OpenRaiser/Intern-Atlas huggingface dataset:
Transceiver Design for Multi-user Multi-antenna Two-way Relay Cellular Systems
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we design interference free transceivers for multi-user two-way relay systems, where a multi-antenna base station (BS) simultaneously exchanges information with multiple single-antenna users via a multi-antenna amplify-and-forward relay station (RS). To offer a performance benchmark and provide useful insight into the transceiver structure, we employ alternating optimization to find optimal transceivers at the BS and RS that maximizes the bidirectional sum rate. We then propose a low complexity scheme, where the BS transceiver is the zero-forcing precoder and detector, and the RS transceiver is designed to balance the uplink and downlink sum rates. Simulation results demonstrate that the proposed scheme is superior to the existing zero forcing and signal alignment schemes, and the performance gap between the proposed scheme and the alternating optimization is minor.
Shortest Paths in Less Than a Millisecond
Venue: arXiv cs.SI 2012
Year: 2012

We consider the problem of answering point-to-point shortest path queries on massive social networks. The goal is to answer queries within tens of milliseconds while minimizing the memory requirements. We present a technique that achieves this goal for an extremely large fraction of path queries by exploiting the structure of the social networks. Using evaluations on real-world datasets, we argue that our technique offers a unique trade-off between latency, memory and accuracy. For instance, for the LiveJournal social network (roughly 5 million nodes and 69 million edges), our technique can answer 99.9% of the queries in less than a millisecond. In comparison to storing all pair shortest paths, our technique requires at least 550x less memory; the average query time is roughly 365 microseconds --- 430x faster than the state-of-the-art shortest path algorithm. Furthermore, the relative performance of our technique improves with the size (and density) of the network. For the Orkut social network (3 million nodes and 220 million edges), for instance, our technique is roughly 2588x faster than the state-of-the-art algorithm for computing shortest paths.
Reciprocally induced coevolution: A computational metaphor in Mathematics
Venue: arXiv cs.OH 2012
Year: 2012

Natural phenomenon of coevolution is the reciprocally induced evolutionary change between two or more species or population. Though this biological occurrence is a natural fact, there are only few attempts to use this as a simile in computation. This paper is an attempt to introduce reciprocally induced coevolution as a mechanism to counter problems faced by a typical genetic algorithm applied as an optimization technique. The domain selected for testing the efficacy of the procedure is the process of finding numerical solutions of Diophantine equations. Diophantine equations are polynomial equations in Mathematics where only integer solutions are sought. Such equations and its solutions are significant in three aspects-(i) historically they are important as Hilbert's tenth problem with a background of more than twenty six centuries; (ii) there are many modern application areas of Diophantine equations like public key cryptography and data dependency in super computers (iii) it has been proved that there does not exist any general method to find solutions of such equations. The proposed procedure has been tested with Diophantine equations with different powers and different number of variables.
Dispelling Classes Gradually to Improve Quality of Feature Reduction Approaches
Venue: arXiv cs.AI 2012
Year: 2012

Feature reduction is an important concept which is used for reducing dimensions to decrease the computation complexity and time of classification. Since now many approaches have been proposed for solving this problem, but almost all of them just presented a fix output for each input dataset that some of them aren't satisfied cases for classification. In this we proposed an approach as processing input dataset to increase accuracy rate of each feature extraction methods. First of all, a new concept called dispelling classes gradually (DCG) is proposed to increase separability of classes based on their labels. Next, this method is used to process input dataset of the feature reduction approaches to decrease the misclassification error rate of their outputs more than when output is achieved without any processing. In addition our method has a good quality to collate with noise based on adapting dataset with feature reduction approaches. In the result part, two conditions (With process and without that) are compared to support our idea by using some of UCI datasets.
Ordinary Search Engine Users Carrying Out Complex Search Tasks
Venue: arXiv cs.IR 2012
Year: 2012

Web search engines have become the dominant tools for finding information on the Internet. Due to their popularity, users apply them to a wide range of search needs, from simple look-ups to rather complex information tasks. This paper presents the results of a study to investigate the characteristics of these complex information needs in the context of Web search engines. The aim of the study is to find out more about (1) what makes complex search tasks distinct from simple tasks and if it is possible to find simple measures for describing their complexity, (2) if search success for a task can be predicted by means of unique measures, and (3) if successful searchers show a different behavior than unsuccessful ones. The study includes 60 people who carried out a set of 12 search tasks with current commercial search engines. Their behavior was logged with the Search-Logger tool. The results confirm that complex tasks show significantly different characteristics than simple tasks. Yet it seems to be difficult to distinguish successful from unsuccessful search behaviors. Good searchers can be differentiated from bad searchers by means of measurable parameters. The implications of these findings for search engine vendors are discussed.
Nagios Based Enhanced IT Management System
Venue: arXiv cs.NI 2012
Year: 2012

