed over different interestingness measures.
0912.1826
Robust Video Watermarking using Multi-Band Wavelet Transform
cs.IT math.IT
This paper addresses copyright protection as a major security demand in digital marketplaces. Two watermarking techniques are proposed and compared for compressed and uncompressed video with the intention to show the advantages and the possible weaknesses in the schemes working in the frequency domain and in the spatial domain. In this paper a robust video watermarking method is presented. This method embeds data to the specific bands in the wavelet domain using motion estimation approach. The algorithm uses the HL and LH bands to add the watermark where the motion in these bands does not affect the quality of extracted watermark if the video is subjected to different types of malicious attacks. Watermark is embedded in an additive way using random Gaussian distribution in video sequences. The method is tested on different types of video (compressed DVD quality movie and uncompressed digital camera movie). The proposed watermarking method in frequency domain has strong robustness against some attacks such as frame dropping, frame filtering and lossy compression. The experimental results indicate that the similarity measure before and after certain attacks is very close to each other in frequency domain in comparison to the spatial domain.
0912.1828
Using social annotation and web log to enhance search engine
cs.IR cs.CY
Search services have been developed rapidly in social Internet. It can help web users easily to find their documents. So that, finding a best method search is always an imagine. This paper would like introduce hybrid method of LPageRank algorithm and Social Sim Rank algorithm. LPageRank is the method using link structure to rank priority of page. It doesn't care content of page and content of query. Therefore, we want to use benefit of social annotations to create the latent semantic association between queries and annotations. This model, we use algorithm SocialPageRank and LPageRank to enhance accuracy of search system. To experiment and evaluate the proposed of the new model, we have used this model for Music Machine Website with their web logs.
0912.1829
Document Searching System based on Natural Language Query Processing for Vietnam Open Courseware Library
cs.IR cs.CL
The necessary of buiding the searching system being able to support users expressing their searching by natural language queries is very important and opens the researching direction with many potential. It combines the traditional methods of information retrieval and the researching of Question Answering (QA). In this paper, we introduce a searching system built by us for searching courses on the Vietnam OpenCourseWare Program (VOCW). It can be considered as the first tool to be able to perform the user's Vietnamese questions. The experiment results are rather good when we evaluate this system on the precision
0912.1830
Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph
cs.CV cs.LG
This paper proposes a method of gesture recognition with a focus on important actions for distinguishing similar gestures. The method generates a partial action sequence by using optical flow images, expresses the sequence in the eigenspace, and checks the feature vector sequence by applying an optimum path-searching method of weighted graph to focus the important actions. Also presented are the results of an experiment on the recognition of similar sign language words.
0912.1883
The Bellman equation for power utility maximization with semimartingales
q-fin.PM cs.SY math.OC math.PR q-fin.CP
We study utility maximization for power utility random fields with and without intermediate consumption in a general semimartingale model with closed portfolio constraints. We show that any optimal strategy leads to a solution of the corresponding Bellman equation. The optimal strategies are described pointwise in terms of the opportunity process, which is characterized as the minimal solution of the Bellman equation. We also give verification theorems for this equation.
0912.1909
MIMO Precoding with X- and Y-Codes
cs.IT math.IT
We consider a time division duplex (TDD) $n_t \times n_r$ multiple-input multiple-output (MIMO) system with channel state information (CSI) at both the transmitter and receiver. We propose X- and Y-Codes to achieve high multiplexing and diversity gains at low complexity. The proposed precoding schemes are based upon the singular value decomposition (SVD) of the channel matrix which transforms the MIMO channel into parallel subchannels. Then X- and Y-Codes are used to improve the diversity gain by pairing the subchannels, prior to SVD precoding. In particular, the subchannels with good diversity are paired with those having low diversity gains. Hence, a pair of channels is jointly encoded using a $2 \times 2$ real matrix, which is fixed {\em a priori} and does not change with each channel realization. For X-Codes these matrices are 2-dimensional rotation matrices parameterized by a single angle, while for Y-Codes, these matrices are 2-dimensional upper left triangular matrices. The complexity of the maximum likelihood decoding (MLD) for both X- and Y-Codes is low. Specifically, the decoding complexity of Y-Codes is the same as that of a scalar channel. Moreover, we propose X-, Y-Precoders with the same structure as X-, Y-Codes, but the encoding matrices adapt to each channel realization. The optimal encoding matrices for X-, Y-Codes/Precoders are derived analytically. Finally, it is observed that X-Codes/Precoders perform better for well-conditioned channels, while Y-Codes/Precoders perform better for ill-conditioned channels, when compared to other precoding schemes in the literature.
0912.1987
Training and Feedback Optimization for Multiuser MIMO Downlink
cs.IT math.IT
We consider a MIMO fading broadcast channel where the fading channel coefficients are constant over time-frequency blocks that span a coherent time $\times$ a coherence bandwidth. In closed-loop systems, channel state information at transmitter (CSIT) is acquired by the downlink training sent by the base station and an explicit feedback from each user terminal. In open-loop systems, CSIT is obtained by exploiting uplink training and channel reciprocity. We use a tight closed-form lower bound on the ergodic achievable rate in the presence of CSIT errors in order to optimize the overall system throughput, by taking explicitly into account the overhead due to channel estimation and channel state feedback. Based on three time-frequency block models inspired by actual systems, we provide some useful guidelines for the overall system optimization. In particular, digital (quantized) feedback is found to offer a substantial advantage over analog (unquantized) feedback.
0912.2134
Enterprise Multi-Branch Database Synchronization with MSMQ
cs.DB cs.NI
When we talk about databases there have always been problems concerning data synchronization. The latter is a technique for maintaining consistency among different copies of data (often called replicas). In general, there is no universal solution to this problem and often a particular situation requires a particular approach driven by specific conditions. This paper presents an approach tackling the issue of data synchronization in a distributed multi-branch enterprise database. The proposed solution is based on MSMQ (Microsoft Message Queue), a mechanism for asynchronous messaging.
0912.2282
Design of Intelligent layer for flexible querying in databases
cs.DB cs.AI
Computer-based information technologies have been extensively used to help many organizations, private companies, and academic and education institutions manage their processes and information systems hereby become their nervous centre. The explosion of massive data sets created by businesses, science and governments necessitates intelligent and more powerful computing paradigms so that users can benefit from this data. Therefore most new-generation database applications demand intelligent information management to enhance efficient interactions between database and the users. Database systems support only a Boolean query model. A selection query on SQL database returns all those tuples that satisfy the conditions in the query.
0912.2302
Synthesis of supervised classification algorithm using intelligent and statistical tools
cs.CV cs.LG
A fundamental task in detecting foreground objects in both static and dynamic scenes is to take the best choice of color system representation and the efficient technique for background modeling. We propose in this paper a non-parametric algorithm dedicated to segment and to detect objects in color images issued from a football sports meeting. Indeed segmentation by pixel concern many applications and revealed how the method is robust to detect objects, even in presence of strong shadows and highlights. In the other hand to refine their playing strategy such as in football, handball, volley ball, Rugby..., the coach need to have a maximum of technical-tactics information about the on-going of the game and the players. We propose in this paper a range of algorithms allowing the resolution of many problems appearing in the automated process of team identification, where each player is affected to his corresponding team relying on visual data. The developed system was tested on a match of the Tunisian national competition. This work is prominent for many next computer vision studies as it's detailed in this study.
