OpenRaiser/Intern-Atlas huggingface dataset:
Coping with Physical Attacks on Random Network Structures
Venue: arXiv cs.SY 2013
Year: 2013

Communication networks are vulnerable to natural disasters, such as earthquakes or floods, as well as to physical attacks, such as an Electromagnetic Pulse (EMP) attack. Such real-world events happen at specific geographical locations and disrupt specific parts of the network. Therefore, the geographical layout of the network determines the impact of such events on the network's physical topology in terms of capacity, connectivity, and flow. Recent works focused on assessing the vulnerability of a deterministic network to such events. In this work, we focus on assessing the vulnerability of (geographical) random networks to such disasters. We consider stochastic graph models in which nodes and links are probabilistically distributed on a plane, and model the disaster event as a circular cut that destroys any node or link within or intersecting the circle. We develop algorithms for assessing the damage of both targeted and non-targeted (random) attacks and determining which attack locations have the expected most disruptive impact on the network. Then, we provide experimental results for assessing the impact of circular disasters to communications networks in the USA, where the network's geographical layout was modeled probabilistically, relying on demographic information only. Our results demonstrates the applicability of our algorithms to real-world scenarios. Our algorithms allows to examine how valuable is public information about the network's geographical area (e.g., demography, topography, economy) to an attacker's destruction assessment capabilities in the case the network's physical topology is hidden or examine the affect of hiding the actual physical location of the fibers on the attack strategy. Thereby, our schemes can be used as a tool for policy makers and engineers to design more robust networks and identifying locations which require additional protection efforts.
Generalized simulation model of teaching and its research on PC
Venue: arXiv cs.CY 2013
Year: 2013

One of the important problems of cyber pedagogy is the following: how, knowing the parameters of the student, his initial level of knowledge and the impact of the teacher to predict knowledge of student at subsequent times. Simulation method allows you to create a computer program that simulates the behavior of the 'teacher-student'-system and investigate the influence of system parameters on the results of learning.
An Efficient Edge Detection Technique by Two Dimensional Rectangular Cellular Automata
Venue: arXiv cs.CV 2013
Year: 2013

This paper proposes a new pattern of two dimensional cellular automata linear rules that are used for efficient edge detection of an image. Since cellular automata is inherently parallel in nature, it has produced desired output within a unit time interval. We have observed four linear rules among 512 total linear rules of a rectangular cellular automata in adiabatic or reflexive boundary condition that produces an optimal result. These four rules are directly applied once to the images and produced edge detected output. We compare our results with the existing edge detection algorithms and found that our results shows better edge detection with an enhancement of edges.
A Survey on Eye-Gaze Tracking Techniques
Venue: arXiv cs.CV 2013
Year: 2013

Study of eye-movement is being employed in Human Computer Interaction (HCI) research. Eye - gaze tracking is one of the most challenging problems in the area of computer vision. The goal of this paper is to present a review of latest research in this continued growth of remote eye-gaze tracking. This overview includes the basic definitions and terminologies, recent advances in the field and finally the need of future development in the field.
Mobile Multimedia Recommendation in Smart Communities: A Survey
Venue: arXiv cs.IR 2013
Year: 2013

Due to the rapid growth of internet broadband access and proliferation of modern mobile devices, various types of multimedia (e.g. text, images, audios and videos) have become ubiquitously available anytime. Mobile device users usually store and use multimedia contents based on their personal interests and preferences. Mobile device challenges such as storage limitation have however introduced the problem of mobile multimedia overload to users. In order to tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users. In this survey paper, we examine the importance of mobile multimedia recommendation systems from the perspective of three smart communities, namely, mobile social learning, mobile event guide and context-aware services. A cautious analysis of existing research reveals that the implementation of proactive, sensor-based and hybrid recommender systems can improve mobile multimedia recommendations. Nevertheless, there are still challenges and open issues such as the incorporation of context and social properties, which need to be tackled in order to generate accurate and trustworthy mobile multimedia recommendations.
The Value Iteration Algorithm is Not Strongly Polynomial for Discounted Dynamic Programming
Venue: arXiv cs.AI 2013
Year: 2013

This note provides a simple example demonstrating that, if exact computations are allowed, the number of iterations required for the value iteration algorithm to find an optimal policy for discounted dynamic programming problems may grow arbitrarily quickly with the size of the problem. In particular, the number of iterations can be exponential in the number of actions. Thus, unlike policy iterations, the value iteration algorithm is not strongly polynomial for discounted dynamic programming.
Face Detection from still and Video Images using Unsupervised Cellular Automata with K means clustering algorithm
Venue: arXiv cs.CV 2013
Year: 2013

