OpenRaiser/Intern-Atlas huggingface dataset:
On the Correlation Distribution for a Ternary Niho Decimation
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, let $n=2m$ and $d=3^{m+1}-2$ with $m\geq2$ and $\gcd(d,3^n-1)=1$. By studying the weight distribution of the ternary Zetterberg code and counting the numbers of solutions of some equations over the finite field $\mathbb{F}_{3^n}$, the correlation distribution between a ternary $m$-sequence of period $3^n-1$ and its $d$-decimation sequence is completely determined. This is the first time that the correlation distribution for a non-binary Niho decimation has been determined since 1976.
Equibit: A Peer-to-Peer Electronic Equity System
Venue: arXiv cs.CR 2016
Year: 2016

The registration, transfer, clearing and settlement of equities represents a significant part of economic activity currently underserved by modern technological innovation. In addition, recent events have revealed problems of transparency, inviting public criticism and scrutiny from regulatory authorities. A peer-to-peer platform facilitating the creation and exchange of directly registered shares represents a shift in equity markets towards more efficient, transparent operations as well as greater accessibility to the investing public and issuing companies. Blockchain technology solves the problem of transaction processing and clearing but the fungibility of their units pose a challenge in identifying the issuers and holders of specific equities. Furthermore, as the issuers are in a constant state of flux the benefits of a decentralized network are lost if a central manager is required to cancel equities from companies that no longer exist. We propose a solution to these problems using digital signatures, based on blockchain technology.
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling
Venue: arXiv cs.CL 2016
Year: 2016

In this paper we propose and carefully evaluate a sequence labeling framework which solely utilizes sparse indicator features derived from dense distributed word representations. The proposed model obtains (near) state-of-the art performance for both part-of-speech tagging and named entity recognition for a variety of languages. Our model relies only on a few thousand sparse coding-derived features, without applying any modification of the word representations employed for the different tasks. The proposed model has favorable generalization properties as it retains over 89.8% of its average POS tagging accuracy when trained at 1.2% of the total available training data, i.e.~150 sentences per language.
Secure and Robust Authentication for DC MicroGrids based on Power Talk Communication
Venue: arXiv cs.SY 2016
Year: 2016

We propose a novel framework for secure and reliable authentication of Distributed Energy Resources to the centralized secondary/tertiary control system of a DC MicroGrid (MG), networked using the IEEE 802.11 wireless interface. The key idea is to perform the authentication using power talk, which is a powerline communication technique executed by the primary control loops of the power electronic converters, without the use of a dedicated hardware for its modem. In addition, the scheme also promotes direct and active participation of the control system in the authentication process, a feature not commonly encountered in current networked control systems for MicroGrids. The PLECS-based simulations verifies the viability of our scheme.
Anti-Jamming Strategy for Distributed Microgrid Control based on Power Talk Communication
Venue: arXiv cs.IT 2016
Year: 2016

In standard implementations of distributed secondary control for DC MicroGrids (MGs), the exchange of local measurements among neighboring control agents is enabled via off-the-shelf wireless solutions, such as IEEE 802.11. However, Denial of Service (DoS) attacks on the wireless interface through jamming prevents the secondary control system from performing its main tasks, which might compromise the stability of the MG. In this paper, we propose novel, robust and secure secondary control reconfiguration strategy, tailored to counteract DoS attacks. Specifically, upon detecting the impairment of the wireless interface, the jammed secondary control agent notifies its peers via a secure, low-rate powerline channel based on Power Talk communication. This triggers reconfiguration of the wireless communication graph through primary control mode switching, where the jammed agents leave the secondary control by switching to current source mode, and are replaced by nonjammed current sources that switch to voltage source mode and join the secondary control. The strategy fits within the software-defined networking framework, where the network control is split from the data plane using reliable and secure side power talk communication channel, created via software modification of the MG primary control loops. The simulation results illustrate the feasibility of the solution and prove that the MG resilience and performance can be indeed improved via software-defined networking approaches.
Understanding Error Correction and its Role as Part of the Communication Channel in Environments composed of Self-Integrating Systems
Venue: arXiv cs.IT 2016
Year: 2016

