OpenRaiser/Intern-Atlas huggingface dataset:
Implementation of DYMO routing protocol
Venue: arXiv cs.NI 2013
Year: 2013

Mobile ad hoc networks communicate without any fixed infrastructure or ant centralized domain. All the nodes are free to move randomly within the network and share information dynamically. To achieve an efficient routing various protocols have been developed so far which vary in their nature and have their own salient properties. In this paper, we have discussed one of the latest protocols i.e. Dynamic Manet on demand (DYMO) routing Protocol, implemented and analysed its performance with other similar protocols against different parameters. Finally a comparison has been presented between all of them.
Certified HLints with Isabelle/HOLCF-Prelude
Venue: arXiv cs.LO 2013
Year: 2013

We present the HOLCF-Prelude, a formalization of a large part of Haskell's standard prelude in Isabelle/HOLCF. Applying this formalization to the hints suggested by HLint allows us to certify them formally.
Geometric operations implemented by conformal geometric algebra neural nodes
Venue: arXiv cs.CV 2013
Year: 2013

Geometric algebra is an optimal frame work for calculating with vectors. The geometric algebra of a space includes elements that represent all the its subspaces (lines, planes, volumes, ...). Conformal geometric algebra expands this approach to elementary representations of arbitrary points, point pairs, lines, circles, planes and spheres. Apart from including curved objects, conformal geometric algebra has an elegant unified quaternion like representation for all proper and improper Euclidean transformations, including reflections at spheres, general screw transformations and scaling. Expanding the concepts of real and complex neurons we arrive at the new powerful concept of conformal geometric algebra neurons. These neurons can easily take the above mentioned geometric objects or sets of these objects as inputs and apply a wide range of geometric transformations via the geometric algebra valued weights.
CUDA Based Performance Evaluation of the Computational Efficiency of the DCT Image Compression Technique on Both the CPU and GPU
Venue: arXiv cs.DC 2013
Year: 2013

Recent advances in computing such as the massively parallel GPUs (Graphical Processing Units),coupled with the need to store and deliver large quantities of digital data especially images, has brought a number of challenges for Computer Scientists, the research community and other stakeholders. These challenges, such as prohibitively large costs to manipulate the digital data amongst others, have been the focus of the research community in recent years and has led to the investigation of image compression techniques that can achieve excellent results. One such technique is the Discrete Cosine Transform, which helps separate an image into parts of differing frequencies and has the advantage of excellent energy-compaction. This paper investigates the use of the Compute Unified Device Architecture (CUDA) programming model to implement the DCT based Cordic based Loeffler algorithm for efficient image compression. The computational efficiency is analyzed and evaluated under both the CPU and GPU. The PSNR (Peak Signal to Noise Ratio) is used to evaluate image reconstruction quality in this paper. The results are presented and discussed.
Tight Lower Bound on the Probability of a Binomial Exceeding its Expectation
Venue: arXiv cs.LG 2013
Year: 2013

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in learning theory and generalization bounds for unbounded loss functions.
Managing Knowledge to Enhance Learning
Venue: arXiv cs.CY 2013
Year: 2013

The article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.
SPATA: A Seeding and Patching Algorithm for Hybrid Transcriptome Assembly
Venue: arXiv cs.CE 2013
Year: 2013

Transcriptome assembly from RNA-Seq reads is an active area of bioinformatics research. The ever-declining cost and the increasing depth of RNA-Seq have provided unprecedented opportunities to better identify expressed transcripts. However, the nonlinear transcript structures and the ultra-high throughput of RNA-Seq reads pose significant algorithmic and computational challenges to the existing transcriptome assembly approaches, either reference-guided or de novo. While reference-guided approaches offer good sensitivity, they rely on alignment results of the splice-aware aligners and are thus unsuitable for species with incomplete reference genomes. In contrast, de novo approaches do not depend on the reference genome but face a computational daunting task derived from the complexity of the graph built for the whole transcriptome. In response to these challenges, we present a hybrid approach to exploit an incomplete reference genome without relying on splice-aware aligners. We have designed a split-and-align procedure to efficiently localize the reads to individual genomic loci, which is followed by an accurate de novo assembly to assemble reads falling into each locus. Using extensive simulation data, we demonstrate a high accuracy and precision in transcriptome reconstruction by comparing to selected transcriptome assembly tools. Our method is implemented in assemblySAM, a GUI software freely available at http://sammate.sourceforge.net.
Beyond Locality-Sensitive Hashing
Venue: arXiv cs.DS 2013
Year: 2013