Pattern recognition problem rely upon the features inherent in the pattern of images. Face detection and recognition is one of the challenging research areas in the field of computer vision. In this paper, we present a method to identify skin pixels from still and video images using skin color. Face regions are identified from this skin pixel region. Facial features such as eyes, nose and mouth are then located. Faces are recognized from color images using an RBF based neural network. Unsupervised Cellular Automata with K means clustering algorithm is used to locate different facial elements. Orientation is corrected by using eyes. Parameters like inter eye distance, nose length, mouth position, Discrete Cosine Transform (DCT) coefficients etc. are computed and used for a Radial Basis Function (RBF) based neural network. This approach reliably works for face sequence with orientation in head, expressions etc.
Refinement of the random coding bound
Venue: arXiv cs.IT 2013
Year: 2013

An improved pre-factor for the random coding bound is proved. Specifically, for channels with critical rate not equal to capacity, if a regularity condition is satisfied (resp. not satisfied), then for any $ε>0$ a pre-factor of $O(N^{-\frac{1}{2}\left( 1 - ε+ \barρ^\ast_R \right)})$ (resp. $O(N^{-\frac{1}{2}})$) is achievable for rates above the critical rate, where $N$ and $R$ is the blocklength and rate, respectively. The extra term $\barρ^\ast_R$ is related to the slope of the random coding exponent. Further, the relation of these bounds with the authors' recent refinement of the sphere-packing bound, as well as the pre-factor for the random coding bound below the critical rate, is discussed.
Description Logics based Formalization of Wh-Queries
Venue: arXiv cs.CL 2013
Year: 2013

The problem of Natural Language Query Formalization (NLQF) is to translate a given user query in natural language (NL) into a formal language so that the semantic interpretation has equivalence with the NL interpretation. Formalization of NL queries enables logic based reasoning during information retrieval, database query, question-answering, etc. Formalization also helps in Web query normalization and indexing, query intent analysis, etc. In this paper we are proposing a Description Logics based formal methodology for wh-query intent (also called desire) identification and corresponding formal translation. We evaluated the scalability of our proposed formalism using Microsoft Encarta 98 query dataset and OWL-S TC v.4.0 dataset.
Empirical modeling of the impact factor distribution
Venue: arXiv cs.DL 2013
Year: 2013

The distribution of impact factors has been modeled in the recent informetric literature using two-exponent law proposed by Mansilla et al. (2007). This paper shows that two distributions widely-used in economics, namely the Dagum and Singh-Maddala models, possess several advantages over the two-exponent model. Compared to the latter, the former give as good as or slightly better fit to data on impact factors in eight important scientific fields. In contrast to the two-exponent model, both proposed distributions have closed-from probability density functions and cumulative distribution functions, which facilitates fitting these distributions to data and deriving their statistical properties.
Finding More Relevance: Propagating Similarity on Markov Random Field for Image Retrieval
Venue: arXiv cs.CV 2013
Year: 2013

To effectively retrieve objects from large corpus with high accuracy is a challenge task. In this paper, we propose a method that propagates visual feature level similarities on a Markov random field (MRF) to obtain a high level correspondence in image space for image pairs. The proposed correspondence between image pair reflects not only the similarity of low-level visual features but also the relations built through other images in the database and it can be easily integrated into the existing bag-of-visual-words(BoW) based systems to reduce the missing rate. We evaluate our method on the standard Oxford-5K, Oxford-105K and Paris-6K dataset. The experiment results show that the proposed method significantly improves the retrieval accuracy on three datasets and exceeds the current state-of-the-art retrieval performance.
Analysis of Geometric Disaster Evaluation Model for Physical Networks
Venue: arXiv cs.NI 2013
Year: 2013

A geometric model of a physical network affected by a disaster is proposed and analyzed using integral geometry (geometric probability). This analysis provides a theoretical method of evaluating performance metrics, such as the probability of maintaining connectivity, and a network design rule that can make the network robust against disasters. The proposed model is of when the disaster area is much larger than the part of the network in which we are interested. Performance metrics, such as the probability of maintaining connectivity, are explicitly given by linear functions of the perimeter length of convex hulls determined by physical routes. The derived network design rule includes the following. (1) Reducing the convex hull of the physical route reduces the expected number of nodes that cannot connect to the destination. (2) The probability of maintaining the connectivity of two nodes on a loop cannot be changed by changing the physical route of that loop. (3) The effect of introducing a loop is identical to that of a single physical route implemented by the straight-line route.
Quality Estimation of English-Hindi Outputs using Naive Bayes Classifier
Venue: arXiv cs.CL 2013
Year: 2013

