OpenRaiser/Intern-Atlas huggingface dataset:
An Order of Magnitude Calculus
Venue: arXiv cs.AI 2013
Year: 2013

This paper develops a simple calculus for order of magnitude reasoning. A semantics is given with soundness and completeness results. Order of magnitude probability functions are easily defined and turn out to be equivalent to kappa functions, which are slight generalizations of Spohn's Natural Conditional Functions. The calculus also gives rise to an order of magnitude decision theory, which can be used to justify an amended version of Pearl's decision theory for kappa functions, although the latter is weaker and less expressive.
Model-driven engineering approach to design and implementation of robot control system
Venue: arXiv cs.RO 2013
Year: 2013

In this paper we apply a model-driven engineering approach to designing domain-specific solutions for robot control system development. We present a case study of the complete process, including identification of the domain meta-model, graphical notation definition and source code generation for subsumption architecture -- a well-known example of robot control architecture. Our goal is to show that both the definition of the robot-control architecture and its supporting tools fits well into the typical workflow of model-driven engineering development.
Verifying PRAM Consistency over Read/Write Traces of Data Replicas
Venue: arXiv cs.DC 2013
Year: 2013

Data replication technologies enable efficient and highly-available data access, thus gaining more and more interests in both the academia and the industry. However, data replication introduces the problem of data consistency. Modern commercial data replication systems often provide weak consistency for high availability under certain failure scenarios. An important weak consistency is Pipelined-RAM (PRAM) consistency. It allows different processes to hold different views of data. To determine whether a data replication system indeed provides PRAM consistency, we study the problem of Verifying PRAM Consistency over read/write traces (or VPC, for short). We first identify four variants of VPC according to a) whether there are Multiple shared variables (or one Single variable), and b) whether write operations can assign Duplicate values (or only Unique values) for each shared variable; the four variants are labeled VPC-SU, VPC-MU, VPC-SD, and VPC-MD. Second, we present a simple VPC-MU algorithm, called RW-CLOSURE. It constructs an operation graph $\mathcal{G}$ by iteratively adding edges according to three rules. Its time complexity is $O(n^5)$, where n is the number of operations in the trace. Third, we present an improved VPC-MU algorithm, called READ-CENTRIC, with time complexity $O(n^4)$. Basically it attempts to construct the operation graph $\mathcal{G}$ in an incremental and efficient way. Its correctness is based on that of RW-CLOSURE. Finally, we prove that VPC-SD (so is VPC-MD) is $\sf{NP}$-complete by reducing the strongly $\sf{NP}$-complete problem 3-PARTITION to it.
The CORE Storage Primitive: Cross-Object Redundancy for Efficient Data Repair & Access in Erasure Coded Storage
Venue: arXiv cs.DC 2013
Year: 2013

Erasure codes are an integral part of many distributed storage systems aimed at Big Data, since they provide high fault-tolerance for low overheads. However, traditional erasure codes are inefficient on reading stored data in degraded environments (when nodes might be unavailable), and on replenishing lost data (vital for long term resilience). Consequently, novel codes optimized to cope with distributed storage system nuances are vigorously being researched. In this paper, we take an engineering alternative, exploring the use of simple and mature techniques -juxtaposing a standard erasure code with RAID-4 like parity. We carry out an analytical study to determine the efficacy of this approach over traditional as well as some novel codes. We build upon this study to design CORE, a general storage primitive that we integrate into HDFS. We benchmark this implementation in a proprietary cluster and in EC2. Our experiments show that compared to traditional erasure codes, CORE uses 50% less bandwidth and is up to 75% faster while recovering a single failed node, while the gains are respectively 15% and 60% for double node failures.
Predicting the Temporal Dynamics of Information Diffusion in Social Networks
Venue: arXiv cs.SI 2013
Year: 2013

Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyse this phenomenon. In this paper we address the issue of predicting the temporal dynamics of the information diffusion process. We develop a graph-based approach built on the assumption that the macroscopic dynamics of the spreading process are explained by the topology of the network and the interactions that occur through it, between pairs of users, on the basis of properties at the microscopic level. We introduce a generic model, called T-BaSIC, and describe how to estimate its parameters from users behaviours using machine learning techniques. Contrary to classical approaches where the parameters are fixed in advance, T-BaSIC's parameters are functions depending of time, which permit to better approximate and adapt to the diffusion phenomenon observed in online social networks. Our proposal has been validated on real Twitter datasets. Experiments show that our approach is able to capture the particular patterns of diffusion depending of the studied sub-networks of users and topics. The results corroborate the "two-step" theory (1955) that states that information flows from media to a few "opinion leaders" who then transfer it to the mass population via social networks and show that it applies in the online context. This work also highlights interesting recommendations for future investigations.
Sparse Fault-Tolerant BFS Trees
Venue: arXiv cs.DS 2013
Year: 2013

This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the surviving part $T'$ of $T$ still contains a BFS spanning tree for (the surviving part of) $G$. Our main results are as follows. We present an algorithm that for every $n$-vertex graph $G$ and source node $s$ constructs a (single edge failure) FT-BFS tree rooted at $s$ with $O(n \cdot \min\{\Depth(s), \sqrt{n}\})$ edges, where $\Depth(s)$ is the depth of the BFS tree rooted at $s$. This result is complemented by a matching lower bound, showing that there exist $n$-vertex graphs with a source node $s$ for which any edge (or vertex) FT-BFS tree rooted at $s$ has $Ω(n^{3/2})$ edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source $s\in S$ for some subset of sources $S\subseteq V$. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every $n$-vertex graph and source set $S \subseteq V$ of size $σ$ constructs a (single failure) FT-MBFS tree $T^*(S)$ from each source $s_i \in S$, with $O(\sqrtσ \cdot n^{3/2})$ edges, and on the other hand there exist $n$-vertex graphs with source sets $S \subseteq V$ of cardinality $σ$, on which any FT-MBFS tree from $S$ has $Ω(\sqrtσ\cdot n^{3/2})$ edges. Finally, we propose an $O(\log n)$ approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no $Ω(\log n)$ approximation algorithm for these problems under standard complexity assumptions.
Nonparametric Basis Pursuit via Sparse Kernel-based Learning
Venue: arXiv cs.LG 2013
Year: 2013

Signal processing tasks as fundamental as sampling, reconstruction, minimum mean-square error interpolation and prediction can be viewed under the prism of reproducing kernel Hilbert spaces. Endowing this vantage point with contemporary advances in sparsity-aware modeling and processing, promotes the nonparametric basis pursuit advocated in this paper as the overarching framework for the confluence of kernel-based learning (KBL) approaches leveraging sparse linear regression, nuclear-norm regularization, and dictionary learning. The novel sparse KBL toolbox goes beyond translating sparse parametric approaches to their nonparametric counterparts, to incorporate new possibilities such as multi-kernel selection and matrix smoothing. The impact of sparse KBL to signal processing applications is illustrated through test cases from cognitive radio sensing, microarray data imputation, and network traffic prediction.
Mapping Citation Patterns of Book Chapters in the Book Citation Index
Venue: arXiv cs.DL 2013
Year: 2013

In this paper we provide the reader with a visual representation of relationships among the impact of book chapters indexed in the Book Citation Index using information gain values and published by different academic publishers in specific disciplines. The impact of book chapters can be characterized statistically by citations histograms. For instance, we can compute the probability of occurrence of book chapters with a number of citations in different intervals for each academic publisher. We predict the similarity between two citation histograms based on the amount of relative information between such characterizations. We observe that the citation patterns of book chapters follow a Lotkaian distribution. This paper describes the structure of the Book Citation Index using 'heliocentric clockwise maps' which allow the reader not only to determine the grade of similarity of a given academic publisher indexed in the Book Citation Index with a specific discipline according to their citation distribution, but also to easily observe the general structure of a discipline, identifying the publishers with higher impact and output.
A tournament of order 24 with two disjoint TEQ-retentive sets
Venue: arXiv cs.MA 2013
Year: 2013

