OpenRaiser/Intern-Atlas huggingface dataset:
An adaptive block based integrated LDP,GLCM,and Morphological features for Face Recognition
Venue: arXiv cs.CV 2013
Year: 2013

This paper proposes a technique for automatic face recognition using integrated multiple feature sets extracted from the significant blocks of a gradient image. We discuss about the use of novel morphological, local directional pattern (LDP) and gray-level co-occurrence matrix GLCM based feature extraction technique to recognize human faces. Firstly, the new morphological features i.e., features based on number of runs of pixels in four directions (N,NE,E,NW) are extracted, together with the GLCM based statistical features and LDP features that are less sensitive to the noise and non-monotonic illumination changes, are extracted from the significant blocks of the gradient image. Then these features are concatenated together. We integrate the above mentioned methods to take full advantage of the three approaches. Extraction of the significant blocks from the absolute gradient image and hence from the original image to extract pertinent information with the idea of dimension reduction forms the basis of the work. The efficiency of our method is demonstrated by the experiment on 1100 images from the FRAV2D face database, 2200 images from the FERET database, where the images vary in pose, expression, illumination and scale and 400 images from the ORL face database, where the images slightly vary in pose. Our method has shown 90.3%, 93% and 98.75% recognition accuracy for the FRAV2D, FERET and the ORL database respectively.
Performance Analysis of Network Coded Systems Under Quasi-static Rayleigh Fading Channels
Venue: arXiv cs.IT 2013
Year: 2013

In the area of basic and network coded cooperative communication, the expected end-to-end bit error rate (BER) values are frequently required to compare the proposed coding, relaying, and decoding techniques. Instead of obtaining these values via time consuming Monte Carlo simulations, deriving closed form expressions using approximations is crucial. In this work, the ultimate goal is to derive an approximate average BER expression for a network coded system. While reaching this goal, we firstly consider the cooperative systems' instantaneous BER values that are commonly composed of Q-functions of more than one variables. For these Q-functions, we investigate the convergence characteristics of the sampling property and generalize this property to arbitrary functions of multiple variables. Second, we adapt the equivalent channel approach to the network coded scenario for the ease of analysis and propose a network decoder with reduced complexity. Finally, by combining these techniques, we show that the obtained closed form expressions well agree with simulation results in a wide SNR range.
On the relation generation method of Joux for computing discrete logarithms
Venue: arXiv cs.CC 2013
Year: 2013

In \cite{joux}, Joux devised an algorithm to compute discrete logarithms between elements in a certain subset of the multiplicative group of an extension of the finite field $\mathbb{F}_{p^n}$ in time polynomial in $p$ and $n$. Shortly after, Barbulescu, Gaudry, Joux and Thome \cite{bgjt} proposed a descent algorithm that in $(p n)^{\mathcal{O}(\log n)}$ time projects an arbitrary element in $\mathbb{F}_{p^n}^\times$ as a product of powers of elements in the aforementioned subset. Together, these two algorithms yield a quasi-polynomial time algorithm for computing discrete logarithms in finite fields of small characteristic. The success of both the algorithms are reliant on heuristic assumptions. We identify obstructions that prevent certain heuristic assumptions they make from being true in general. Further, we describe methods to overcome these obstructions.
Upper semicomputable sumtests for lower semicomputable semimeasures
Venue: arXiv cs.CC 2013
Year: 2013

A sumtest for a discrete semimeasure $P$ is a function $f$ mapping bitstrings to non-negative rational numbers such that \[ \sum P(x)f(x) \le 1 \,. \] Sumtests are the discrete analogue of Martin-Löf tests. The behavior of sumtests for computable $P$ seems well understood, but for some applications lower semicomputable $P$ seem more appropriate. In the case of tests for independence, it is natural to consider upper semicomputable tests (see [B.Bauwens and S.Terwijn, Theory of Computing Systems 48.2 (2011): 247-268]). In this paper, we characterize upper semicomputable sumtests relative to any lower semicomputable semimeasures using Kolmogorov complexity. It is studied to what extend such tests are pathological: can upper semicomputable sumtests for $m(x)$ be large? It is shown that the logarithm of such tests does not exceed $\log |x| + O(\log^{(2)} |x|)$ (where $|x|$ denotes the length of $x$ and $\log^{(2)} = \log\log$) and that this bound is tight, i.e. there is a test whose logarithm exceeds $\log |x| - O(\log^{(2)} |x|$) infinitely often. Finally, it is shown that for each such test $e$ the mutual information of a string with the Halting problem is at least $\log e(x)-O(1)$; thus $e$ can only be large for ``exotic'' strings.
Book embeddings of Reeb graphs
Venue: arXiv cs.CG 2013
Year: 2013