0912.2307
Rank Based Clustering For Document Retrieval From Biomedical Databases
cs.IR cs.DB
Now a day's, search engines are been most widely used for extracting information's from various resources throughout the world. Where, majority of searches lies in the field of biomedical for retrieving related documents from various biomedical databases. Currently search engines lacks in document clustering and representing relativeness level of documents extracted from the databases. In order to overcome these pitfalls a text based search engine have been developed for retrieving documents from Medline and PubMed biomedical databases. The search engine has incorporated page ranking bases clustering concept which automatically represents relativeness on clustering bases. Apart from this graph tree construction is made for representing the level of relatedness of the documents that are networked together. This advance functionality incorporation for biomedical document based search engine found to provide better results in reviewing related documents based on relativeness.
0912.2310
NeuralNetwork Based 3D Surface Reconstruction
cs.NE
This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach
0912.2311
VirusPKT: A Search Tool For Assimilating Assorted Acquaintance For Viruses
cs.IR q-bio.OT
Viruses utilize various means to circumvent the immune detection in the biological systems. Several mathematical models have been investigated for the description of viral dynamics in the biological system of human and various other species. One common strategy for evasion and recognition of viruses is, through acquaintance in the systems by means of search engines. In this perspective a search tool have been developed to provide a wider comprehension about the structure and other details on viruses which have been narrated in this paper. This provides an adequate knowledge in evolution and building of viruses, its functions through information extraction from various websites. Apart from this, tool aim to automate the activities associated with it in a self-maintainable, self-sustainable, proactive one which has been evaluated through analysis made and have been discussed in this paper.
0912.2314
Early Detection of Breast Cancer using SVM Classifier Technique
cs.LG
This paper presents a tumor detection algorithm from mammogram. The proposed system focuses on the solution of two problems. One is how to detect tumors as suspicious regions with a very weak contrast to their background and another is how to extract features which categorize tumors. The tumor detection method follows the scheme of (a) mammogram enhancement. (b) The segmentation of the tumor area. (c) The extraction of features from the segmented tumor area. (d) The use of SVM classifier. The enhancement can be defined as conversion of the image quality to a better and more understandable level. The mammogram enhancement procedure includes filtering, top hat operation, DWT. Then the contrast stretching is used to increase the contrast of the image. The segmentation of mammogram images has been playing an important role to improve the detection and diagnosis of breast cancer. The most common segmentation method used is thresholding. The features are extracted from the segmented breast area. Next stage include, which classifies the regions using the SVM classifier. The method was tested on 75 mammographic images, from the mini-MIAS database. The methodology achieved a sensitivity of 88.75%.
0912.2316
Heart Rate Variability Analysis Using Threshold of Wavelet Package Coefficients
cs.CV physics.data-an physics.med-ph
In this paper, a new efficient feature extraction method based on the adaptive threshold of wavelet package coefficients is presented. This paper especially deals with the assessment of autonomic nervous system using the background variation of the signal Heart Rate Variability HRV extracted from the wavelet package coefficients. The application of a wavelet package transform allows us to obtain a time-frequency representation of the signal, which provides better insight in the frequency distribution of the signal with time. A 6 level decomposition of HRV was achieved with db4 as mother wavelet, and the above two bands LF and HF were combined in 12 specialized frequencies sub-bands obtained in wavelet package transform. Features extracted from these coefficients can efficiently represent the characteristics of the original signal. ANOVA statistical test is used for the evaluation of proposed algorithm.
0912.2378
Limited Feedback for Temporally Correlated MIMO Channels with Other Cell Interference
cs.IT math.IT
Limited feedback improves link reliability with a small amount of feedback from the receiver back to the transmitter. In cellular systems, the performance of limited feedback will be degraded in the presence of other cell interference, when the base stations have limited or no coordination. This paper establishes the degradation in sum rate of users in a cellular system, due to uncoordinated other cell interference and delay on the feedback channel. A goodput metric is defined as the rate when the bits are successfully received at the mobile station, and used to derive an upper bound on the performance of limited feedback systems with delay. This paper shows that the goodput gained from having delayed limited feedback decreases doubly exponentially as the delay increases. The analysis is extended to precoded spatial multiplexing systems where it is shown that the same upper bound can be used to evaluate the decay in the achievable sum rate. To reduce the effects of interference, zero forcing interference cancellation is applied at the receiver, where it is shown that the effect of the interference on the achievable sum rate can be suppressed by nulling out the interferer. Numerical results show that the decay rate of the goodput decreases when the codebook quantization size increases and when the doppler shift in the channel decreases.
0912.2381
LAGOVirtual: A Collaborative Environment for the Large Aperture GRB Observatory
cs.CE astro-ph.HE astro-ph.IM hep-ex
We present the LAGOVirtual Project: an ongoing project to develop platform to collaborate in the Large Aperture GRB Observatory (LAGO). This continental-wide observatory is devised to detect high energy (around 100 GeV) component of Gamma Ray Bursts, by using the single particle technique in arrays of Water Cherenkov Detectors (WCD) at high mountain sites (Chacaltaya, Bolivia, 5300 m a.s.l., Pico Espejo, Venezuela, 4750 m a.s.l., Sierra Negra, Mexico, 4650 m a.s.l). This platform will allow LAGO collaboration to share data, and computer resources through its different sites. This environment has the possibility to generate synthetic data by simulating the showers through AIRES application and to store/preserve distributed data files collected by the WCD at the LAGO sites. The present article concerns the implementation of a prototype of LAGO-DR adapting DSpace, with a hierarchical structure (i.e. country, institution, followed by collections that contain the metadata and data files), for the captured/simulated data. This structure was generated by using the community, sub-community, collection, item model; available at the DSpace software. Each member institution-country of the project has the appropriate permissions on the system to publish information (descriptive metadata and associated data files). The platform can also associate multiple files to each item of data (data from the instruments, graphics, postprocessed-data, etc.).
0912.2385
Closing the Learning-Planning Loop with Predictive State Representations
cs.LG cs.AI
A central problem in artificial intelligence is that of planning to maximize future reward under uncertainty in a partially observable environment. In this paper we propose and demonstrate a novel algorithm which accurately learns a model of such an environment directly from sequences of action-observation pairs. We then close the loop from observations to actions by planning in the learned model and recovering a policy which is near-optimal in the original environment. Specifically, we present an efficient and statistically consistent spectral algorithm for learning the parameters of a Predictive State Representation (PSR). We demonstrate the algorithm by learning a model of a simulated high-dimensional, vision-based mobile robot planning task, and then perform approximate point-based planning in the learned PSR. Analysis of our results shows that the algorithm learns a state space which efficiently captures the essential features of the environment. This representation allows accurate prediction with a small number of parameters, and enables successful and efficient planning.