The integrated management of multi-providers equipments is a key asset for telecommunication operators or service providers when selecting the appropriate network and service management platform for their network. In this paper, we present an open and adaptable platform that support fault and configuration management for next-generation networks. This platform Named Nagios based - information technology management system (NB-ITMS) leverage of the well-known Nagios platform to implement new capabilities. Offering additional features applications and management functions enable easy and low cost management of advanced services and networks technologies. The performance of our platform has been compared to existing off-the-shell platforms.
Measure of Similarity between Fuzzy Concepts for Optimization of Fuzzy Semantic Nets
Venue: arXiv cs.IR 2012
Year: 2012

This paper presents a method to measure the similarity between different fuzzy concepts in order to optimize Semantic networks. The problem approached is the minimization of the time of research and identification of user's Objects and Goals. Indeed, it concerns to determine to each instant the totality of Objects (respectively Goals) among which one can identify rapidly the most satisfactory for the user's Object and Goal. Alone Objects and most similar Goals to Objects and researched Goals of the viewpoint of attribute values will be processed, what will avoid the analysis of all Objects and system Goals far of needs of the user.
Algebraic Characterization of the Class of Languages recognized by Measure Only Quantum Automata
Venue: arXiv cs.FL 2012
Year: 2012

We study a model of one-way quantum automaton where only measurement operations are allowed (MOn-1qfa). We give an algebraic characterization of LMO, showing that the syntactic monoids of the languages in LMO are exactly the literal pseudovariety of J-trivial literally idempotent monoids, where J is the Green's relation determined by two-sided ideals. We also prove that LMO coincides with the literal variety of literally idempotent piecewise testable regular languages. This allows us to prove the existence of a polynomial time algorithm for deciding whether a regular language belongs to LMO.
CARE: Content Aware Redundancy Elimination for Disaster Communications on Damaged Networks
Venue: arXiv cs.NI 2012
Year: 2012

During a disaster scenario, situational awareness information, such as location, physical status and images of the surrounding area, is essential for minimizing loss of life, injury, and property damage. Today's handhelds make it easy for people to gather data from within the disaster area in many formats, including text, images and video. Studies show that the extreme anxiety induced by disasters causes humans to create a substantial amount of repetitive and redundant content. Transporting this content outside the disaster zone can be problematic when the network infrastructure is disrupted by the disaster. This paper presents the design of a novel architecture called CARE (Content-Aware Redundancy Elimination) for better utilizing network resources in disaster-affected regions. Motivated by measurement-driven insights on redundancy patterns found in real-world disaster area photos, we demonstrate that CARE can detect the semantic similarity between photos in the networking layer, thus reducing redundant transfers and improving buffer utilization. Using DTN simulations, we explore the boundaries of the usefulness of deploying CARE on a damaged network, and show that CARE can reduce packet delivery times and drops, and enables 20-40% more unique information to reach the rescue teams outside the disaster area than when CARE is not deployed.
A Survey on Various Data Hiding Techniques and their Comparative Analysis
Venue: arXiv cs.CR 2012
Year: 2012

With the explosive growth of internet and the fast communication techniques in recent years the security and the confidentiality of the sensitive data has become of prime and supreme importance and concern. To protect this data from unauthorized access and tampering various methods for data hiding like cryptography, hashing, authentication have been developed and are in practice today. In this paper we will be discussing one such data hiding technique called Steganography. Steganography is the process of concealing sensitive information in any media to transfer it securely over the underlying unreliable and unsecured communication network. Our paper presents a survey on various data hiding techniques in Steganography that are in practice today along with the comparative analysis of these techniques.
A Connectionist Network Approach to Find Numerical Solutions of Diophantine Equations
Venue: arXiv cs.NE 2012
Year: 2012

The paper introduces a connectionist network approach to find numerical solutions of Diophantine equations as an attempt to address the famous Hilbert's tenth problem. The proposed methodology uses a three layer feed forward neural network with back propagation as sequential learning procedure to find numerical solutions of a class of Diophantine equations. It uses a dynamically constructed network architecture where number of nodes in the input layer is chosen based on the number of variables in the equation. The powers of the given Diophantine equation are taken as input to the input layer. The training of the network starts with initial random integral weights. The weights are updated based on the back propagation of the error values at the output layer. The optimization of weights is augmented by adding a momentum factor into the network. The optimized weights of the connection between the input layer and the hidden layer are taken as numerical solution of the given Diophantine equation. The procedure is validated using different Diophantine Equations of different number of variables and different powers.
Communications-Inspired Projection Design with Application to Compressive Sensing
Venue: arXiv cs.IT 2012
Year: 2012

