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1009.3888
A General Proof of Convergence for Adaptive Distributed Beamforming Schemes
cs.SY
This work focuses on the convergence analysis of adaptive distributed beamforming schemes that can be reformulated as local random search algorithms via a random search framework. Once reformulated as local random search algorithms, it is proved that under two sufficient conditions: a) the objective function of the a...
1009.3891
Secure Lossy Source Coding with Side Information at the Decoders
cs.IT math.IT
This paper investigates the problem of secure lossy source coding in the presence of an eavesdropper with arbitrary correlated side informations at the legitimate decoder (referred to as Bob) and the eavesdropper (referred to as Eve). This scenario consists of an encoder that wishes to compress a source to satisfy th...
1009.3896
Optimistic Rates for Learning with a Smooth Loss
cs.LG
We establish an excess risk bound of O(H R_n^2 + R_n \sqrt{H L*}) for empirical risk minimization with an H-smooth loss function and a hypothesis class with Rademacher complexity R_n, where L* is the best risk achievable by the hypothesis class. For typical hypothesis classes where R_n = \sqrt{R/n}, this translates t...
1009.3916
Finite-SNR Diversity-Multiplexing Tradeoff via Asymptotic Analysis of Large MIMO Systems
cs.IT math.IT
Diversity-multiplexing tradeoff (DMT) was characterized asymptotically (SNR-> infinity) for i.i.d. Rayleigh fading channel by Zheng and Tse [1]. The SNR-asymptotic DMT overestimates the finite-SNR one [2]. This paper outlines a number of additional limitations and difficulties of the DMT framework and discusses their...
1009.3951
Quantifying Information Leakage in Finite Order Deterministic Programs
cs.CR cs.IT math.IT
Information flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. While past work has proposed information theoretic metrics (e.g., Shannon entropy, min-entropy, guessing entropy, etc.) to quantify such information leakage, we argue that some of...
1009.3955
Random Sequential Renormalization of Networks I: Application to Critical Trees
cond-mat.stat-mech cs.SI physics.soc-ph
We introduce the concept of Random Sequential Renormalization (RSR) for arbitrary networks. RSR is a graph renormalization procedure that locally aggregates nodes to produce a coarse grained network. It is analogous to the (quasi-)parallel renormalization schemes introduced by C. Song {\it et al.} (Nature {\bf 433}, ...
1009.3958
Approximate Inference and Stochastic Optimal Control
cs.LG stat.ML
We propose a novel reformulation of the stochastic optimal control problem as an approximate inference problem, demonstrating, that such a interpretation leads to new practical methods for the original problem. In particular we characterise a novel class of iterative solutions to the stochastic optimal control proble...
1009.3961
Optimization of ARQ Protocols in Interference Networks with QoS Constraints
cs.SY cs.NI
We study optimal transmission strategies in interfering wireless networks, under Quality of Service constraints. A buffered, dynamic network with multiple sources is considered, and sources use a retransmission strategy in order to improve packet delivery probability. The optimization problem is formulated as a Marko...
1009.3984
A memory-efficient data structure representing exact-match overlap graphs with application for next generation DNA assembly
cs.DS cs.CE
An exact-match overlap graph of $n$ given strings of length $\ell$ is an edge-weighted graph in which each vertex is associated with a string and there is an edge $(x,y)$ of weight $\omega = \ell - |ov_{max}(x,y)|$ if and only if $\omega \leq \lambda$, where $|ov_{max}(x,y)|$ is the length of $ov_{max}(x,y)$ and $\la...
1009.4004
A family of statistical symmetric divergences based on Jensen's inequality
cs.CV cs.IT math.IT
We introduce a novel parametric family of symmetric information-theoretic distances based on Jensen's inequality for a convex functional generator. In particular, this family unifies the celebrated Jeffreys divergence with the Jensen-Shannon divergence when the Shannon entropy generator is chosen. We then design a ge...
1009.4013
An Analysis of Transaction and Joint-patent Application Networks
cs.SI cs.CY
Many firms these days are opting to specialize rather than generalize as a way of maintaining their competitiveness. Consequently, they cannot rely solely on themselves, but must cooperate by combining their advantages. To obtain the actual condition for this cooperation, a multi-layered network based on two differen...
