OpenRaiser/Intern-Atlas huggingface dataset:
Characterizing the Rate Region of the (4,3,3) Exact-Repair Regenerating Codes
Venue: arXiv cs.IT 2013
Year: 2013

Exact-repair regenerating codes are considered for the case (n,k,d)=(4,3,3), for which a complete characterization of the rate region is provided. This characterization answers in the affirmative the open question whether there exists a non-vanishing gap between the optimal bandwidth-storage tradeoff of the functional-repair regenerating codes (i.e., the cut-set bound) and that of the exact-repair regenerating codes. To obtain an explicit information theoretic converse, a computer-aided proof (CAP) approach based on primal and dual relation is developed. This CAP approach extends Yeung's linear programming (LP) method, which was previously only used on information theoretic problems with a few random variables due to the exponential growth of the number of variables in the corresponding LP problem. The symmetry in the exact-repair regenerating code problem allows an effective reduction of the number of variables, and together with several other problem-specific reductions, the LP problem is reduced to a manageable scale. For the achievability, only one non-trivial corner point of the rate region needs to be addressed in this case, for which an explicit binary code construction is given.
Case-Based Merging Techniques in OAKPLAN
Venue: arXiv cs.AI 2013
Year: 2013

Case-based planning can take advantage of former problem-solving experiences by storing in a plan library previously generated plans that can be reused to solve similar planning problems in the future. Although comparative worst-case complexity analyses of plan generation and reuse techniques reveal that it is not possible to achieve provable efficiency gain of reuse over generation, we show that the case-based planning approach can be an effective alternative to plan generation when similar reuse candidates can be chosen.
Optimality of Operator-Like Wavelets for Representing Sparse AR(1) Processes
Venue: arXiv cs.IT 2013
Year: 2013

It is known that the Karhunen-Loève transform (KLT) of Gaussian first-order auto-regressive (AR(1)) processes results in sinusoidal basis functions. The same sinusoidal bases come out of the independent-component analysis (ICA) and actually correspond to processes with completely independent samples. In this paper, we relax the Gaussian hypothesis and study how orthogonal transforms decouple symmetric-alpha-stable (S$α$S) AR(1) processes. The Gaussian case is not sparse and corresponds to $α=2$, while $0<α<2$ yields processes with sparse linear-prediction error. In the presence of sparsity, we show that operator-like wavelet bases do outperform the sinusoidal ones. Also, we observe that, for processes with very sparse increments ($0<α\leq 1$), the operator-like wavelet basis is indistinguishable from the ICA solution obtained through numerical optimization. We consider two criteria for independence. The first is the Kullback-Leibler divergence between the joint probability density function (pdf) of the original signal and the product of the marginals in the transformed domain. The second is a divergence between the joint pdf of the original signal and the product of the marginals in the transformed domain, which is based on Stein's formula for the mean-square estimation error in additive Gaussian noise. Our framework then offers a unified view that encompasses the discrete cosine transform (known to be asymptotically optimal for $α=2$) and Haar-like wavelets (for which we achieve optimality for $0<α\leq1$).
Study on Delaunay tessellations of 1-irregular cuboids for 3D mixed element meshes
Venue: arXiv cs.CG 2013
Year: 2013

Mixed elements meshes based on the modified octree approach contain several co-spherical point configurations. While generating Delaunay tessellations to be used together with the finite volume method, it is not necessary to partition them into tetrahedra; co-spherical elements can be used as final elements. This paper presents a study of all co-spherical elements that appear while tessellating a 1-irregular cuboid (cuboid with at most one Steiner point on its edges) with different aspect ratio. Steiner points can be located at any position between the edge endpoints. When Steiner points are located at edge midpoints, 24 co-spherical elements appear while tessellating 1-irregular cubes. By inserting internal faces and edges to these new elements, this number is reduced to 13. When 1-irregular cuboids with aspect ratio equal to $\sqrt{2}$ are tessellated, 10 co-spherical elements are required. If 1-irregular cuboids have aspect ratio between 1 and $\sqrt{2}$, all the tessellations are adequate for the finite volume method. When Steiner points are located at any position, the study was done for a specific Steiner point distribution on a cube. 38 co-spherical elements were required to tessellate all the generated 1-irregular cubes. Statistics about the impact of each new element in the tessellations of 1-irregular cuboids are also included. This study was done by developing an algorithm that construct Delaunay tessellations by starting from a Delaunay tetrahedral mesh built by Qhull.
An Ontology Model for Organizing Information Resources Sharing on Personal Web
Venue: arXiv cs.DL 2013
Year: 2013