The raise of complexity of technical systems also raises knowledge required to set them up and to maintain them. The cost to evolve such systems can be prohibitive. In the field of Autonomic Computing, technical systems should therefore have various self-healing capabilities allowing system owners to provide only partial, potentially inconsistent updates of the system. The self-healing or self-integrating system shall find out the remaining changes to communications and functionalities in order to accommodate change and yet still restore function. This issue becomes even more interesting in context of Internet of Things and Industrial Internet where previously unexpected device combinations can be assembled in order to provide a surprising new function. In order to pursue higher levels of self-integration capabilities I propose to think of self-integration as sophisticated error correcting communications. Therefore, this paper discusses an extended scope of error correction with the purpose to emphasize error correction's role as an integrated element of bi-directional communication channels in self-integrating, autonomic communication scenarios.
Detecting Unusual Input-Output Associations in Multivariate Conditional Data
Venue: arXiv cs.LG 2016
Year: 2016

Despite tremendous progress in outlier detection research in recent years, the majority of existing methods are designed only to detect unconditional outliers that correspond to unusual data patterns expressed in the joint space of all data attributes. Such methods are not applicable when we seek to detect conditional outliers that reflect unusual responses associated with a given context or condition. This work focuses on multivariate conditional outlier detection, a special type of the conditional outlier detection problem, where data instances consist of multi-dimensional input (context) and output (responses) pairs. We present a novel outlier detection framework that identifies abnormal input-output associations in data with the help of a decomposable conditional probabilistic model that is learned from all data instances. Since components of this model can vary in their quality, we combine them with the help of weights reflecting their reliability in assessment of outliers. We study two ways of calculating the component weights: global that relies on all data, and local that relies only on instances similar to the target instance. Experimental results on data from various domains demonstrate the ability of our framework to successfully identify multivariate conditional outliers.
The "paradox" of computability and a recursive relative version of the Busy Beaver function
Venue: arXiv cs.LO 2016
Year: 2016

In this article, we will show that uncomputability is a relative property not only of oracle Turing machines, but also of subrecursive classes. We will define the concept of a Turing submachine, and a recursive relative version for the Busy Beaver function which we will call Busy Beaver Plus function. Therefore, we will prove that the computable Busy Beaver Plus function defined on any Turing submachine is not computable by any program running on this submachine. We will thereby demonstrate the existence of a "paradox" of computability a la Skolem: a function is computable when "seen from the outside" the subsystem, but uncomputable when "seen from within" the same subsystem. Finally, we will raise the possibility of defining universal submachines, and a hierarchy of negative Turing degrees.
Getting Started with PATSTAT Register
Venue: arXiv cs.DB 2016
Year: 2016

This paper provides a technical introduction to the PATSTAT Register database, which contains bibliographical, procedural and legal status data on patent applications handled by the European Patent Office. It presents eight MySQL queries that cover some of the most relevant aspects of the database for research purposes. It targets academic researchers and practitioners who are familiar with the PATSTAT database and the MySQL language.
Robustness of Voice Conversion Techniques Under Mismatched Conditions
Venue: arXiv cs.SD 2016
Year: 2016

Most of the existing studies on voice conversion (VC) are conducted in acoustically matched conditions between source and target signal. However, the robustness of VC methods in presence of mismatch remains unknown. In this paper, we report a comparative analysis of different VC techniques under mismatched conditions. The extensive experiments with five different VC techniques on CMU ARCTIC corpus suggest that performance of VC methods substantially degrades in noisy conditions. We have found that bilinear frequency warping with amplitude scaling (BLFWAS) outperforms other methods in most of the noisy conditions. We further explore the suitability of different speech enhancement techniques for robust conversion. The objective evaluation results indicate that spectral subtraction and log minimum mean square error (logMMSE) based speech enhancement techniques can be used to improve the performance in specific noisy conditions.
Non-Deterministic Policy Improvement Stabilizes Approximated Reinforcement Learning
Venue: arXiv cs.AI 2016
Year: 2016

This paper investigates a type of instability that is linked to the greedy policy improvement in approximated reinforcement learning. We show empirically that non-deterministic policy improvement can stabilize methods like LSPI by controlling the improvements' stochasticity. Additionally we show that a suitable representation of the value function also stabilizes the solution to some degree. The presented approach is simple and should also be easily transferable to more sophisticated algorithms like deep reinforcement learning.
Construction and implementation of asymptotic expansions for Laguerre-type orthogonal polynomials
Venue: arXiv cs.NA 2016
Year: 2016

