OpenRaiser/Intern-Atlas huggingface dataset:
RISM -- Reputation Based Intrusion Detection System for Mobile Ad hoc Networks
Venue: arXiv cs.CR 2013
Year: 2013

This paper proposes a combination of an Intrusion Detection System with a routing protocol to strengthen the defense of a Mobile Ad hoc Network. Our system is Socially Inspired, since we use the new paradigm of Reputation inherited from human behavior. The proposed IDS also has a unique characteristic of being Semi-distributed, since it neither distributes its Observation results globally nor keeps them entirely locally; however, managing to communicate this vital information without accretion of the network traffic. This innovative approach also avoids void assumptions and complex calculations for calculating and maintaining trust values used to estimate the reliability of other nodes observations. A robust Path Manager and Monitor system and Redemption and Fading concepts are other salient features of this design. The design has shown to outperform normal DSR in terms of Packet Delivery Ratio and Routing Overhead even when up to half of nodes in the network behave as malicious.
Scalable $k$-NN graph construction
Venue: arXiv cs.CV 2013
Year: 2013

The $k$-NN graph has played a central role in increasingly popular data-driven techniques for various learning and vision tasks; yet, finding an efficient and effective way to construct $k$-NN graphs remains a challenge, especially for large-scale high-dimensional data. In this paper, we propose a new approach to construct approximate $k$-NN graphs with emphasis in: efficiency and accuracy. We hierarchically and randomly divide the data points into subsets and build an exact neighborhood graph over each subset, achieving a base approximate neighborhood graph; we then repeat this process for several times to generate multiple neighborhood graphs, which are combined to yield a more accurate approximate neighborhood graph. Furthermore, we propose a neighborhood propagation scheme to further enhance the accuracy. We show both theoretical and empirical accuracy and efficiency of our approach to $k$-NN graph construction and demonstrate significant speed-up in dealing with large scale visual data.
The Implications of Diverse Applications and Scalable Data Sets in Benchmarking Big Data Systems
Venue: arXiv cs.PF 2013
Year: 2013

Now we live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in short big data systems) is a hot topic. In this paper, we focus on measuring the performance impacts of diverse applications and scalable volumes of data sets on big data systems. For four typical data analysis applications---an important class of big data applications, we find two major results through experiments: first, the data scale has a significant impact on the performance of big data systems, so we must provide scalable volumes of data sets in big data benchmarks. Second, for the four applications, even all of them use the simple algorithms, the performance trends are different with increasing data scales, and hence we must consider not only variety of data sets but also variety of applications in benchmarking big data systems.
Neural Network Capacity for Multilevel Inputs
Venue: arXiv cs.NE 2013
Year: 2013

This paper examines the memory capacity of generalized neural networks. Hopfield networks trained with a variety of learning techniques are investigated for their capacity both for binary and non-binary alphabets. It is shown that the capacity can be much increased when multilevel inputs are used. New learning strategies are proposed to increase Hopfield network capacity, and the scalability of these methods is also examined in respect to size of the network. The ability to recall entire patterns from stimulation of a single neuron is examined for the increased capacity networks.
POMDPs Make Better Hackers: Accounting for Uncertainty in Penetration Testing
Venue: arXiv cs.AI 2013
Year: 2013

Penetration Testing is a methodology for assessing network security, by generating and executing possible hacking attacks. Doing so automatically allows for regular and systematic testing. A key question is how to generate the attacks. This is naturally formulated as planning under uncertainty, i.e., under incomplete knowledge about the network configuration. Previous work uses classical planning, and requires costly pre-processes reducing this uncertainty by extensive application of scanning methods. By contrast, we herein model the attack planning problem in terms of partially observable Markov decision processes (POMDP). This allows to reason about the knowledge available, and to intelligently employ scanning actions as part of the attack. As one would expect, this accurate solution does not scale. We devise a method that relies on POMDPs to find good attacks on individual machines, which are then composed into an attack on the network as a whole. This decomposition exploits network structure to the extent possible, making targeted approximations (only) where needed. Evaluating this method on a suitably adapted industrial test suite, we demonstrate its effectiveness in both runtime and solution quality.
Sistem Informasi Penjualan Dan Perbaikan Komputer (Studi Kasus: CV Computer Plus Palembang)
Venue: arXiv cs.OH 2013
Year: 2013

The purpose of this research is to develop an Information System of Selling and Services using Microsoft Visual Basic and Microsoft Access for it database. The benefits of this research is to help CV Computer Plus in selling and services data processing everyday. To develop this IS is used 5 (five) steps: 1) Planning, 2) Analysis, 3) Design, 4) Implementation, and 5) Evaluation. The Information System can record the selling and services data, it also prepared usefull reports. By using this IS, CV Computer Plus can operate their selling and services efficiency and effectively. In the future it can be upgraded for network application.
Toward Isomorphism of Intersection and Union types
Venue: arXiv cs.LO 2013
Year: 2013