Let $X$ be a simplicial complex with a piecewise linear function $f:X\to\mathbb{R}$. The Reeb graph $Reeb(f,X)$ is the quotient of $X$, where we collapse each connected component of $f^{-1}(t)$ to a single point. Let the nodes of $Reeb(f,X)$ be all homologically critical points where any homology of the corresponding component of the level set $f^{-1}(t)$ changes. Then we can label every arc of $Reeb(f,X)$ with the Betti numbers $(β_1,β_2,\dots,β_d)$ of the corresponding $d$-dimensional component of a level set. The homology labels give more information about the original complex $X$ than the classical Reeb graph. We describe a canonical embedding of a Reeb graph into a multi-page book (a star cross a line) and give a unique linear code of this book embedding.
Towards Normalizing the Edit Distance Using a Genetic Algorithms Based Scheme
Venue: arXiv cs.NE 2013
Year: 2013

The normalized edit distance is one of the distances derived from the edit distance. It is useful in some applications because it takes into account the lengths of the two strings compared. The normalized edit distance is not defined in terms of edit operations but rather in terms of the edit path. In this paper we propose a new derivative of the edit distance that also takes into consideration the lengths of the two strings, but the new distance is related directly to the edit distance. The particularity of the new distance is that it uses the genetic algorithms to set the values of the parameters it uses. We conduct experiments to test the new distance and we obtain promising results.
Towards the Framework of the File Systems Performance Evaluation Techniques and the Taxonomy of Replay Traces
Venue: arXiv cs.OS 2013
Year: 2013

This is the era of High Performance Computing (HPC). There is a great demand of the best performance evaluation techniques for the file and storage systems. The task of evaluation is both necessary and hard. It gives in depth analysis of the target system and that becomes the decision points for the users. That is also helpful for the inventors or developers to find out the bottleneck in their systems. In this paper many performance evaluation techniques are described for file and storage system evaluation and the main stress is given on the important one that is replay traces. A survey has been done for the performance evaluation techniques used by the researchers and on the replay traces. And the taxonomy of the replay traces is described. The some of the popular replay traces are just like, Tracefs [1], //Trace [2], Replayfs [3] and VFS Interceptor [12]. At last we have concluded all the features that must be considered when we are going to develop the new tool for the replay traces. The complete work of this paper shows that the storage system developers must care about all the techniques which can be used for the performance evaluation of the file systems. So they can develop highly efficient future file and storage systems.
Introduction to computer animation and its possible educational applications
Venue: arXiv cs.GR 2013
Year: 2013

Animation, which is basically a form of pictorial presentation, has become the most prominent feature of technology-based learning environments. It refers to simulated motion pictures showing movement of drawn objects. Recently, educational computer animation has turned out to be one of the most elegant tools for presenting multimedia materials for learners, and its significance in helping to understand and remember information has greatly increased since the advent of powerful graphics-oriented computers. In this book chapter we introduce and discuss the history of computer animation, its well-known fundamental principles and some educational applications. It is however still debatable if truly educational computer animations help in learning, as the research on whether animation aids learners' understanding of dynamic phenomena has come up with positive, negative and neutral results. We have tried to provide as much detailed information on computer animation as we could, and we hope that this book chapter will be useful for students who study computer science, computer-assisted education or some other courses connected with contemporary education, as well as researchers who conduct their research in the field of computer animation.
A Distributed Algorithm for Constructing a Minimum Diameter Spanning Tree
Venue: arXiv cs.DC 2013
Year: 2013

