OpenRaiser/Intern-Atlas huggingface dataset:
Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images
Venue: arXiv cs.CV 2014
Year: 2014

A novel coding strategy for block-based compressive sens-ing named spatially directional predictive coding (SDPC) is proposed, which efficiently utilizes the intrinsic spatial cor-relation of natural images. At the encoder, for each block of compressive sensing (CS) measurements, the optimal pre-diction is selected from a set of prediction candidates that are generated by four designed directional predictive modes. Then, the resulting residual is processed by scalar quantiza-tion (SQ). At the decoder, the same prediction is added onto the de-quantized residuals to produce the quantized CS measurements, which is exploited for CS reconstruction. Experimental results substantiate significant improvements achieved by SDPC-plus-SQ in rate distortion performance as compared with SQ alone and DPCM-plus-SQ.
A Smart Intelligent Way of Video Authentication Using Classification and Decomposition of Watermarking Methods
Venue: arXiv cs.MM 2014
Year: 2014

Video Watermarking serves as a new technology mainly used to provide security to the illegal distribution of digital video over the web. The purpose of any video watermarking scheme is to embed extra information into video in such a way that must be perceptually undetectable while still holding enough information in order to extract the watermark beginning with the resultant video. Information which is embedded within the original image is a Digital Watermark, which could be visible or invisible. To improved more security, embedding and extraction Watermark process should be complex against attackers. Recent research indicates SVD (Singular Value Decomposition) algorithms are employed owing to their simple scheme with mathematical function. In this proposed work an advanced SVD transformation algorithm is used for embedding and extraction process. Experimental results show proposed watermarking process is more secured than existing SVD approach.
Assessing the players'performance in the game of bridge: A fuzzy logic approach
Venue: arXiv cs.AI 2014
Year: 2014

Contract bridge occupies nowadays a position of great prestige being, together with chess, the only mind games officially recognized by the International Olympic Committee. In the present paper an innovative method for assessing the total performance of bridge- players' belonging to groups of special interest(e.g. different bridge clubs during a tournament, men and women, new and old players, etc) is introduced, which is based on principles of fuzzy logic. For this, the cohorts under assessment are represented as fuzzy subsets of a set of linguistic labels characterizing their performance and the centroid defuzzification method is used to convert the fuzzy data collected from the game to a crisp number. This new method of assessment could be used informally as a complement of the official bridge-scoring methods for statistical and other obvious reasons. Two real applications related to simultaneous tournaments with pre-dealt boards, organized by the Hellenic Bridge Federation, are also presented, illustrating the importance of our results in practice.
Building active and collaborative learning environment in introductory physics course of faculty of technology education
Venue: arXiv cs.CY 2014
Year: 2014

Model of active and collaborative learning applied in training specific subject makes clear advantage due to the goals of knowledge, enhanced activeness, skills that students got to develop successful future job. Studying and applying the model to build a learning environment in the Introductory Physics course with the support of ICT, especially social network and eLearning system of HNUE.
An Introduction to the Patstat Database with Example Queries
Venue: arXiv cs.DL 2014
Year: 2014

This paper provides an introduction to the Patstat patent database. It offers guided examples of ten popular queries that are relevant for research purposes and that cover the most important data tables. It is targeted at academic researchers and practitioners willing to learn the basics of the database.
Automatic Differentiation of Algorithms for Machine Learning
Venue: arXiv cs.LG 2014
Year: 2014

Automatic differentiation---the mechanical transformation of numeric computer programs to calculate derivatives efficiently and accurately---dates to the origin of the computer age. Reverse mode automatic differentiation both antedates and generalizes the method of backwards propagation of errors used in machine learning. Despite this, practitioners in a variety of fields, including machine learning, have been little influenced by automatic differentiation, and make scant use of available tools. Here we review the technique of automatic differentiation, describe its two main modes, and explain how it can benefit machine learning practitioners. To reach the widest possible audience our treatment assumes only elementary differential calculus, and does not assume any knowledge of linear algebra.
The Power of Two Choices in Distributed Voting
Venue: arXiv cs.DS 2014
Year: 2014

