OpenRaiser/Intern-Atlas huggingface dataset:
Explicit constructions of high-rate MDS array codes with optimal repair bandwidth
Venue: arXiv cs.IT 2016
Year: 2016

Maximum distance separable (MDS) codes are optimal error-correcting codes in the sense that they provide the maximum failure-tolerance for a given number of parity nodes. Suppose that an MDS code with $k$ information nodes and $r=n-k$ parity nodes is used to encode data in a distributed storage system. It is known that if $h$ out of the $n$ nodes are inaccessible and $d$ surviving (helper) nodes are used to recover the lost data, then we need to download at least $h/(d+h-k)$ fraction of the data stored in each of the helper nodes (Dimakis et. al., 2010 and Cadambe et al., 2013). If this lower bound is achieved for the repair of any $h$ erased nodes from any $d$ helper nodes, we say that the MDS code has the $(h,d)$-optimal repair property. We study high-rate MDS array codes with the optimal repair property. Explicit constructions of such codes in the literature are only available for the cases where there are at most 3 parity nodes, and these existing constructions can only optimally repair a single node failure by accessing all the surviving nodes. In this paper, given any $r$ and $n$, we present two explicit constructions of MDS array codes with the $(h,d)$-optimal repair property for all $h\le r$ and $k\le d\le n-h$ simultaneously. Codes in the first family can be constructed over any base field $F$ as long as $|F|\ge sn,$ where $s=\text{lcm}(1,2,\dots,r).$ The encoding, decoding, repair of failed nodes, and update procedures of these codes all have low complexity. Codes in the second family have the optimal access property and can be constructed over any base field $F$ as long as $|F|\ge n+1.$ Moreover, both code families have the optimal error resilience capability when repairing failed nodes. We also construct several other related families of MDS codes with the optimal repair property.
Two Dimensional Angle of Arrival Estimation
Venue: arXiv cs.CE 2016
Year: 2016

We present a new method for the estimation of two dimensional (2D) angles of arrival (AOAs), namely, azimuth and incidence angles of multiple narrowband signals of same frequency in the far field of antenna array.
COARA: Code Offloading on Android with AspectJ
Venue: arXiv cs.DC 2016
Year: 2016

Smartphones suffer from limited computational capabilities and battery life. A method to mitigate these problems is code offloading: executing application code on a remote server. We introduce COARA, a middleware platform for code offloading on Android that uses aspect-oriented programming (AOP) with AspectJ. AOP allows COARA to intercept code for offloading without a customized compiler or modification of the operating system. COARA requires minimal changes to application source code, and does not require the application developer to be aware of AOP. Since state transfer to the server is often a bottleneck that hinders performance, COARA uses AOP to intercept the transmission of large objects from the client and replaces them with object proxies. The server can begin execution of the offloaded application code, regardless of whether all required objects been transferred to the server. We run COARA with Android applications from the Google Play store on a Nexus 4 running unmodified Android 4.3 to prove that our platform improves performance and reduces energy consumption. Our approach yields speedups of 24x and 6x over WiFi and 3G respectively.
An electronic-game framework for evaluating coevolutionary algorithms
Venue: arXiv cs.NE 2016
Year: 2016

One of the common artificial intelligence applications in electronic games consists of making an artificial agent learn how to execute some determined task successfully in a game environment. One way to perform this task is through machine learning algorithms capable of learning the sequence of actions required to win in a given game environment. There are several supervised learning techniques able to learn the correct answer for a problem through examples. However, when learning how to play electronic games, the correct answer might only be known by the end of the game, after all the actions were already taken. Thus, not being possible to measure the accuracy of each individual action to be taken at each time step. A way for dealing with this problem is through Neuroevolution, a method which trains Artificial Neural Networks using evolutionary algorithms. In this article, we introduce a framework for testing optimization algorithms with artificial agent controllers in electronic games, called EvoMan, which is inspired in the action-platformer game Mega Man II. The environment can be configured to run in different experiment modes, as single evolution, coevolution and others. To demonstrate some challenges regarding the proposed platform, as initial experiments we applied Neuroevolution using Genetic Algorithms and the NEAT algorithm, in the context of competitively coevolving two distinct agents in this game.
Design and implementation of the advanced cloud privacy threat modeling
Venue: arXiv cs.CR 2016
Year: 2016

Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat modeling as a part of requirements engineering in secure software development provides a structured approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities in a system . This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for privacy threat modeling in relation to processing sensitive data in cloud computing environments. It describes the modeling methodology that involved applying Method Engineering to specify characteristics of a cloud privacy threat modeling methodology, different steps in the proposed methodology and corresponding products. In addition, a case study has been implemented as a proof of concept to demonstrate the usability of the proposed methodology. We believe that the extended methodology facilitates the application of a privacy-preserving cloud software development approach from requirements engineering to design.
Heading for the Clouds: Implications for Cloud Computing Adopters
Venue: arXiv cs.CY 2016
Year: 2016

Cloud computing projects have many implications, including issues such as security, compliance, funding, cohesion with existing systems, operational resource requirements, and number of employees involved. In order to gain a better understanding of why businesses are interested in adopting cloud services in spite of these potential difficulties, we interviewed senior IT personnel at five different organizations about their processes related to cloud decisions, their thoughts before and during the process, and the outcome of their endeavor. Our results provide insights from their perspectives into the similarities and differences among the organizations and the implications of going into the cloud. We conclude with a list of recommended questions and areas to consider for use by other organizations looking into adopting cloud services. The ultimate goal is to help businesses considering a cloud computing project by providing advice from other organizations based on their experience.
A Novel Compressive Sensing based Enhanced Multiplexing Scheme for MIMO System
Venue: arXiv cs.IT 2016
Year: 2016

A novel compressive-sensing based signal multiplexing scheme is proposed in this paper to further improve the multiplexing gain for multiple input multiple output (MIMO) system. At the transmitter side, a Gaussian random measurement matrix in compressive sensing is employed before the traditional spatial multiplexing in order to carry more data streams on the available spatial multiplexing streams of the underlying MIMO system. At the receiver side, it is proposed to reformulate the detection of the multiplexing signal into two steps. In the first step, the traditional MIMO equalization can be used to restore the transmitted spatial multiplexing signal of the MIMO system. While in the second step, the standard optimization based detection algorithm assumed in the compressive sensing framework is utilized to restore the CS multiplexing data streams, wherein the exhaustive over-complete dictionary is used to guarantee the sparse representation of the CS multiplexing signal. In order to avoid the excessive complexity, the sub-block based dictionary and the sub-block based CS restoration is proposed. Finally, simulation results are presented to show the feasibility of the proposed CS based enhanced MIMO multiplexing scheme. And our efforts in this paper shed some lights on the great potential in further improving the spatial multiplexing gain for the MIMO system.
Probabilistic bounds on the trapping redundancy of linear codes
Venue: arXiv cs.IT 2016
Year: 2016

The trapping redundancy of a linear code is the number of rows of a smallest parity-check matrix such that no submatrix forms an $(a,b)$-trapping set. This concept was first introduced in the context of low-density parity-check (LDPC) codes in an attempt to estimate the number of redundant rows in a parity-check matrix suitable for iterative decoding. Essentially the same concepts appear in other contexts as well such as robust syndrome extraction for quantum error correction. Among the known upper bounds on the trapping redundancy, the strongest one was proposed by employing a powerful tool in probabilistic combinatorics, called the Lovász Local Lemma. Unfortunately, the proposed proof invoked this tool in a situation where an assumption made in the lemma does not necessarily hold. Hence, although we do not doubt that nonetheless the proposed bound actually holds, for it to be a mathematical theorem, a more rigorous proof is desired. Another disadvantage of the proposed bound is that it is only applicable to $(a,b)$-trapping sets with rather small $a$. Here, we give a more general and sharper upper bound on trapping redundancy by making mathematically more rigorous use of probabilistic combinatorics without relying on the lemma. Our bound is applicable to all potentially avoidable $(a,b)$-trapping sets with $a$ smaller than the minimum distance of a given linear code, while being generally much sharper than the bound through the Lovász Local Lemma. In fact, our upper bound is sharp enough to exactly determine the trapping redundancy for many cases, thereby providing precise knowledge in the form of a more general bound with mathematical rigor.
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead
Venue: arXiv cs.IT 2016
Year: 2016

After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.
Asymptotic Analysis of Self-Adjusting Contraction Trees
Venue: arXiv cs.DC 2016
Year: 2016

In this paper, we present asymptotic analysis of self-adjusting contraction trees for incremental sliding window analytics.
Extending DLR with Labelled Tuples, Projections, Functional Dependencies and Objectification (full version)
Venue: arXiv cs.AI 2016
Year: 2016

We introduce an extension of the n-ary description logic DLR to deal with attribute-labelled tuples (generalising the positional notation), with arbitrary projections of relations (inclusion dependencies), generic functional dependencies and with global and local objectification (reifying relations or their projections). We show how a simple syntactic condition on the appearance of projections and functional dependencies in a knowledge base makes the language decidable without increasing the computational complexity of the basic DLR language.
Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks
Venue: arXiv cs.CV 2016
Year: 2016