We present a new algorithm, which solves the problem of distributively finding a minimum diameter spanning tree of any (non-negatively) real-weighted graph $G = (V,E,ω)$. As an intermediate step, we use a new, fast, linear-time all-pairs shortest paths distributed algorithm to find an absolute center of $G$. The resulting distributed algorithm is asynchronous, it works for named asynchronous arbitrary networks and achieves $\mathcal{O}(|V|)$ time complexity and $\mathcal{O}\left(|V|\,|E|\right)$
Power-Aware Hybrid Intrusion Detection System (PHIDS) using Cellular Automata in Wireless AdHoc Networks
Venue: arXiv cs.NI 2013
Year: 2013

Adhoc wireless network with their changing topology and distributed nature are more prone to intruders. The network monitoring functionality should be in operation as long as the network exists with nil constraints. The efficiency of an Intrusion detection system in the case of an adhoc network is not only determined by its dynamicity in monitoring but also in its flexibility in utilizing the available power in each of its nodes. In this paper we propose a hybrid intrusion detection system, based on a power level metric for potential adhoc hosts, which is used to determine the duration for which a particular node can support a network monitoring node. Power aware hybrid intrusion detection system focuses on the available power level in each of the nodes and determines the network monitors. Power awareness in the network results in maintaining power for network monitoring, with monitors changing often, since it is an iterative power optimal solution to identify nodes for distributed agent based intrusion detection. The advantage that this approach entails is the inherent flexibility it provides, by means of considering only fewer nodes for reestablishing network monitors. The detection of intrusions in the network is done with the help of Cellular Automat CA. The CAs classify a packet routed through the network either as normal or an intrusion. The use of CAs enable in the identification of already occurred intrusions as well as new intrusions.
Load Balancing using Ant Colony in Cloud Computing
Venue: arXiv cs.DC 2013
Year: 2013

Ants are very small insects.They are capable to find food even they are complete blind. The ants lives in their nest and their job is to search food while they get hungry. We are not interested in their living style, such as how they live, how they sleep. But we are interested in how they search for food, and how they find the shortest path. The technique for finding the shortest path are now applying in cloud computing. The Ant Colony approach towards Cloud Computing gives better performance.
Name: A Naming Mechanism for Delay/Disruption-Tolerant Network
Venue: arXiv cs.NI 2013
Year: 2013

This paper presents the design and implementation of the naming mechanism (NAME), a resource discovery and service location approach for Delay/Disruption-Tolerant Network (DTN). First discuss the architecture of NAME mainly including Name Knowledge Base, Name Dissemination, Name Resolution and Name-based Routing. In the design and implementation of NAME, we introduce the simple namespecifiers to describe name, the name-tree for name storage and the efficient predicate-based routing algorithm. Future work is finally discussed for completing NAME and providing APIs for abundant applications.
A Comparative Study on Remote Tracking of Parkinsons Disease Progression Using Data Mining Methods
Venue: arXiv cs.CE 2013
Year: 2013

In recent years, applications of data mining methods are become more popular in many fields of medical diagnosis and evaluations. The data mining methods are appropriate tools for discovering and extracting of available knowledge in medical databases. In this study, we divided 11 data mining algorithms into five groups which are applied to a data set of patients clinical variables data with Parkinsons Disease (PD) to study the disease progression. The data set includes 22 properties of 42 people that all of our algorithms are applied to this data set. The Decision Table with 0.9985 correlation coefficients has the best accuracy and Decision Stump with 0.7919 correlation coefficients has the lowest accuracy.
Cross-layer Design of CSMA/CA with Spectrum Sensing for Cognitive Radio Networks
Venue: arXiv cs.NI 2013
Year: 2013

