OpenRaiser/Intern-Atlas huggingface dataset:
Hybrid MPI-OpenMP Paradigm on SMP Clusters: MPEG-2 Encoder and N-Body Simulation
Venue: arXiv cs.DC 2012
Year: 2012

Clusters of SMP nodes provide support for a wide diversity of parallel programming paradigms. Combining both shared memory and message passing parallelizations within the same application, the hybrid MPI-OpenMP paradigm is an emerging trend for parallel programming to fully exploit distributed shared-memory architecture. In this paper, we improve the performance of MPEG-2 encoder and n-body simulation by employing the hybrid MPI-OpenMP programming paradigm on SMP clusters. The hierarchical image data structure of the MPEG bit-stream is eminently suitable for the hybrid model to achieve multiple levels of parallelism: MPI for parallelism at the group of pictures level across SMP nodes and OpenMP for parallelism within pictures at the slice level within each SMP node. Similarly, the work load of the force calculation which accounts for upwards of 90% of the cycles in typical computations in the n-body simulation is shared among OpenMP threads after ORB domain decomposition among MPI processes. Besides, loop scheduling of OpenMP threads is adopted with appropriate chunk size to provide better load balance of work, leading to enhanced performance. With the n-body simulation, experimental results demonstrate that the hybrid MPI-OpenMP program outperforms the corresponding pure MPI program by average factors of 1.52 on a 4-way cluster and 1.21 on a 2-way cluster. Likewise, the hybrid model offers a performance improvement of 18% compared to the MPI model for the MPEG-2 encoder.
MDSA: Modified Distributed Storage Algorithm for Wireless Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

In this paper, we propose a Modified distributed storage algorithm for wireless sensor networks (MDSA). Wireless Sensor Networks, as it is well known, suffer of power limitation, small memory capacity,and limited processing capabilities. Therefore, every node may disappear temporarily or permanently from the network due to many different reasons such as battery failure or physical damage. Since every node collects significant data about its region, it is important to find a methodology to recover these data in case of failure of the source node. Distributed storage algorithms provide reliable access to data through the redundancy spread over individual unreliable nodes. The proposed algorithm uses flooding to spread data over the network and unicasting to provide controlled data redundancy through the network. We evaluate the performance of the proposed algorithm through implementation and simulation. We show the results and the performance evaluation of the proposed algorithm.
Government Initiatives: The Missing Key for E-commerce Growth in KSA
Venue: arXiv cs.CY 2012
Year: 2012

This paper explores the issues that influence online retailing in Saudi Arabia. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, several factors influencing online retailing diffusion in Saudi Arabia are identified. However, government support comes the highest and most influencing factor for online retailing growth as identified by both parties; retailers and potential customers in Saudi Arabia.
Factors unflinching e-commerce adoption by retailers in Saudi Arabia: Qual Analysis
Venue: arXiv cs.CY 2012
Year: 2012

This paper presents the preliminary findings of a study researching the diffusion and the adoption of online retailing in Saudi Arabia. It reports new research that identifies and explores the key issues that positively and negatively influence retailers in Saudi Arabia regarding the adoption of electronic commerce. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, ecommerce activities are not progressing at the same speed. Only a tiny number of Saudi commercial organizations, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data, collected by conducting interviews with a sample population of retail sector decision makers in Saudi Arabia, both positive and negative issues influencing retailer adoption of electronic retailing systems in Saudi Arabia are identified. A number of impediments which include cultural, business and technical issues were reported. Facilitating factors include access to educational programs and awareness building of e-commerce, government support and assistance for ecommerce, trustworthy and secure online payment options, developing strong ICT infrastructure, and provision of sample e-commerce software to trial. While literature reveals that government promotion has had limited effects on the diffusion of e-commerce in most countries, this study significantly indicates government promotion and support as a key driver to online retailing in KSA.
Work Integrated Learning (WIL) In Virtual Reality (VR)
Venue: arXiv cs.HC 2012
Year: 2012