This paper investigates type isomorphism in a lambda-calculus with intersection and union types. It is known that in lambda-calculus, the isomorphism between two types is realised by a pair of terms inverse one each other. Notably, invertible terms are linear terms of a particular shape, called finite hereditary permutators. Typing properties of finite hereditary permutators are then studied in a relevant type inference system with intersection and union types for linear terms. In particular, an isomorphism preserving reduction between types is defined. Type reduction is confluent and terminating, and induces a notion of normal form of types. The properties of normal types are a crucial step toward the complete characterisation of type isomorphism. The main results of this paper are, on one hand, the fact that two types with the same normal form are isomorphic, on the other hand, the characterisation of the isomorphism between types in normal form, modulo isomorphism of arrow types.
A New PVSS Scheme with a Simple Encryption Function
Venue: arXiv cs.CR 2013
Year: 2013

A Publicly Verifiable Secret Sharing (PVSS) scheme allows anyone to verify the validity of the shares computed and distributed by a dealer. The idea of PVSS was introduced by Stadler in [18] where he presented a PVSS scheme based on Discrete Logarithm. Later, several PVSS schemes were proposed. In [2], Behnad and Eghlidos present an interesting PVSS scheme with explicit membership and disputation processes. In this paper, we present a new PVSS having the advantage of being simpler while offering the same features.
Towards a General Framework for Formal Reasoning about Java Bytecode Transformation
Venue: arXiv cs.LO 2013
Year: 2013

Program transformation has gained a wide interest since it is used for several purposes: altering semantics of a program, adding features to a program or performing optimizations. In this paper we focus on program transformations at the bytecode level. Because these transformations may introduce errors, our goal is to provide a formal way to verify the update and establish its correctness. The formal framework presented includes a definition of a formal semantics of updates which is the base of a static verification and a scheme based on Hoare triples and weakest precondition calculus to reason about behavioral aspects in bytecode transformation
Introducing Access Control in Webdamlog
Venue: arXiv cs.DB 2013
Year: 2013

We survey recent work on the specification of an access control mechanism in a collaborative environment. The work is presented in the context of the WebdamLog language, an extension of datalog to a distributed context. We discuss a fine-grained access control mechanism for intentional data based on provenance as well as a control mechanism for delegation, i.e., for deploying rules at remote peers.
The Planning-ahead SMO Algorithm
Venue: arXiv cs.LG 2013
Year: 2013

The sequential minimal optimization (SMO) algorithm and variants thereof are the de facto standard method for solving large quadratic programs for support vector machine (SVM) training. In this paper we propose a simple yet powerful modification. The main emphasis is on an algorithm improving the SMO step size by planning-ahead. The theoretical analysis ensures its convergence to the optimum. Experiments involving a large number of datasets were carried out to demonstrate the superiority of the new algorithm.
Allocating the chains of consecutive additions for optimal fixed-point data path synthesis
Venue: arXiv cs.AR 2013
Year: 2013

Minimization of computational errors in the fixed-point data path is often difficult task. Many signal processing algorithms use chains of consecutive additions. The analyzing technique that can be applied to fixed-point data path synthesis has been proposed. This technique takes advantage of allocating the chains of consecutive additions in order to predict growing width of the data path and minimize the design complexity and computational errors.
Who and Where: People and Location Co-Clustering
Venue: arXiv cs.CV 2013
Year: 2013

In this paper, we consider the clustering problem on images where each image contains patches in people and location domains. We exploit the correlation between people and location domains, and proposed a semi-supervised co-clustering algorithm to cluster images. Our algorithm updates the correlation links at the runtime, and produces clustering in both domains simultaneously. We conduct experiments in a manually collected dataset and a Flickr dataset. The result shows that the such correlation improves the clustering performance.
Fast Simultaneous Training of Generalized Linear Models (FaSTGLZ)
Venue: arXiv cs.LG 2013
Year: 2013

We present an efficient algorithm for simultaneously training sparse generalized linear models across many related problems, which may arise from bootstrapping, cross-validation and nonparametric permutation testing. Our approach leverages the redundancies across problems to obtain significant computational improvements relative to solving the problems sequentially by a conventional algorithm. We demonstrate our fast simultaneous training of generalized linear models (FaSTGLZ) algorithm on a number of real-world datasets, and we run otherwise computationally intensive bootstrapping and permutation test analyses that are typically necessary for obtaining statistically rigorous classification results and meaningful interpretation. Code is freely available at http://liinc.bme.columbia.edu/fastglz.
A new approach in position-based routing protocol using learning automata for vanets in city scenario
Venue: arXiv cs.NI 2013
Year: 2013