We devise a cross-layer design (CLD) of carrier sensing multiple access with collision avoidance (CSMA/CA) at the medium access control (MAC) layer with spectrum sensing (SpSe) at the physical layer for cognitive radio networks (CRNs). The proposed CLD relies on a Markov chain model with a state pair containing both the SpSe and the CSMA/CA with exponential backoff from which we derive the transmission and collision probabilities. Due to the 2-dimensions of CSMA/CA model with exponential backoff, the resulted Markov chain is obtained with 3-dimensions. Simulation and numerical results are derived and illustrated highlighting the impact of SpSe in CSMA/CA with exponential backoff. The obtained results could be used as performance criteria to evaluate the performance of specific CRNs when they are deployed in a distributed coordination fashion that is prone to collisions.
Construct Graph Logic
Venue: arXiv cs.DM 2013
Year: 2013

In this paper, author uses set theory to construct a logic model of abstract figure from binary relation. Based on the uniform quantified structure, author gives two logic system for graph traversal and graph coloring respectively, moreover shows a new method of cutting graph. Around this model, there are six algorithms in this paper including exact graph traversal, Algebra calculation of natural number, graph partition and graph coloring.
Decision Fusion with Unknown Sensor Detection Probability
Venue: arXiv cs.IT 2013
Year: 2013

In this correspondence we study the problem of channel-aware decision fusion when the sensor detection probability is not known at the decision fusion center. Several alternatives proposed in the literature are compared and new fusion rules (namely 'ideal sensors' and 'locally-optimum detection') are proposed, showing attractive performance and linear complexity. Simulations are provided to compare the performance of the aforementioned rules.
Noisy Bayesian Active Learning
Venue: arXiv cs.IT 2013
Year: 2013

We consider the problem of noisy Bayesian active learning, where we are given a finite set of functions $\mathcal{H}$, a sample space $\mathcal{X}$, and a label set $\mathcal{L}$. One of the functions in $\mathcal{H}$ assigns labels to samples in $\mathcal{X}$. The goal is to identify the function that generates the labels even though the result of a label query on a sample is corrupted by independent noise. More precisely, the objective is to declare one of the functions in $\mathcal{H}$ as the true label generating function with high confidence using as few label queries as possible, by selecting the queries adaptively and in a strategic manner. Previous work in Bayesian active learning considers Generalized Binary Search, and its variants for the noisy case, and analyzes the number of queries required by these sampling strategies. In this paper, we show that these schemes are, in general, suboptimal. Instead we propose and analyze an alternative strategy for sample collection. Our sampling strategy is motivated by a connection between Bayesian active learning and active hypothesis testing, and is based on querying the label of a sample which maximizes the Extrinsic Jensen-Shannon divergence at each step. We provide upper and lower bounds on the performance of this sampling strategy, and show that these bounds are better than previous bounds.
Exploiting Data Representation for Fault Tolerance
Venue: arXiv cs.NA 2013
Year: 2013

We explore the link between data representation and soft errors in dot products. We present an analytic model for the absolute error introduced should a soft error corrupt a bit in an IEEE-754 floating-point number. We show how this finding relates to the fundamental linear algebra concepts of normalization and matrix equilibration. We present a case study illustrating that the probability of experiencing a large error in a dot product is minimized when both vectors are normalized. Furthermore, when data is normalized we show that the absolute error is less than one or very large, which allows us to detect large errors. We demonstrate how this finding can be used by instrumenting the GMRES iterative solver. We count all possible errors that can be introduced through faults in arithmetic in the computationally intensive orthogonalization phase, and show that when scaling is used the absolute error can be bounded above by one.
A Note on the Longest Common Compatible Prefix Problem for Partial Words
Venue: arXiv cs.DS 2013
Year: 2013

For a partial word $w$ the longest common compatible prefix of two positions $i,j$, denoted $lccp(i,j)$, is the largest $k$ such that $w[i,i+k-1]\uparrow w[j,j+k-1]$, where $\uparrow$ is the compatibility relation of partial words (it is not an equivalence relation). The LCCP problem is to preprocess a partial word in such a way that any query $lccp(i,j)$ about this word can be answered in $O(1)$ time. It is a natural generalization of the longest common prefix (LCP) problem for regular words, for which an $O(n)$ preprocessing time and $O(1)$ query time solution exists. Recently an efficient algorithm for this problem has been given by F. Blanchet-Sadri and J. Lazarow (LATA 2013). The preprocessing time was $O(nh+n)$, where $h$ is the number of "holes" in $w$. The algorithm was designed for partial words over a constant alphabet and was quite involved. We present a simple solution to this problem with slightly better runtime that works for any linearly-sortable alphabet. Our preprocessing is in time $O(nμ+n)$, where $μ$ is the number of blocks of holes in $w$. Our algorithm uses ideas from alignment algorithms and dynamic programming.
Typologies of Computation and Computational Models
Venue: arXiv cs.GL 2013
Year: 2013

