OpenRaiser/Intern-Atlas huggingface dataset:
Energy balancing through cluster head selection using K-Theorem in homogeneous wireless sensor networks
Venue: arXiv cs.NI 2012
Year: 2012

The objective of this paper is to increase life time of homogeneous wireless sensor networks (WSNs) through minimizing long range communication and energy balancing. Sensor nodes are resource constrained particularly with limited energy that is difficult or impossible to replenish. LEACH (Low Energy Adaptive Clustering Hierarchy) is most well-known cluster based architecture for WSN that aims to evenly dissipate energy among all sensor nodes. In cluster based architecture, the role of cluster head is very crucial for the successful operation of WSN because once the cluster head becomes non functional, the whole cluster becomes dysfunctional. We have proposed a modified cluster based WSN architecture by introducing a coordinator node (CN) that is rich in terms of resources. This CN take up the responsibility of transmitting data to the base station over longer distances from cluster heads. We have proposed a cluster head selection algorithm based on K-theorem and other parameters i.e. residual energy, distance to coordinator node, reliability and degree of mobility. The K-theorem is used to select candidate cluster heads based on bunch of sensor nodes in a cluster. We believe that the proposed architecture and algorithm achieves higher energy efficiency through minimizing communication and energy balancing. The proposed architecture is more scalable and proposed algorithm is robust against even/uneven node deployment and node mobility.
Learning the Gain Values and Discount Factors of DCG
Venue: arXiv cs.IR 2012
Year: 2012

Evaluation metrics are an essential part of a ranking system, and in the past many evaluation metrics have been proposed in information retrieval and Web search. Discounted Cumulated Gains (DCG) has emerged as one of the evaluation metrics widely adopted for evaluating the performance of ranking functions used in Web search. However, the two sets of parameters, gain values and discount factors, used in DCG are determined in a rather ad-hoc way. In this paper we first show that DCG is generally not coherent, meaning that comparing the performance of ranking functions using DCG very much depends on the particular gain values and discount factors used. We then propose a novel methodology that can learn the gain values and discount factors from user preferences over rankings. Numerical simulations illustrate the effectiveness of our proposed methods. Please contact the authors for the full version of this work.
Modeling Non-Uniform UE Distributions in Downlink Cellular Networks
Venue: arXiv cs.IT 2012
Year: 2012

A recent way to model and analyze downlink cellular networks is by using random spatial models. Assuming user equipment (UE) distribution to be uniform, the analysis is performed at a typical UE located at the origin. While this method of sampling UEs provides statistics averaged over the UE locations, it is not possible to sample cell interior and cell edge UEs separately. This complicates the problem of analyzing deployment scenarios involving non-uniform distribution of UEs, especially when the locations of the UEs and the base stations (BSs) are dependent. To facilitate this separation, we propose a new tractable method of sampling UEs by conditionally thinning the BS point process and show that the resulting framework can be used as a tractable generative model to study cellular networks with non-uniform UE distribution.
Keep Ballots Secret: On the Futility of Social Learning in Decision Making by Voting
Venue: arXiv cs.IT 2012
Year: 2012

We show that social learning is not useful in a model of team binary decision making by voting, where each vote carries equal weight. Specifically, we consider Bayesian binary hypothesis testing where agents have any conditionally-independent observation distribution and their local decisions are fused by any L-out-of-N fusion rule. The agents make local decisions sequentially, with each allowed to use its own private signal and all precedent local decisions. Though social learning generally occurs in that precedent local decisions affect an agent's belief, optimal team performance is obtained when all precedent local decisions are ignored. Thus, social learning is futile, and secret ballots are optimal. This contrasts with typical studies of social learning because we include a fusion center rather than concentrating on the performance of the latest-acting agents.
Complexity of super-coherence problems in ASP
Venue: arXiv cs.LO 2012
Year: 2012

Adapting techniques from database theory in order to optimize Answer Set Programming (ASP) systems, and in particular the grounding components of ASP systems, is an important topic in ASP. In recent years, the Magic Set method has received some interest in this setting, and a variant of it, called DMS, has been proposed for ASP. However, this technique has a caveat, because it is not correct (in the sense of being query-equivalent) for all ASP programs. In recent work, a large fragment of ASP programs, referred to as super-coherent programs, has been identified, for which DMS is correct. The fragment contains all programs which possess at least one answer set, no matter which set of facts is added to them. Two open question remained: How complex is it to determine whether a given program is super-coherent? Does the restriction to super-coherent programs limit the problems that can be solved? Especially the first question turned out to be quite difficult to answer precisely. In this paper, we formally prove that deciding whether a propositional program is super-coherent is Π^P_3-complete in the disjunctive case, while it is Π^P_2-complete for normal programs. The hardness proofs are the difficult part in this endeavor: We proceed by characterizing the reductions by the models and reduct models which the ASP programs should have, and then provide instantiations that meet the given specifications. Concerning the second question, we show that all relevant ASP reasoning tasks can be transformed into tasks over super-coherent programs, even though this transformation is more of theoretical than practical interest. To appear in Theory and Practice of Logic Programming (TPLP).
T-Base: A Triangle-Based Iterative Algorithm for Smoothing Quadrilateral Meshes
Venue: arXiv cs.CG 2012
Year: 2012