0912.2404
Succinct Coverage Oracles
cs.DS cs.DB
In this paper, we identify a fundamental algorithmic problem that we term succinct dynamic covering (SDC), arising in many modern-day web applications, including ad-serving and online recommendation systems in eBay and Netflix. Roughly speaking, SDC applies two restrictions to the well-studied Max-Coverage problem: Given an integer k, X={1,2,...,n} and I={S_1, ..., S_m}, S_i a subset of X, find a subset J of I, such that |J| <= k and the union of S in J is as large as possible. The two restrictions applied by SDC are: (1) Dynamic: At query-time, we are given a query Q, a subset of X, and our goal is to find J such that the intersection of Q with the union of S in J is as large as possible; (2) Space-constrained: We don't have enough space to store (and process) the entire input; specifically, we have o(mn), and maybe as little as O((m+n)polylog(mn)) space. The goal of SDC is to maintain a small data structure so as to answer most dynamic queries with high accuracy. We call such a scheme a Coverage Oracle. We present algorithms and complexity results for coverage oracles. We present deterministic and probabilistic near-tight upper and lower bounds on the approximation ratio of SDC as a function of the amount of space available to the oracle. Our lower bound results show that to obtain constant-factor approximations we need Omega(mn) space. Fortunately, our upper bounds present an explicit tradeoff between space and approximation ratio, allowing us to determine the amount of space needed to guarantee certain accuracy.
0912.2415
Adapting Heuristic Mastermind Strategies to Evolutionary Algorithms
cs.NE cs.AI
The art of solving the Mastermind puzzle was initiated by Donald Knuth and is already more than 30 years old; despite that, it still receives much attention in operational research and computer games journals, not to mention the nature-inspired stochastic algorithm literature. In this paper we try to suggest a strategy that will allow nature-inspired algorithms to obtain results as good as those based on exhaustive search strategies; in order to do that, we first review, compare and improve current approaches to solving the puzzle; then we test one of these strategies with an estimation of distribution algorithm. Finally, we try to find a strategy that falls short of being exhaustive, and is then amenable for inclusion in nature inspired algorithms (such as evolutionary or particle swarm algorithms). This paper proves that by the incorporation of local entropy into the fitness function of the evolutionary algorithm it becomes a better player than a random one, and gives a rule of thumb on how to incorporate the best heuristic strategies to evolutionary algorithms without incurring in an excessive computational cost.
0912.2425
Consensus and synchronization in discrete-time networks of multi-agents with stochastically switching topologies and time delays
math.DS cs.SY math.OC
We analyze stability of consensus algorithms in networks of multi-agents with time-varying topologies and delays. The topology and delays are modeled as induced by an adapted process and are rather general, including i.i.d.\ topology processes, asynchronous consensus algorithms, and Markovian jumping switching. In case the self-links are instantaneous, we prove that the network reaches consensus for all bounded delays if the graph corresponding to the conditional expectation of the coupling matrix sum across a finite time interval has a spanning tree almost surely. Moreover, when self-links are also delayed and when the delays satisfy certain integer patterns, we observe and prove that the algorithm may not reach consensus but instead synchronize at a periodic trajectory, whose period depends on the delay pattern. We also give a brief discussion on the dynamics in the absence of self-links.
0912.2492
Learning an Interactive Segmentation System
stat.ML cs.CV stat.ME
Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive systems have been treated in the same manner as their fully automatic counterparts. Their performance is evaluated by computing the accuracy of their solutions under some fixed set of user interactions. This paper proposes a new evaluation and learning method which brings the user in the loop. It is based on the use of an active robot user - a simulated model of a human user. We show how this approach can be used to evaluate and learn parameters of state-of-the-art interactive segmentation systems. We also show how simulated user models can be integrated into the popular max-margin method for parameter learning and propose an algorithm to solve the resulting optimisation problem.
0912.2548
Towards Utility-driven Anonymization of Transactions
cs.DB cs.CR
Publishing person-specific transactions in an anonymous form is increasingly required by organizations. Recent approaches ensure that potentially identifying information (e.g., a set of diagnosis codes) cannot be used to link published transactions to persons' identities, but all are limited in application because they incorporate coarse privacy requirements (e.g., protecting a certain set of m diagnosis codes requires protecting all m-sized sets), do not integrate utility requirements, and tend to explore a small portion of the solution space. In this paper, we propose a more general framework for anonymizing transactional data under specific privacy and utility requirements. We model such requirements as constraints, investigate how these constraints can be specified, and propose COAT (COnstraint-based Anonymization of Transactions), an algorithm that anonymizes transactions using a flexible hierarchy-free generalization scheme to meet the specified constraints. Experiments with benchmark datasets verify that COAT significantly outperforms the current state-of-the-art algorithm in terms of data utility, while being comparable in terms of efficiency. The effectiveness of our approach is also demonstrated in a real-world scenario, which requires disseminating a private, patient-specific transactional dataset in a way that preserves both privacy and utility in intended studies.
0912.2551
Efficient Parallel Statistical Model Checking of Biochemical Networks
cs.CE cs.DC cs.LO q-bio.QM
We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture.
0912.2563
A Model-Based Approach to Predicting Predator-Prey & Friend-Foe Relationships in Ant Colonies
cs.AI cs.CV q-bio.PE
Understanding predator-prey relationships among insects is a challenging task in the domain of insect-colony research. This is due to several factors involved, such as determining whether a particular behavior is the result of a predator-prey interaction, a friend-foe interaction or another kind of interaction. In this paper, we analyze a series of predator-prey and friend-foe interactions in two colonies of carpenter ants to better understand and predict such behavior. Using the data gathered, we have also come up with a preliminary model for predicting such behavior under the specific conditions the experiment was conducted in. In this paper, we present the results of our data analysis as well as an overview of the processes involved.
0912.2630
Transmission Capacity of Ad-hoc Networks with Multiple Antennas using Transmit Stream Adaptation and Interference Cancelation
cs.IT math.IT
The transmission capacity of an ad-hoc network is the maximum density of active transmitters per unit area, given an outage constraint at each receiver for a fixed rate of transmission. Assuming that the transmitter locations are distributed as a Poisson point process, this paper derives upper and lower bounds on the transmission capacity of an ad-hoc network when each node is equipped with multiple antennas. The transmitter either uses eigen multi-mode beamforming or a subset of its antennas to transmit multiple data streams, while the receiver uses partial zero forcing to cancel certain interferers using some of its spatial receive degrees of freedom (SRDOF). The receiver either cancels the nearest interferers or those interferers that maximize the post-cancelation signal-to-interference ratio. Using the obtained bounds, the optimal number of data streams to transmit, and the optimal SRDOF to use for interference cancelation are derived that provide the best scaling of the transmission capacity with the number of antennas. With beamforming, single data stream transmission together with using all but one SRDOF for interference cancelation is optimal, while without beamforming, single data stream transmission together with using a fraction of the total SRDOF for interference cancelation is optimal.
0912.2709
The Gaussian Surface Area and Noise Sensitivity of Degree-$d$ Polynomials
cs.CC cs.LG
We provide asymptotically sharp bounds for the Gaussian surface area and the Gaussian noise sensitivity of polynomial threshold functions. In particular we show that if $f$ is a degree-$d$ polynomial threshold function, then its Gaussian sensitivity at noise rate $\epsilon$ is less than some quantity asymptotic to $\frac{d\sqrt{2\epsilon}}{\pi}$ and the Gaussian surface area is at most $\frac{d}{\sqrt{2\pi}}$. Furthermore these bounds are asymptotically tight as $\epsilon\to 0$ and $f$ the threshold function of a product of $d$ distinct homogeneous linear functions.
