OpenRaiser/Intern-Atlas huggingface dataset:
A Density-Based Approach to the Retrieval of Top-K Spatial Textual Clusters
Venue: arXiv cs.DB 2016
Year: 2016

Keyword-based web queries with local intent retrieve web content that is relevant to supplied keywords and that represent points of interest that are near the query location. Two broad categories of such queries exist. The first encompasses queries that retrieve single spatial web objects that each satisfy the query arguments. Most proposals belong to this category. The second category, to which this paper's proposal belongs, encompasses queries that support exploratory user behavior and retrieve sets of objects that represent regions of space that may be of interest to the user. Specifically, the paper proposes a new type of query, namely the top-k spatial textual clusters (k-STC) query that returns the top-k clusters that (i) are located the closest to a given query location, (ii) contain the most relevant objects with regard to given query keywords, and (iii) have an object density that exceeds a given threshold. To compute this query, we propose a basic algorithm that relies on on-line density-based clustering and exploits an early stop condition. To improve the response time, we design an advanced approach that includes three techniques: (i) an object skipping rule, (ii) spatially gridded posting lists, and (iii) a fast range query algorithm. An empirical study on real data demonstrates that the paper's proposals offer scalability and are capable of excellent performance.
Multi-contact Walking Pattern Generation based on Model Preview Control of 3D COM Accelerations
Venue: arXiv cs.RO 2016
Year: 2016

We present a multi-contact walking pattern generator based on preview-control of the 3D acceleration of the center of mass (COM). A key point in the design of our algorithm is the calculation of contact-stability constraints. Thanks to a mathematical observation on the algebraic nature of the frictional wrench cone, we show that the 3D volume of feasible COM accelerations is a always a downward-pointing cone. We reduce its computation to a convex hull of (dual) 2D points, for which optimal O(n log n) algorithms are readily available. This reformulation brings a significant speedup compared to previous methods, which allows us to compute time-varying contact-stability criteria fast enough for the control loop. Next, we propose a conservative trajectory-wide contact-stability criterion, which can be derived from COM-acceleration volumes at marginal cost and directly applied in a model-predictive controller. We finally implement this pipeline and exemplify it with the HRP-4 humanoid model in multi-contact dynamically walking scenarios.
Shall we collaborate? A model to analyse the benefits of information sharing
Venue: arXiv cs.CR 2016
Year: 2016

Nowadays, both the amount of cyberattacks and their sophistication have considerably increased, and their prevention is of concern of most of organizations. Cooperation by means of information sharing is a promising strategy to address this problem, but unfortunately it poses many challenges. Indeed, looking for a win-win environment is not straightforward and organizations are not properly motivated to share information. This work presents a model to analyse the benefits and drawbacks of information sharing among organizations that presents a certain level of dependency. The proposed model applies functional dependency network analysis to emulate attacks propagation and game theory for information sharing management. We present a simulation framework implementing the model that allows for testing different sharing strategies under several network and attack settings. Experiments using simulated environments show how the proposed model provides insights on which conditions and scenarios are beneficial for information sharing.
Predicting Anchor Links between Heterogeneous Social Networks
Venue: arXiv cs.SI 2016
Year: 2016

People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks. In this paper, we concentrated on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the formation of a link between two existing users within a single network is predicted, in anchor link prediction, the target user is missing and will be added to the target network once the anchor link is created. To solve this problem, we use meta-paths as a powerful tool for utilizing heterogeneous information in both the source and target networks. To this end, we propose an effective general meta-path-based approach called Connector and Recursive Meta-Paths (CRMP). By using those two different categories of meta-paths, we model different aspects of social factors that may affect a source user to join the target network, resulting in the formation of a new anchor link. Extensive experiments on real-world heterogeneous social networks demonstrate the effectiveness of the proposed method against the recent methods.
Modeling Improved Fuzzy and Sliding-Mode for Single-Phase Inverter as Controllers in an EPS
Venue: arXiv cs.SY 2016
Year: 2016

In the last decades, the applications of power inverter increased rapidly. As a result, in spite of rectifier, an inverter with a high-power electronic oscillator has capability to convert direct current (DC) into alternating current (AC) in different forms. In this paper, a new fuzzy logic control (FLC) is suggested to an improved modeling inverter of a single-phase voltage source using LC filter and voltage sensor. Moreover, two sliding and fuzzy modes of non-linear voltage inverter controller are simulated and compared. The results proved the high efficiency and performance of the proposed method while reduce total harmonic distortion (THD) under linear loading conditions as well. All the data are applied on emergency power supply (EPS).
A Unified Approach for Beam-to-Beam Contact
Venue: arXiv cs.CE 2016
Year: 2016