We present a novel approach named TBase for smoothing planar and surface quadrilateral meshes. Our motivation is that the best shape of quadrilateral element (square) can be virtually divided into a pair of equilateral right triangles by any of its diagonals. When move a node to smooth a quadrilateral, it is optimal to make a pair of triangles divided by a diagonal be equilateral right triangles separately. The finally smoothed position is obtained by weighting all individual optimal positions. Three variants are produced according to the determination of weights. Tests by the TBase are given and compared with Laplacian smoothing: The Vari.1 of TBase is effectively identical to Laplacian smoothing for planar quad meshes, while Vari.2 is the best. For the quad mesh on underlying parametric surface and interpolation surface, Vari.2 and Vari.1 are best, respectively.
Ear-clipping Based Algorithms of Generating High-quality Polygon Triangulation
Venue: arXiv cs.CG 2012
Year: 2012

A basic and an improved ear clipping based algorithm for triangulating simple polygons and polygons with holes are presented. In the basic version, the ear with smallest interior angle is always selected to be cut in order to create fewer sliver triangles. To reduce sliver triangles in further, a bound of angle is set to determine whether a newly formed triangle has sharp angles, and edge swapping is accepted when the triangle is sharp. To apply the two algorithms on polygons with holes, "Bridge" edges are created to transform a polygon with holes to a degenerate polygon which can be triangulated by the two algorithms. Applications show that the basic algorithm can avoid creating sliver triangles and obtain better triangulations than the traditional ear clipping algorithm, and the improved algorithm can in further reduce sliver triangles effectively. Both of the algorithms run in O(n2) time and O(n) space.
Toward New Vision in Teaching Calculus
Venue: arXiv cs.CY 2012
Year: 2012

Usually the first course in mathematics is calculus. Its a core course in the curriculum of the Business, Engineering and the Sciences. However many students face difficulties to learn calculus. These difficulties are often caused by the prior fear of mathematics. The students today cant live without using computer technology. The uses of computer for teaching and learning can transform the boring traditional methodology of teach to more active and attractive method. In this paper, we will show how we can use Excel in teaching calculus to improve our students learning and understanding through different types of applications ranging from Business to Engineering. The effectiveness of the proposed methodology was tested on a random sample of 45 students from different majors over a period of two semesters.
XML parser GUI using .NET Technology
Venue: arXiv cs.SE 2012
Year: 2012

The purpose of this paper is to implement software that can save time, effort, and facilitate XML and XSL programming. The XML parser helps the programmer to determine whether the XML document is Well-formed or not, by specifying if any the positions of the errors.
Applying Social Network Analysis to Analyze a Web-Based Community
Venue: arXiv cs.SI 2012
Year: 2012

This paper deals with a very renowned website (that is Book-Crossing) from two angles: The first angle focuses on the direct relations between users and books. Many things can be inferred from this part of analysis such as who is more interested in book reading than others and why? Which books are most popular and which users are most active and why? The task requires the use of certain social network analysis measures (e.g. degree centrality). What does it mean when two users like the same book? Is it the same when other two users have one thousand books in common? Who is more likely to be a friend of whom and why? Are there specific people in the community who are more qualified to establish large circles of social relations? These questions (and of course others) were answered through the other part of the analysis, which will take us to probe the potential social relations between users in this community. Although these relationships do not exist explicitly, they can be inferred with the help of affiliation network analysis and techniques such as m-slice.
Automatic approach for generating ETL operators
Venue: arXiv cs.DB 2012
Year: 2012

This article addresses the generation of the ETL operators(Extract-Transform-Load) for supplying a Data Warehouse from a relational data source. As a first step, we add new rules to those proposed by the authors of [1], these rules deal with the combination of ETL operators. In a second step, we propose an automatic approach based on model transformations to generate the ETL operations needed for loading a data warehouse. This approach offers the possibility to set some designer requirements for loading.
Prover and Verifier Based Password Protection: PVBPP
Venue: arXiv cs.CR 2012
Year: 2012

In today's world password are mostly used for authentication. This makes them prone to various kinds of attacks like dictionary attacks. A dictionary attack is a method of breaking the password by systematically entering every word in a dictionary as a password. This attack leads to an overload on the server leading to denial of service attack. This paper presents a protocol to reduce the rate of dictionary attack by using a prover and a verifier system. This system makes it difficult for the attacker to prove it as a valid user by becoming computationally intensive. The rate of attempts is also reduced and thus restricting the Denial of Service attack.
Irrespective Priority-Based Regular Properties of High-Intensity Virtual Environments
Venue: arXiv cs.AI 2012
Year: 2012