0912.2737
An Extreme form of Superactivation for Quantum Zero-Error Capacities
quant-ph cs.IT math.IT
The zero-error capacity of a channel is the rate at which it can send information perfectly, with zero probability of error, and has long been studied in classical information theory. We show that the zero-error capacity of quantum channels exhibits an extreme form of non-additivity, one which is not possible for classical channels, or even for the usual capacities of quantum channels. By combining probabilistic arguments with algebraic geometry, we prove that there exist channels E1 and E2 with no zero-error classical capacity whatsoever, C_0(E1) = C_0(E2) = 0, but whose joint zero-error quantum capacity is positive, Q_0(E1 x E2) >= 1. This striking effect is an extreme from of the superactivation phenomenon, as it implies that both the classical and quantum zero-error capacities of these channels can be superactivated simultaneously, whilst being a strictly stronger property of capacities. Superactivation of the quantum zero-error capacity was not previously known.
0912.2820
Network Coding for Computing: Cut-Set Bounds
cs.IT math.IT
The following \textit{network computing} problem is considered. Source nodes in a directed acyclic network generate independent messages and a single receiver node computes a target function $f$ of the messages. The objective is to maximize the average number of times $f$ can be computed per network usage, i.e., the ``computing capacity''. The \textit{network coding} problem for a single-receiver network is a special case of the network computing problem in which all of the source messages must be reproduced at the receiver. For network coding with a single receiver, routing is known to achieve the capacity by achieving the network \textit{min-cut} upper bound. We extend the definition of min-cut to the network computing problem and show that the min-cut is still an upper bound on the maximum achievable rate and is tight for computing (using coding) any target function in multi-edge tree networks and for computing linear target functions in any network. We also study the bound's tightness for different classes of target functions. In particular, we give a lower bound on the computing capacity in terms of the Steiner tree packing number and a different bound for symmetric functions. We also show that for certain networks and target functions, the computing capacity can be less than an arbitrarily small fraction of the min-cut bound.
0912.2822
Data management in Systems biology II - Outlook towards the semantic web
cs.DB q-bio.OT
The benefit of using ontologies, defined by the respective data standards, is shown. It is presented how ontologies can be used for the semantic enrichment of data and how this can contribute to the vision of the semantic web to become true. The problems existing today on the way to a true semantic web are pinpointed, different semantic web standards, tools and development frameworks are overlooked and an outlook towards artificial intelligence and agents for searching and mining the data in the semantic web are given, paving the way from data management to information and in the end true knowledge management systems.
0912.2826
An iterative approach for generating statistically realistic populations of households
cs.MA cs.CY
Background: Many different simulation frameworks, in different topics, need to treat realistic datasets to initialize and calibrate the system. A precise reproduction of initial states is extremely important to obtain reliable forecast from the model. Methodology/Principal Findings: This paper proposes an algorithm to create an artificial population where individuals are described by their age, and are gathered in households respecting a variety of statistical constraints (distribution of household types, sizes, age of household head, difference of age between partners and among parents and children). Such a population is often the initial state of microsimulation or (agent) individual-based models. To get a realistic distribution of households is often very important, because this distribution has an impact on the demographic evolution. Usual techniques from microsimulation approach cross different sources of aggregated data for generating individuals. In our case the number of combinations of different households (types, sizes, age of participants) makes it computationally difficult to use directly such methods. Hence we developed a specific algorithm to make the problem more easily tractable. Conclusions/Significance: We generate the populations of two pilot municipalities in Auvergne region (France), to illustrate the approach. The generated populations show a good agreement with the available statistical datasets (not used for the generation) and are obtained in a reasonable computational time.
0912.2828
Pulse Shaping, Localization and the Approximate Eigenstructure of LTV Channels
cs.IT math.IT
In this article we show the relation between the theory of pulse shaping for WSSUS channels and the notion of approximate eigenstructure for time-varying channels. We consider pulse shaping for a general signaling scheme, called Weyl-Heisenberg signaling, which includes OFDM with cyclic prefix and OFDM/OQAM. The pulse design problem in the view of optimal WSSUS--averaged SINR is an interplay between localization and "orthogonality". The localization problem itself can be expressed in terms of eigenvalues of localization operators and is intimately connected to the concept of approximate eigenstructure of LTV channel operators. In fact, on the L_2-level both are equivalent as we will show. The concept of "orthogonality" in turn can be related to notion of tight frames. The right balance between these two sides is still an open problem. However, several statements on achievable values of certain localization measures and fundamental limits on SINR can already be made as will be shown in the paper.
0912.2843
Intrusion Detection In Mobile Ad Hoc Networks Using GA Based Feature Selection
cs.NE cs.CR cs.LG
Mobile ad hoc networking (MANET) has become an exciting and important technology in recent years because of the rapid proliferation of wireless devices. MANETs are highly vulnerable to attacks due to the open medium, dynamically changing network topology and lack of centralized monitoring point. It is important to search new architecture and mechanisms to protect the wireless networks and mobile computing application. IDS analyze the network activities by means of audit data and use patterns of well-known attacks or normal profile to detect potential attacks. There are two methods to analyze: misuse detection and anomaly detection. Misuse detection is not effective against unknown attacks and therefore, anomaly detection method is used. In this approach, the audit data is collected from each mobile node after simulating the attack and compared with the normal behavior of the system. If there is any deviation from normal behavior then the event is considered as an attack. Some of the features of collected audit data may be redundant or contribute little to the detection process. So it is essential to select the important features to increase the detection rate. This paper focuses on implementing two feature selection methods namely, markov blanket discovery and genetic algorithm. In genetic algorithm, bayesian network is constructed over the collected features and fitness function is calculated. Based on the fitness value the features are selected. Markov blanket discovery also uses bayesian network and the features are selected depending on the minimum description length. During the evaluation phase, the performances of both approaches are compared based on detection rate and false alarm rate.
0912.2846
Multi-valued Action Languages in CLP(FD)
cs.AI cs.LO cs.PL
Action description languages, such as A and B, are expressive instruments introduced for formalizing planning domains and planning problem instances. The paper starts by proposing a methodology to encode an action language (with conditional effects and static causal laws), a slight variation of B, using Constraint Logic Programming over Finite Domains. The approach is then generalized to raise the use of constraints to the level of the action language itself. A prototype implementation has been developed, and the preliminary results are presented and discussed. To appear in Theory and Practice of Logic Programming (TPLP)
0912.2881
Representing human and machine dictionaries in Markup languages
cs.CL
In this chapter we present the main issues in representing machine readable dictionaries in XML, and in particular according to the Text Encoding Dictionary (TEI) guidelines.