The focus of this report is to initially discuss the concepts WIL and VR, their main characteristics and current applications. Moreover, the pros and cons of VWIL are also analyzed. Finally, the report presents some recommendation including further researches into areas where VWIL has potential to be successful in the future.
A Non-Blind Watermarking Scheme for Gray Scale Images in Discrete Wavelet Transform Domain using Two Subbands
Venue: arXiv cs.MM 2012
Year: 2012

Digital watermarking is the process to hide digital pattern directly into a digital content. Digital watermarking techniques are used to address digital rights management, protect information and conceal secrets. An invisible non-blind watermarking approach for gray scale images is proposed in this paper. The host image is decomposed into 3-levels using Discrete Wavelet Transform. Based on the parent-child relationship between the wavelet coefficients the Set Partitioning in Hierarchical Trees (SPIHT) compression algorithm is performed on the LH3, LH2, HL3 and HL2 subbands to find out the significant coefficients. The most significant coefficients of LH2 and HL2 bands are selected to embed a binary watermark image. The selected significant coefficients are modulated using Noise Visibility Function, which is considered as the best strength to ensure better imperceptibility. The approach is tested against various image processing attacks such as addition of noise, filtering, cropping, JPEG compression, histogram equalization and contrast adjustment. The experimental results reveal the high effectiveness of the method.
Extending Refusal Testing by Stochastic Refusals for Testing Non-deterministic Systems
Venue: arXiv cs.SE 2012
Year: 2012

Testing is a validation activity used to check the system's correctness with respect to the specification. In this context,test based on refusals is studied in theory and tools are effectively constructed. This paper addresses,a formal testing based on stochastic refusals graphs (SRG) in order to test stochastic system represented by maximality-based labeled stochastic transition systems (MLSTS). First, we propose a framework to generate SRGs from MLSTSs. Second,we present a new technique to generate automatically a canonical tester from stochastic refusal graph and conformance relation confSRG. Finally, implementation is proposed and the application of our approach is shown by an example.
Hybrid Systems for Knowledge Representation in Artificial Intelligence
Venue: arXiv cs.AI 2012
Year: 2012

There are few knowledge representation (KR) techniques available for efficiently representing knowledge. However, with the increase in complexity, better methods are needed. Some researchers came up with hybrid mechanisms by combining two or more methods. In an effort to construct an intelligent computer system, a primary consideration is to represent large amounts of knowledge in a way that allows effective use and efficiently organizing information to facilitate making the recommended inferences. There are merits and demerits of combinations, and standardized method of KR is needed. In this paper, various hybrid schemes of KR were explored at length and details presented.
Multi-Sensor Fusion via Reduction of Dimensionality
Venue: arXiv cs.CV 2012
Year: 2012

Large high-dimensional datasets are becoming more and more popular in an increasing number of research areas. Processing the high dimensional data incurs a high computational cost and is inherently inefficient since many of the values that describe a data object are redundant due to noise and inner correlations. Consequently, the dimensionality, i.e. the number of values that are used to describe a data object, needs to be reduced prior to any other processing of the data. The dimensionality reduction removes, in most cases, noise from the data and reduces substantially the computational cost of algorithms that are applied to the data. In this thesis, a novel coherent integrated methodology is introduced (theory, algorithm and applications) to reduce the dimensionality of high-dimensional datasets. The method constructs a diffusion process among the data coordinates via a random walk. The dimensionality reduction is obtained based on the eigen-decomposition of the Markov matrix that is associated with the random walk. The proposed method is utilized for: (a) segmentation and detection of anomalies in hyper-spectral images; (b) segmentation of multi-contrast MRI images; and (c) segmentation of video sequences. We also present algorithms for: (a) the characterization of materials using their spectral signatures to enable their identification; (b) detection of vehicles according to their acoustic signatures; and (c) classification of vascular vessels recordings to detect hyper-tension and cardio-vascular diseases. The proposed methodology and algorithms produce excellent results that successfully compete with current state-of-the-art algorithms.
Enumeration of sequences with large alphabets
Venue: arXiv cs.DS 2012
Year: 2012