Existing beam contact formulations can be categorized in point contact models that consider a discrete contact force at the closest point of the beams, and line contact models that assume distributed contact forces. In this work, it will be shown that line contact formulations provide accurate and robust mechanical models in the range of small contact angles, whereas the computational efficiency considerably decreases with increasing contact angles. On the other hand, point contact formulations serve as sufficiently accurate and very efficient models in the regime of large contact angles, while they are not applicable for small contact angles as a consequence of non-unique closest point projections. In order to combine the advantages of these basic formulations, a novel all-angle beam contact (ABC) formulation is developed that applies a point contact formulation for large contact angles and a recently developed line contact formulation for small contact angles, the two being smoothly connected by means of a variationally consistent model transition. Based on a stringent analysis, two different transition laws are investigated, optimal algorithmic parameters are suggested and conservation of energy and momentum is shown. All configuration-dependent quantities are consistently linearized, thus allowing for their application within implicit time integration schemes. Furthermore, a step size control of the nonlinear solution scheme that allows for large displacement increments per time step and an efficient two-stage contact search based on dynamically adapted search segments are proposed. A series of numerical test cases is analyzed in order to verify the accuracy and consistency of the proposed contact model transition regarding contact force distributions and conservation properties, but also for quantifying the efficiency gains as compared to standard beam contact formulations.
An Asynchronous Task-based Fan-Both Sparse Cholesky Solver
Venue: arXiv cs.MS 2016
Year: 2016

Systems of linear equations arise at the heart of many scientific and engineering applications. Many of these linear systems are sparse; i.e., most of the elements in the coefficient matrix are zero. Direct methods based on matrix factorizations are sometimes needed to ensure accurate solutions. For example, accurate solution of sparse linear systems is needed in shift-invert Lanczos to compute interior eigenvalues. The performance and resource usage of sparse matrix factorizations are critical to time-to-solution and maximum problem size solvable on a given platform. In many applications, the coefficient matrices are symmetric, and exploiting symmetry will reduce both the amount of work and storage cost required for factorization. When the factorization is performed on large-scale distributed memory platforms, communication cost is critical to the performance of the algorithm. At the same time, network topologies have become increasingly complex, so that modern platforms exhibit a high level of performance variability. This makes scheduling of computations an intricate and performance-critical task. In this paper, we investigate the use of an asynchronous task paradigm, one-sided communication and dynamic scheduling in implementing sparse Cholesky factorization (symPACK) on large-scale distributed memory platforms. Our solver symPACK relies on efficient and flexible communication primitives provided by the UPC++ library. Performance evaluation shows good scalability and that symPACK outperforms state-of-the-art parallel distributed memory factorization packages, validating our approach on practical cases.
Octopus: A Cooperative Hierarchical Caching Strategy for Cloud Radio Access Networks
Venue: arXiv cs.NI 2016
Year: 2016

Recently, implementing Radio Access Network (RAN) functionalities on cloud-based computing platform has become an emerging solution that leverages the many advantages of cloud infrastructure, such as shared computing resources and storage capacity, while lowering the operational cost. In this paper, we propose a novel caching framework aimed at fully exploiting the potential of such Cloud-based RAN (C-RAN) systems through cooperative hierarchical caching which minimizes the network costs of content delivery and improves users' Quality of Experience (QoE). In particular, we consider the cloud-cache in the cloud processing unit (CPU) as a new layer in the RAN cache hierarchy, bridging the capacity-performance gap between the traditional edge-based and core-based caching schemes. A delay cost model is introduced to characterize and formulate the cache placement optimization problem, which is shown to be NP-complete. As such, a low complexity, heuristic cache management strategy is proposed, constituting of a proactive cache distribution algorithm and a reactive cache replacement algorithm. Extensive numerical simulations are carried out using both real-world YouTube video requests and synthetic content requests. It is demonstrated that our proposed Octopus caching strategy significantly outperforms the traditional caching strategies in terms of cache hit ratio, average content access delay and backhaul traffic load.
Segmentation of Soft atherosclerotic plaques using active contour models
Venue: arXiv cs.CV 2016
Year: 2016