Brandt et al. (2013) have recently disproved a conjecture by Schwartz (1990) by non-constructively showing the existence of a counterexample with about 10^136 alternatives. We provide a concrete counterexample for Schwartz's conjecture with only 24 alternatives.
Role of temporal inference in the recognition of textual inference
Venue: arXiv cs.CL 2013
Year: 2013

This project is a part of nature language processing and its aims to develop a system of recognition inference text-appointed TIMINF. This type of system can detect, given two portions of text, if a text is semantically deducted from the other. We focused on making the inference time in this type of system. For that we have built and analyzed a body built from questions collected through the web. This study has enabled us to classify different types of times inferences and for designing the architecture of TIMINF which seeks to integrate a module inference time in a detection system inference text. We also assess the performance of sorties TIMINF system on a test corpus with the same strategy adopted in the challenge RTE.
Development of Yes/No Arabic Question Answering System
Venue: arXiv cs.CL 2013
Year: 2013

Developing Question Answering systems has been one of the important research issues because it requires insights from a variety of disciplines,including,Artificial Intelligence,Information Retrieval, Information Extraction,Natural Language Processing, and Psychology.In this paper we realize a formal model for a lightweight semantic based open domain yes/no Arabic question answering system based on paragraph retrieval with variable length. We propose a constrained semantic representation. Using an explicit unification framework based on semantic similarities and query expansion synonyms and antonyms.This frequently improves the precision of the system. Employing the passage retrieval system achieves a better precision by retrieving more paragraphs that contain relevant answers to the question; It significantly reduces the amount of text to be processed by the system.
Enumeration Based Search Algorithm For Finding A Regular Bi-partite Graph Of Maximum Attainable Girth For Specified Degree And Number Of Vertices
Venue: arXiv cs.DM 2013
Year: 2013

We introduce a search problem for finding a regular bi-partite graph of maximum attainable girth for specified degree and number of vertices, by restricting the search space using a series of mathematically rigourous arguments from [1] and [2]. The goal of this paper is to derive the enumeration search algorithm for finding a girth maximum (m, r) BTU, which is notation for regular partite graph that has been introduced in [1], using the optimal partition results from [2] as a starting point, and also understand the structure of the search space and the computational complexity of the algorithm.
Analysis Of The Girth For Regular Bi-partite Graphs With Degree 3
Venue: arXiv cs.DM 2013
Year: 2013

The goal of this paper is to derive the detailed description of the Enumeration Based Search Algorithm from the high level description provided in [16], analyze the experimental results from our implementation of the Enumeration Based Search Algorithm for finding a regular bi-partite graph of degree 3, and compare it with known results from the available literature. We show that the values of m for a given girth g for (m, 3) BTUs are within the known mathematical bounds for regular bi-partitite graphs from the available literature.
Towards Randomized Testing of $q$-Monomials in Multivariate Polynomials
Venue: arXiv cs.CC 2013
Year: 2013

Given any fixed integer $q\ge 2$, a $q$-monomial is of the format $\displaystyle x^{s_1}_{i_1}x^{s_2}_{i_2}...x_{i_t}^{s_t}$ such that $1\le s_j \le q-1$, $1\le j \le t$. $q$-monomials are natural generalizations of multilinear monomials. Recent research on testing multilinear monomials and $q$-monomails for prime $q$ in multivariate polynomials relies on the property that $Z_q$ is a field when $q\ge 2 $ is prime. When $q>2$ is not prime, it remains open whether the problem of testing $q$-monomials can be solved in some compatible complexity. In this paper, we present a randomized $O^*(7.15^k)$ algorithm for testing $q$-monomials of degree $k$ that are found in a multivariate polynomial that is represented by a tree-like circuit with a polynomial size, thus giving a positive, affirming answer to the above question. Our algorithm works regardless of the primality of $q$ and improves upon the time complexity of the previously known algorithm for testing $q$-monomials for prime $q>7$.
Performances of Low Temperature Radiant Heating Systems
Venue: arXiv cs.CE 2013
Year: 2013