We consider the recovery of an underlying signal x \in C^m based on projection measurements of the form y=Mx+w, where y \in C^l and w is measurement noise; we are interested in the case l < m. It is assumed that the signal model p(x) is known, and w CN(w;0,S_w), for known S_W. The objective is to design a projection matrix M \in C^(l x m) to maximize key information-theoretic quantities with operational significance, including the mutual information between the signal and the projections I(x;y) or the Renyi entropy of the projections h_a(y) (Shannon entropy is a special case). By capitalizing on explicit characterizations of the gradients of the information measures with respect to the projections matrix, where we also partially extend the well-known results of Palomar and Verdu from the mutual information to the Renyi entropy domain, we unveil the key operations carried out by the optimal projections designs: mode exposure and mode alignment. Experiments are considered for the case of compressive sensing (CS) applied to imagery. In this context, we provide a demonstration of the performance improvement possible through the application of the novel projection designs in relation to conventional ones, as well as justification for a fast online projections design method with which state-of-the-art adaptive CS signal recovery is achieved.
An Energy Driven Architecture for Wireless Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

Most wireless sensor networks operate with very limited energy sources-their batteries, and hence their usefulness in real life applications is severely constrained. The challenging issues are how to optimize the use of their energy or to harvest their own energy in order to lengthen their lives for wider classes of application. Tackling these important issues requires a robust architecture that takes into account the energy consumption level of functional constituents and their interdependency. Without such architecture, it would be difficult to formulate and optimize the overall energy consumption of a wireless sensor network. Unlike most current researches that focus on a single energy constituent of WSNs independent from and regardless of other constituents, this paper presents an Energy Driven Architecture (EDA) as a new architecture and indicates a novel approach for minimising the total energy consumption of a WSN
Network Load Analysis and Provisioning of MapReduce Applications
Venue: arXiv cs.DC 2012
Year: 2012

In this paper, we study the dependency between configuration parameters and network load of fixed-size MapReduce applications in shuffle phase and then propose an analytical method to model this dependency. Our approach consists of three key phases: profiling, modeling, and prediction. In the first stage, an application is run several times with different sets of MapReduce configuration parameters (here number of mappers and number of reducers) to profile the network load of the application in the shuffle phase on a given cluster. Then, the relation between these parameters and the network load is modeled by multivariate linear regression. For evaluation, three applications (WordCount, Exim Mainlog parsing, and TeraSort) are utilized to evaluate our technique on a 4-node MapReduce private cluster.
Pixastic: Steganography based Anti-Phihsing Browser Plug-in
Venue: arXiv cs.CR 2012
Year: 2012

In spite of existence of many standard security mechanisms for ensuring secure e-Commerce business, users still fall prey for online attacks. One such simple but powerful attack is 'Phishing'. Phishing is the most alarming threat in the e-Commerce world and effective anti-phishing technique is the need of the hour. This paper focuses on a novel anti-phishing browser plug-in which uses information hiding technique - Steganography. A Robust Message based Image Steganography (RMIS) algorithm has been proposed. The same has been incorporated in the form of a browser plug-in (safari) called Pixastic. Pixastic is tested in an online banking scenario and it is compared with other well-known anti-phishing plug-in methods in practice. Various parameters such as robustness, usability and its behavior on various attacks have been analysed. From experimental results, it is evident that our method Pixastic performs well compared to other anti-phishing plug-ins.
Improved Inapproximability for TSP
Venue: arXiv cs.CC 2012
Year: 2012

The Traveling Salesman Problem is one of the most studied problems in computational complexity and its approximability has been a long standing open question. Currently, the best known inapproximability threshold known is 220/219 due to Papadimitriou and Vempala. Here, using an essentially different construction and also relying on the work of Berman and Karpinski on bounded occurrence CSPs, we give an alternative and simpler inapproximability proof which improves the bound to 185/184.
Generic Subsequence Matching Framework: Modularity, Flexibility, Efficiency
Venue: arXiv cs.MM 2012
Year: 2012

Subsequence matching has appeared to be an ideal approach for solving many problems related to the fields of data mining and similarity retrieval. It has been shown that almost any data class (audio, image, biometrics, signals) is or can be represented by some kind of time series or string of symbols, which can be seen as an input for various subsequence matching approaches. The variety of data types, specific tasks and their partial or full solutions is so wide that the choice, implementation and parametrization of a suitable solution for a given task might be complicated and time-consuming; a possibly fruitful combination of fragments from different research areas may not be obvious nor easy to realize. The leading authors of this field also mention the implementation bias that makes difficult a proper comparison of competing approaches. Therefore we present a new generic Subsequence Matching Framework (SMF) that tries to overcome the aforementioned problems by a uniform frame that simplifies and speeds up the design, development and evaluation of subsequence matching related systems. We identify several relatively separate subtasks solved differently over the literature and SMF enables to combine them in straightforward manner achieving new quality and efficiency. This framework can be used in many application domains and its components can be reused effectively. Its strictly modular architecture and openness enables also involvement of efficient solutions from different fields, for instance efficient metric-based indexes. This is an extended version of a paper published on DEXA 2012.
Implementation of the Domain-Specific Language EasyTime using a LISA Compiler Generator
Venue: arXiv cs.PL 2012
Year: 2012