Distributed voting is a fundamental topic in distributed computing. In pull voting, in each step every vertex chooses a neighbour uniformly at random, and adopts its opinion. The voting is completed when all vertices hold the same opinion. On many graph classes including regular graphs, pull voting requires $Θ(n)$ expected steps to complete, even if initially there are only two distinct opinions. In this paper we consider a related process which we call two-sample voting: every vertex chooses two random neighbours in each step. If the opinions of these neighbours coincide, then the vertex revises its opinion according to the chosen sample. Otherwise, it keeps its own opinion. We consider the performance of this process in the case where two different opinions reside on vertices of some (arbitrary) sets $A$ and $B$, respectively. Here, $|A| + |B| = n$ is the number of vertices of the graph. We show that there is a constant $K$ such that if the initial imbalance between the two opinions is ?$ν_0 = (|A| - |B|)/n \geq K \sqrt{(1/d) + (d/n)}$, then with high probability two sample voting completes in a random $d$ regular graph in $O(\log n)$ steps and the initial majority opinion wins. We also show the same performance for any regular graph, if $ν_0 \geq K λ_2$ where $λ_2$ is the second largest eigenvalue of the transition matrix. In the graphs we consider, standard pull voting requires $Ω(n)$ steps, and the minority can still win with probability $|B|/n$.
Recognizable Series on Hypergraphs
Venue: arXiv cs.FL 2014
Year: 2014

We introduce the notion of Hypergraph Weighted Model (HWM) that generically associates a tensor network to a hypergraph and then computes a value by tensor contractions directed by its hyperedges. A series r defined on a hypergraph family is said to be recognizable if there exists a HWM that computes it. This model generalizes the notion of rational series on strings and trees. We prove some properties of the model and study at which conditions finite support series are recognizable.
A formal experiment to assess the efficacy of certification standards
Venue: arXiv cs.SE 2014
Year: 2014

Proving the efficacy of certification standards
Faster Transaction Commit even when Nodes Crash
Venue: arXiv cs.DC 2014
Year: 2014

Atomic broadcasts play a central role in serialisable in-memory transactions. Best performing ones block, when a node crashes, until a new view is installed. We augment a new protocol for uninterrupted progress in the interim period.
End-users needs and requirements for tools to support critical infrastructures protection
Venue: arXiv cs.SE 2014
Year: 2014

The role of the services described in this paper is to support decisions in the Critical Infrastructure Protection (CIP) domain. Those services are perceived as the most fundamental functionalities, that will serve as a basis for the planned European simulation centre for modelling the behaviour of Critical Infrastructures (CI). The proposed services are: CI-related data accessing and gathering, threat forecasting and visualisation, consequence analysis, crowd management, as well as resources and capability management. In general, services proposed in the current paper will contribute to reducing the problem of overwhelming decision makers by too large amount of information. In the crisis, their decisions are made on the basis of the large amount of data related to the current situation, such as the status of CI, localisation of capabilities, weather and threat forecasts etc. The design of the services has been established with the help of the future end-users. The work presented in this paper is the result of preliminary activities performed in the FP7 project CIPRNet.
Investigating SCADA Failures in Interdependent Critical Infrastructure Systems
Venue: arXiv cs.SE 2014
Year: 2014

This paper is based on the initial ideas of a PhD proposal which will investigate SCADA failures in physical infrastructure systems. The results will be used to develop a new notation to help risk assessment using dependable computing concepts. SCADA systems are widely used within critical infrastructures to perform system controls and deliver services to linked and dependent systems. Failures in SCADA systems will be investigated to help us understand and prevent cascading failures in future.
Continuous Matrix Approximation on Distributed Data
Venue: arXiv cs.DB 2014
Year: 2014

Tracking and approximating data matrices in streaming fashion is a fundamental challenge. The problem requires more care and attention when data comes from multiple distributed sites, each receiving a stream of data. This paper considers the problem of "tracking approximations to a matrix" in the distributed streaming model. In this model, there are m distributed sites each observing a distinct stream of data (where each element is a row of a distributed matrix) and has a communication channel with a coordinator, and the goal is to track an eps-approximation to the norm of the matrix along any direction. To that end, we present novel algorithms to address the matrix approximation problem. Our algorithms maintain a smaller matrix B, as an approximation to a distributed streaming matrix A, such that for any unit vector x: | ||A x||^2 - ||B x||^2 | <= eps ||A||_F^2. Our algorithms work in streaming fashion and incur small communication, which is critical for distributed computation. Our best method is deterministic and uses only O((m/eps) log(beta N)) communication, where N is the size of stream (at the time of the query) and beta is an upper-bound on the squared norm of any row of the matrix. In addition to proving all algorithmic properties theoretically, extensive experiments with real large datasets demonstrate the efficiency of these protocols.
Dynamic Mode Decomposition for Real-Time Background/Foreground Separation in Video
Venue: arXiv cs.CV 2014
Year: 2014