1009.4046
Channel-coded Collision Resolution by Exploiting Symbol Misalignment
cs.IT math.IT
In random-access networks, such as the IEEE 802.11 network, different users may transmit their packets simultaneously, resulting in packet collisions. Traditionally, the collided packets are simply discarded. To improve performance, advanced signal processing techniques can be applied to extract the individual packet...
1009.4128
Asymptotic Spectral Efficiency of Multi-antenna Links in Wireless Networks with Limited Tx CSI
cs.IT math.IT
An asymptotic technique is presented for finding the spectral efficiency of multi-antenna links in wireless networks where transmitters have Channel-State-Information (CSI) corresponding to their target receiver. Transmitters are assumed to transmit independent data streams on a limited number of channel modes which ...
1009.4188
Robust Coin Flipping
cs.CC cs.CR cs.IT math.IT math.PR
Alice seeks an information-theoretically secure source of private random data. Unfortunately, she lacks a personal source and must use remote sources controlled by other parties. Alice wants to simulate a coin flip of specified bias $\alpha$, as a function of data she receives from $p$ sources; she seeks privacy from...
1009.4219
Safe Feature Elimination for the LASSO and Sparse Supervised Learning Problems
cs.LG cs.SY math.OC
We describe a fast method to eliminate features (variables) in l1 -penalized least-square regression (or LASSO) problems. The elimination of features leads to a potentially substantial reduction in running time, specially for large values of the penalty parameter. Our method is not heuristic: it only eliminates featu...
1009.4268
Rank-Constrained Schur-Convex Optimization with Multiple Trace/Log-Det Constraints
cs.IT math.IT
Rank-constrained optimization problems have received an increasing intensity of interest recently, because many optimization problems in communications and signal processing applications can be cast into a rank-constrained optimization problem. However, due to the non-convex nature of rank constraints, a systematic s...
1009.4269
Distributed Interference Cancellation in Multiple Access Channel with Transmitter Cooperation
cs.IT math.IT
We consider a two-user Gaussian multiple access channel with two independent additive white Gaussian interferences. Each interference is known to exactly one transmitter non-causally. Transmitters are allowed to cooperate through finite-capacity links. The capacity region is characterized to within 3 and 1.5 bits for...
1009.4287
Tree-Structure Expectation Propagation for LDPC Decoding in Erasure Channels
cs.IT math.IT
In this paper we present a new algorithm, denoted as TEP, to decode low-density parity-check (LDPC) codes over the Binary Erasure Channel (BEC). The TEP decoder is derived applying the expectation propagation (EP) algorithm with a tree- structured approximation. Expectation Propagation (EP) is a generalization to Bel...
1009.4300
Robust Transceiver Design for K-Pairs Quasi-Static MIMO Interference Channels via Semi-Definite Relaxation
cs.IT math.IT
In this paper, we propose a robust transceiver design for the K-pair quasi-static MIMO interference channel. Each transmitter is equipped with M antennas, each receiver is equipped with N antennas, and the k-th transmitter sends L_k independent data streams to the desired receiver. In the literature, there exist a va...
1009.4318
Performance Analysis of Estimation of Distribution Algorithm and Genetic Algorithm in Zone Routing Protocol
cs.NE
In this paper, Estimation of Distribution Algorithm (EDA) is used for Zone Routing Protocol (ZRP) in Mobile Ad-hoc Network (MANET) instead of Genetic Algorithm (GA). It is an evolutionary approach, and used when the network size grows and the search space increases. When the destination is outside the zone, EDA is ap...
1009.4352
An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels
cs.IT math.IT
In this paper, we introduce an efficient iterative solver for the joint linear-programming (LP) decoding of low-density parity-check (LDPC) codes and finite-state channels (FSCs). In particular, we extend the approach of iterative approximate LP decoding, proposed by Vontobel and Koetter and explored by Burshtein, to...