We present a new data structure for the c-approximate near neighbor problem (ANN) in the Euclidean space. For n points in R^d, our algorithm achieves O(n^ρ + d log n) query time and O(n^{1 + ρ} + d log n) space, where ρ<= 7/(8c^2) + O(1 / c^3) + o(1). This is the first improvement over the result by Andoni and Indyk (FOCS 2006) and the first data structure that bypasses a locality-sensitive hashing lower bound proved by O'Donnell, Wu and Zhou (ICS 2011). By a standard reduction we obtain a data structure for the Hamming space and \ell_1 norm with ρ<= 7/(8c) + O(1/c^{3/2}) + o(1), which is the first improvement over the result of Indyk and Motwani (STOC 1998).
Enhancing Tourism Destination Accessibility in Developing Countries through Virtual Worlds
Venue: arXiv cs.HC 2013
Year: 2013

The problem of destination accessibility is a vital concern in the sustainable tourism development in the emerging regions due to the increasing numbers of tourism business growth in the recent times. Tourism is one of the potential foreign exchange earning sectors, which place sustainability as one of the main success metrics for benchmarking the overall development of the industry. On the other hand, there are several destinations, which are inaccessible to tourists due to several reasons. Underutilization of potential destinations in both pre purchase and consumption stages is a strategic disadvantage for emerging countries on leading their tourism industry towards sustainability. This research embarks on a content analysis of second life based tourism groups and places. Requirement of a virtual world model to increase the destination accessibility of tourism products has been outlined. The model has to be designed with visual and auditory experience to tourists. The model is expected to enhance the accessibility of destinations for users of different categories.
Delivering IT as A Utility- A Systematic Review
Venue: arXiv cs.DC 2013
Year: 2013

Utility Computing has facilitated the creation of new markets that has made it possible to realize the long held dream of delivering IT as a Utility. Even though utility computing is in its nascent stage today, the proponents of utility computing envisage that it will become a commodity business in the upcoming time and utility service providers will meet all the IT requests of the companies. This paper takes a cross-sectional view at the emergence of utility computing along with different requirements needed to realize utility model. It also surveys the current trends in utility computing highlighting diverse architecture models aligned towards delivering IT as a utility. Different resource management systems for proficient allocation of resources have been listed together with various resource scheduling and pricing strategies used by them. Further, a review of generic key perspectives closely related to the concept of delivering IT as a Utility has been taken citing the contenders for the future enhancements in this technology in the form of Grid and Cloud Computing.
Stable equilibrium study cascaded one bit sigma-delta modulator
Venue: arXiv cs.OH 2013
Year: 2013

In the paper defines a boundary of stability zone for sigma-delta modulator. The boundary depends from inner sigma-delta modulator coefficients. For designing purposes such result could be used to find or compare some appropriate schemes with each other. It is proved some statements and showed that boundary could be found theoretically for any order of sigma-delta modulator, but practically till 5-th order.
Fast greedy algorithm for subspace clustering from corrupted and incomplete data
Venue: arXiv cs.LG 2013
Year: 2013

We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our algorithm from predecessors is its ability to work with noisy data having a high rate of erasures (missed entries with the known coordinates) and errors (corrupted entries with unknown coordinates). We discuss here how to implement the fast version of the greedy algorithm with the maximum efficiency whose greedy strategy is incorporated into iterations of the basic algorithm. We provide numerical evidences that, in the subspace clustering capability, the fast greedy algorithm outperforms not only the existing state-of-the art SSC algorithm taken by the authors as a basic algorithm but also the recent GSSC algorithm. At the same time, its computational cost is only slightly higher than the cost of SSC. The numerical evidence of the algorithm significant advantage is presented for a few synthetic models as well as for the Extended Yale B dataset of facial images. In particular, the face recognition misclassification rate turned out to be 6-20 times lower than for the SSC algorithm. We provide also the numerical evidence that the FGSSC algorithm is able to perform clustering of corrupted data efficiently even when the sum of subspace dimensions significantly exceeds the dimension of the ambient space.
Appropriation as neglected practice in communities: presenting a framework to enable EUD design for CoPs
Venue: arXiv cs.HC 2013
Year: 2013

Communities present considerable challenges for the design and application of supportive information technology (IT), especially when these develop in loosely-integrated, informal and scarcely organized contexts, like it is often the case of Communities of Practice (CoP). An approach that actively supports user communities in the process of IT appropriation can help alleviate the impossibility of the members of these communities to rely on professional support, and enable even complex forms of tailoring and End-User Development (EUD). Although this approach has been already explored by an increasing number of researchers, however there is still a lack of a general framework that could play a role in the comparison of existing proposals and in the development of new EUD solutions for CoPs. The paper proposes a conceptual framework and a related architecture, called Logic of Bricolage, that aims to be a step further in this direction to enable better EUD-oriented support for digitized communities. The framework is described and the architecture instantiated in three concrete EUD environments that specifically regard collaborative activities in order to show the generality and applicability of the framework.
Performance Evaluation of Low Power MIPS Crypto Processor based on Cryptography Algorithms
Venue: arXiv cs.CR 2013
Year: 2013