Low temperature heating panel systems offer distinctive advantages in terms of thermal comfort and energy consumption, allowing work with low exergy sources. The purpose of this paper is to compare floor, wall, ceiling, and floor-ceiling panel heating systems in terms of energy, exergy and CO2 emissions. Simulation results for each of the analyzed panel system are given by its energy (the consumption of gas for heating, electricity for pumps and primary energy) and exergy consumption, the price of heating, and its carbon dioxide emission. Then, the values of the air temperatures of rooms are investigated and that of the surrounding walls and floors. It is found that the floor-ceiling heating system has the lowest energy, exergy, CO2 emissions, operating costs, and uses boiler of the lowest power. The worst system by all these parameters is the classical ceiling heating
Estimating Sectoral Pollution Load in Lagos, Nigeria Using Data Mining Techniques
Venue: arXiv cs.NE 2013
Year: 2013

Industrial pollution is often considered to be one of the prime factors contributing to air, water and soil pollution. Sectoral pollution loads (ton/yr) into different media (i.e. air, water and land) in Lagos were estimated using Industrial Pollution Projected System (IPPS). These were further studied using Artificial neural Networks (ANNs), a data mining technique that has the ability of detecting and describing patterns in large data sets with variables that are non- linearly related. Time Lagged Recurrent Network (TLRN) appeared as the best Neural Network model among all the neural networks considered which includes Multilayer Perceptron (MLP) Network, Generalized Feed Forward Neural Network (GFNN), Radial Basis Function (RBF) Network and Recurrent Network (RN). TLRN modelled the data-sets better than the others in terms of the mean average error (MAE) (0.14), time (39 s) and linear correlation coefficient (0.84). The results showed that Artificial Neural Networks (ANNs) technique (i.e., Time Lagged Recurrent Network) is also applicable and effective in environmental assessment study. Keywords: Artificial Neural Networks (ANNs), Data Mining Techniques, Industrial Pollution Projection System (IPPS), Pollution load, Pollution Intensity.
An event-based model for contracts
Venue: arXiv cs.LO 2013
Year: 2013

We introduce a basic model for contracts. Our model extends event structures with a new relation, which faithfully captures the circular dependencies among contract clauses. We establish whether an agreement exists which respects all the contracts at hand (i.e. all the dependencies can be resolved), and we detect the obligations of each participant. The main technical contribution is a correspondence between our model and a fragment of the contract logic PCL. More precisely, we show that the reachable events are exactly those which correspond to provable atoms in the logic. Despite of this strong correspondence, our model improves previous work on PCL by exhibiting a finer-grained notion of culpability, which takes into account the legitimate orderings of events.
Convergence in Infinitary Term Graph Rewriting Systems is Simple (Extended Abstract)
Venue: arXiv cs.LO 2013
Year: 2013

In this extended abstract, we present a simple approach to convergence on term graphs that allows us to unify term graph rewriting and infinitary term rewriting. This approach is based on a partial order and a metric on term graphs. These structures arise as straightforward generalisations of the corresponding structures used in infinitary term rewriting. We compare our simple approach to a more complicated approach that we developed earlier and show that this new approach is superior in many ways. The only unfavourable property that we were able to identify, viz. failure of full correspondence between weak metric and partial order convergence, is rectified by adopting a strong convergence discipline.
Assessing the Dimensions of Relationship Quality in B2C E Banking Services: An Empirical Comparative Study
Venue: arXiv cs.CY 2013
Year: 2013

