OpenRaiser/Intern-Atlas huggingface dataset:
Agent-Based μ-Tools Integrated into a Co-Design Platform
Venue: arXiv cs.HC 2012
Year: 2012

In this paper we present successively the proposition and the design of: 1) μ-tools adapted to collaborative activity of design, and 2) a multi-agent platform adapted to innovative and distributed design of products or services. This platform called PLACID (innovating and distributed design platform) must support applications of assistance to actors implies in a design process that we have called μ-tools. μ-tools are developed with an aim of bringing assistance to Co-design. The use of the paradigm agent as well relates to the modeling and the development of various layers of the platform, that those of the human-computer interfaces. With these objectives, constraints are added to facilitate the integration of new co-operative tools.
Floating-Point Arithmetic on Round-to-Nearest Representations
Venue: arXiv cs.NA 2012
Year: 2012

Recently we introduced a class of number representations denoted RN-representations, allowing an un-biased rounding-to-nearest to take place by a simple truncation. In this paper we briefly review the binary fixed-point representation in an encoding which is essentially an ordinary 2's complement representation with an appended round-bit. Not only is this rounding a constant time operation, so is also sign inversion, both of which are at best log-time operations on ordinary 2's complement representations. Addition, multiplication and division is defined in such a way that rounding information can be carried along in a meaningful way, at minimal cost. Based on the fixed-point encoding we here define a floating point representation, and describe to some detail a possible implementation of a floating point arithmetic unit employing this representation, including also the directed roundings.
A comparison algorithm to check LTSA Layer 1 and SCORM compliance in e-Learning sites
Venue: arXiv cs.OH 2012
Year: 2012

The success of e-Learning is largely dependent on the impact of its multimedia aided learning content on the learner over the hyper media. The e-Learning portals with different proportion of multimedia elements have different impact on the learner, as there is lack of standardization. The Learning Technology System Architecture (LTSA) Layer 1 deals with the effect of environment on the learner. From an information technology perspective it specifies learner interaction from the environment to the learner via multimedia content. Sharable Content Object Reference Model (SCROM) is a collection of standards and specifications for content of web-based e-learning and specifies how JavaScript API can be used to integrate content development. In this paper an examination is made on the design features of interactive multimedia components of the learning packages by creating an algorithm which will give a comparative study of multimedia component used by different learning packages. The resultant graph as output helps us to analysis to what extent any LMS compliance LTSA layer 1 and SCORM specification.
Fault Localization for Java Programs using Probabilistic Program Dependence Graph
Venue: arXiv cs.SE 2012
Year: 2012

Fault localization is a process to find the location of faults. It determines the root cause of the failure. It identifies the causes of abnormal behaviour of a faulty program. It identifies exactly where the bugs are. Existing fault localization techniques are Slice based technique, Program- Spectrum based Technique, Statistics Based Technique, Program State Based Technique, Machine learning based Technique and Similarity Based Technique. In the proposed method Model Based Fault Localization Technique is used, which is called Probabilistic Program Dependence Graph . Probabilistic Program Dependence Graph (PPDG) is an innovative model that scans the internal behaviour of the project. PPDG construction is enhanced by Program Dependence Graph (PDG). PDG is achieved by the Control Flow Graph (CFG). The PPDG construction augments the structural dependences represented by a program dependence graph with estimates of statistical dependences between node states, which are computed from the test set. The PPDG is based on the established framework of probabilistic graphical models. This work presents algorithms for constructing PPDGs and applying fault localization.
Staircase Codes: FEC for 100 Gb/s OTN
Venue: arXiv cs.IT 2012
Year: 2012

Staircase codes, a new class of forward-error-correction (FEC) codes suitable for high-speed optical communications, are introduced. An ITU-T G.709-compatible staircase code with rate R=239/255 is proposed, and FPGA-based simulation results are presented, exhibiting a net coding gain (NCG) of 9.41 dB at an output error rate of 1E-15, an improvement of 0.42 dB relative to the best code from the ITU-T G.975.1 recommendation. An error floor analysis technique is presented, and the proposed code is shown to have an error floor at 4.0E-21.
Optimal Threshold Control by the Robots of Web Search Engines with Obsolescence of Documents
Venue: arXiv cs.NI 2012
Year: 2012