Retrieve information resources made by the machine processing may refer to multiple sources. A personal web as part of information resources in the Internet requires a feature that can be understood by computer machines. Therefore, in this paper an ontology semantic web approach is used to map the resources in a meaningful scheme. In the design of concept, resources on the web are viewed as documents that have some property and ownership. Domain interest or web scope is used to describe a classification of resources that navigate into relevant documents. If instances are completed to the concept, then the ontology file can be loaded and shared as annotation on personal web. This allows computer machine to query multiple ontology from different personal webs that use it.
An Analytical Model for Loc/ID Mappings Caches
Venue: arXiv cs.NI 2013
Year: 2013

Concerns regarding the scalability of the inter-domain routing have encouraged researchers to start elaborating a more robust Internet architecture. While consensus on the exact form of the solution is yet to be found, the need for a semantic decoupling of a node's location and identity is generally accepted as a promising way forward. However, this typically requires the use of caches that store temporal bindings between the two namespaces, to avoid hampering router packet forwarding speeds. In this article, we propose a methodology for an analytical analysis of cache performance that relies on the working-set theory. We first identify the conditions that network traffic must comply with for the theory to be applicable and then develop a model that predicts average cache miss rates relying on easily measurable traffic parameters. We validate the result by emulation, using real packet traces collected at the egress points of a campus and an academic network. To prove its versatility, we extend the model to consider cache polluting user traffic and observe that simple, low intensity attacks drastically reduce performance, whereby manufacturers should either overprovision router memory or implement more complex cache eviction policies.
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds
Venue: arXiv cs.DS 2013
Year: 2013

In edge orientations, the goal is usually to orient (direct) the edges of an undirected $n$-vertex graph $G$ such that all out-degrees are bounded. When the graph $G$ is fully dynamic, i.e., admits edge insertions and deletions, we wish to maintain such an orientation while keeping a tab on the update time. Low out-degree orientations turned out to be a surprisingly useful tool, with several algorithmic applications involving static or dynamic graphs. Brodal and Fagerberg (1999) initiated the study of the edge orientation problem in terms of the graph's arboricity, which is very natural in this context. They provided a solution with constant out-degree and \emph{amortized} logarithmic update time for all graphs with constant arboricity, which include all planar and excluded-minor graphs. However, it remained an open question (first proposed by Brodal and Fagerberg, later by others) to obtain similar bounds with worst-case update time. We resolve this 15 year old question in the affirmative, by providing a simple algorithm with worst-case bounds that nearly match the previous amortized bounds. Our algorithm is based on a new approach of a combinatorial invariant, and achieves a logarithmic out-degree with logarithmic worst-case update times. This result has applications in various dynamic graph problems such as maintaining a maximal matching, where we obtain $O(\log n)$ worst-case update time compared to the $O(\frac{\log n}{\log\log n})$ amortized update time of Neiman and Solomon (2013).
Handling Algebraic Effects
Venue: arXiv cs.LO 2013
Year: 2013

Algebraic effects are computational effects that can be represented by an equational theory whose operations produce the effects at hand. The free model of this theory induces the expected computational monad for the corresponding effect. Algebraic effects include exceptions, state, nondeterminism, interactive input/output, and time, and their combinations. Exception handling, however, has so far received no algebraic treatment. We present such a treatment, in which each handler yields a model of the theory for exceptions, and each handling construct yields the homomorphism induced by the universal property of the free model. We further generalise exception handlers to arbitrary algebraic effects. The resulting programming construct includes many previously unrelated examples from both theory and practice, including relabelling and restriction in Milner's CCS, timeout, rollback, and stream redirection.
Asynchronous Convolutional-Coded Physical-Layer Network Coding
Venue: arXiv cs.IT 2013
Year: 2013

This paper investigates the decoding process of asynchronous convolutional-coded physical-layer network coding (PNC) systems. Specifically, we put forth a layered decoding framework for convolutional-coded PNC consisting of three layers: symbol realignment layer, codeword realignment layer, and joint channel-decoding network coding (Jt-CNC) decoding layer. Our framework can deal with phase asynchrony and symbol arrival-time asynchrony between the signals simultaneously transmitted by multiple sources. A salient feature of this framework is that it can handle both fractional and integral symbol offsets; previously proposed PNC decoding algorithms (e.g., XOR-CD and reduced-state Viterbi algorithms) can only deal with fractional symbol offset. Moreover, the Jt-CNC algorithm, based on belief propagation (BP), is BER-optimal for synchronous PNC and near optimal for asynchronous PNC. Extending beyond convolutional codes, we further generalize the Jt-CNC decoding algorithm for all cyclic codes. Our simulation shows that Jt-CNC outperforms the previously proposed XOR-CD algorithm and reduced-state Viterbi algorithm by 2dB for synchronous PNC. For phase-asynchronous PNC, Jt-CNC is 4dB better than the other two algorithms. Importantly, for real wireless environment testing, we have also implemented our decoding algorithm in a PNC system built on the USRP software radio platform. Our experiment shows that the proposed Jt-CNC decoder works well in practice.
Food Recommendation using Ontology and Heuristics
Venue: arXiv cs.IR 2013
Year: 2013