0912.3029
Interference Alignment and a Noisy Interference Regime for Many-to-One Interference Channels
cs.IT math.IT
We study the capacity of discrete memoryless many-to-one interference channels, i.e., K user interference channels where only one receiver faces interference. For a class of many-to-one interference channels, we identify a noisy interference regime, i.e., a regime where random coding and treating interference as noise achieves sum-capacity. Specializing our results to the Gaussian MIMO many-to-one interference channel, which is a special case of the class of channels considered, we obtain new capacity results. Firstly, we extend the noisy interference regime, previously studied for (many-to-one) interference channels with average power constraints on the inputs, to a more general class of inputs. This more general class includes the practical scenario of inputs being restricted to fixed finite-size constellations such as PSK or QAM. Secondly, we extend noisy interference results previously studied in SISO interference channels with full channel state information (CSI) at all nodes, to MIMO and parallel Gaussian many-to-one interference channels, and to fading Gaussian many-to-one interference channels without CSI at the transmitters. While the many-to-one interference channel requires interference alignment, which in turn requires structured codes in general, we argue that in the noisy interference regime, interference is implicitly aligned by random coding irrespective of the input distribution. As a byproduct of our study, we identify a second class of many-to-one interference channels (albeit deterministic) where random coding is optimal (though interference is not treated as noise). The optimality of random coding in this second class of channels is due to an interference resolvability condition which precludes interference alignment and hence obviates the need of structured codes.
0912.3036
Proceedings 8th International Workshop on Parallel and Distributed Methods in verifiCation
cs.LO cs.CE cs.DC cs.SE
The 8th International Workshop on Parallel and Distributed Methods in verifiCation (PDMC 2009) took place on November 4, 2009 at the Eindhoven University of Technology, in conjunction with Formal Methods 2009 and other related events for the first time under the heading of Formal Methods Week. This volume contains the final workshop proceedings.
0912.3067
A Recursive Formula for Power Moments of 2-Dimensional Kloosterman Sums Assiciated with General Linear Groups
math.NT cs.IT math.IT
In this paper, we construct a binary linear code connected with the Kloosterman sum for $GL(2,q)$. Here $q$ is a power of two. Then we obtain a recursive formula generating the power moments 2-dimensional Kloosterman sum, equivalently that generating the even power moments of Kloosterman sum in terms of the frequencies of weights in the code. This is done via Pless power moment identity and by utilizing the explicit expression of the Kloosterman sum for $GL(2,q)$.
0912.3134
Complexity of Propositional Abduction for Restricted Sets of Boolean Functions
cs.CC cs.AI cs.LO
Abduction is a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining how the world behaves it aims at finding an explanation for some observed manifestation. In this paper we focus on propositional abduction, where the knowledge base and the manifestation are represented by propositional formulae. The problem of deciding whether there exists an explanation has been shown to be SigmaP2-complete in general. We consider variants obtained by restricting the allowed connectives in the formulae to certain sets of Boolean functions. We give a complete classification of the complexity for all considerable sets of Boolean functions. In this way, we identify easier cases, namely NP-complete and polynomial cases; and we highlight sources of intractability. Further, we address the problem of counting the explanations and draw a complete picture for the counting complexity.
0912.3228
On Backtracking in Real-time Heuristic Search
cs.AI
Real-time heuristic search algorithms are suitable for situated agents that need to make their decisions in constant time. Since the original work by Korf nearly two decades ago, numerous extensions have been suggested. One of the most intriguing extensions is the idea of backtracking wherein the agent decides to return to a previously visited state as opposed to moving forward greedily. This idea has been empirically shown to have a significant impact on various performance measures. The studies have been carried out in particular empirical testbeds with specific real-time search algorithms that use backtracking. Consequently, the extent to which the trends observed are characteristic of backtracking in general is unclear. In this paper, we present the first entirely theoretical study of backtracking in real-time heuristic search. In particular, we present upper bounds on the solution cost exponential and linear in a parameter regulating the amount of backtracking. The results hold for a wide class of real-time heuristic search algorithms that includes many existing algorithms as a small subclass.
0912.3245
Structured Error Recovery for Codeword-Stabilized Quantum Codes
quant-ph cs.IT math.IT
Codeword stabilized (CWS) codes are, in general, non-additive quantum codes that can correct errors by an exhaustive search of different error patterns, similar to the way that we decode classical non-linear codes. For an n-qubit quantum code correcting errors on up to t qubits, this brute-force approach consecutively tests different errors of weight t or less, and employs a separate n-qubit measurement in each test. In this paper, we suggest an error grouping technique that allows to simultaneously test large groups of errors in a single measurement. This structured error recovery technique exponentially reduces the number of measurements by about 3^t times. While it still leaves exponentially many measurements for a generic CWS code, the technique is equivalent to syndrome-based recovery for the special case of additive CWS codes.
0912.3264
Random Access: An Information-Theoretic Perspective
cs.IT math.IT
This paper considers a random access system where each sender can be in two modes of operation, active or not active, and where the set of active users is available to a common receiver only. Active transmitters encode data into independent streams of information, a subset of which are decoded by the receiver, depending on the value of the collective interference. The main contribution is to present an information-theoretic formulation of the problem which allows us to characterize, with a guaranteed gap to optimality, the rates that can be achieved by different data streams. Our results are articulated as follows. First, we exactly characterize the capacity region of a two-user system assuming a binary-expansion deterministic channel model. Second, we extend this result to a two-user additive white Gaussian noise channel, providing an approximate characterization within $\sqrt{3}/2$ bit of the actual capacity. Third, we focus on the symmetric scenario in which users are active with the same probability and subject to the same received power constraint, and study the maximum achievable expected sum-rate, or throughput, for any number of users. In this case, for the symmetric binary expansion deterministic channel (which is related to the packet collision model used in the networking literature), we show that a simple coding scheme which does not employ superposition coding achieves the system throughput. This result also shows that the performance of slotted ALOHA systems can be improved by allowing encoding rate adaptation at the transmitters. For the symmetric additive white Gaussian noise channel, we propose a scheme that is within one bit of the system throughput for any value of the underlying parameters.
0912.3275
A Formal Framework for Mobile Robot Patrolling in Arbitrary Environments with Adversaries
cs.GT cs.MA
Using mobile robots for autonomous patrolling of environments to prevent intrusions is a topic of increasing practical relevance. One of the most challenging scientific issues is the problem of finding effective patrolling strategies that, at each time point, determine the next moves of the patrollers in order to maximize some objective function. In the very last years this problem has been addressed in a game theoretical fashion, explicitly considering the presence of an adversarial intruder. The general idea is that of modeling a patrolling situation as a game, played by the patrollers and the intruder, and of studying the equilibria of this game to derive effective patrolling strategies. In this paper we present a game theoretical formal framework for the determination of effective patrolling strategies that extends the previous proposals appeared in the literature, by considering environments with arbitrary topology and arbitrary preferences for the agents. The main original contributions of this paper are the formulation of the patrolling game for generic graph environments, an algorithm for finding a deterministic equilibrium strategy, which is a fixed path through the vertices of the graph, and an algorithm for finding a non-deterministic equilibrium strategy, which is a set of probabilities for moving between adjacent vertices of the graph. Both the algorithms are analytically studied and experimentally validated, to assess their properties and efficiency.