Automatic Offline Handwritten Signature Verification has been researched over the last few decades from several perspectives, using insights from graphology, computer vision, signal processing, among others. In spite of the advancements on the field, building classifiers that can separate between genuine signatures and skilled forgeries (forgeries made targeting a particular signature) is still hard. We propose approaching the problem from a feature learning perspective. Our hypothesis is that, in the absence of a good model of the data generation process, it is better to learn the features from data, instead of using hand-crafted features that have no resemblance to the signature generation process. To this end, we use Deep Convolutional Neural Networks to learn features in a writer-independent format, and use this model to obtain a feature representation on another set of users, where we train writer-dependent classifiers. We tested our method in two datasets: GPDS-960 and Brazilian PUC-PR. Our experimental results show that the features learned in a subset of the users are discriminative for the other users, including across different datasets, reaching close to the state-of-the-art in the GPDS dataset, and improving the state-of-the-art in the Brazilian PUC-PR dataset.
Information Structures of Maximizing Distributions of Feedback Capacity for General Channels with Memory & Applications
Venue: arXiv cs.IT 2016
Year: 2016

For any class of channel conditional distributions, with finite memory dependence on channel input RVs $A^n {\stackrel{\triangle}{=}} \{A_i: i=0, \ldots, n\}$ or channel output RVs $B^n {\stackrel{\triangle}{=}} \{B_i: i=0, \ldots, n\}$ or both, we characterize the sets of channel input distributions, which maximize directed information defined by $ I(A^n \rightarrow B^n) {\stackrel{\triangle}{=}} \sum_{i=0}^n I(A^i;B_i|B^{i-1}) $ and we derive the corresponding expressions, called "characterizations of Finite Transmission Feedback Information (FTFI) capacity". The main theorems state that optimal channel input distributions occur in subsets ${\cal P}_{[0,n]}^{CI}\subseteq {\cal P}_{[0,n]} {\stackrel{\triangle}{=}}\big\{ {\bf P}_{A_i|A^{i-1}, B^{i-1}}: i=0, \ldots, n\big\}$, which satisfy conditional independence on past information. We derive similar characterizations, when general transmission cost constraints are imposed. Moreover, we also show that the structural properties apply to general nonlinear and linear autoregressive channel models defined by discrete-time recursions on general alphabet spaces, and driven by arbitrary distributed noise processes. We derive these structural properties by invoking stochastic optimal control theory and variational equalities of directed information, to identify tight upper bounds on $I(A^n \rightarrow B^n)$, which are achievable over subsets of conditional distributions ${\cal P}_{[0,n]}^{CI} \subseteq {\cal P}_{[0,n]}$, which satisfy conditional independence and they are specified by the dependence of channel distributions and transmission cost functions on inputs and output symbols. We apply the characterizations to recursive Multiple Input Multiple Output Gaussian Linear Channel Models with limited memory and we show a separation principle between the computation of the elements of the optimal strategies.
Use of Non-Orthogonal Multiple Access in Dual-hop relaying
Venue: arXiv cs.IT 2016
Year: 2016

To improve the sum-rate (SR) of the dual-hop relay system, a novel two-stage power allocation scheme with non-orthogonal multiple access (NOMA) is proposed. In this scheme, after the reception of the superposition coded symbol with a power allocation from the source, the relay node forwards a new superposition coded symbol with another power allocation to the destination. By employing the maximum ratio combination (MRC), the destination jointly decodes the information symbols from the source and the relay. Assuming Rayleigh fading channels, closed-form solution of the ergodic SR at high signal-to-noise ratio (SNR) is derived and a practical power allocation is also designed for the proposed NOMA scheme. Through numerical results, it is shown that the performance of the proposed scheme is significantly improved compared with the existing work.
Control System Design for Tricopter using Filters and PID controller
Venue: arXiv cs.SY 2016
Year: 2016

The purpose of this paper is to present the control system design of Tricopter. We have presented the implementation of control system in software in this paper. Tricopter's control system mainly consists of two parts Complimentary filter and PID block. The angles along X, Y and Z axis are taken from the complementary filter which acts as a feedback block. We have used the combination of gyroscope and accelerometer for finding the angle. We have also shown the role of the complimentary filter in finding out the angle along X, Y, and Z axis instead of using gyroscope and accelerometer directly. The second main part is the PID Controller which calculates the error in angle along X, Y and Z axis and produces an output signal which reduces error. We have shown the importance of the constant parameters of PID Controller. The results of this paper are tested on an actual Tricopter and also plotted in the form of graph using Matlab and Processing software.
Modeling Relational Information in Question-Answer Pairs with Convolutional Neural Networks
Venue: arXiv cs.CL 2016
Year: 2016