1009.4383
Expansion and Search in Networks
cs.SI cs.NI physics.data-an physics.soc-ph
Borrowing from concepts in expander graphs, we study the expansion properties of real-world, complex networks (e.g. social networks, unstructured peer-to-peer or P2P networks) and the extent to which these properties can be exploited to understand and address the problem of decentralized search. We first produce samp...
1009.4409
Efficient delay-tolerant particle filtering
stat.AP cs.MA
This paper proposes a novel framework for delay-tolerant particle filtering that is computationally efficient and has limited memory requirements. Within this framework the informativeness of a delayed (out-of-sequence) measurement (OOSM) is estimated using a lightweight procedure and uninformative measurements are i...
1009.4489
Complex Networks and Symmetry II: Reciprocity and Evolution of World Trade
q-fin.GN cs.SI nlin.AO physics.soc-ph
We exploit the symmetry concepts developed in the companion review of this article to introduce a stochastic version of link reversal symmetry, which leads to an improved understanding of the reciprocity of directed networks. We apply our formalism to the international trade network and show that a strong embedding i...
1009.4495
Unary Coding for Neural Network Learning
cs.NE
This paper presents some properties of unary coding of significance for biological learning and instantaneously trained neural networks.
1009.4503
On Repetition Protocols and Power Control for Multiple Access Block-Fading Channels
cs.IT math.IT
In this paper we study the long-term throughput performance of repetition protocols coupled with power control for multiple access block-fading channels. We propose to use the feedback bits to inform the transmitter about the decoding status and the instantaneous channel quality. We determine the throughput of simple...
1009.4509
Complex networks derived from cellular automata
nlin.CG cs.SI math-ph math.MP
We propose a method for deriving networks from one-dimensional binary cellular automata. The derived networks are usually directed and have structural properties corresponding to the dynamical behaviors of their cellular automata. Network parameters, particularly the efficiency and the degree distribution, show that ...
1009.4556
A new closed-loop output error method for parameter identification of robot dynamics
cs.RO
Off-line robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to...
1009.4564
A Constructive Algorithm for Feedforward Neural Networks for Medical Diagnostic Reasoning
cs.NE
This research is to search for alternatives to the resolution of complex medical diagnosis where human knowledge should be apprehended in a general fashion. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic system. Our research describes a const...
1009.4566
An Algorithm to Extract Rules from Artificial Neural Networks for Medical Diagnosis Problems
cs.NE
Artificial neural networks (ANNs) have been successfully applied to solve a variety of classification and function approximation problems. Although ANNs can generally predict better than decision trees for pattern classification problems, ANNs are often regarded as black boxes since their predictions cannot be explai...
1009.4569
Fastest Distributed Consensus on Star-Mesh Hybrid Sensor Networks
cs.IT cs.DM math.IT
Solving Fastest Distributed Consensus (FDC) averaging problem over sensor networks with different topologies has received some attention recently and one of the well known topologies in this issue is star-mesh hybrid topology. Here in this work we present analytical solution for the problem of FDC algorithm by means ...
1009.4570
Extraction of Symbolic Rules from Artificial Neural Networks
cs.NE
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users ...
1009.4572
Medical diagnosis using neural network
cs.NE
This research is to search for alternatives to the resolution of complex medical diagnosis where human knowledge should be apprehended in a general fashion. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic system. This paper describes a modifie...
1009.4574
A hybrid learning algorithm for text classification
cs.NE cs.IR cs.LG
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification that requires fewer documents...
1009.4581
3D-Mesh denoising using an improved vertex based anisotropic diffusion
cs.CV
This paper deals with an improvement of vertex based nonlinear diffusion for mesh denoising. This method directly filters the position of the vertices using Laplace, reduced centered Gaussian and Rayleigh probability density functions as diffusivities. The use of these PDFs improves the performance of a vertex-based ...
1009.4582
Text Classification using the Concept of Association Rule of Data Mining
cs.LG cs.DB cs.IR
As the amount of online text increases, the demand for text classification to aid the analysis and management of text is increasing. Text is cheap, but information, in the form of knowing what classes a text belongs to, is expensive. Automatic classification of text can provide this information at low cost, but the c...