This paper presents the design and implementation of low power 32-bit encrypted and decrypted MIPS processor for Data Encryption Standard (DES), Triple DES, Advanced Encryption Standard (AES) based on MIPS pipeline architecture. The organization of pipeline stages has been done in such a way that pipeline can be clocked at high frequency. Encryption and Decryption blocks of three standard cryptography algorithms on MIPS processor and dependency among themselves are explained in detail with the help of a block diagram. Clock gating technique is used to reduce the power consumption in MIPS crypto processor. This approach results in processor that meets power consumption and performance specification for security applications. Proposed Implementation approach concludes higher system performance while reducing operating power consumption. Testing results shows that the MIPS crypto processor operates successfully at a working frequency of 218MHz and a bandwidth of 664Mbits/s.
Automatic Abstraction in SMT-Based Unbounded Software Model Checking
Venue: arXiv cs.LO 2013
Year: 2013

Software model checkers based on under-approximations and SMT solvers are very successful at verifying safety (i.e. reachability) properties. They combine two key ideas -- (a) "concreteness": a counterexample in an under-approximation is a counterexample in the original program as well, and (b) "generalization": a proof of safety of an under-approximation, produced by an SMT solver, are generalizable to proofs of safety of the original program. In this paper, we present a combination of "automatic abstraction" with the under-approximation-driven framework. We explore two iterative approaches for obtaining and refining abstractions -- "proof based" and "counterexample based" -- and show how they can be combined into a unified algorithm. To the best of our knowledge, this is the first application of Proof-Based Abstraction, primarily used to verify hardware, to Software Verification. We have implemented a prototype of the framework using Z3, and evaluate it on many benchmarks from the Software Verification Competition. We show experimentally that our combination is quite effective on hard instances.
The Formal Metabasis For Conformity Assessment of Information Security Software and Hardware
Venue: arXiv cs.CR 2013
Year: 2013

An approach to the development of security test procedures for information security controls is presented. The recommendations for optimizing the test procedure are obtained
Discriminative extended canonical correlation analysis for pattern set matching
Venue: arXiv cs.CV 2013
Year: 2013

In this paper we address the problem of matching sets of vectors embedded in the same input space. We propose an approach which is motivated by canonical correlation analysis (CCA), a statistical technique which has proven successful in a wide variety of pattern recognition problems. Like CCA when applied to the matching of sets, our extended canonical correlation analysis (E-CCA) aims to extract the most similar modes of variability within two sets. Our first major contribution is the formulation of a principled framework for robust inference of such modes from data in the presence of uncertainty associated with noise and sampling randomness. E-CCA retains the efficiency and closed form computability of CCA, but unlike it, does not possess free parameters which cannot be inferred directly from data (inherent data dimensionality, and the number of canonical correlations used for set similarity computation). Our second major contribution is to show that in contrast to CCA, E-CCA is readily adapted to match sets in a discriminative learning scheme which we call discriminative extended canonical correlation analysis (DE-CCA). Theoretical contributions of this paper are followed by an empirical evaluation of its premises on the task of face recognition from sets of rasterized appearance images. The results demonstrate that our approach, E-CCA, already outperforms both CCA and its quasi-discriminative counterpart constrained CCA (C-CCA), for all values of their free parameters. An even greater improvement is achieved with the discriminative variant, DE-CCA.
Metric Dimension for Gabriel Unit Disk Graphs is NP-Complete
Venue: arXiv cs.CC 2013
Year: 2013

We show that finding a minimal number of landmark nodes for a unique virtual addressing by hop-distances in wireless ad-hoc sensor networks is NP-complete even if the networks are unit disk graphs that contain only Gabriel edges. This problem is equivalent to Metric Dimension for Gabriel unit disk graphs. The Gabriel edges of a unit disc graph induce a planar O(\sqrt{n}) distance and an optimal energy spanner. This is one of the most interesting restrictions of Metric Dimension in the context of wireless multi-hop networks.
An Insight to Covert Channels
Venue: arXiv cs.CR 2013
Year: 2013

This paper presents an overview of different concepts regarding covert channels. It discusses the various classifications and the detailing of various fields used to manipulate for the covert channel execution.Different evaluation criterias are presented for measuring the strength of covert channels. The defenses and prevention schemes for this covert channel will also be discussed. This paper also discuss about an advanced timing channel i.e.Temperature Based Covert Channel.
Distributed Detection in Coexisting Large-scale Sensor Networks
Venue: arXiv cs.IT 2013
Year: 2013