0912.3309
New Generalization Bounds for Learning Kernels
cs.AI
This paper presents several novel generalization bounds for the problem of learning kernels based on the analysis of the Rademacher complexity of the corresponding hypothesis sets. Our bound for learning kernels with a convex combination of p base kernels has only a log(p) dependency on the number of kernels, p, which is considerably more favorable than the previous best bound given for the same problem. We also give a novel bound for learning with a linear combination of p base kernels with an L_2 regularization whose dependency on p is only in p^{1/4}.
0912.3323
Minimizing Sum-MSE Implies Identical Downlink and Dual Uplink Power Allocations
cs.IT math.IT
In the multiuser downlink, power allocation for linear precoders that minimize the sum of mean squared errors under a sum power constraint is a non-convex problem. Many existing algorithms solve an equivalent convex problem in the virtual uplink and apply a transformation based on uplink-downlink duality to find a downlink solution. In this letter, we analyze the optimality criteria for the power allocation subproblem in the virtual uplink, and demonstrate that the optimal solution leads to identical power allocations in the downlink and virtual uplink. We thus extend the known duality results and, importantly, simplify the existing algorithms used for iterative transceiver design.
0912.3419
Application Driven Joint Uplink-Downlink Optimization in Wireless Communications
cs.IT math.IT
This paper introduces a new mathematical framework, which is used to derive joint uplink/downlink achievable rate regions for multi-user spatial multiplexing between one base station and multiple terminals. The framework consists of two models: the first one is a simple transmission model for uplink and downlink, which is capable to give a lower bound on the capacity for the case that the transmission is subject to imperfect CSI. A detailed model for concrete channel estimation and feedback schemes provides parameter input to the former model and covers the most important aspects such as pilot design optimization, linear channel estimation, feedback delay, and feedback quantization. We apply this framework to determine optimal pilot densities and CSI feedback quantity, given that a weighted sum of uplink and downlink throughput is to be maximized for a certain user velocity. We show that for low speed, and if downlink throughput is of particular importance, a significant portion of the uplink should be invested into CSI feedback. At higher velocity, however, downlink performance becomes mainly affected by CSI feedback delay, and hence CSI feedback brings little gain considering the inherent sacrifice of uplink capacity. We further show that for high velocities, it becomes beneficial to use no CSI feedback at all, but apply random beamforming in the downlink and operate in time-division duplex.
0912.3441
On Space-Time Capacity Limits in Mobile and Delay Tolerant Networks
cs.NI cs.IT math.IT
We investigate the fundamental capacity limits of space-time journeys of information in mobile and Delay Tolerant Networks (DTNs), where information is either transmitted or carried by mobile nodes, using store-carry-forward routing. We define the capacity of a journey (i.e., a path in space and time, from a source to a destination) as the maximum amount of data that can be transferred from the source to the destination in the given journey. Combining a stochastic model (conveying all possible journeys) and an analysis of the durations of the nodes' encounters, we study the properties of journeys that maximize the space-time information propagation capacity, in bit-meters per second. More specifically, we provide theoretical lower and upper bounds on the information propagation speed, as a function of the journey capacity. In the particular case of random way-point-like models (i.e., when nodes move for a distance of the order of the network domain size before changing direction), we show that, for relatively large journey capacities, the information propagation speed is of the same order as the mobile node speed. This implies that, surprisingly, in sparse but large-scale mobile DTNs, the space-time information propagation capacity in bit-meters per second remains proportional to the mobile node speed and to the size of the transported data bundles, when the bundles are relatively large. We also verify that all our analytical bounds are accurate in several simulation scenarios.
0912.3461
Application of Graph Coloring to Biological Networks
cs.CE q-bio.QM
We explore the application of graph coloring to biological networks, specifically protein-protein interaction (PPI) networks. First, we find that given similar conditions (i.e. number of nodes, number of links, degree distribution and clustering), fewer colors are needed to color disassortative (high degree nodes tend to connect to low degree nodes and vice versa) than assortative networks. Fewer colors create fewer independent sets which in turn imply higher concurrency potential for a network. Since PPI networks tend to be disassortative, we suggest that in addition to functional specificity and stability proposed previously by Maslov and Sneppen (Science 296, 2002), the disassortative nature of PPI networks may promote the ability of cells to perform multiple, crucial and functionally diverse tasks concurrently. Second, since graph coloring is closely related to the presence of cliques in a graph, the significance of node coloring information to the problem of identifying protein complexes, i.e. dense subgraphs in a PPI network, is investigated. We find that for PPI networks where 1% to 11% of nodes participate in at least one identified protein complex, such as H. sapien (DIP20070219, DIP20081014 and HPRD070609), DSATUR (a well-known complete graph coloring algorithm) node coloring information can improve the quality (homogeneity and separation) of initial candidate complexes. This finding may help to improve existing protein complex detection methods, and/or suggest new methods.
0912.3503
Absolutely Secure Communications by Johnson-like Noise and Kirchhoff's Laws
physics.gen-ph cond-mat.stat-mech cs.IT math.IT quant-ph
We survey the most important results and some recent developments about the secure key exchange protocol where the security is based on the Second Law of Thermodynamics and the robustness of classical physical information. We conclude that a classical physical system offers a higher level of control and security during the communication. We also mention some recent attempts inspired by this communicator to create other systems where Alice and Bob do not form an organic single system and/or the Second Law is irrelevant. It seems philosophically that they cannot be unconditionally secure, however it is yet an open question how to crack them; how can they be best used for conditionally secure communications, and what are the practical implications.
0912.3541
Spectrum Sharing as Network Congestion Games
cs.IT cs.GT math.IT math.OC
This paper has been withdrawn by the first author due to incomplete bibliography and incorporation of multiple formats in the same file.
0912.3589
Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation
cs.CV
Finding the three-dimensional representation of all or a part of a scene from a single two dimensional image is a challenging task. In this paper we propose a method for identifying the pose and location of objects with circular protrusions in three dimensions from a single image and a 3d representation or model of the object of interest. To do this, we present a method for identifying ellipses and their properties quickly and reliably with a novel technique that exploits intensity differences between objects and a geometric technique for matching an ellipse in 2d to a circle in 3d. We apply these techniques to the specific problem of determining the pose and location of vehicles, particularly cars, from a single image. We have achieved excellent pose recovery performance on artificially generated car images and show promising results on real vehicle images. We also make use of the ellipse detection method to identify car wheels from images, with a very high successful match rate.
0912.3599
Robust Principal Component Analysis?
cs.IT math.IT
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component individually? We prove that under some suitable assumptions, it is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the L1 norm. This suggests the possibility of a principled approach to robust principal component analysis since our methodology and results assert that one can recover the principal components of a data matrix even though a positive fraction of its entries are arbitrarily corrupted. This extends to the situation where a fraction of the entries are missing as well. We discuss an algorithm for solving this optimization problem, and present applications in the area of video surveillance, where our methodology allows for the detection of objects in a cluttered background, and in the area of face recognition, where it offers a principled way of removing shadows and specularities in images of faces.