In this paper we present an approach for estimating the quality of machine translation system. There are various methods for estimating the quality of output sentences, but in this paper we focus on Naïve Bayes classifier to build model using features which are extracted from the input sentences. These features are used for finding the likelihood of each of the sentences of the training data which are then further used for determining the scores of the test data. On the basis of these scores we determine the class labels of the test data.
Design of Reversible Random Access Memory
Venue: arXiv cs.ET 2013
Year: 2013

Reversible logic has become immensely popular research area and its applications have spread in various technologies for their low power consumption. In this paper we proposed an efficient design of random access memory using reversible logic. In the way of designing the reversible random access memory we proposed a reversible decoder and a write enable reversible master slave D flip-flop. All the reversible designs are superior in terms of quantum cost, delay and garbage outputs compared to the designs existing in literature.
A Novel Approach for Designing Online Testable Reversible Circuits
Venue: arXiv cs.ET 2013
Year: 2013

Reversible logic is gaining interest of many researchers due to its low power dissipating characteristic. In this paper we proposed a new approach for designing online testable reversible circuits. The resultant testable reversible circuit can detect any single bit error whiles it is operating. Appropriate theorems and lemmas are presented to clarify the proposed design. The experimental results show that our design approach is superior in terms of number of number of gates, garbage outputs and quantum cost.
How beta-skeletons lose their edges
Venue: arXiv cs.CG 2013
Year: 2013

A β-skeleton is a proximity graphs with node neighbourhood defined by continuous-valued parameter β. Two nodes in a β-skeleton are connected by an edge if their lune-based neighbourhood contains no other nodes. With increase of β some edges a skeleton are disappear. We study how a number of edges in β-skeleton depends on β. We speculate how this dependence can be used to discriminate between random and non-random planar sets. We also analyse stability of β-skeletons and their sensitivity to perturbations.
Stopping Rules for Bag-of-Words Image Search and Its Application in Appearance-Based Localization
Venue: arXiv cs.CV 2013
Year: 2013

We propose a technique to improve the search efficiency of the bag-of-words (BoW) method for image retrieval. We introduce a notion of difficulty for the image matching problems and propose methods that reduce the amount of computations required for the feature vector-quantization task in BoW by exploiting the fact that easier queries need less computational resources. Measuring the difficulty of a query and stopping the search accordingly is formulated as a stopping problem. We introduce stopping rules that terminate the image search depending on the difficulty of each query, thereby significantly reducing the computational cost. Our experimental results show the effectiveness of our approach when it is applied to appearance-based localization problem.
A General Algorithm for Deciding Transportability of Experimental Results
Venue: arXiv cs.AI 2013
Year: 2013

Generalizing empirical findings to new environments, settings, or populations is essential in most scientific explorations. This article treats a particular problem of generalizability, called "transportability", defined as a license to transfer information learned in experimental studies to a different population, on which only observational studies can be conducted. Given a set of assumptions concerning commonalities and differences between the two populations, Pearl and Bareinboim (2011) derived sufficient conditions that permit such transfer to take place. This article summarizes their findings and supplements them with an effective procedure for deciding when and how transportability is feasible. It establishes a necessary and sufficient condition for deciding when causal effects in the target population are estimable from both the statistical information available and the causal information transferred from the experiments. The article further provides a complete algorithm for computing the transport formula, that is, a way of combining observational and experimental information to synthesize bias-free estimate of the desired causal relation. Finally, the article examines the differences between transportability and other variants of generalizability.
Implementation of Hand Detection based Techniques for Human Computer Interaction
Venue: arXiv cs.CV 2013
Year: 2013

The computer industry is developing at a fast pace. With this development almost all of the fields under computers have advanced in the past couple of decades. But the same technology is being used for human computer interaction that was used in 1970s. Even today the same type of keyboard and mouse is used for interacting with computer systems. With the recent boom in the mobile segment touchscreens have become popular for interaction with cell phones. But these touchscreens are rarely used on traditional systems. This paper tries to introduce methods for human computer interaction using the users hand which can be used both on traditional computer platforms as well as cell phones. The methods explain how the users detected hand can be used as input for applications and also explain applications that can take advantage of this type of interaction mechanism.
A Top-Down Approach to Managing Variability in Robotics Algorithms
Venue: arXiv cs.RO 2013
Year: 2013