This paper considers signal detection in coexisting wireless sensor networks (WSNs). We characterize the aggregate signal and interference from a Poisson random field of nodes and define a binary hypothesis testing problem to detect a signal in the presence of interference. For the testing problem, we introduce the maximum likelihood (ML) detector and simpler alternatives. The proposed mixed-fractional lower order moment (FLOM) detector is computationally simple and close to the ML performance, and robust to estimation errors in system parameters. We also derived asymptotic theoretical performances for the proposed simple detectors. Monte-Carlo simulations are used to supplement our analytical results and compare the performance of the receivers.
An Aggregation-Based Overall Quality Measurement for Visualization
Venue: arXiv cs.HC 2013
Year: 2013

Aesthetics are often used to evaluate the quality of graph drawings. However, the existing aesthetic criteria are useful in judging the extents to which a drawing conforms to particular drawing rules. They have limitations in evaluating overall quality. Currently the overall quality of graph drawings is mainly evaluated based on personal judgments and user studies. Personal judgments are not reliable, while user studies can be costly to run. Therefore, there is a need for a direct measure of overall quality. This measure can be used by visualization designers to quickly compare the quality of drawings at hand at the design stage and make decisions accordingly. In an attempt to meet this need, we propose a measure that measures overall quality based on aggregation of individual aesthetic criteria. We present a user study that validates this measure and demonstrates its capacity in predicting the performance of human graph comprehension. The implications of the proposed measure for future research are discussed.
Action Research Can Swing the Balance in Experimental Software Engineering
Venue: arXiv cs.SE 2013
Year: 2013

In general, professionals still ignore scientific evidence in place of expert opinions in most of their decision-making. For this reason, it is still common to see the adoption of new software technologies in the field without any scientific basis or well-grounded criteria, but on the opinions of experts. Experimental Software Engineering is of paramount importance to provide the foundations to understand the limits and applicability of software technologies. The need to better observe and understand the practice of Software Engineering leads us to look for alternative experimental approaches to support our studies. Different research strategies can be used to explore different Software Engineering practices. Action Research can be seen as one alternative to intensify the conducting of important experimental studies with results of great value while investigating the Software Engineering practices in depth. In this paper, a discussion on the use of Action Research in Software Engineering is presented. Aiming at better explaining the application of Action Research, an experimental study (in vivo) on the investigation of the subjective decisions of software developers, concerned with the refactoring of source code to improve source code quality in a distributed software development context is depicted. In addition, some guidance on how to accomplish an Action Research study in Software Engineering supplement the discussions.
A Systematically Empirical Evaluation of Vulnerability Discovery Models: a Study on Browsers' Vulnerabilities
Venue: arXiv cs.CR 2013
Year: 2013

A precise vulnerability discovery model (VDM) will provide a useful insight to assess software security, and could be a good prediction instrument for both software vendors and users to understand security trends and plan ahead patching schedule accordingly. Thus far, several models have been proposed and validated. Yet, no systematically independent validation by somebody other than the author exists. Furthermore, there are a number of issues that might bias previous studies in the field. In this work, we fill in the gap by introducing an empirical methodology that systematically evaluates the performance of a VDM in two aspects: quality and predictability. We further apply this methodology to assess existing VDMs. The results show that some models should be rejected outright, while some others might be adequate to capture the discovery process of vulnerabilities. We also consider different usage scenarios of VDMs and find that the simplest linear model is the most appropriate choice in terms of both quality and predictability when browsers are young. Otherwise, logistics-based models are better choices.
Introducing LETOR 4.0 Datasets
Venue: arXiv cs.IR 2013
Year: 2013

LETOR is a package of benchmark data sets for research on LEarning TO Rank, which contains standard features, relevance judgments, data partitioning, evaluation tools, and several baselines. Version 1.0 was released in April 2007. Version 2.0 was released in Dec. 2007. Version 3.0 was released in Dec. 2008. This version, 4.0, was released in July 2009. Very different from previous versions (V3.0 is an update based on V2.0 and V2.0 is an update based on V1.0), LETOR4.0 is a totally new release. It uses the Gov2 web page collection (~25M pages) and two query sets from Million Query track of TREC 2007 and TREC 2008. We call the two query sets MQ2007 and MQ2008 for short. There are about 1700 queries in MQ2007 with labeled documents and about 800 queries in MQ2008 with labeled documents. If you have any questions or suggestions about the datasets, please kindly email us (letor@microsoft.com). Our goal is to make the dataset reliable and useful for the community.