1009.4586
Optimal Bangla Keyboard Layout using Association Rule of Data Mining
cs.AI
In this paper we present an optimal Bangla Keyboard Layout, which distributes the load equally on both hands so that maximizing the ease and minimizing the effort. Bangla alphabet has a large number of letters, for this it is difficult to type faster using Bangla keyboard. Our proposed keyboard will maximize the spee...
1009.4595
Diversity Spectra of Spatial Multipath Fading Processes
cs.IT math.IT
We analyse the spatial diversity of a multipath fading process for a finite region or curve in the plane. By means of the Karhunen-Lo\`eve (KL) expansion, this diversity can be characterised by the eigenvalue spectrum of the spatial autocorrelation kernel. This justifies to use the term diversity spectrum for it. We ...
1009.4610
Performance Analysis and Design of Two Edge Type LDPC Codes for the BEC Wiretap Channel
cs.IT math.IT
We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We propose a code construction method using two edge type LDPC codes based on the coset encoding scheme. Using a standard LDPC ensemble with a given threshold over the BEC, we gi...
1009.4638
Novel Codes Family for Modified Spectral-Amplitude-Coding OCDMA Systems and Performance Analysis
cs.IT math.IT
In this paper a novel family of codes for modified spectral-amplitude-coding optical code division multiple access (SAC-OCDMA) is introduced. The proposed codes exist for more number of processing gains comparing to the previously reported codes. In the network using these codes, the number of users can be extended w...
1009.4683
Efficient Computation of Optimal Trading Strategies
cs.CE q-fin.CP
Given the return series for a set of instruments, a \emph{trading strategy} is a switching function that transfers wealth from one instrument to another at specified times. We present efficient algorithms for constructing (ex-post) trading strategies that are optimal with respect to the total return, the Sterling rat...
1009.4693
Uniqueness transition in noisy phase retrieval
physics.data-an cs.IT math.IT physics.optics
Previous criteria for the feasibility of reconstructing phase information from intensity measurements, both in x-ray crystallography and more recently in coherent x-ray imaging, have been based on the Maxwell constraint counting principle. We propose a new criterion, based on Shannon's mutual information, that is bet...
1009.4719
A Fast Audio Clustering Using Vector Quantization and Second Order Statistics
cs.SD cs.LG
This paper describes an effective unsupervised speaker indexing approach. We suggest a two stage algorithm to speed-up the state-of-the-art algorithm based on the Bayesian Information Criterion (BIC). In the first stage of the merging process a computationally cheap method based on the vector quantization (VQ) is use...
1009.4739
Balancing clusters to reduce response time variability in large scale image search
cs.CV
Many algorithms for approximate nearest neighbor search in high-dimensional spaces partition the data into clusters. At query time, in order to avoid exhaustive search, an index selects the few (or a single) clusters nearest to the query point. Clusters are often produced by the well-known $k$-means approach since it...
1009.4757
Modeling Instantaneous Changes In Natural Scenes
cs.CV
This project aims to create 3d model of the natural world and model changes in it instantaneously. A framework for modeling instantaneous changes natural scenes in real time using Lagrangian Particle Framework and a fluid-particle grid approach is presented. This project is presented in the form of a proof-based syst...
1009.4766
Efficient L1/Lq Norm Regularization
cs.LG
Sparse learning has recently received increasing attention in many areas including machine learning, statistics, and applied mathematics. The mixed-norm regularization based on the L1/Lq norm with q > 1 is attractive in many applications of regression and classification in that it facilitates group sparsity in the mo...
1009.4773
NCSA: A New Protocol for Random Multiple Access Based on Physical Layer Network Coding
cs.IT cs.NI math.IT
This paper introduces a random multiple access method for satellite communications, named Network Coding-based Slotted Aloha (NCSA). The goal is to improve diversity of data bursts on a slotted-ALOHA-like channel thanks to error correcting codes and Physical-layer Network Coding (PNC). This scheme can be considered a...
1009.4780
Spectrum Sharing between Cooperative Relay and Ad-hoc Networks: Dynamic Transmissions under Computation and Signaling Limitations
cs.IT math.IT math.OC
This paper studies a spectrum sharing scenario between a cooperative relay network (CRN) and a nearby ad-hoc network. In particular, we consider a dynamic spectrum access and resource allocation problem of the CRN. Based on sensing and predicting the ad-hoc transmission behaviors, the ergodic traffic collision time b...