We have a lot of relation to the encoding and the Theory of Information, when considering thinking. This is a natural process and, at once, the complex thing we investigate. This always was a challenge - to understand how our mind works, and we are trying to find some universal models for this. A lot of ways have been considered so far, but we are looking for Something, we seek for approaches. And the goal is to find a consistent, noncontradictory view, which should at once be enough flexible in any dimensions to allow to represent various kinds of processes and environments, matters of different nature and diverse objects. Developing of such a model is the destination of this article.
Computer-Assisted Interactive Documentary and Performance Arts in Illimitable Space
Venue: arXiv cs.MM 2012
Year: 2012

This major component of the research described in this thesis is 3D computer graphics, specifically the realistic physics-based softbody simulation and haptic responsive environments. Minor components include advanced human-computer interaction environments, non-linear documentary storytelling, and theatre performance. The journey of this research has been unusual because it requires a researcher with solid knowledge and background in multiple disciplines; who also has to be creative and sensitive in order to combine the possible areas into a new research direction. [...] It focuses on the advanced computer graphics and emerges from experimental cinematic works and theatrical artistic practices. Some development content and installations are completed to prove and evaluate the described concepts and to be convincing. [...] To summarize, the resulting work involves not only artistic creativity, but solving or combining technological hurdles in motion tracking, pattern recognition, force feedback control, etc., with the available documentary footage on film, video, or images, and text via a variety of devices [....] and programming, and installing all the needed interfaces such that it all works in real-time. Thus, the contribution to the knowledge advancement is in solving these interfacing problems and the real-time aspects of the interaction that have uses in film industry, fashion industry, new age interactive theatre, computer games, and web-based technologies and services for entertainment and education. It also includes building up on this experience to integrate Kinect- and haptic-based interaction, artistic scenery rendering, and other forms of control. This research work connects all the research disciplines, seemingly disjoint fields of research, such as computer graphics, documentary film, interactive media, and theatre performance together.
A brief experience on journey through hardware developments for image processing and its applications on Cryptography
Venue: arXiv cs.AR 2012
Year: 2012

The importance of embedded applications on image and video processing,communication and cryptography domain has been taking a larger space in current research era. Improvement of pictorial information for betterment of human perception like deblurring, de-noising in several fields such as satellite imaging, medical imaging etc are renewed research thrust. Specifically we would like to elaborate our experience on the significance of computer vision as one of the domains where hardware implemented algorithms perform far better than those implemented through software. So far embedded design engineers have successfully implemented their designs by means of Application Specific Integrated Circuits (ASICs) and/or Digital Signal Processors (DSP), however with the advancement of VLSI technology a very powerful hardware device namely the Field Programmable Gate Array (FPGA) combining the key advantages of ASICs and DSPs was developed which have the possibility of reprogramming making them a very attractive device for rapid prototyping.Communication of image and video data in multiple FPGA is no longer far away from the thrust of secured transmission among them, and then the relevance of cryptography is indeed unavoidable. This paper shows how the Xilinx hardware development platform as well Mathworks Matlab can be used to develop hardware based computer vision algorithms and its corresponding crypto transmission channel between multiple FPGA platform from a system level approach, making it favourable for developing a hardware-software co-design environment.
Explicit-Value Analysis Based on CEGAR and Interpolation
Venue: arXiv cs.SE 2012
Year: 2012

Abstraction, counterexample-guided refinement, and interpolation are techniques that are essential to the success of predicate-based program analysis. These techniques have not yet been applied together to explicit-value program analysis. We present an approach that integrates abstraction and interpolation-based refinement into an explicit-value analysis, i.e., a program analysis that tracks explicit values for a specified set of variables (the precision). The algorithm uses an abstract reachability graph as central data structure and a path-sensitive dynamic approach for precision adjustment. We evaluate our algorithm on the benchmark set of the Competition on Software Verification 2012 (SV-COMP'12) to show that our new approach is highly competitive. In addition, we show that combining our new approach with an auxiliary predicate analysis scores significantly higher than the SV-COMP'12 winner.
Social Teaching: Being Informative vs. Being Right in Sequential Decision Making
Venue: arXiv cs.IT 2012
Year: 2012