This paper introduces the method of dynamic mode decomposition (DMD) for robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. The method is a novel application of a technique used for characterizing nonlinear dynamical systems in an equation-free manner by decomposing the state of the system into low-rank terms whose Fourier components in time are known. DMD terms with Fourier frequencies near the origin (zero-modes) are interpreted as background (low-rank) portions of the given video frames, and the terms with Fourier frequencies bounded away from the origin are their sparse counterparts. An approximate low-rank/sparse separation is achieved at the computational cost of just one singular value decomposition and one linear equation solve, thus producing results orders of magnitude faster than a leading separation method, namely robust principal component analysis (RPCA). The DMD method that is developed here is demonstrated to work robustly in real-time with personal laptop-class computing power and without any parameter tuning, which is a transformative improvement in performance that is ideal for video surveillance and recognition applications.
The stable set polytope of ($P_6$,triangle)-free graphs and new facet-inducing graphs
Venue: arXiv cs.DM 2014
Year: 2014

The stable set polytope of a graph $G$, denoted as STAB($G$), is the convex hull of all the incidence vectors of stable sets of $G$. To describe a linear system which defines STAB($G$) seems to be a difficult task in the general case. In this paper we present a complete description of the stable set polytope of ($P_6$,triangle)-free graphs (and more generally of ($P_6$,paw)-free graphs). For that we combine different tools, in the context of a well known result of Chvátal \cite{Chvatal1975} which allows to focus just on prime facet-inducing graphs, with particular reference to a structure result on prime ($P_6$,triangle)-free graphs due to Brandstädt et al. \cite{BraKleMah2005}. Also we point out some peculiarities of new facet-inducing graphs detected along this study with the help of a software.
Determining Majority in Networks with Local Interactions and very Small Local Memory
Venue: arXiv cs.DC 2014
Year: 2014

We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. The vertices may have a few additional possible states and can interact in pairs only if they share an edge. Any (population) protocol is required to stabilize in the initial majority. We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. We study the performance of this protocol in arbitrary networks. We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is $n - Θ(\ln{n})$. We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. Surprisingly, the resistance of the clique to failure causes the failure in general graphs. Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved.
On User Availability Prediction and Network Applications
Venue: arXiv cs.DC 2014
Year: 2014

User connectivity patterns in network applications are known to be heterogeneous, and to follow periodic (daily and weekly) patterns. In many cases, the regularity and the correlation of those patterns is problematic: for network applications, many connected users create peaks of demand; in contrast, in peer-to-peer scenarios, having few users online results in a scarcity of available resources. On the other hand, since connectivity patterns exhibit a periodic behavior, they are to some extent predictable. This work shows how this can be exploited to anticipate future user connectivity and to have applications proactively responding to it. We evaluate the probability that any given user will be online at any given time, and assess the prediction on six-month availability traces from three different Internet applications. Building upon this, we show how our probabilistic approach makes it easy to evaluate and optimize the performance in a number of diverse network application models, and to use them to optimize systems. In particular, we show how this approach can be used in distributed hash tables, friend-to-friend storage, and cache pre-loading for social networks, resulting in substantial gains in data availability and system efficiency at negligible costs.
Between Treewidth and Clique-width
Venue: arXiv cs.DS 2014
Year: 2014

Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set that are all FPT parameterized by treewidth but none of which can be FPT parameterized by clique-width unless FPT = W[1], as shown by Fomin et al [7, 8]. We therefore seek a structural graph parameter that shares some of the generality of clique-width without paying this price. Based on splits, branch decompositions and the work of Vatshelle [18] on Maximum Matching-width, we consider the graph parameter sm-width which lies between treewidth and clique-width. Some graph classes of unbounded treewidth, like distance-hereditary graphs, have bounded sm-width. We show that MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set are all FPT parameterized by sm-width.
Parameterized Complexity of Bandwidth on Trees
Venue: arXiv cs.DS 2014
Year: 2014