One of the defining features of the field of robotics is its breadth and heterogeneity. Unfortunately, despite the availability of several robotics middleware services, robotics software still fails to smoothly handle at least two kinds of variability: algorithmic variability and lower-level variability. The consequence is that implementations of algorithms are hard to understand and impacted by changes to lower-level details such as the choice or configuration of sensors or actuators. Moreover, when several algorithms or algorithmic variants are available it is difficult to compare and combine them. In order to alleviate these problems we propose a top-down approach to express and implement robotics algorithms and families of algorithms so that they are both less dependent on lower-level details and easier to understand and combine. This approach goes top-down from the algorithms and shields them from lower-level details by introducing very high level abstractions atop the intermediate abstractions of robotics middleware. This approach is illustrated on 7 variants of the Bug family that were implemented using both laser and infra-red sensors.
Mind Your Own Bandwidth: An Edge Solution to Peak-hour Broadband Congestion
Venue: arXiv cs.NI 2013
Year: 2013

Motivated by recent increases in network traffic, we propose a decentralized network edge-based solution to peak-hour broadband congestion that incentivizes users to moderate their bandwidth demands to their actual needs. Our solution is centered on smart home gateways that allocate bandwidth in a two-level hierarchy: first, a gateway purchases guaranteed bandwidth from the Internet Service Provider (ISP) with virtual credits. It then self-limits its bandwidth usage and distributes the bandwidth among its apps and devices according to their relative priorities. To this end, we design a credit allocation and redistribution mechanism for the first level, and implement our gateways on commodity wireless routers for the second level. We demonstrate our system's effectiveness and practicality with theoretical analysis, simulations and experiments on real traffic. Compared to a baseline equal sharing algorithm, our solution significantly improves users' overall satisfaction and yields a fair allocation of bandwidth across users.
Multi-modal filtering for non-linear estimation
Venue: arXiv cs.SY 2013
Year: 2013

Multi-modal densities appear frequently in time series and practical applications. However, they cannot be represented by common state estimators, such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF), which additionally suffer from the fact that uncertainty is often not captured sufficiently well, which can result in incoherent and divergent tracking performance. In this paper, we address these issues by devising a non-linear filtering algorithm where densities are represented by Gaussian mixture models, whose parameters are estimated in closed form. The resulting method exhibits a superior performance on typical benchmarks.
PSO-MISMO Modeling Strategy for Multi-Step-Ahead Time Series Prediction
Venue: arXiv cs.AI 2013
Year: 2013

Multi-step-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multi-step-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this study proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.
Controlled Sparsity Kernel Learning
Venue: arXiv cs.LG 2013
Year: 2013

Multiple Kernel Learning(MKL) on Support Vector Machines(SVMs) has been a popular front of research in recent times due to its success in application problems like Object Categorization. This success is due to the fact that MKL has the ability to choose from a variety of feature kernels to identify the optimal kernel combination. But the initial formulation of MKL was only able to select the best of the features and misses out many other informative kernels presented. To overcome this, the Lp norm based formulation was proposed by Kloft et. al. This formulation is capable of choosing a non-sparse set of kernels through a control parameter p. Unfortunately, the parameter p does not have a direct meaning to the number of kernels selected. We have observed that stricter control over the number of kernels selected gives us an edge over these techniques in terms of accuracy of classification and also helps us to fine tune the algorithms to the time requirements at hand. In this work, we propose a Controlled Sparsity Kernel Learning (CSKL) formulation that can strictly control the number of kernels which we wish to select. The CSKL formulation introduces a parameter t which directly corresponds to the number of kernels selected. It is important to note that a search in t space is finite and fast as compared to p. We have also provided an efficient Reduced Gradient Descent based algorithm to solve the CSKL formulation, which is proven to converge. Through our experiments on the Caltech101 Object Categorization dataset, we have also shown that one can achieve better accuracies than the previous formulations through the right choice of t.
System Analysis And Design For Multimedia Retrieval Systems
Venue: arXiv cs.IR 2013
Year: 2013

Due to the extensive use of information technology and the recent developments in multimedia systems, the amount of multimedia data available to users has increased exponentially. Video is an example of multimedia data as it contains several kinds of data such as text, image, meta-data, visual and audio. Content based video retrieval is an approach for facilitating the searching and browsing of large multimedia collections over WWW. In order to create an effective video retrieval system, visual perception must be taken into account. We conjectured that a technique which employs multiple features for indexing and retrieval would be more effective in the discrimination and search tasks of videos. In order to validate this, content based indexing and retrieval systems were implemented using color histogram, Texture feature (GLCM), edge density and motion..