A manually time-measuring tool in mass sporting competitions cannot be imagined nowadays because many modern disciplines, such as IronMan, take a long time and, therefore, demand additional reliability. Moreover, automatic timing devices, based on RFID technology, have become cheaper. However, these devices cannot operate stand-alone because they need a computer measuring system that is capable of processing the incoming events, encoding the results, assigning them to the correct competitor, sorting the results according to the achieved times, and then providing a printout of the results. In this article, the domain-specific language EasyTime is presented, which enables the controlling of an agent by writing the events in a database. In particular, we are focused on the implementation of EasyTime with a LISA tool that enables the automatic construction of compilers from language specifications using Attribute Grammars. By using of EasyTime, we can also decrease the number of measuring devices. Furthermore, EasyTime is universal and can be applied to many different sporting competitions in practice.
LP decoding of expander codes: a simpler proof
Venue: arXiv cs.IT 2012
Year: 2012

A code $C \subseteq \F_2^n$ is a $(c,ε,δ)$-expander code if it has a Tanner graph, where every variable node has degree $c$, and every subset of variable nodes $L_0$ such that $|L_0|\leq δn$ has at least $εc |L_0|$ neighbors. Feldman et al. (IEEE IT, 2007) proved that LP decoding corrects $\frac{3ε-2}{2ε-1} \cdot (δn-1)$ errors of $(c,ε,δ)$-expander code, where $ε> 2/3+\frac{1}{3c}$. In this paper, we provide a simpler proof of their result and show that this result holds for every expansion parameter $ε> 2/3$.
Dynamic Pattern Based Image Steganography
Venue: arXiv cs.CR 2012
Year: 2012

Steganography is the art of hiding secret information in media such as image, audio and video. The purpose of steganography is to conceal the existence of the secret information in any given medium. This work aims at strengthening the security in steganography algorithm by generating dynamic pattern in selection of indicator sequence. In addition to this dynamicity is also encompassed in number of bits embedded in data channel. This technique has been implemented and the results have been compared and evaluated with existing similar techniques.
IDS: An Incremental Learning Algorithm for Finite Automata
Venue: arXiv cs.LG 2012
Year: 2012

We present a new algorithm IDS for incremental learning of deterministic finite automata (DFA). This algorithm is based on the concept of distinguishing sequences introduced in (Angluin81). We give a rigorous proof that two versions of this learning algorithm correctly learn in the limit. Finally we present an empirical performance analysis that compares these two algorithms, focussing on learning times and different types of learning queries. We conclude that IDS is an efficient algorithm for software engineering applications of automata learning, such as testing and model inference.
Creating Interaction Scenarios With a New Graphical User Interface
Venue: arXiv cs.HC 2012
Year: 2012

The field of human-centered computing has known a major progress these past few years. It is admitted that this field is multidisciplinary and that the human is the core of the system. It shows two matters of concern: multidisciplinary and human. The first one reveals that each discipline plays an important role in the global research and that the collaboration between everyone is needed. The second one explains that a growing number of researches aims at making the human commitment degree increase by giving him/her a decisive role in the human-machine interaction. This paper focuses on these both concerns and presents MICE (Machines Interaction Control in their Environment) which is a system where the human is the one who makes the decisions to manage the interaction with the machines. In an ambient context, the human can decide of objects actions by creating interaction scenarios with a new visual programming language: scenL.
Sparse Distributed Learning Based on Diffusion Adaptation
Venue: arXiv cs.LG 2012
Year: 2012

This article proposes diffusion LMS strategies for distributed estimation over adaptive networks that are able to exploit sparsity in the underlying system model. The approach relies on convex regularization, common in compressive sensing, to enhance the detection of sparsity via a diffusive process over the network. The resulting algorithms endow networks with learning abilities and allow them to learn the sparse structure from the incoming data in real-time, and also to track variations in the sparsity of the model. We provide convergence and mean-square performance analysis of the proposed method and show under what conditions it outperforms the unregularized diffusion version. We also show how to adaptively select the regularization parameter. Simulation results illustrate the advantage of the proposed filters for sparse data recovery.