A typical web search engine consists of three principal parts: crawling engine, indexing engine, and searching engine. The present work aims to optimize the performance of the crawling engine. The crawling engine finds new web pages and updates web pages existing in the database of the web search engine. The crawling engine has several robots collecting information from the Internet. We first calculate various performance measures of the system (e.g., probability of arbitrary page loss due to the buffer overflow, probability of starvation of the system, the average time waiting in the buffer). Intuitively, we would like to avoid system starvation and at the same time to minimize the information loss. We formulate the problem as a multi-criteria optimization problem and attributing a weight to each criterion. We solve it in the class of threshold policies. We consider a very general web page arrival process modeled by Batch Marked Markov Arrival Process and a very general service time modeled by Phase-type distribution. The model has been applied to the performance evaluation and optimization of the crawler designed by INRIA Maestro team in the framework of the RIAM INRIA-Canon research project.
Iterative Approximate Byzantine Consensus in Arbitrary Directed Graphs
Venue: arXiv cs.DC 2012
Year: 2012

In this paper, we explore the problem of iterative approximate Byzantine consensus in arbitrary directed graphs. In particular, we prove a necessary and sufficient condition for the existence of iterative byzantine consensus algorithms. Additionally, we use our sufficient condition to examine whether such algorithms exist for some specific graphs.
A simple D^2-sampling based PTAS for k-means and other Clustering Problems
Venue: arXiv cs.DS 2012
Year: 2012

Given a set of points $P \subset \mathbb{R}^d$, the $k$-means clustering problem is to find a set of $k$ {\em centers} $C = \{c_1,...,c_k\}, c_i \in \mathbb{R}^d,$ such that the objective function $\sum_{x \in P} d(x,C)^2$, where $d(x,C)$ denotes the distance between $x$ and the closest center in $C$, is minimized. This is one of the most prominent objective functions that have been studied with respect to clustering. $D^2$-sampling \cite{ArthurV07} is a simple non-uniform sampling technique for choosing points from a set of points. It works as follows: given a set of points $P \subseteq \mathbb{R}^d$, the first point is chosen uniformly at random from $P$. Subsequently, a point from $P$ is chosen as the next sample with probability proportional to the square of the distance of this point to the nearest previously sampled points. $D^2$-sampling has been shown to have nice properties with respect to the $k$-means clustering problem. Arthur and Vassilvitskii \cite{ArthurV07} show that $k$ points chosen as centers from $P$ using $D^2$-sampling gives an $O(\log{k})$ approximation in expectation. Ailon et. al. \cite{AJMonteleoni09} and Aggarwal et. al. \cite{AggarwalDK09} extended results of \cite{ArthurV07} to show that $O(k)$ points chosen as centers using $D^2$-sampling give $O(1)$ approximation to the $k$-means objective function with high probability. In this paper, we further demonstrate the power of $D^2$-sampling by giving a simple randomized $(1 + ε)$-approximation algorithm that uses the $D^2$-sampling in its core.
Channel Exploration and Exploitation with Imperfect Spectrum Sensing in Cognitive Radio Networks
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, the problem of opportunistic channel sensing and access in cognitive radio networks when the sensing is imperfect and a secondary user has limited traffic to send at a time is investigated. Primary users' statistical information is assumed to be unknown, and therefore, a secondary user needs to learn the information online during channel sensing and access process, which means learning loss, also referred to as regret, is inevitable. In this research, the case when all potential channels can be sensed simultaneously is investigated first. The channel access process is modeled as a multi-armed bandit problem with side observation. And channel access rules are derived and theoretically proved to have asymptotically finite regret. Then the case when the secondary user can sense only a limited number of channels at a time is investigated. The channel sensing and access process is modeled as a bi-level multi-armed bandit problem. It is shown that any adaptive rule has at least logarithmic regret. Then we derive channel sensing and access rules and theoretically prove they have logarithmic regret asymptotically and with finite time. The effectiveness of the derived rules is validated by computer simulation.
A Robust Client Verification in cloud enabled m-Commerce using Gaining Protocol
Venue: arXiv cs.NI 2012
Year: 2012

The proposed system highlights a novel approach of exclusive verification process using gain protocol for ensuring security among both the parties (client-service provider) in m-commerce application with cloud enabled service. The proposed system is based on the potential to verify the clients with trusted hand held device depending on the set of frequent events and actions to be carried out. The framework of the proposed work is design after collecting a real time data sets from an android enabled hand set, which when subjected to gain protocol, will result in detection of malicious behavior of illegal clients in the network. The real time experiment is performed with applicable datasets gather, which show the best result for identifying threats from last 2 months data collected.
The milling process monitoring using 3D envelope method
Venue: arXiv cs.OH 2012
Year: 2012

This paper proposes a method to vibration analysis in order to on-line monitoring of milling process quality. Adapting envelope analysis to characterize the milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.
Experimental Characterization of Robot Arm Rigidity in Order to Be Used in Machining Operation
Venue: arXiv cs.RO 2012
Year: 2012