In this paper, we propose convolutional neural networks for learning an optimal representation of question and answer sentences. Their main aspect is the use of relational information given by the matches between words from the two members of the pair. The matches are encoded as embeddings with additional parameters (dimensions), which are tuned by the network. These allows for better capturing interactions between questions and answers, resulting in a significant boost in accuracy. We test our models on two widely used answer sentence selection benchmarks. The results clearly show the effectiveness of our relational information, which allows our relatively simple network to approach the state of the art.
Age of Information: The Gamma Awakening
Venue: arXiv cs.IT 2016
Year: 2016

We consider a scenario where a monitor is interested in being up to date with respect to the status of some system which is not directly accessible to this monitor. However, we assume a source node has access to the status and can send status updates as packets to the monitor through a communication system. We also assume that the status updates are generated randomly as a Poisson process. The source node can manage the packet transmission to minimize the age of information at the destination node, which is defined as the time elapsed since the last successfully transmitted update was generated at the source. We use queuing theory to model the source-destination link and we assume that the time to successfully transmit a packet is a gamma distributed service time. We consider two packet management schemes: LCFS (Last Come First Served) with preemption and LCFS without preemption. We compute and analyze the average age and the average peak age of information under these assumptions. Moreover, we extend these results to the case where the service time is deterministic.
Global sensitivity analysis of battery equivalent circuit model parameters
Venue: arXiv cs.SY 2016
Year: 2016

This paper considers one of the most commonly used equivalent circuit models (ECMs) for lithium-ion batteries and investigates the sensitivity of the model output to changes of model parameters using the Morris method. Experiments are carried out on a lithium-ion cell with nickel manganese cobalt oxide (NMC) electrode and parameters of the model are identified in the state of charge (SOC) range [100%,10%]. Although all the model parameters do vary with SOC, global sensitivity analysis reveals that the uncertainties of some of the parameters generate very little uncertainty in the voltage output, implying that those parameters can be taken as constants without compromising the accuracy of the model. This is further confirmed by experimental validation.
Towards Label Imbalance in Multi-label Classification with Many Labels
Venue: arXiv cs.LG 2016
Year: 2016

In multi-label classification, an instance may be associated with a set of labels simultaneously. Recently, the research on multi-label classification has largely shifted its focus to the other end of the spectrum where the number of labels is assumed to be extremely large. The existing works focus on how to design scalable algorithms that offer fast training procedures and have a small memory footprint. However they ignore and even compound another challenge - the label imbalance problem. To address this drawback, we propose a novel Representation-based Multi-label Learning with Sampling (RMLS) approach. To the best of our knowledge, we are the first to tackle the imbalance problem in multi-label classification with many labels. Our experimentations with real-world datasets demonstrate the effectiveness of the proposed approach.
Isogeometric nonlinear bending and buckling analysis of variable-thickness composite plate structures
Venue: arXiv cs.CE 2016
Year: 2016

This paper investigates nonlinear bending and buckling behaviours of composite plates characterized by a thickness variation. Layer interfaces are described as functions of inplane coordinates. Top and bottom surfaces of the plate are symmetric about the midplane and the plate could be considered as a flat surface in analysis along with thickness parameters which vary over the plate. The variable thickness at a certain position in the midplane is modeled by a set of control points (or thickness-parameters) through NURBS (Non-Uniform Rational B-Spline) basic functions. The knot parameter space which is referred in modelling geometry and approximating displacement variables is employed for approximating thickness, simultaneously. The use of quadratic NURBS functions results in C^1 continuity of modeling variable thickness and analyzing solutions. Thin to moderately thick laminates in bound of first-order shear deformation theory (FSDT) are taken into account. Strain-displacement relations in sense of von-Karman theory are employed for large deformation. Riks method is used for geometrically nonlinear analysis. The weak form is approximated numerically by the isogeometric analysis (IGA), which has been found to be a robust, stable and realistic numerical tool. Numerical results confirm the reliability and capacity of the propose method.
The Probabilistic Analysis of the Communication Network created by Dynamic Boundary Coverage
Venue: arXiv cs.RO 2016
Year: 2016

We do a Probabilistic Analysis of the Network generated by robots involved in Stochastic Boundary Coverage