Laguerre and Laguerre-type polynomials are orthogonal polynomials on the interval $[0,\infty)$ with respect to a weight function of the form $w(x) = x^α e^{-Q(x)}, Q(x) = \sum_{k=0}^m q_k x^k, α> -1, q_m > 0$. The classical Laguerre polynomials correspond to $Q(x)=x$. The computation of higher-order terms of the asymptotic expansions of these polynomials for large degree becomes quite complicated, and a full description seems to be lacking in literature. However, this information is implicitly available in the work of Vanlessen, based on a non-linear steepest descent analysis of an associated so-called Riemann--Hilbert problem. We will extend this work and show how to efficiently compute an arbitrary number of higher-order terms in the asymptotic expansions of Laguerre and Laguerre-type polynomials. This effort is similar to the case of Jacobi and Jacobi-type polynomials in a previous paper. We supply an implementation with explicit expansions in four different regions of the complex plane. These expansions can also be extended to Hermite-type weights of the form $\exp(-\sum_{k=0}^m q_k x^{2k})$ on $(-\infty,\infty)$, and to general non-polynomial functions $Q(x)$ using contour integrals. The expansions may be used, e.g., to compute Gauss-Laguerre quadrature rules in a lower computational complexity than based on the recurrence relation, and with improved accuracy for large degree. They are also of interest in random matrix theory.
Re-evaluating Automatic Metrics for Image Captioning
Venue: arXiv cs.CL 2016
Year: 2016

The task of generating natural language descriptions from images has received a lot of attention in recent years. Consequently, it is becoming increasingly important to evaluate such image captioning approaches in an automatic manner. In this paper, we provide an in-depth evaluation of the existing image captioning metrics through a series of carefully designed experiments. Moreover, we explore the utilization of the recently proposed Word Mover's Distance (WMD) document metric for the purpose of image captioning. Our findings outline the differences and/or similarities between metrics and their relative robustness by means of extensive correlation, accuracy and distraction based evaluations. Our results also demonstrate that WMD provides strong advantages over other metrics.
Counting Answer Sets via Dynamic Programming
Venue: arXiv cs.LO 2016
Year: 2016

While the solution counting problem for propositional satisfiability (#SAT) has received renewed attention in recent years, this research trend has not affected other AI solving paradigms like answer set programming (ASP). Although ASP solvers are designed to enumerate all solutions, and counting can therefore be easily done, the involved materialization of all solutions is a clear bottleneck for the counting problem of ASP (#ASP). In this paper we propose dynamic programming-based #ASP algorithms that exploit the structure of the underlying (ground) ASP program. Experimental results for a prototype implementation show promise when compared to existing solvers.
A short review and primer on cardiovascular signals in human computer interaction applications
Venue: arXiv cs.HC 2016
Year: 2016

The use of psychophysiologic signals in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of different physiological signals and analysis techniques. Cardiovascular signals such as heart rate variability and blood pressure variability are commonly used in psychophysiology in order to investigate phenomena such as mental workload. In this paper we present a short review of different cardiovascular metrics useful in the context of human-computer interaction. This paper aims to serve as a primer for the novice, enabling rapid familiarisation with the latest core concepts. We emphasise everyday human-computer interface applications to distinguish from the more common clinical or sports uses of psychophysiology. This paper is an extract from a comprehensive review of the entire field of ambulatory psychophysiology, with 12 similar chapters, plus application guidelines and systematic review. Any citation to this paper should be made using the following reference: B. Cowley, M. Filetti, K. Lukander, J. Torniainen, A. Henelius, L. Ahonen, O. Barral, I. Kosunen, T. Valtonen, M. Huotilainen, N. Ravaja, G. Jacucci. The Psychophysiology Primer: a guide to methods and a broad review with a focus on human-computer interaction. Foundations and Trends in Human-Computer Interaction, vol. 9, no. 3-4, pp. 150--307, 2016. http://dx.doi.org/10.1561/1100000065
Development of UMLS Based Health Care Web Services for Android Platform
Venue: arXiv cs.CY 2016
Year: 2016

In this fast developing world of information, the amount of medical knowledge is rising at an exponential level. The UMLS (Unified Medical Language Systems), is rich knowledge base consisting files and software that provides many health and biomedical vocabularies and standards. A Web service is a web solution to facilitate machine-to-machine interaction over a network. Few UMLS web services are currently available for portable devices, but most of them lack in efficiency and performance. It is proposed to develop Android-based web services for healthcare systems underlying rich knowledge source of UMLS. The experimental evaluation was made to analyse the efficiency and performance effect with and without using the designed prototype. The understand-ability and interaction with the prototype were greater than those who used the alternate sources to obtain the answers to their questions. The overall performance indicates that the system is convenient and easy to use. The result of the evaluation clearly proved that designed system retrieves all the pertinent information better than syntactic searches.
Sum-networks from undirected graphs: construction and capacity analysis
Venue: arXiv cs.IT 2016
Year: 2016