One of the main issues in Vehicular Ad-hoc NETworks (VANETs) is providing a reliable and efficient routing in urban scenarios with regard to the high vehicle mobility and presence of radio obstacle. In this paper, we propose a Position-Based routing protocol using Learning Automata (PBLA). In addition, PBLA uses the traffic information for enhancing learning. As we know, a main characteristic of learning is increasing performance over time. We exploit this characteristic to decreasing use of traffic information. Initially, PBLA make effort to finding best and shortest path to mobile destination using traffic information.
Joint Distributed Source-Channel Decoding for LDPC-Coded Binary Markov Sources
Venue: arXiv cs.IT 2013
Year: 2013

We propose a novel joint decoding technique for distributed source-channel (DSC) coded systems for transmission of correlated binary Markov sources over additive white Gaussian noise (AWGN) channels. In the proposed scheme, relatively short-length, low-density parity-check (LDPC) codes are independently used to encode the bit sequences of each source. To reconstruct the original bit sequence, a joint source-channel decoding (JSCD) technique is proposed which exploits the knowledge of both temporal and source correlations. The JSCD technique is composed of two stages, which are iteratively performed. First, a sum-product (SP) decoder is serially concatenated with a BCJR decoder, where the knowledge of source memory is utilized during {\em local (horizontal) iterations}. Then, the estimate of correlation between the sources is used to update the concatenated decoder during {\em global (vertical) iterations}. Therefore, the correlation of the sources is assumed as side information in the subsequent global iteration of each concatenated decoder. From the simulation results of frame/bit error rate (FER/BER), we note that significant gains are achieved by the proposed decoding scheme with respect to the case where the correlation knowledge is not completely utilized at the decoder.
Performance Analysis of VoIP Traffic in WiMAX using various Service Classes
Venue: arXiv cs.NI 2013
Year: 2013

Worldwide Interoperability for Microwave Access (WiMAX) is currently one of the hottest technologies in wireless, it is a standard-based on the IEEE 802.16 wireless technology that provides high throughput broadband connections over long distance, which supports Point to MultiPoint (PMP) broadband wireless access. In parallel, Voice over Internet Protocol is a promising new technology which provides access to voice communication over internet protocol based network, it becomes an alternative to public switched telephone networks due to its capability of transmission of voice as packets over IP networks. Therefore VoIP is largely intolerant of delay and hence it needs a high priority transmission. In this paper we investigate the performances of the most common VoIP codecs, which are G711, G7231 and G729 over a WiMAX network using various service classes and NOAH as a transport protocol. To analyze the QoS parameters, the popular network simulator ns2 was used. Various parameters that determine QoS of real life usage scenarios and traffic flows of applications is analyzed. The objective is to compare different types of service classes with respect to the QoS parameters, such as, throughput, average jitter and average delay.
Exact and Heuristic Methods for the Assembly Line Worker Assignment and Balancing Problem
Venue: arXiv cs.AI 2013
Year: 2013

In traditional assembly lines, it is reasonable to assume that task execution times are the same for each worker. However, in sheltered work centres for disabled this assumption is not valid: some workers may execute some tasks considerably slower or even be incapable of executing them. Worker heterogeneity leads to a problem called the assembly line worker assignment and balancing problem (ALWABP). For a fixed number of workers the problem is to maximize the production rate of an assembly line by assigning workers to stations and tasks to workers, while satisfying precedence constraints between the tasks. This paper introduces new heuristic and exact methods to solve this problem. We present a new MIP model, propose a novel heuristic algorithm based on beam search, as well as a task-oriented branch-and-bound procedure which uses new reduction rules and lower bounds for solving the problem. Extensive computational tests on a large set of instances show that these methods are effective and improve over existing ones.
Social Data Mining through Distributed Mobile Sensing
Venue: arXiv cs.HC 2013
Year: 2013

In this article, we present a distributed framework for collecting and analyzing environmental and location data recorded by human users (carriers) with the use of portable sensors. We demonstrate the data mining analysis potential among the recorded environmental and location variables, as well as the potential for classification analysis of human activities. We recognize that the success of such an experimental framework relies on the adoption rate by its candidate user network; thus, we have built our experimental prototype on top of hardware equipment already embedded within the potential users' everyday routine - i.e. hardware sensors installed on modern mobile phones. Finally, we present preliminary analysis results on our collected data sample, as well as potential further work directions and proposed use case scenarios.
Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes
Venue: arXiv cs.CV 2013
Year: 2013

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.
L1-Optimal Splines for Outlier Rejection
Venue: arXiv cs.SY 2013
Year: 2013