Attempts to install a rotating tool at the end of a robot arm poly-articulated date back twenty years, but these robots were not designed for that. Indeed, two essential features are necessary for machining: high rigidity and precision in a given workspace. The experimental results presented are the dynamic identification of a poly-articulated robot equipped with an integrated spindle. This study aims to highlight the influence of the geometric configuration of the robot arm on the overall stiffness of the system. The spindle is taken into account as an additional weight on board but also as a dynamical excitation for the robot KUKA KR_240_2. Study of the robotic machining vibrations shows the suitable directions of movement in milling process
Wireless Network Coding for MIMO Two-way Relaying using Latin Rectangles
Venue: arXiv cs.IT 2012
Year: 2012

The design of modulation schemes for the physical layer network-coded two-way MIMO relaying scenario is considered, with $n_R$ antennas at the relay R, $n_A$ and $n_B$ antennas respectively at the end nodes A and B. We consider the denoise-and-forward (DNF) protocol which employs two phases: Multiple access (MA) phase and Broadcast (BC) phase. It is known for the network-coded SISO two-way relaying that adaptively changing the networking coding map used at the relay, also known as the denoising map, according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA phase and all these network coding maps should satisfy a requirement called the {\it exclusive law}. The network coding maps which satisfy exclusive law can be viewed equivalently as Latin Rectangles. In this paper, it is shown that for MIMO two-way relaying, deep fade occurs at the relay when the row space of the channel fade coefficient matrix is a subspace of a finite number of vector subspaces of $\mathbb{C}^{n_A+n_B}$ which are referred to as the singular fade subspaces. It is shown that proper choice of network coding map can remove most of the singular fade subspaces, referred to as the removable singular fade subspaces. For $2^λ$-PSK signal set, it is shown that the number of non-removable singular fade subspaces is a small fraction of the total number of singular fade subspaces. The Latin Rectangles for the case when the end nodes use different number of antennas are shown to be obtainable from the Latin Squares for the case when they use the same number of antennas. Also, the network coding maps which remove all the removable singular singular fade subspaces are shown to be obtainable from a small set of Latin Squares.
Implementation of Portion Approach in Distributed Firewall Application for Network Security Framework
Venue: arXiv cs.NI 2012
Year: 2012

The stimulate of this research seeks collaboration of firewalls which, could reach to the capability of distributed points of security policy; the front-end entity may much interact by the invaders so the separation between this entity and back-end entity to make the secure domain protection is necessary; collaborative security entity has the various task in the organization and there is a certain security policy to apply in; the entities like DPFF have to be protected from outsiders. Firewalls are utilized typically to be the main layer of security in the network framework. The research is presented the particular segment of the proposed framework that DPFF based on the developed iptable firewall to be the layers of defense, which is protected front and backend of the framework with a dynamic security and policy update to control the framework's safeguard through proposed portion approach algorithm that utilize to reduce the traffic and efficiency in detection and policy update mechanism. The policy update mechanism for DPFF is given the way of its employment. The complete framework signifies a distributed firewall, where the administrator configures the policy rules set, which could be separately or else from administration nodes' side.
A metric learning perspective of SVM: on the relation of SVM and LMNN
Venue: arXiv cs.LG 2012
Year: 2012

Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor algorithm, LMNN, are two very popular learning algorithms with quite different learning biases. In this paper we bring them into a unified view and show that they have a much stronger relation than what is commonly thought. We analyze SVMs from a metric learning perspective and cast them as a metric learning problem, a view which helps us uncover the relations of the two algorithms. We show that LMNN can be seen as learning a set of local SVM-like models in a quadratic space. Along the way and inspired by the metric-based interpretation of SVM s we derive a novel variant of SVMs, epsilon-SVM, to which LMNN is even more similar. We give a unified view of LMNN and the different SVM variants. Finally we provide some preliminary experiments on a number of benchmark datasets in which show that epsilon-SVM compares favorably both with respect to LMNN and SVM.
Du TAL au TIL
Venue: arXiv cs.CL 2012
Year: 2012

Historically two types of NLP have been investigated: fully automated processing of language by machines (NLP) and autonomous processing of natural language by people, i.e. the human brain (psycholinguistics). We believe that there is room and need for another kind, INLP: interactive natural language processing. This intermediate approach starts from peoples' needs, trying to bridge the gap between their actual knowledge and a given goal. Given the fact that peoples' knowledge is variable and often incomplete, the aim is to build bridges linking a given knowledge state to a given goal. We present some examples, trying to show that this goal is worth pursuing, achievable and at a reasonable cost.
Existence of Stability in Hedonic Coalition Formation Games
Venue: arXiv cs.GT 2012
Year: 2012