1009.4787
Improving the Quality of Non-Holonomic Motion by Hybridizing C-PRM Paths
cs.RO
Sampling-based motion planners are an effective means for generating collision-free motion paths. However, the quality of these motion paths, with respect to different quality measures such as path length, clearance, smoothness or energy, is often notoriously low. This problem is accentuated in the case of non-holono...
1009.4791
Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines
cs.LG
An instance-weighted variant of the support vector machine (SVM) has attracted considerable attention recently since they are useful in various machine learning tasks such as non-stationary data analysis, heteroscedastic data modeling, transfer learning, learning to rank, and transduction. An important challenge in t...
1009.4797
Extracting directed information flow networks: an application to genetics and semantics
physics.data-an cs.SI physics.soc-ph
We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two...
1009.4798
Role of feedback and broadcasting in the naming game
physics.soc-ph cond-mat.stat-mech cs.GT cs.MA cs.NI q-bio.PE
The naming game (NG) describes the agreement dynamics of a population of agents that interact locally in a pairwise fashion, and in recent years statistical physics tools and techniques have greatly contributed to shed light on its rich phenomenology. Here we investigate in details the role played by the way in which...
1009.4823
Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques
cs.CV
We propose a mid-level image segmentation framework that combines multiple figure-ground hypothesis (FG) constrained at different locations and scales, into interpretations that tile the entire image. The problem is cast as optimization over sets of maximal cliques sampled from the graph connecting non-overlapping, p...
1009.4877
Towards Quality of Service and Resource Aware Robotic Systems through Model-Driven Software Development
cs.RO
Engineering the software development process in robotics is one of the basic necessities towards industrial-strength service robotic systems. A major challenge is to make the step from code-driven to model-driven systems. This is essential to replace hand-crafted single-unit systems by systems composed out of compone...
1009.4954
Delay-Guaranteed Cross-Layer Scheduling in Multi-Hop Wireless Networks
cs.IT math.IT
In this paper, we propose a cross-layer scheduling algorithm that achieves a throughput "epsilon-close" to the optimal throughput in multi-hop wireless networks with a tradeoff of O(1/epsilon) in delay guarantees. The algorithm aims to solve a joint congestion control, routing, and scheduling problem in a multi-hop w...
1009.4962
RGANN: An Efficient Algorithm to Extract Rules from ANNs
cs.NE
This paper describes an efficient rule generation algorithm, called rule generation from artificial neural networks (RGANN) to generate symbolic rules from ANNs. Classification rules are sought in many areas from automatic knowledge acquisition to data mining and ANN rule extraction. This is because classification ru...
1009.4964
Text Classification using Artificial Intelligence
cs.IR
Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, ...
1009.4966
The minimum distance of parameterized codes on projective tori
math.AC cs.IT math.AG math.IT
Let X be a subset of a projective space, over a finite field K, which is parameterized by the monomials arising from the edges of a clutter. Let I(X) be the vanishing ideal of X. It is shown that I(X) is a complete intersection if and only if X is a projective torus. In this case we determine the minimum distance of ...
1009.4969
Extended Range Profiling in Stepped-Frequency Radar with Sparse Recovery
cs.IT math.IT
The newly emerging theory of compressed sensing (CS) enables restoring a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new algorithm of high-resolution range profiling for stepped-frequency (SF) radar suffering from missing pulses is proposed. The new algorithm reco...
1009.4971
Fastest Distributed Consensus on Petal Networks
cs.IT cs.DM math.IT
Providing an analytical solution for the problem of finding Fastest Distributed Consensus (FDC) is one of the challenging problems in the field of sensor networks. Here in this work we present analytical solution for the problem of fastest distributed consensus averaging algorithm by means of stratification and semi-...
1009.4972
Speaker Identification using MFCC-Domain Support Vector Machine
cs.LG cs.SD
Speech recognition and speaker identification are important for authentication and verification in security purpose, but they are difficult to achieve. Speaker identification methods can be divided into text-independent and text-dependent. This paper presents a technique of text-dependent speaker identification using...