Detection of non-calcified plaques in the coronary tree is a challenging problem due to the nature of comprising substances. Hard plaques are easily discernible in CTA data cloud due to apparent bright behaviour, therefore many approaches have been proposed for automatic segmentation of calcified plaques. In contrast soft plaques show very small difference in intensity with respect to surrounding heart tissues & blood voxels. This similarity in intensity makes the isolation and detection of soft plaques very difficult. This work aims to develop framework for segmentation of vulnerable plaques with minimal user dependency. In first step automatic seed point has been established based on the fact that coronary artery behaves as tubular structure through axial slices. In the following step the behaviour of contrast agent has been modelled mathematically to reflect the dye diffusion in respective CTA volume. Consequently based on detected seed point & intensity behaviour, localized active contour segmentation has been applied to extract complete coronary tree. Bidirectional segmentation has been applied to avoid loss of coronary information due to the seed point location whereas auto adjustment feature of contour grabs new emerging branches. Medial axis for extracted coronary tree is generated using fast marching method for obtaining curve planar reformation for validation of contrast agent behaviour. Obtained coronary tree is to be evaluated for soft plaques in second phase of this research.
Improved stochastic trace estimation using mutually unbiased bases
Venue: arXiv cs.NA 2016
Year: 2016

We examine the problem of estimating the trace of a matrix $A$ when given access to an oracle which computes $x^\dagger A x$ for an input vector $x$. We make use of the basis vectors from a set of mutually unbiased bases, widely studied in the field of quantum information processing, in the selection of probing vectors $x$. This approach offers a new state of the art single shot sampling variance while requiring only $O(\log(n))$ random bits to generate each vector. This significantly improves on traditional methods such as Hutchinson's and Gaussian estimators in terms of the number of random bits required and worst case sample variance.
Delay and Backlog Analysis for 60 GHz Wireless Networks
Venue: arXiv cs.PF 2016
Year: 2016

To meet the ever-increasing demands on higher throughput and better network delay performance, 60 GHZ networking is proposed as a promising solution for the next generation of wireless communications. To successfully deploy such networks, its important to understand their performance first. However, due to the unique fading characteristic of the 60 GHz channel, the characterization of the corresponding service process, offered by the channel, using the conventional methodologies may not be tractable. In this work, we provide an alternative approach to derive a closed-form expression that characterizes the cumulative service process of the 60 GHz channel in terms of the moment generating function (MGF) of its instantaneous channel capacity. We then use this expression to derive probabilistic upper bounds on the backlog and delay that are experienced by a flow traversing this network, using results from the MGF-based network calculus. The computed bounds are validated using simulation. We provide numerical results for different networking scenarios and for different traffic and channel parameters and we show that the 60 GHz wireless network is capable of satisfying stringent quality-of-Service (QoS) requirements, in terms of network delay and reliability. With this analysis approach at hand, a larger scale 60 GHz network design and optimization is possible.
Improved Non-Malleable Extractors, Non-Malleable Codes and Independent Source Extractors
Venue: arXiv cs.CC 2016
Year: 2016

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error $ε$ and seed length $d=O(\log n)+O(\log(1/ε)\log \log (1/ε))$, that supports min-entropy $k=Ω(d)$ and outputs $Ω(k)$ bits. Combined with the protocol in \cite{DW09}, this gives a two round privacy amplification protocol with optimal entropy loss in the presence of an active adversary, for all security parameters up to $Ω(k/\log k)$. (2) An explicit non-malleable two-source extractor for min-entropy $k \geq (1-γ)n$, some constant $γ>0$, that outputs $Ω(k)$ bits with error $2^{-Ω(n/\log n)}$. Combined with the connection in \cite{CG14b} this gives a non-malleable code in the two-split-state model with relative rate $Ω(1/\log n)$. This exponentially improves previous constructions, all of which only achieve rate $n^{-Ω(1)}$.\footnote{The work of Aggarwal et. al \cite{ADKO15} had a construction which "achieves" constant rate, but recently the author found an error in their proof.} (3)A two-source extractor for min-entropy $O(\log n \log \log n)$, which also implies a $K$-Ramsey graph on $N$ vertices with $K=(\log N)^{O(\log \log \log N)}$. We also obtain a seeded non-malleable $9$-source extractor with optimal seed length, which in turn gives a $10$-source extractor for min-entropy $O(\log n)$. Previously the best known extractor for such min-entropy requires $O(\log \log n)$ sources \cite{CohL16}. Independent of our work, Cohen \cite{Cohen16} obtained similar results to (1) and the two-source extractor, except the dependence on $ε$ is $\log(1/ε)(\log \log (1/ε))^{O(1)}$ and the two-source extractor requires min-entropy $\log n (\log \log n)^{O(1)}$.
Computational complexity of solving polynomial differential equations over unbounded domains with non-rational coefficients
Venue: arXiv cs.CC 2016
Year: 2016