Recommender systems are needed to find food items of ones interest. We review recommender systems and recommendation methods. We propose a food personalization framework based on adaptive hypermedia. We extend Hermes framework with food recommendation functionality. We combine TF-IDF term extraction method with cosine similarity measure. Healthy heuristics and standard food database are incorporated into the knowledgebase. Based on the performed evaluation, we conclude that semantic recommender systems in general outperform traditional recommenders systems with respect to accuracy, precision, and recall, and that the proposed recommender has a better F-measure than existing semantic recommenders.
Developer Experience: Concept and Definition
Venue: arXiv cs.SE 2013
Year: 2013

New ways of working such as globally distributed development or the integration of self-motivated external developers into software ecosystems will require a better and more comprehensive understanding of developers' feelings, perceptions, motivations and identification with their tasks in their respective project environments. User experience is a concept that captures how persons feel about products, systems and services. It evolved from disciplines such as interaction design and usability to a much richer scope that includes feelings, motivations, and satisfaction. Similarly, developer experience could be defined as a means for capturing how developers think and feel about their activities within their working environments, with the assumption that an improvement of the developer experience has positive impacts on characteristics such as sustained team and project performance. This article motivates the importance of developer experience, sketches related approaches from other domains, proposes a definition of developer experience that is derived from similar concepts in other domains, describes an ongoing empirical study to better understand developer experience, and finally gives an outlook on planned future research activities.
Multi-Sensor Image Fusion Based on Moment Calculation
Venue: arXiv cs.CV 2013
Year: 2013

An image fusion method based on salient features is proposed in this paper. In this work, we have concentrated on salient features of the image for fusion in order to preserve all relevant information contained in the input images and tried to enhance the contrast in fused image and also suppressed noise to a maximum extent. In our system, first we have applied a mask on two input images in order to conserve the high frequency information along with some low frequency information and stifle noise to a maximum extent. Thereafter, for identification of salience features from sources images, a local moment is computed in the neighborhood of a coefficient. Finally, a decision map is generated based on local moment in order to get the fused image. To verify our proposed algorithm, we have tested it on 120 sensor image pairs collected from Manchester University UK database. The experimental results show that the proposed method can provide superior fused image in terms of several quantitative fusion evaluation index.
On Coordinating Ultra-Dense Wireless Access Networks: Optimization Modeling, Algorithms and Insights
Venue: arXiv cs.IT 2013
Year: 2013

Network densification along with universal resources reuse is expected to play a key role in the realization of 5G radio access as an enabler for delivering most of the anticipated network capacity improvements. On the one hand, neither the expected additional spectrum allocation nor the forthcoming novel air-interface processing techniques will be sufficient for sustaining the anticipated exponentially-increasing mobile data traffic. On the other hand, enhanced ultra-dense infrastructure deployments are expected to provide remarkable capacity gains, regardless of the evolutionary or revolutionary approach followed towards 5G development. In this work, we thoroughly examine global network coordination as the main enabler for future 5G large dense small-cell deployments. We propose a powerful radio resources coordination framework through which interference management is handled network-wise and jointly over multiple dimensions. In particular, we explore strategies for pairing serving and served access nodes, partitioning the available network resources, as well as dynamically allocating power per pair, towards optimizing system performance and guaranteeing individual minimum performance levels. We develop new optimization formulations, providing network scaling performance upper bounds, along with lower complexity algorithmic solutions tailored to large networks. We apply the proposed solutions to dense network deployments, in order to obtain useful insights on network performance and optimization, such as rate scaling, infrastructure density, optimal bandwidth partitioning and spatial reuse factor optimization.
Particle Swarm Optimization of Information-Content Weighting of Symbolic Aggregate Approximation
Venue: arXiv cs.NE 2013
Year: 2013

Bio-inspired optimization algorithms have been gaining more popularity recently. One of the most important of these algorithms is particle swarm optimization (PSO). PSO is based on the collective intelligence of a swam of particles. Each particle explores a part of the search space looking for the optimal position and adjusts its position according to two factors; the first is its own experience and the second is the collective experience of the whole swarm. PSO has been successfully used to solve many optimization problems. In this work we use PSO to improve the performance of a well-known representation method of time series data which is the symbolic aggregate approximation (SAX). As with other time series representation methods, SAX results in loss of information when applied to represent time series. In this paper we use PSO to propose a new minimum distance WMD for SAX to remedy this problem. Unlike the original minimum distance, the new distance sets different weights to different segments of the time series according to their information content. This weighted minimum distance enhances the performance of SAX as we show through experiments using different time series datasets.
The PageRank Problem, Multi-Agent Consensus and Web Aggregation -- A Systems and Control Viewpoint
Venue: arXiv cs.SY 2013
Year: 2013