1009.4973
Performance Analysis of Pulse Shaping Technique for OFDM PAPR Reduction
cs.IT math.IT
Orthogonal Frequency Division Multiplexing (OFDM) is an attractive modulation and multiple access techniques for channels with a nonflat frequency response, as it saves the need for complex equalizers. It can offer high quality performance in terms of bandwidth efficiency, robustness against multipath fading and cost...
1009.4974
Rotation Invariant Face Detection Using Wavelet, PCA and Radial Basis Function Networks
cs.CV
This paper introduces a novel method for human face detection with its orientation by using wavelet, principle component analysis (PCA) and redial basis networks. The input image is analyzed by two-dimensional wavelet and a two-dimensional stationary wavelet. The common goals concern are the image clearance and simpl...
1009.4975
Dynamic Adaptive Mesh Refinement for Topology Optimization
math.NA cs.CE
We present an improved method for topology optimization with both adaptive mesh refinement and derefinement. Since the total volume fraction in topology optimization is usually modest, after a few initial iterations the domain of computation is largely void. Hence, it is inefficient to have many small elements, in su...
1009.4976
Text Classification using Association Rule with a Hybrid Concept of Naive Bayes Classifier and Genetic Algorithm
cs.IR cs.DB cs.LG
Text classification is the automated assignment of natural language texts to predefined categories based on their content. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such a...
1009.4978
Extracting Symbolic Rules for Medical Diagnosis Problem
cs.NE
Neural networks (NNs) have been successfully applied to solve a variety of application problems involving classification and function approximation. Although backpropagation NNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their pre...
1009.4981
An Efficient Technique for Text Compression
cs.IT cs.IR math.IT
For storing a word or the whole text segment, we need a huge storage space. Typically a character requires 1 Byte for storing it in memory. Compression of the memory is very important for data management. In case of memory requirement compression for text data, lossless memory compression is needed. We are suggesting...
1009.4982
Optimal Bangla Keyboard Layout using Data Mining Technique
cs.AI
This paper presents an optimal Bangla Keyboard Layout, which distributes the load equally on both hands so that maximizing the ease and minimizing the effort. Bangla alphabet has a large number of letters, for this it is difficult to type faster using Bangla keyboard. Our proposed keyboard will maximize the speed of ...
1009.4983
Pattern Classification using Simplified Neural Networks
cs.NE
In recent years, many neural network models have been proposed for pattern classification, function approximation and regression problems. This paper presents an approach for classifying patterns from simplified NNs. Although the predictive accuracy of ANNs is often higher than that of other methods or human experts,...
1009.4984
Rule Extraction using Artificial Neural Networks
cs.NE
Artificial neural networks have been successfully applied to a variety of business application problems involving classification and regression. Although backpropagation neural networks generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., t...
1009.4987
Text Classification using Data Mining
cs.IR cs.DB
Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, ...
1009.4988
REx: An Efficient Rule Generator
cs.NE
This paper describes an efficient algorithm REx for generating symbolic rules from artificial neural network (ANN). Classification rules are sought in many areas from automatic knowledge acquisition to data mining and ANN rule extraction. This is because classification rules possess some attractive features. They are...
1009.4991
Web Page Categorization Using Artificial Neural Networks
cs.NE cs.IR
Web page categorization is one of the challenging tasks in the world of ever increasing web technologies. There are many ways of categorization of web pages based on different approach and features. This paper proposes a new dimension in the way of categorization of web pages using artificial neural network (ANN) thr...
1009.4994
Text Categorization using Association Rule and Naive Bayes Classifier
cs.IR cs.DB
As the amount of online text increases, the demand for text categorization to aid the analysis and management of text is increasing. Text is cheap, but information, in the form of knowing what classes a text belongs to, is expensive. Automatic categorization of text can provide this information at low cost, but the c...
1009.5003
Demonstrating a Service-Enhanced Retrieval System
cs.IR cs.DL
This paper is a short description of an information retrieval system enhanced by three model driven retrieval services: (1) co-word analysis based query expansion, re-ranking via (2) Bradfordizing and (3) author centrality. The different services each favor quite other - but still relevant - documents than pure term-...