We show that it can be suboptimal for Bayesian decision-making agents employing social learning to use correct prior probabilities as their initial beliefs. We consider sequential Bayesian binary hypothesis testing where each individual agent makes a binary decision based on an initial belief, a private signal, and the decisions of all earlier-acting agents---with the actions of precedent agents causing updates of the initial belief. Each agent acts to minimize Bayes risk, with all agents sharing the same Bayes costs for Type I (false alarm) and Type II (missed detection) errors. The effect of the set of initial beliefs on the decision-making performance of the last agent is studied. The last agent makes the best decision when the initial beliefs are inaccurate. When the private signals are described by Gaussian likelihoods, the optimal initial beliefs are not haphazard but rather follow a systematic pattern: the earlier-acting agents should act as if the prior probability is larger than it is in reality when the true prior probability is small, and vice versa. We interpret this as being open minded toward the unlikely hypothesis. The early-acting agents face a trade-off between making a correct decision and being maximally informative to the later-acting agents.
Multidimensional Analytic Signals and the Bedrosian Identity
Venue: arXiv cs.IT 2012
Year: 2012

The analytic signal method via the Hilbert transform is a key tool in signal analysis and processing, especially in the time-frquency analysis. Imaging and other applications to multidimensional signals call for extension of the method to higher dimensions. We justify the usage of partial Hilbert transforms to define multidimensional analytic signals from both engineering and mathematical perspectives. The important associated Bedrosian identity $T(fg)=fTg$ for partial Hilbert transforms $T$ are then studied. Characterizations and several necessity theorems are established. We also make use of the identity to construct basis functions for the time-frequency analysis.
Exploring Relay Cooperation Scheme for Load-Balance Control in Two-hop Secure Communication System
Venue: arXiv cs.IT 2012
Year: 2012

This work considers load-balance control among the relays under the secure transmission protocol via relay cooperation in two-hop wireless networks without the information of both eavesdropper channels and locations. The available two-hop secure transmission protocols in physical layer secrecy framework cannot provide a flexible load-balance control, which may significantly limit their application scopes. This paper proposes a secure transmission protocol in case that the path-loss is identical between all pairs of nodes, in which the relay is randomly selected from the first $k$ preferable assistant relays. This protocol enables load-balance among relays to be flexibly controlled by a proper setting of the parameter $k$, and covers the available works as special cases, like ones with the optimal relay selection ($k=1$) and ones with the random relay selection ($k = n$, i.e. the number of system nodes). The theoretic analysis is further provided to determine the maximum number of eavesdroppers one network can tolerate by applying the proposed protocol to ensure a desired performance in terms of the secrecy outage probability and transmission outage probability.
Early Warning Analysis for Social Diffusion Events
Venue: arXiv cs.SI 2012
Year: 2012

There is considerable interest in developing predictive capabilities for social diffusion processes, for instance to permit early identification of emerging contentious situations, rapid detection of disease outbreaks, or accurate forecasting of the ultimate reach of potentially viral ideas or behaviors. This paper proposes a new approach to this predictive analytics problem, in which analysis of meso-scale network dynamics is leveraged to generate useful predictions for complex social phenomena. We begin by deriving a stochastic hybrid dynamical systems (S-HDS) model for diffusion processes taking place over social networks with realistic topologies; this modeling approach is inspired by recent work in biology demonstrating that S-HDS offer a useful mathematical formalism with which to represent complex, multi-scale biological network dynamics. We then perform formal stochastic reachability analysis with this S-HDS model and conclude that the outcomes of social diffusion processes may depend crucially upon the way the early dynamics of the process interacts with the underlying network's community structure and core-periphery structure. This theoretical finding provides the foundations for developing a machine learning algorithm that enables accurate early warning analysis for social diffusion events. The utility of the warning algorithm, and the power of network-based predictive metrics, are demonstrated through an empirical investigation of the propagation of political memes over social media networks. Additionally, we illustrate the potential of the approach for security informatics applications through case studies involving early warning analysis of large-scale protests events and politically-motivated cyber attacks.
Fast Solutions to Projective Monotone Linear Complementarity Problems
Venue: arXiv cs.LG 2012
Year: 2012

We present a new interior-point potential-reduction algorithm for solving monotone linear complementarity problems (LCPs) that have a particular special structure: their matrix $M\in{\mathbb R}^{n\times n}$ can be decomposed as $M=ΦU + Π_0$, where the rank of $Φ$ is $k<n$, and $Π_0$ denotes Euclidean projection onto the nullspace of $Φ^\top$. We call such LCPs projective. Our algorithm solves a monotone projective LCP to relative accuracy $ε$ in $O(\sqrt n \ln(1/ε))$ iterations, with each iteration requiring $O(nk^2)$ flops. This complexity compares favorably with interior-point algorithms for general monotone LCPs: these algorithms also require $O(\sqrt n \ln(1/ε))$ iterations, but each iteration needs to solve an $n\times n$ system of linear equations, a much higher cost than our algorithm when $k\ll n$. Our algorithm works even though the solution to a projective LCP is not restricted to lie in any low-rank subspace.