PageRank is an algorithm introduced in 1998 and used by the Google Internet search engine. It assigns a numerical value to each element of a set of hyperlinked documents (that is, web pages) within the World Wide Web with the purpose of measuring the relative importance of the page. The key idea in the algorithm is to give a higher PageRank value to web pages which are visited often by web surfers. On its website, Google describes PageRank as follows: ``PageRank reflects our view of the importance of web pages by considering more than 500 million variables and 2 billion terms. Pages that are considered important receive a higher PageRank and are more likely to appear at the top of the search results." Today PageRank is a paradigmatic problem of great interest in various areas, such as information technology, bibliometrics, biology, and e-commerce, where objects are often ranked in order of importance. This article considers a distributed randomized approach based on techniques from the area of Markov chains using a graph representation consisting of nodes and links. We also outline connections with other problems of current interest to the systems and control community, which include ranking of control journals, consensus of multi-agent systems, and aggregation-based techniques.
Long-Lived Distributed Relative Localization of Robot Swarms
Venue: arXiv cs.RO 2013
Year: 2013

This paper studies the problem of having mobile robots in a multi-robot system maintain an estimate of the relative position and relative orientation of near-by robots in the environment. This problem is studied in the context of large swarms of simple robots which are capable of measuring only the distance to near-by robots. We present two distributed localization algorithms with different trade-offs between their computational complexity and their coordination requirements. The first algorithm does not require the robots to coordinate their motion. It relies on a non-linear least squares based strategy to allow robots to compute the relative pose of near-by robots. The second algorithm borrows tools from distributed computing theory to coordinate which robots must remain stationary and which robots are allowed to move. This coordination allows the robots to use standard trilateration techniques to compute the relative pose of near-by robots. Both algorithms are analyzed theoretically and validated through simulations.
HarborNet: A Real-World Testbed for Vehicular Networks
Venue: arXiv cs.NI 2013
Year: 2013

We present a real-world testbed for research and development in vehicular networking that has been deployed successfully in the sea port of Leixões in Portugal. The testbed allows for cloud-based code deployment, remote network control and distributed data collection from moving container trucks, cranes, tow boats, patrol vessels and roadside units, thereby enabling a wide range of experiments and performance analyses. After describing the testbed architecture and its various modes of operation, we give concrete examples of its use and offer insights on how to build effective testbeds for wireless networking with moving vehicles.
Modeling Suspicious Email Detection using Enhanced Feature Selection
Venue: arXiv cs.AI 2013
Year: 2013

The paper presents a suspicious email detection model which incorporates enhanced feature selection. In the paper we proposed the use of feature selection strategies along with classification technique for terrorists email detection. The presented model focuses on the evaluation of machine learning algorithms such as decision tree (ID3), logistic regression, Naïve Bayes (NB), and Support Vector Machine (SVM) for detecting emails containing suspicious content. In the literature, various algorithms achieved good accuracy for the desired task. However, the results achieved by those algorithms can be further improved by using appropriate feature selection mechanisms. We have identified the use of a specific feature selection scheme that improves the performance of the existing algorithms.
RAM-Efficient External Memory Sorting
Venue: arXiv cs.DS 2013
Year: 2013

In recent years a large number of problems have been considered in external memory models of computation, where the complexity measure is the number of blocks of data that are moved between slow external memory and fast internal memory (also called I/Os). In practice, however, internal memory time often dominates the total running time once I/O-efficiency has been obtained. In this paper we study algorithms for fundamental problems that are simultaneously I/O-efficient and internal memory efficient in the RAM model of computation.
Diagnosis of Switching Systems using Hybrid Bond Graph
Venue: arXiv cs.SY 2013
Year: 2013

Hybrid Bond Graph (HBG) is a Bond Graph-based modelling approach which provides an effective tool not only for dynamic modeling but also for fault detection and isolation (FDI) of switching systems. Bond graph (BG) has been proven useful for FDI for continuous systems. In addition, BG provides the causal relations between systems variables which allow FDI algorithms to be developed systematically from the graph. There are many methods that exploit structural relations and functional redundancy in the system model to find efficient solutions for the residual generation and residual evaluation steps in FDI of switching systems. This paper describes two different techniques, quantitative and qualitative, based on common modelling approach that employs HBG. In quantitative approach, global analytical redundancy relationships (GARRs) are derived from the HBG model with a specified causality assignment procedure. GARRs describe the system behaviour at all of its operating modes. In qualitative approach, functional redundancy can be captured by a Temporal Causal Graph (TCG), a directed graph that may include temporal information