0912.3747
A Survey of Paraphrasing and Textual Entailment Methods
cs.CL cs.AI
Paraphrasing methods recognize, generate, or extract phrases, sentences, or longer natural language expressions that convey almost the same information. Textual entailment methods, on the other hand, recognize, generate, or extract pairs of natural language expressions, such that a human who reads (and trusts) the first element of a pair would most likely infer that the other element is also true. Paraphrasing can be seen as bidirectional textual entailment and methods from the two areas are often similar. Both kinds of methods are useful, at least in principle, in a wide range of natural language processing applications, including question answering, summarization, text generation, and machine translation. We summarize key ideas from the two areas by considering in turn recognition, generation, and extraction methods, also pointing to prominent articles and resources.
0912.3848
Wavelets on Graphs via Spectral Graph Theory
math.FA cs.IT math.IT
We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite weighted graph. Our approach is based on defining scaling using the the graph analogue of the Fourier domain, namely the spectral decomposition of the discrete graph Laplacian $\L$. Given a wavelet generating kernel $g$ and a scale parameter $t$, we define the scaled wavelet operator $T_g^t = g(t\L)$. The spectral graph wavelets are then formed by localizing this operator by applying it to an indicator function. Subject to an admissibility condition on $g$, this procedure defines an invertible transform. We explore the localization properties of the wavelets in the limit of fine scales. Additionally, we present a fast Chebyshev polynomial approximation algorithm for computing the transform that avoids the need for diagonalizing $\L$. We highlight potential applications of the transform through examples of wavelets on graphs corresponding to a variety of different problem domains.
0912.3882
Science overlay maps: a new tool for research policy and library management
cs.DL cs.IR physics.soc-ph
We present a novel approach to visually locate bodies of research within the sciences, both at each moment of time and dynamically. This article describes how this approach fits with other efforts to locally and globally map scientific outputs. We then show how these science overlay maps help benchmark, explore collaborations, and track temporal changes, using examples of universities, corporations, funding agencies, and research topics. We address conditions of application, with their advantages, downsides and limitations. Overlay maps especially help investigate the increasing number of scientific developments and organisations that do not fit within traditional disciplinary categories. We make these tools accessible to help researchers explore the ongoing socio-cognitive transformation of science and technology systems.
0912.3907
Efficient Linear Programming Decoding of HDPC Codes
cs.IT math.IT
We propose several improvements for Linear Programming (LP) decoding algorithms for High Density Parity Check (HDPC) codes. First, we use the automorphism groups of a code to create parity check matrix diversity and to generate valid cuts from redundant parity checks. Second, we propose an efficient mixed integer decoder utilizing the branch and bound method. We further enhance the proposed decoders by removing inactive constraints and by adapting the parity check matrix prior to decoding according to the channel observations. Based on simulation results the proposed decoders achieve near-ML performance with reasonable complexity.
0912.3917
Speech Recognition Oriented Vowel Classification Using Temporal Radial Basis Functions
cs.CL cs.MM
The recent resurgence of interest in spatio-temporal neural network as speech recognition tool motivates the present investigation. In this paper an approach was developed based on temporal radial basis function "TRBF" looking to many advantages: few parameters, speed convergence and time invariance. This application aims to identify vowels taken from natural speech samples from the Timit corpus of American speech. We report a recognition accuracy of 98.06 percent in training and 90.13 in test on a subset of 6 vowel phonemes, with the possibility to expend the vowel sets in future.
0912.3924
A Study on Feature Selection Techniques in Educational Data Mining
cs.DB
Educational data mining (EDM) is a new growing research area and the essence of data mining concepts are used in the educational field for the purpose of extracting useful information on the behaviors of students in the learning process. In this EDM, feature selection is to be made for the generation of subset of candidate variables. As the feature selection influences the predictive accuracy of any performance model, it is essential to study elaborately the effectiveness of student performance model in connection with feature selection techniques. In this connection, the present study is devoted not only to investigate the most relevant subset features with minimum cardinality for achieving high predictive performance by adopting various filtered feature selection techniques in data mining but also to evaluate the goodness of subsets with different cardinalities and the quality of six filtered feature selection algorithms in terms of F-measure value and Receiver Operating Characteristics (ROC) value, generated by the NaiveBayes algorithm as base-line classifier method. The comparative study carried out by us on six filter feature section algorithms reveals the best method, as well as optimal dimensionality of the feature subset. Benchmarking of filter feature selection method is subsequently carried out by deploying different classifier models. The result of the present study effectively supports the well known fact of increase in the predictive accuracy with the existence of minimum number of features. The expected outcomes show a reduction in computational time and constructional cost in both training and classification phases of the student performance model.
0912.3956
Modeling and Application of Series Elastic Actuators for Force Control Multi Legged Robots
cs.RO
Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic Actuators employ a novel mechanical design architecture which goes against the common machine design principal of "stiffer is better". A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke's Law (F=Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions. We describe several variations of Series Elastic Actuators that have been developed using both electric and hydraulic components.
0912.3957
Realization of Semantic Atom Blog
cs.IR
Web blog is used as a collaborative platform to publish and share information. The information accumulated in the blog intrinsically contains the knowledge. The knowledge shared by the community of people has intangible value proposition. The blog is viewed as a multimedia information resource available on the Internet. In a blog, information in the form of text, image, audio and video builds up exponentially. The multimedia information contained in an Atom blog does not have the capability, which is required by the software processes so that Atom blog content can be accessed, processed and reused over the Internet. This shortcoming is addressed by exploring OWL knowledge modeling, semantic annotation and semantic categorization techniques in an Atom blog sphere. By adopting these techniques, futuristic Atom blogs can be created and deployed over the Internet.
0912.3960
Optimal Design of Fuzzy Based Power System Stabilizer Self Tuned by Robust Search Algorithm
cs.NE
In the interconnected power system network, instability problems are caused mainly by the low frequency oscillations of 0.2 to 2.5 Hz. The supplementary control signal in addition with AVR and high gain excitation systems are provided by means of Power System Stabilizer (PSS). Conventional power system stabilizers provide effective damping only on a particular operating point. But fuzzy based PSS provides good damping for a wide range of operating points. The bottlenecks faced in designing a fuzzy logic controller can be minimized by using appropriate optimization techniques like Genetic Algorithm, Particle Swam Optimization, Ant Colony Optimization etc.In this paper the membership functions of FLC are optimized by the new breed optimization technique called Genetic Algorithm. This design methodology is implemented on a Single Machine Infinite Bus (SMIB) system. Simulation results on SMIB show the effectiveness and robustness of the proposed PSS over a wide range of operating conditions and system configurations.
0912.3961
Enhancing Multi-Agent Based Simulation with Human-Agents Interactive Spatial Behaviour
cs.MA
We are exploring the enhancement of models of agent behaviour with more "human-like" decision making strategies than are presently available. Our motivation is to developed with a view to as the decision analysis and support for electric taxi company under the mission of energy saving and reduction of CO2, in particular car-pool and car-sharing management policies. In order to achieve the object of decision analysis for user, we provide a human-agents interactive spatial behaviour to support user making decision real time. We adopt passenger average waiting time and electric taxi average idle time as the performance measures and decision support fro electric taxi company. Finally, according to the analysis result, we demonstrate that our multi-agent simulation and GUI can help users or companies quickly make a quality and accurate decision to reduce the decision-making cost and time.