This study focuses on efficient schemes for enumerative coding of $σ$--ary sequences by mainly borrowing ideas from Öktem & Astola's \cite{Oktem99} hierarchical enumerative coding and Schalkwijk's \cite{Schalkwijk72} asymptotically optimal combinatorial code on binary sequences. By observing that the number of distinct $σ$--dimensional vectors having an inner sum of $n$, where the values in each dimension are in range $[0...n]$ is $K(σ,n) = \sum_{i=0}^{σ-1} {{n-1} \choose {σ-1-i}} {σ \choose {i}}$, we propose representing $C$ vector via enumeration, and present necessary algorithms to perform this task. We prove $\log K(σ,n)$ requires approximately $ (σ-1) \log (σ-1) $ less bits than the naive $(σ-1)\lceil \log (n+1) \rceil$ representation for relatively large $n$, and examine the results for varying alphabet sizes experimentally. We extend the basic scheme for the enumerative coding of $σ$--ary sequences by introducing a new method for large alphabets. We experimentally show that the newly introduced technique is superior to the basic scheme by providing experiments on DNA sequences.
Segregating event streams and noise with a Markov renewal process model
Venue: arXiv cs.AI 2012
Year: 2012

We describe an inference task in which a set of timestamped event observations must be clustered into an unknown number of temporal sequences with independent and varying rates of observations. Various existing approaches to multi-object tracking assume a fixed number of sources and/or a fixed observation rate; we develop an approach to inferring structure in timestamped data produced by a mixture of an unknown and varying number of similar Markov renewal processes, plus independent clutter noise. The inference simultaneously distinguishes signal from noise as well as clustering signal observations into separate source streams. We illustrate the technique via a synthetic experiment as well as an experiment to track a mixture of singing birds.
Non-asymptotic Upper Bounds for Deletion Correcting Codes
Venue: arXiv cs.IT 2012
Year: 2012

Explicit non-asymptotic upper bounds on the sizes of multiple-deletion correcting codes are presented. In particular, the largest single-deletion correcting code for $q$-ary alphabet and string length $n$ is shown to be of size at most $\frac{q^n-q}{(q-1)(n-1)}$. An improved bound on the asymptotic rate function is obtained as a corollary. Upper bounds are also derived on sizes of codes for a constrained source that does not necessarily comprise of all strings of a particular length, and this idea is demonstrated by application to sets of run-length limited strings. The problem of finding the largest deletion correcting code is modeled as a matching problem on a hypergraph. This problem is formulated as an integer linear program. The upper bound is obtained by the construction of a feasible point for the dual of the linear programming relaxation of this integer linear program. The non-asymptotic bounds derived imply the known asymptotic bounds of Levenshtein and Tenengolts and improve on known non-asymptotic bounds. Numerical results support the conjecture that in the binary case, the Varshamov-Tenengolts codes are the largest single-deletion correcting codes.
A characterization of two-weight projective cyclic codes
Venue: arXiv cs.IT 2012
Year: 2012

We give necessary conditions for a two-weight projective cyclic code to be the direct sum of two one-weight irreducible cyclic subcodes of the same dimension, following the work of Wolfmann and Vega. This confirms Vega's conjecture that all the two-weight cyclic codes of this type are the known ones in the projective case.
The Robustness of Scale-free Networks Under Edge Attacks with the Quantitative Analysis
Venue: arXiv cs.SI 2012
Year: 2012