1009.5004
On reverse-engineering the KUKA Robot Language
cs.RO
Most commercial manufacturers of industrial robots require their robots to be programmed in a proprietary language tailored to the domain - a typical domain-specific language (DSL). However, these languages oftentimes suffer from shortcomings such as controller-specific design, limited expressiveness and a lack of ex...
1009.5026
On the Fictitious Play and Channel Selection Games
cs.GT cs.IT math.IT
Considering the interaction through mutual interference of the different radio devices, the channel selection (CS) problem in decentralized parallel multiple access channels can be modeled by strategic-form games. Here, we show that the CS problem is a potential game (PG) and thus the fictitious play (FP) converges t...
1009.5029
On the complexity of the multiple stack TSP, kSTSP
cs.CC cs.RO
The multiple Stack Travelling Salesman Problem, STSP, deals with the collect and the deliverance of n commodities in two distinct cities. The two cities are represented by means of two edge-valued graphs (G1,d2) and (G2,d2). During the pick-up tour, the commodities are stored into a container whose rows are subject t...
1009.5030
Approximability of the Multiple Stack TSP
cs.CC cs.RO
STSP seeks a pair of pickup and delivery tours in two distinct networks, where the two tours are related by LIFO contraints. We address here the problem approximability. We notably establish that asymmetric MaxSTSP and MinSTSP12 are APX, and propose a heuristic that yields to a 1/2, 3/4 and 3/2 standard approximation...
1009.5031
A Genetic Algorithm for the Multi-Pickup and Delivery Problem with time windows
cs.NE
In This paper we present a genetic algorithm for the multi-pickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. This paper purposes a...
1009.5048
The Most Advantageous Bangla Keyboard Layout Using Data Mining Technique
cs.AI
Bangla alphabet has a large number of letters, for this it is complicated to type faster using Bangla keyboard. The proposed keyboard will maximize the speed of operator as they can type with both hands parallel. Association rule of data mining to distribute the Bangla characters in the keyboard is used here. The fre...
1009.5055
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices
math.OC cs.NA cs.SY
This paper proposes scalable and fast algorithms for solving the Robust PCA problem, namely recovering a low-rank matrix with an unknown fraction of its entries being arbitrarily corrupted. This problem arises in many applications, such as image processing, web data ranking, and bioinformatic data analysis. It was re...
1009.5094
Minimal-time bioremediation of natural water resources
math.OC cs.SY math.DS
We study minimal time strategies for the treatment of pollution of large volumes, such as lakes or natural reservoirs, with the help of an autonomous bioreactor. The control consists in feeding the bioreactor from the resource, the clean output returning to the resource with the same flow rate. We first characterize ...
1009.5121
Noncoherent Interference Alignment: Trade Signal Power for Diversity Towards Multiplexing
cs.IT math.IT
This paper proposes the first known universal interference alignment scheme for general $(1\times{}1)^K$ interference networks, either Gaussian or deterministic, with only 2 symbol extension. While interference alignment is theoretically powerful to increase the total network throughput tremendously, no existing sche...
1009.5145
Relay Selection with Network Coding in Two-Way Relay Channels
cs.IT math.IT
In this paper, we consider the design of joint network coding (NC)and relay selection (RS) in two-way relay channels. In the proposed schemes, two users first sequentially broadcast their respective information to all the relays. We propose two RS schemes, a single relay selection with NC and a dual relay selection w...
1009.5146
Robust Linear Precoder Design for Multi-cell Downlink Transmission
cs.IT math.IT
Coordinated information processing by the base stations of multi-cell wireless networks enhances the overall quality of communication in the network. Such coordinations for optimizing any desired network-wide quality of service (QoS) necessitate the base stations to acquire and share some channel state information (C...
1009.5149
Towards an incremental maintenance of cyclic association rules
cs.DB
Recently, the cyclic association rules have been introduced in order to discover rules from items characterized by their regular variation over time. In real life situations, temporal databases are often appended or updated. Rescanning the whole database every time is highly expensive while existing incremental minin...