0912.3964
A Novel Channel Coding for Progressive Transmission of Medical Images
cs.IT math.IT
A novel channel coding scheme for progressive transmission of large images is proposed. The transmission time, low distortion reconstructed image and low complexity are most concerned in this paper. In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. The progressive transmission is based on the process that the input image is decomposed into many subblocks each to be coded, compressed, and transmitted individually. Therefore, firstly the image is segmented into a number of subblocks and then the discrete wavelet transform decomposes each subblock into different time-frequency components. Finally the components are coded for error control and transmitted. The complete system is coded in VHDL. In the proposed system, we choose a 3-level Haar wavelet transform to perform the wavelet transform for each subblock. It is simple, faster and easier to implement when compared with other transform method. The channel coding used here is Hamming code which is a simpler and efficient forward error control code.
0912.3973
A Novel Feature Extraction for Robust EMG Pattern Recognition
cs.CV
Varieties of noises are major problem in recognition of Electromyography (EMG) signal. Hence, methods to remove noise become most significant in EMG signal analysis. White Gaussian noise (WGN) is used to represent interference in this paper. Generally, WGN is difficult to be removed using typical filtering and solutions to remove WGN are limited. In addition, noise removal is an important step before performing feature extraction, which is used in EMG-based recognition. This research is aimed to present a novel feature that tolerate with WGN. As a result, noise removal algorithm is not needed. Two novel mean and median frequencies (MMNF and MMDF) are presented for robust feature extraction. Sixteen existing features and two novelties are evaluated in a noisy environment. WGN with various signal-to-noise ratios (SNRs), i.e. 20-0 dB, was added to the original EMG signal. The results showed that MMNF performed very well especially in weak EMG signal compared with others. The error of MMNF in weak EMG signal with very high noise, 0 dB SNR, is about 5-10 percent and closed by MMDF and Histogram, whereas the error of other features is more than 20 percent. While in strong EMG signal, the error of MMNF is better than those from other features. Moreover, the combination of MMNF, Histrogram of EMG and Willison amplitude is used as feature vector in classification task. The experimental result shows the better recognition result in noisy environment than other success feature candidates. From the above results demonstrate that MMNF can be used for new robust feature extraction.
0912.3978
Diversity-Multiplexing Tradeoff in Multi-Antenna Multi-Relay Networks: Improvements and Some Optimality Results
cs.IT math.IT
This paper investigates the benefits of Amplify-and-Forward (AF) relaying in the setup of multi-antenna wireless networks. The concept of Random Sequential (RS) relaying is previously introduced in the literature and showed that it achieves the maximum diversity gain in a general multi-antenna network. Here, we show that random unitary matrix multiplication at the relay nodes empowers the RS scheme to achieve a better Diversity-Multiplexing Tradeoff (DMT) as compared to the traditional AF relaying. First, we study the case of a multi-antenna full-duplex single-relay two-hop network, for which we show that the RS achieves the optimum DMT. Applying this result, we derive a new achievable DMT for the case of multi-antenna half-duplex parallel relay network. Interestingly, it turns out that the DMT of the RS scheme is optimum for the case of multi-antenna two parallel non-interfering half-duplex relays. Next, we show that random unitary matrix multiplication also improves the DMT of the Non-Orthogonal AF relaying scheme in the case of a multi-antenna single relay channel. Finally, we study the general case of multi-antenna full-duplex relay networks and derive a new lower-bound on its DMT using the RS scheme.
0912.3981
Multiplexing Gain of Amplify-Forward Relaying in Wireless Multi-Antenna Relay Networks
cs.IT math.IT
This paper studies the general multi-antenna multiple-relay network. Every two nodes of the network are either connected together through a Rayleigh fading channel or disconnected. We study the ergodic capacity of the network in the high SNR regime. We prove that the traditional amplify-forward relaying achieves the maximum multiplexing gain of the network. Furthermore, we show that the maximum multiplexing gain of the network is equal to the minimum vertex cut-set of the underlying graph of the network, which can be computed in polynomial time in terms of the number of network nodes. Finally, the argument is extended to the multicast and multi-access scenarios.
0912.3983
Performance Analysis of AIM-K-means & K-means in Quality Cluster Generation
cs.LG
Among all the partition based clustering algorithms K-means is the most popular and well known method. It generally shows impressive results even in considerably large data sets. The computational complexity of K-means does not suffer from the size of the data set. The main disadvantage faced in performing this clustering is that the selection of initial means. If the user does not have adequate knowledge about the data set, it may lead to erroneous results. The algorithm Automatic Initialization of Means (AIM), which is an extension to K-means, has been proposed to overcome the problem of initial mean generation. In this paper an attempt has been made to compare the performance of the algorithms through implementation
0912.3984
Multi-Agent Model using Secure Multi-Party Computing in e-Governance
cs.MA
Information management and retrieval of all the citizen occurs in almost all the public service functions. Electronic Government system is an emerging trend in India through which efforts are made to strive maximum safety and security. Various solutions for this have been proposed like Shibboleth, Public Key Infrastructure, Smart Cards and Light Weight Directory Access Protocols. Still, none of these guarantee 100 percent security. Efforts are being made to provide common national identity solution to various diverse Government identity cards. In this paper, we discuss issues related to these solutions.
0912.3995
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
cs.LG
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multi-armed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization. We analyze GP-UCB, an intuitive upper-confidence based algorithm, and bound its cumulative regret in terms of maximal information gain, establishing a novel connection between GP optimization and experimental design. Moreover, by bounding the latter in terms of operator spectra, we obtain explicit sublinear regret bounds for many commonly used covariance functions. In some important cases, our bounds have surprisingly weak dependence on the dimensionality. In our experiments on real sensor data, GP-UCB compares favorably with other heuristical GP optimization approaches.
0912.4012
Balancing Traffic in Networks: Redundancy, Learning and the Effect of Stochastic Fluctuations
math.PR cs.GT cs.IT cs.NI math.IT
We study the distribution of traffic in networks whose users try to minimise their delays by adhering to a simple learning scheme inspired by the replicator dynamics of evolutionary game theory. The stable steady states of these dynamics coincide with the network's Wardrop equilibria and form a convex polytope whose dimension is determined by the network's redundancy (an important concept which measures the "linear dependence" of the users' paths). Despite this abundance of stationary points, the long-term behaviour of the replicator dynamics turns out to be remarkably simple: every solution orbit converges to a Wardrop equilibrium. On the other hand, a major challenge occurs when the users' delays fluctuate unpredictably due to random external factors. In that case, interior equilibria are no longer stationary, but strict equilibria remain stochastically stable irrespective of the fluctuations' magnitude. In fact, if the network has no redundancy and the users are patient enough, we show that the long-term averages of the users' traffic flows converge to the vicinity of an equilibrium, and we also estimate the corresponding invariant measure.
0912.4107
New [48,16,16] Optimal Linear Binary Block Code
cs.IT math.IT
A new [48,16,16] optimal linear binary block code is given. To get this code a general construction is used which is also described in this paper. The construction of this new code settles an conjecture mentioned in a 2008 paper by Janosov et al. where the authors found an new optimal [47,15,16]-code, which is relevant to the applied construction.