Previous studies on the invulnerability of scale-free networks under edge attacks supported the conclusion that scale-free networks would be fragile under selective attacks. However, these studies are based on qualitative methods with obscure definitions on the robustness. This paper therefore employs a quantitative method to analyze the invulnerability of the scale-free networks, and uses four scale-free networks as the experimental group and four random networks as the control group. The experimental results show that some scale-free networks are robust under selective edge attacks, different to previous studies. Thus, this paper analyzes the difference between the experimental results and previous studies, and suggests reasonable explanations.
On the principal impossibility to prove P=NP
Venue: arXiv cs.CC 2012
Year: 2012

The material of the article is devoted to the most complicated and interesting problem -- a problem of P = NP?. This research was presented to mathematical community in Hyderabad during International Congress of Mathematicians. But there it was published in a very brief form, so this article is an attempt to give those, who are interested in the problem, my reasoning on the theme. It is not a proof in full, because it is very difficult to prove something, which is not provable, but it seems that these reasoning will help us to understand the problem of the combinatorial explosion more deeply and to realize in full all the problems to which we are going because of the combinatorial explosion. Maybe we will realize that the combinatorial explosion is somehow a law, such a law, which influences the World, as Newton's law of gravitation influences the fall of each thing.
Spectral Efficiency in Large-Scale MIMO-OFDM Systems with Per-Antenna Power Cost
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, resource allocation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) downlink networks with large numbers of base station antennas is studied. Assuming perfect channel state information at the transmitter, the resource allocation algorithm design is modeled as a non-convex optimization problem which takes into account the joint power consumption of the power amplifiers, antenna unit, and signal processing circuit unit. Subsequently, by exploiting the law of large numbers and dual decomposition, an efficient suboptimal iterative resource allocation algorithm is proposed for maximization of the system capacity (bit/s). In particular, closed-form power allocation and antenna allocation policies are derived in each iteration. Simulation results illustrate that the proposed iterative resource allocation algorithm achieves a close-to-optimal performance in a small number of iterations and unveil a trade-off between system capacity and the number of activated antennas: Activating all antennas may not be a good solution for system capacity maximization when a system with a per antenna power cost is considered.
Radio Resource Allocation Algorithms for Multi-Service OFDMA Networks: The Uniform Power Loading Scenario
Venue: arXiv cs.IT 2012
Year: 2012

Adaptive Radio Resource Allocation is essential for guaranteeing high bandwidth and power utilization as well as satisfying heterogeneous Quality-of-Service requests regarding next generation broadband multicarrier wireless access networks like LTE and Mobile WiMAX. A downlink OFDMA single-cell scenario is considered where heterogeneous Constant-Bit-Rate and Best-Effort QoS profiles coexist and the power is uniformly spread over the system bandwidth utilizing a Uniform Power Loading (UPL) scenario. We express this particular QoS provision scenario in mathematical terms, as a variation of the well-known generalized assignment problem answered in the combinatorial optimization field. Based on this concept, we propose two heuristic search algorithms for dynamically allocating subchannels to the competing QoS classes and users which are executed under polynomially-bounded cost. We also propose an Integer Linear Programming model for optimally solving and acquiring a performance upper bound for the same problem at reasonable yet high execution times. Through extensive simulation results we show that the proposed algorithms exhibit high close-to-optimal performance, thus comprising attractive candidates for implementation in modern OFDMA-based systems.
How to compute the constant term of a power of a Laurent polynomial efficiently
Venue: arXiv cs.SC 2012
Year: 2012

We present an algorithm for efficient computation of the constant term of a power of a multivariate Laurent polynomial. The algorithm is based on univariate interpolation, does not require the storage of intermediate data and can be easily parallelized. As an application we compute the power series expansion of the principal period of some toric Calabi-Yau varieties and find previously unknown differential operators of Calabi-Yau type.
Standardization in resource lambda-calculus
Venue: arXiv cs.LO 2012
Year: 2012