We need much better understanding of information processing and computation as its primary form. Future progress of new computational devices capable of dealing with problems of big data, internet of things, semantic web, cognitive robotics and neuroinformatics depends on the adequate models of computation. In this article we first present the current state of the art through systematization of existing models and mechanisms, and outline basic structural framework of computation. We argue that defining computation as information processing, and given that there is no information without (physical) representation, the dynamics of information on the fundamental level is physical/ intrinsic/ natural computation. As a special case, intrinsic computation is used for designed computation in computing machinery. Intrinsic natural computation occurs on variety of levels of physical processes, containing the levels of computation of living organisms (including highly intelligent animals) as well as designed computational devices. The present article offers a typology of current models of computation and indicates future paths for the advancement of the field; both by the development of new computational models and by learning from nature how to better compute using different mechanisms of intrinsic computation.
A New Modular Division Algorithm and Applications
Venue: arXiv cs.DC 2013
Year: 2013

The present paper proposes a new parallel algorithm for the modular division $u/v\bmod β^s$, where $u,\; v,\; β$ and $s$ are positive integers $(β\ge 2)$. The algorithm combines the classical add-and-shift multiplication scheme with a new propagation carry technique. This "Pen and Paper Inverse" ({\em PPI}) algorithm, is better suited for systolic parallelization in a "least-significant digit first" pipelined manner. Although it is equivalent to Jebelean's modular division algorithm~\cite{jeb2} in terms of performance (time complexity, work, efficiency), the linear parallelization of the {\em PPI} algorithm improves on the latter when the input size is large. The parallelized versions of the {\em PPI} algorithm leads to various applications, such as the exact division and the digit modulus operation (dmod) of two long integers. It is also applied to the determination of the periods of rational numbers as well as their $p$-adic expansion in any radix $β\ge 2$.
Multi-Task Classification Hypothesis Space with Improved Generalization Bounds
Venue: arXiv cs.LG 2013
Year: 2013

This paper presents a RKHS, in general, of vector-valued functions intended to be used as hypothesis space for multi-task classification. It extends similar hypothesis spaces that have previously considered in the literature. Assuming this space, an improved Empirical Rademacher Complexity-based generalization bound is derived. The analysis is itself extended to an MKL setting. The connection between the proposed hypothesis space and a Group-Lasso type regularizer is discussed. Finally, experimental results, with some SVM-based Multi-Task Learning problems, underline the quality of the derived bounds and validate the paper's analysis.
Session Types in Abelian Logic
Venue: arXiv cs.LO 2013
Year: 2013

There was a PhD student who says "I found a pair of wooden shoes. I put a coin in the left and a key in the right. Next morning, I found those objects in the opposite shoes." We do not claim existence of such shoes, but propose a similar programming abstraction in the context of typed lambda calculi. The result, which we call the Amida calculus, extends Abramsky's linear lambda calculus LF and characterizes Abelian logic.
Session Types Go Dynamic or How to Verify Your Python Conversations
Venue: arXiv cs.PL 2013
Year: 2013

This paper presents the first implementation of session types in a dynamically-typed language - Python. Communication safety of the whole system is guaranteed at runtime by monitors that check the execution traces comply with an associated protocol. Protocols are written in Scribble, a choreography description language based on multiparty session types, with addition of logic formulas for more precise behaviour properties. The presented framework overcomes the limitations of previous works on the session types where all endpoints should be statically typed so that they do not permit interoperability with untyped participants. The advantages, expressiveness and performance of dynamic protocol checking are demonstrated through use case and benchmarks.