In this paper, we examine \emph{hedonic coalition formation games} in which each player's preferences over partitions of players depend only on the members of his coalition. We present three main results in which restrictions on the preferences of the players guarantee the existence of stable partitions for various notions of stability. The preference restrictions pertain to \emph{top responsiveness} and \emph{bottom responsiveness} which model optimistic and pessimistic behavior of players respectively. The existence results apply to natural subclasses of \emph{additive separable hedonic games} and \emph{hedonic games with \B-preferences}. It is also shown that our existence results cannot be strengthened to the case of stronger known stability concepts.
Matroid Prophet Inequalities
Venue: arXiv cs.DS 2012
Year: 2012

Consider a gambler who observes a sequence of independent, non-negative random numbers and is allowed to stop the sequence at any time, claiming a reward equal to the most recent observation. The famous prophet inequality of Krengel, Sucheston, and Garling asserts that a gambler who knows the distribution of each random variable can achieve at least half as much reward, in expectation, as a "prophet" who knows the sampled values of each random variable and can choose the largest one. We generalize this result to the setting in which the gambler and the prophet are allowed to make more than one selection, subject to a matroid constraint. We show that the gambler can still achieve at least half as much reward as the prophet; this result is the best possible, since it is known that the ratio cannot be improved even in the original prophet inequality, which corresponds to the special case of rank-one matroids. Generalizing the result still further, we show that under an intersection of p matroid constraints, the prophet's reward exceeds the gambler's by a factor of at most O(p), and this factor is also tight. Beyond their interest as theorems about pure online algorithms or optimal stopping rules, these results also have applications to mechanism design. Our results imply improved bounds on the ability of sequential posted-price mechanisms to approximate Bayesian optimal mechanisms in both single-parameter and multi-parameter settings. In particular, our results imply the first efficiently computable constant-factor approximations to the Bayesian optimal revenue in certain multi-parameter settings.
Completion Delay Minimization for Instantly Decodable Network Codes
Venue: arXiv cs.NI 2012
Year: 2012

In this paper, we consider the problem of minimizing the completion delay for instantly decodable network coding (IDNC), in wireless multicast and broadcast scenarios. We are interested in this class of network coding due to its numerous benefits, such as low decoding delay, low coding and decoding complexities and simple receiver requirements. We first extend the IDNC graph, which represents all feasible IDNC coding opportunities, to efficiently operate in both multicast and broadcast scenarios. We then formulate the minimum completion delay problem for IDNC as a stochastic shortest path (SSP) problem. Although finding the optimal policy using SSP is intractable, we use this formulation to draw the theoretical guidelines for the policies that can efficiently reduce the completion delay in IDNC. Based on these guidelines, we design a maximum weight clique selection algorithm, which can efficiently reduce the IDNC completion delay in polynomial time. We also design a quadratic time heuristic clique selection algorithm, which can operate in real-time applications. Simulation results show that our proposed algorithms efficiently reduce the IDNC completion delay compared to the random and maximum-rate algorithms, and almost achieve the global optimal completion delay performance over all network codes in broadcast scenarios.
Conception and Use of Ontologies for Indexing and Searching by Semantic Contents of Video Courses
Venue: arXiv cs.DL 2012
Year: 2012

Nowadays, the video documents like educational courses available on the web increases significantly. However, the information retrieval systems today can not return to the users (students or teachers) of parts of those videos that meet their exact needs expressed by a query consisting of semantic information. In this paper, we present a model of pedagogical knowledge of current videos. This knowledge is used throughout the process of indexing and semantic search segments instructional videos. Our experimental results show that the proposed approach is promising.
A New Local Adaptive Thresholding Technique in Binarization
Venue: arXiv cs.CV 2012
Year: 2012

Image binarization is the process of separation of pixel values into two groups, white as background and black as foreground. Thresholding plays a major in binarization of images. Thresholding can be categorized into global thresholding and local thresholding. In images with uniform contrast distribution of background and foreground like document images, global thresholding is more appropriate. In degraded document images, where considerable background noise or variation in contrast and illumination exists, there exists many pixels that cannot be easily classified as foreground or background. In such cases, binarization with local thresholding is more appropriate. This paper describes a locally adaptive thresholding technique that removes background by using local mean and mean deviation. Normally the local mean computational time depends on the window size. Our technique uses integral sum image as a prior processing to calculate local mean. It does not involve calculations of standard deviations as in other local adaptive techniques. This along with the fact that calculations of mean is independent of window size speed up the process as compared to other local thresholding techniques.