The resource calculus is an extension of the lambda-calculus allowing to model resource consumption. It is intrinsically non-deterministic and has two general notions of reduction - one parallel, preserving all the possible results as a formal sum, and one non-deterministic, performing an exclusive choice at every step. We prove that the non-deterministic reduction enjoys a notion of standardization, which is the natural extension with respect to the similar one in classical lambda-calculus. The full parallel reduction only enjoys a weaker notion of standardization instead. The result allows an operational characterization of may-solvability, which has been introduced and already characterized (from the syntactical and logical points of view) by Pagani and Ronchi Della Rocca.
A Logic and Adaptive Approach for Efficient Diagnosis Systems using CBR
Venue: arXiv cs.AI 2012
Year: 2012

Case Based Reasoning (CBR) is an intelligent way of thinking based on experience and capitalization of already solved cases (source cases) to find a solution to a new problem (target case). Retrieval phase consists on identifying source cases that are similar to the target case. This phase may lead to erroneous results if the existing knowledge imperfections are not taken into account. This work presents a novel solution based on Fuzzy logic techniques and adaptation measures which aggregate weighted similarities to improve the retrieval results. To confirm the efficiency of our solution, we have applied it to the industrial diagnosis domain. The obtained results are more efficient results than those obtained by applying typical measures.
On Achievable Schemes of Interference Alignment with Double-Layered Symbol Extensions in Interference Channel
Venue: arXiv cs.IT 2012
Year: 2012

This paper looks into the $K$-user interference channel. Interference Alignment is much likely to be applied with double-layered symbol extensions, either for constant channels in the H$ø$st-Madsen-Nosratinia conjecture or slowly changing channels. In our work, the core idea relies on double-layered symbol extensions to artificially construct equivalent time-variant channels to provide crucial \textit{channel randomness or relativity} required by conventional Cadambe-Jafar scheme in time-variant channels \cite{IA-DOF-Kuser-Interference}.
An Algorithm for Optimized Searching using NON-Overlapping Iterative Neighbor intervals
Venue: arXiv cs.DS 2012
Year: 2012

We have attempted in this paper to reduce the number of checked condition through saving frequency of the tandem replicated words, and also using non-overlapping iterative neighbor intervals on plane sweep algorithm. The essential idea of non-overlapping iterative neighbor search in a document lies in focusing the search not on the full space of solutions but on a smaller subspace considering non-overlapping intervals defined by the solutions. Subspace is defined by the range near the specified minimum keyword. We repeatedly pick a range up and flip the unsatisfied keywords, so the relevant ranges are detected. The proposed method tries to improve the plane sweep algorithm by efficiently calculating the minimal group of words and enumerating intervals in a document which contain the minimum frequency keyword. It decreases the number of comparison and creates the best state of optimized search algorithm especially in a high volume of data. Efficiency and reliability are also increased compared to the previous modes of the technical approach.
An upper bound for the crossing number of bubble-sort graph Bn
Venue: arXiv cs.DM 2012
Year: 2012

The crossing number of a graph G is the minimum number of pairwise intersections of edges in a drawing of G. Motivated by the recent work [Faria, L., Figueiredo, C.M.H. de, Sykora, O., Vrt'o, I.: An improved upper bound on the crossing number of the hypercube. J. Graph Theory 59, 145-161 (2008)], we give an upper bound of the crossing number of n-dimensional bubble-sort graph Bn.
A Rule-Based Approach For Aligning Japanese-Spanish Sentences From A Comparable Corpora
Venue: arXiv cs.CL 2012
Year: 2012

The performance of a Statistical Machine Translation System (SMT) system is proportionally directed to the quality and length of the parallel corpus it uses. However for some pair of languages there is a considerable lack of them. The long term goal is to construct a Japanese-Spanish parallel corpus to be used for SMT, whereas, there are a lack of useful Japanese-Spanish parallel Corpus. To address this problem, In this study we proposed a method for extracting Japanese-Spanish Parallel Sentences from Wikipedia using POS tagging and Rule-Based approach. The main focus of this approach is the syntactic features of both languages. Human evaluation was performed over a sample and shows promising results, in comparison with the baseline.