We consider a directed acyclic network with multiple sources and multiple terminals where each terminal is interested in decoding the sum of independent sources generated at the source nodes. We describe a procedure whereby a simple undirected graph can be used to construct such a sum-network and demonstrate an upper bound on its computation rate. Furthermore, we show sufficient conditions for the construction of a linear network code that achieves this upper bound. Our procedure allows us to construct sum-networks that have any arbitrary computation rate $\frac{p}{q}$ (where $p,q$ are non-negative integers). Our work significantly generalizes a previous approach for constructing sum-networks with arbitrary capacities. Specifically, we answer an open question in prior work by demonstrating sum-networks with significantly fewer number of sources and terminals.
Object Shape Approximation & Contour Adaptive Depth Image Coding for Virtual View Synthesis
Venue: arXiv cs.MM 2016
Year: 2016

A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image-based rendering (DIBR). It has been shown that depth images can be efficiently coded using contour-adaptive codecs that preserve edge sharpness, resulting in visually pleasing DIBR-synthesized images. However, contours are typically losslessly coded as side information (SI), which is expensive if the object shapes are complex. In this paper, we pursue a new paradigm in depth image coding for color-plus-depth representation of a 3D scene: we pro-actively simplify object shapes in a depth and color image pair to reduce depth coding cost, at a penalty of a slight increase in synthesized view distortion. Specifically, we first mathematically derive a distortion upper-bound proxy for 3DSwIM---a quality metric tailored for DIBR-synthesized images. This proxy reduces interdependency among pixel rows in a block to ease optimization. We then approximate object contours via a dynamic programming (DP) algorithm to optimally trade off coding cost of contours using arithmetic edge coding (AEC) with our proposed view synthesis distortion proxy. We modify the depth and color images according to the approximated object contours in an inter-view consistent manner. These are then coded respectively using a contour-adaptive image codec based on graph Fourier transform (GFT) for edge preservation and HEVC intra. Experimental results show that by maintaining sharp but simplified object contours during contour-adaptive coding, for the same visual quality of DIBR-synthesized virtual views, our proposal can reduce depth image coding rate by up to 22% compared to alternative coding strategies such as HEVC intra.
On incomplete and synchronizing finite sets
Venue: arXiv cs.FL 2016
Year: 2016

This paper situates itself in the theory of variable length codes and of finite automata where the concepts of completeness and synchronization play a central role. In this theoretical setting, we investigate the problem of finding upper bounds to the minimal length of synchronizing words and incompletable words of a finite language X in terms of the length of the words of X. This problem is related to two well-known conjectures formulated by Cerny and Restivo, respectively. In particular, if Restivo's conjecture is true, our main result provides a quadratic bound for the minimal length of a synchronizing pair of any finite synchronizing complete code with respect to the maximal length of its words.
TCP SIAD: Congestion Control supporting High Speed and Low Latency
Venue: arXiv cs.NI 2016
Year: 2016

Congestion control has been an open research issue for more than two decades. More and more applications with narrow latency requirements are emerging which are not well addressed by existing proposals. In this paper we present TCP Scalable Increase Adaptive Decrease (SIAD), a new congestion control scheme supporting both high speed and low latency. More precisely, our algorithm aims to provide high utilization under various networking conditions, and therefore would allow operators to configure small buffers for low latency support. To provide full scalability with high speed networks, we designed TCP SIAD based on a new approach that aims for a fixed feedback rate independent of the available bandwidth. Further, our approach provides a configuration knob for the feedback rate. This can be used by a higher layer control loop to impact the capacity share, potentially at the cost of higher congestion, e.g. for applications that need a minimum rate. We evaluated TCP SIAD against well-known high-speed congestion control schemes, such as Scalable TCP and High Speed TCP, as well as H-TCP that among other goals targets small buffers. We show that only SIAD is able to utilize the bottleneck with arbitrary buffer sizes while avoiding a standing queue. Moreover, we demonstrate the capacity sharing of SIAD depending on the configured feedback rate and a high robustness of TCP SIAD to non-congestion related loss.
A CRF Based POS Tagger for Code-mixed Indian Social Media Text
Venue: arXiv cs.CL 2016
Year: 2016

In this work, we describe a conditional random fields (CRF) based system for Part-Of- Speech (POS) tagging of code-mixed Indian social media text as part of our participation in the tool contest on POS tagging for codemixed Indian social media text, held in conjunction with the 2016 International Conference on Natural Language Processing, IIT(BHU), India. We participated only in constrained mode contest for all three language pairs, Bengali-English, Hindi-English and Telegu-English. Our system achieves the overall average F1 score of 79.99, which is the highest overall average F1 score among all 16 systems participated in constrained mode contest.