In this article, we consider control theoretic splines with L1 optimization for rejecting outliers in data. Control theoretic splines are either interpolating or smoothing splines, depending on a cost function with a constraint defined by linear differential equations. Control theoretic splines are effective for Gaussian noise in data since the estimation is based on L2 optimization. However, in practice, there may be outliers in data, which may occur with vanishingly small probability under the Gaussian assumption of noise, to which L2-optimized spline regression may be very sensitive. To achieve robustness against outliers, we propose to use L1 optimality, which is also used in support vector regression. A numerical example shows the effectiveness of the proposed method.
Authentication System Securing Index of Image using SVD and ECC
Venue: arXiv cs.CR 2013
Year: 2013

This paper presents a new approach to securing information stored in a database. It has three components including: an operation for indexing images using Singular Value Decomposition (SVD), which will constitute the reference images, asymmetric encryption operation using Elliptic Curve Cryptosystem (ECC), aiming to make confidential these reference images stored and a technique for comparing these images to a query image using the Euclidian Distance.
Static Enforceability of XPath-Based Access Control Policies
Venue: arXiv cs.DB 2013
Year: 2013

We consider the problem of extending XML databases with fine-grained, high-level access control policies specified using XPath expressions. Most prior work checks individual updates dynamically, which is expensive (requiring worst-case execution time proportional to the size of the database). On the other hand, static enforcement can be performed without accessing the database but may be incomplete, in the sense that it may forbid accesses that dynamic enforcement would allow. We introduce topological characterizations of XPath fragments in order to study the problem of determining when an access control policy can be enforced statically without loss of precision. We introduce the notion of fair policies that are statically enforceable, and study the complexity of determining fairness and of static enforcement itself.
Visualization of Job Scheduling in Grid Computers
Venue: arXiv cs.DC 2013
Year: 2013

One of the hot problems in grid computing is job scheduling. It is known that the job scheduling is NP-complete, and thus the use of heuristics is the de facto approach to deal with this practice in its difficulty. The proposed is an imagination to fish swarm, job dispatcher and Visualization gridsim to execute some jobs.
Estimating the longest increasing sequence in polylogarithmic time
Venue: arXiv cs.DS 2013
Year: 2013

Finding the length of the longest increasing subsequence (LIS) is a classic algorithmic problem. Let $n$ denote the size of the array. Simple $O(n\log n)$ algorithms are known for this problem. We develop a polylogarithmic time randomized algorithm that for any constant $δ> 0$, estimates the length of the LIS of an array to within an additive error of $δn$. More precisely, the running time of the algorithm is $(\log n)^c (1/δ)^{O(1/δ)}$ where the exponent $c$ is independent of $δ$. Previously, the best known polylogarithmic time algorithms could only achieve an additive $n/2$ approximation. With a suitable choice of parameters, our algorithm also gives, for any fixed $τ>0$, a multiplicative $(1+τ)$-approximation to the distance to monotonicity $\varepsilon_f$ (the fraction of entries not in the LIS), whose running time is polynomial in $\log(n)$ and $1/varepsilon_f$. The best previously known algorithm could only guarantee an approximation within a factor (arbitrarily close to) 2.
An Improving Method for Loop Unrolling
Venue: arXiv cs.PL 2013
Year: 2013

In this paper we review main ideas mentioned in several other papers which talk about optimization techniques used by compilers. Here we focus on loop unrolling technique and its effect on power consumption, energy usage and also its impact on program speed up by achieving ILP (Instruction-level parallelism). Concentrating on superscalar processors, we discuss the idea of generalized loop unrolling presented by J.C. Hang and T. Leng and then we present a new method to traverse a linked list to get a better result of loop unrolling in that case. After that we mention the results of some experiments carried out on a Pentium 4 processor (as an instance of super scalar architecture). Furthermore, the results of some other experiments on supercomputer (the Alliat FX/2800 System) containing superscalar node processors would be mentioned. These experiments show that loop unrolling has a slight measurable effect on energy usage as well as power consumption. But it could be an effective way for program speed up.
Ontology Enrichment by Extracting Hidden Assertional Knowledge from Text
Venue: arXiv cs.IR 2013
Year: 2013

In this position paper we present a new approach for discovering some special classes of assertional knowledge in the text by using large RDF repositories, resulting in the extraction of new non-taxonomic ontological relations. Also we use inductive reasoning beside our approach to make it outperform. Then, we prepare a case study by applying our approach on sample data and illustrate the soundness of our proposed approach. Moreover in our point of view current LOD cloud is not a suitable base for our proposal in all informational domains. Therefore we figure out some directions based on prior works to enrich datasets of Linked Data by using web mining. The result of such enrichment can be reused for further relation extraction and ontology enrichment from unstructured free text documents.