In this note, we extend the result of \cite{PoulyG16} about the complexity of solving polynomial differential equations over unbounded domains to work with non-rational input. In order to deal with arbitrary input, we phrase the result in framework of Conputable Analysis \cite{Ko91}. As a side result, we also get a uniform result about complexity of the operator, and not just about the solution.
Identifying vital edges in Chinese air route network via memetic algorithm
Venue: arXiv cs.SI 2016
Year: 2016

Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems.
Complementary Training Programme for Electrical and Computer Engineering Students Through an Industrial-Academic Collaboration (Extended Version)
Venue: arXiv cs.CY 2016
Year: 2016

We describe the results of an industrial-academic collaboration among the Graduate Program in Electrical Engineering (PPGEE), the Electronics and Information Research Centre (CETELI), and Samsung Eletrônica da Amazônia Ltda. (Samsung), which aims at training human resources for Samsung's research and development (R&D) areas. Inspired by co-operative education systems, this collaboration offers an academic experience by means of a complementary training programme (CTP), in order to train undergraduates and graduate students in electrical and computer engineering, with especial emphasis on digital television (TV), industrial automation, and mobile devices technologies. In particular, this cooperation has provided scholarships for students and financial support for professors and coordinators in addition to the construction of a new building with new laboratories, classrooms, and staff rooms, to assist all research and development activities. Additionally, the cooperation outcomes led to applications developed for Samsung's mobile devices, digital TV, and production processes, an increase of 37% in CETELI's scientific production (i.e., conference and journal papers) as well as professional training for undergraduates and graduate students.
Learning deep representation from coarse to fine for face alignment
Venue: arXiv cs.CV 2016
Year: 2016

In this paper, we propose a novel face alignment method that trains deep convolutional network from coarse to fine. It divides given landmarks into principal subset and elaborate subset. We firstly keep a large weight for principal subset to make our network primarily predict their locations while slightly take elaborate subset into account. Next the weight of principal subset is gradually decreased until two subsets have equivalent weights. This process contributes to learn a good initial model and search the optimal model smoothly to avoid missing fairly good intermediate models in subsequent procedures. On the challenging COFW dataset [1], our method achieves 6.33% mean error with a reduction of 21.37% compared with the best previous result [2].
On Regularization Parameter Estimation under Covariate Shift
Venue: arXiv cs.LG 2016
Year: 2016

This paper identifies a problem with the usual procedure for L2-regularization parameter estimation in a domain adaptation setting. In such a setting, there are differences between the distributions generating the training data (source domain) and the test data (target domain). The usual cross-validation procedure requires validation data, which can not be obtained from the unlabeled target data. The problem is that if one decides to use source validation data, the regularization parameter is underestimated. One possible solution is to scale the source validation data through importance weighting, but we show that this correction is not sufficient. We conclude the paper with an empirical analysis of the effect of several importance weight estimators on the estimation of the regularization parameter.
Denoising and compression in wavelet domain via projection onto approximation coefficients
Venue: arXiv cs.CV 2016
Year: 2016

We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.
Keyphrase Extraction using Sequential Labeling
Venue: arXiv cs.CL 2016
Year: 2016

Keyphrases efficiently summarize a document's content and are used in various document processing and retrieval tasks. Several unsupervised techniques and classifiers exist for extracting keyphrases from text documents. Most of these methods operate at a phrase-level and rely on part-of-speech (POS) filters for candidate phrase generation. In addition, they do not directly handle keyphrases of varying lengths. We overcome these modeling shortcomings by addressing keyphrase extraction as a sequential labeling task in this paper. We explore a basic set of features commonly used in NLP tasks as well as predictions from various unsupervised methods to train our taggers. In addition to a more natural modeling for the keyphrase extraction problem, we show that tagging models yield significant performance benefits over existing state-of-the-art extraction methods.