The bandwidth of a $n$-vertex graph $G$ is the smallest integer $b$ such that there exists a bijective function $f : V(G) \rightarrow \{1,...,n\}$, called a layout of $G$, such that for every edge $uv \in E(G)$, $|f(u) - f(v)| \leq b$. In the {\sc Bandwidth} problem we are given as input a graph $G$ and integer $b$, and asked whether the bandwidth of $G$ is at most $b$. We present two results concerning the parameterized complexity of the {\sc Bandwidth} problem on trees. First we show that an algorithm for {\sc Bandwidth} with running time $f(b)n^{o(b)}$ would violate the Exponential Time Hypothesis, even if the input graphs are restricted to be trees of pathwidth at most two. Our lower bound shows that the classical $2^{O(b)}n^{b+1}$ time algorithm by Saxe [SIAM Journal on Algebraic and Discrete Methods, 1980] is essentially optimal. Our second result is a polynomial time algorithm that given a tree $T$ and integer $b$, either correctly concludes that the bandwidth of $T$ is more than $b$ or finds a layout of $T$ of bandwidth at most $b^{O(b)}$. This is the first parameterized approximation algorithm for the bandwidth of trees.
Study of Timing Synchronization in MIMO-OFDM Systems Using DVB-T
Venue: arXiv cs.IT 2014
Year: 2014

OFDM (Orthogonal Frequency Division Multiplexing)provides the promising physical layer for 4G and 3GPP LTE Systems in terms of efficient use of bandwidth and data rates. This paper highlights the implementation of OFDM in Digital Video Broadcasting-Terrestrial (DVB-T). It mainly focuses on the timing offset problem present in OFDM systems and its proposed solution using Cyclic Prefix (CP) as a modified SC (Schmidl and COX) algorithm. It also highlights the timing synchronization as well as performance comparison through bit error rate. Synchronization issues in OFDM are important and can lead to information loss if not properly addressed. Simulations were performed to implement DVB-T system and to compare different synchronization methods under certain distribution model.
Belief Revision and Trust
Venue: arXiv cs.AI 2014
Year: 2014

Belief revision is the process in which an agent incorporates a new piece of information together with a pre-existing set of beliefs. When the new information comes in the form of a report from another agent, then it is clear that we must first determine whether or not that agent should be trusted. In this paper, we provide a formal approach to modeling trust as a pre-processing step before belief revision. We emphasize that trust is not simply a relation between agents; the trust that one agent has in another is often restricted to a particular domain of expertise. We demonstrate that this form of trust can be captured by associating a state-partition with each agent, then relativizing all reports to this state partition before performing belief revision. In this manner, we incorporate only the part of a report that falls under the perceived domain of expertise of the reporting agent. Unfortunately, state partitions based on expertise do not allow us to compare the relative strength of trust held with respect to different agents. To address this problem, we introduce pseudometrics over states to represent differing degrees of trust. This allows us to incorporate simultaneous reports from multiple agents in a way that ensures the most trusted reports will be believed.
A Mobile Management System for Reforming Subsidies Distribution in Developing Countries
Venue: arXiv cs.CY 2014
Year: 2014

This paper has a specific objective of being useful for showing how the advances in mobile technologies can help for solving social and political aspects involved in the reform of subsidies in developing countries. It describes the work done to build a mobile-based supportive network that integrates all subsidies partners: governmental, non-governmental organizations, merchants, and beneficiaries. One main contribution of this work is the setting of a framework for identifying the requirements of subsidies distribution information systems. In the proposed approach, seven domains were identified to build a Mobile Subsidizing Business Model (MSBM). Based on MSBM, detailed requirements were gathered in three stages, with each having its appropriate methodology. In this work, we focus on the layered architecture implementation of the subsidizing mobile system to breakdown the complexities, which are due to variations of mobile technologies, different business rules, and multiple distribution scenarios.
Clome: The Practical Implications of a Cloud-based Smart Home
Venue: arXiv cs.CY 2014
Year: 2014

A rich body of work in recent years has advocated the use of cloud technologies within a home environment, but nothing has materialized so far in terms of real-world implementations. In this paper, we argue that this is due to the fact that none of these proposals have addressed some of the practical challenges of moving home applications to the cloud. Specifically, we discuss the pragmatic implications of moving to the cloud including, data and information security, increase in network traffic, and fault tolerance. To elicit discussion, we take a clean-slate approach and introduce a proof-of-concept smart home, dubbed Clome, that decouples non-trivial computation from home applications and transfers it to the cloud. We also discuss how a Clome-like smart home with decentralized processing and storage can be enabled through OpenFlow programmable switches, home-centric programming platforms, and thin-client computing.