In B2C Online services contexts where relationships between customers and service providers matter due to the lack of faceto- face interactions, uncertainty, intangibility, hyper competition, increasing risk of fraud and lack of trust. Relationship quality (RQ) is replacing service quality as a key source of superior performance and competitive advantage. Accordingly, this study investigates the dimensions of relationship quality from e-Banking services and explores the differences among customers of Jordanian and foreign banks. Many of the foreign banks in Jordan are equipped with large financial capital, having high banking and financial experiences and are offering many modern hi-tech banking services. This situation makes Jordanian banks in front of unprecedented competition and so they have invested heavily to develop their e-banking services, in order to strengthening their relationships with existing customers, enhancing their trust, letting them satisfied, ensuring their commitment and attracting of new ones. This paper aims to identify the key dimensions that shape the relationship quality among Jordanian and foreign banks and their customers who are utilizing the e-Banking services. Based on an extensive review of relevant literature, we have formulated nine hypotheses and identified three factors (satisfaction, trust, and commitment) that may affect the competitiveness and success of Jordanian and foreign banks. Survey data from 350 customers from four Jordanian banks and four foreign banks in Amman city the capital of Jordan were collected and used to test the proposed hypotheses. Based on the structural equation modeling and Ttest analyses, our empirical analysis demonstrates several key findings.
Image-based Face Detection and Recognition: "State of the Art"
Venue: arXiv cs.CV 2013
Year: 2013

Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance system as it doesn't need the object's cooperation. The actual advantages of face based identification over other biometrics are uniqueness and acceptance. As human face is a dynamic object having high degree of variability in its appearance, that makes face detection a difficult problem in computer vision. In this field, accuracy and speed of identification is a main issue. The goal of this paper is to evaluate various face detection and recognition methods, provide complete solution for image based face detection and recognition with higher accuracy, better response rate as an initial step for video surveillance. Solution is proposed based on performed tests on various face rich databases in terms of subjects, pose, emotions, race and light.
Segmentation of Alzheimers Disease in PET scan datasets using MATLAB
Venue: arXiv cs.NE 2013
Year: 2013

Positron Emission Tomography (PET) scan images are one of the bio medical imaging techniques similar to that of MRI scan images but PET scan images are helpful in finding the development of tumors.The PET scan images requires expertise in the segmentation where clustering plays an important role in the automation process.The segmentation of such images is manual to automate the process clustering is used.Clustering is commonly known as unsupervised learning process of n dimensional data sets are clustered into k groups so as to maximize the inter cluster similarity and to minimize the intra cluster similarity.This paper is proposed to implement the commonly used K Means and Fuzzy CMeans (FCM) clustering algorithm.This work is implemented using MATrix LABoratory (MATLAB) and tested with sample PET scan image. The sample data is collected from Alzheimers Disease Neuro imaging Initiative ADNI. Medical Image Processing and Visualization Tool (MIPAV) are used to compare the resultant images.
Embedding of Deterministic Test Data for In-Field Testing
Venue: arXiv cs.OH 2013
Year: 2013

This paper presents a new feedback shift register-based method for embedding deterministic test patterns on-chip suitable for complementing conventional BIST techniques for in-field testing. Our experimental results on 8 real designs show that the presented approach outperforms the bit-flipping approach by 24.7% on average. We also show that it is possible to exploit the uneven distribution of don't care bits in test patterns in order to reduce the area required for storing deterministic test patterns more than 3 times with less than 2% fault coverage drop.
Bisimulation and p-morphism for branching-time logics with indistinguishability relations
Venue: arXiv cs.LO 2013
Year: 2013

In Zanardo, 1998, the Peircean semantics for branching-time logics is enriched with a notion of indistinguishability at a moment t between histories passing through t. Trees with indistinguishability relations provide a semantics for a temporal language with tense and modal operators. In this paper a notion of p-morphism and a notion of bisimulation, wrt this language and semantics, are given and a number of preservation results are proven.