1009.5158
Information Capacity of Energy Harvesting Sensor Nodes
cs.IT math.IT
Sensor nodes with energy harvesting sources are gaining popularity due to their ability to improve the network life time and are becoming a preferred choice supporting `green communication'. We study such a sensor node with an energy harvesting source and compare various architectures by which the harvested energy is...
1009.5161
Information Physics: The New Frontier
math-ph cond-mat.stat-mech cs.IT math.IT math.MP
At this point in time, two major areas of physics, statistical mechanics and quantum mechanics, rest on the foundations of probability and entropy. The last century saw several significant fundamental advances in our understanding of the process of inference, which make it clear that these are inferential theories. T...
1009.5208
Exploiting isochrony in self-triggered control
math.OC cs.SY math.DS
Event-triggered control and self-triggered control have been recently proposed as new implementation paradigms that reduce resource usage for control systems. In self-triggered control, the controller is augmented with the computation of the next time instant at which the feedback control law is to be recomputed. Sin...
1009.5233
A Simple Abstraction for Data Modeling
cs.DB cs.DL
The problems that scientists face in creating well designed databases intersect with the concerns of data curation. Entity-relationship modeling and its variants have been the basis of most relational data modeling for decades. However, these abstractions and the relational model itself are intricate and have proved ...
1009.5249
Defining and Generating Axial Lines from Street Center Lines for better Understanding of Urban Morphologies
cs.CV physics.data-an
Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least number of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space sy...
1009.5257
Approximation of DAC Codeword Distribution for Equiprobable Binary Sources along Proper Decoding Paths
cs.IT math.IT
Distributed Arithmetic Coding (DAC) is an effective implementation of Slepian-Wolf coding, especially for short data blocks. To research its properties, the concept of DAC codeword distribution along proper and wrong decoding paths has been introduced. For DAC codeword distribution of equiprobable binary sources alon...
1009.5268
General Scaled Support Vector Machines
cs.AI
Support Vector Machines (SVMs) are popular tools for data mining tasks such as classification, regression, and density estimation. However, original SVM (C-SVM) only considers local information of data points on or over the margin. Therefore, C-SVM loses robustness. To solve this problem, one approach is to translate...
1009.5290
Measuring Similarity of Graphs and their Nodes by Neighbor Matching
cs.AI
The problem of measuring similarity of graphs and their nodes is important in a range of practical problems. There is a number of proposed measures, some of them being based on iterative calculation of similarity between two graphs and the principle that two nodes are as similar as their neighbors are. In our work, w...
1009.5316
Jamming in complex networks with degree correlation
physics.soc-ph cs.SI physics.comp-ph
We study the effects of the degree-degree correlations on the pressure congestion J when we apply a dynamical process on scale free complex networks using the gradient network approach. We find that the pressure congestion for disassortative (assortative) networks is lower (bigger) than the one for uncorrelated netwo...
1009.5346
A Novel Approach for Cardiac Disease Prediction and Classification Using Intelligent Agents
cs.MA cs.AI
The goal is to develop a novel approach for cardiac disease prediction and diagnosis using intelligent agents. Initially the symptoms are preprocessed using filter and wrapper based agents. The filter removes the missing or irrelevant symptoms. Wrapper is used to extract the data in the data set according to the thre...
1009.5352
Establishing a Multi-Thesauri-Scenario based on SKOS and Cross-Concordances
cs.DL cs.IR
This case study proposes a scenario with three topic-related thesauri, which have been connected with bilateral cross-concordances as part of a major terminology mapping initiative in the project KoMoHe (Mayr & Petras, 2008). The thesauri have already been or will be converted to SKOS and in order to not omit the rel...
1009.5398
A Scenario-Based Mobile Application for Robot-Assisted Smart Digital Homes
cs.RO
Smart homes are becoming more popular, as every day a new home appliance can be digitally controlled. Smart Digital Homes are using a server to make interaction with all the possible devices in one place, on a computer or webpage. In this paper we designed and implemented a mobile application using Windows Mobile pla...
1009.5419
Portfolio Allocation for Bayesian Optimization
cs.LG
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It uses Bayesian methods to sample the objec...