OpenRaiser/Intern-Atlas huggingface dataset:
Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection
Venue: arXiv cs.DB 2016
Year: 2016

Many important forms of data are stored digitally in XML format. Errors can occur in the textual content of the data in the fields of the XML. Fixing these errors manually is time-consuming and expensive, especially for large amounts of data. There is increasing interest in the research, development, and use of automated techniques for assisting with data cleaning. Electronic dictionaries are an important form of data frequently stored in XML format that frequently have errors introduced through a mixture of manual typographical entry errors and optical character recognition errors. In this paper we describe methods for flagging statistical anomalies as likely errors in electronic dictionaries stored in XML format. We describe six systems based on different sources of information. The systems detect errors using various signals in the data including uncommon characters, text length, character-based language models, word-based language models, tied-field length ratios, and tied-field transliteration models. Four of the systems detect errors based on expectations automatically inferred from content within elements of a single field type. We call these single-field systems. Two of the systems detect errors based on correspondence expectations automatically inferred from content within elements of multiple related field types. We call these tied-field systems. For each system, we provide an intuitive analysis of the type of error that it is successful at detecting. Finally, we describe two larger-scale evaluations using crowdsourcing with Amazon's Mechanical Turk platform and using the annotations of a domain expert. The evaluations consistently show that the systems are useful for improving the efficiency with which errors in XML electronic dictionaries can be detected.
"Resource Pooling" for Wireless Networks: Solutions for the Developing World
Venue: arXiv cs.NI 2016
Year: 2016

We live in a world in which there is a great disparity between the lives of the rich and the poor. Technology offers great promise in bridging this gap. In particular, wireless technology unfetters developing communities from the constraints of infrastructure providing a great opportunity to leapfrog years of neglect and technological waywardness. In this paper, we highlight the role of resource pooling for wireless networks in the developing world. Resource pooling involves: (i) abstracting a collection of networked resources to behave like a single unified resource pool and (ii) developing mechanisms for shifting load between the various parts of the unified resource pool. The popularity of resource pooling stems from its ability to provide resilience, high utilization, and flexibility at an acceptable cost. We show that "resource pooling", which is very popular in its various manifestations, is the key unifying principle underlying a diverse number of successful wireless technologies (such as white space networking, community networks, etc.). We discuss various applications of resource pooled wireless technologies and provide a discussion on open issues.
Performance Analysis of Relay Selection With Enhanced Dynamic Decode-and-Forward and Network Coding in Two-Way Relay Channels
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we adopt the relay selection (RS) protocol proposed by Bletsas, Khisti, Reed and Lippman (2006) with Enhanced Dynamic Decode-and-Forward (EDDF) and network coding (NC) system in a two-hop two-way multi-relay network. All nodes are single-input single-output (SISO) and half-duplex, i.e., they cannot transmit and receive data simultaneously. The outage probability is analyzed and we show comparisons of outage probability with various scenarios under Rayleigh fading channel. Our results show that the relay selection with EDDF and network coding (RS-EDDF&NC) scheme has the best performance in the sense of outage probability upon the considered decode-and-forward (DF) relaying if there exist sufficiently relays. In addition, the performance loss is large if we select a relay at random. This shows the importance of relay selection strategies.
Meta-learning within Projective Simulation
Venue: arXiv cs.AI 2016
Year: 2016

Learning models of artificial intelligence can nowadays perform very well on a large variety of tasks. However, in practice different task environments are best handled by different learning models, rather than a single, universal, approach. Most non-trivial models thus require the adjustment of several to many learning parameters, which is often done on a case-by-case basis by an external party. Meta-learning refers to the ability of an agent to autonomously and dynamically adjust its own learning parameters, or meta-parameters. In this work we show how projective simulation, a recently developed model of artificial intelligence, can naturally be extended to account for meta-learning in reinforcement learning settings. The projective simulation approach is based on a random walk process over a network of clips. The suggested meta-learning scheme builds upon the same design and employs clip networks to monitor the agent's performance and to adjust its meta-parameters "on the fly". We distinguish between "reflexive adaptation" and "adaptation through learning", and show the utility of both approaches. In addition, a trade-off between flexibility and learning-time is addressed. The extended model is examined on three different kinds of reinforcement learning tasks, in which the agent has different optimal values of the meta-parameters, and is shown to perform well, reaching near-optimal to optimal success rates in all of them, without ever needing to manually adjust any meta-parameter.
On Adjusting the Learning Rate in Frequency Domain Echo Cancellation With Double-Talk
Venue: arXiv cs.SD 2016
Year: 2016

One of the main difficulties in echo cancellation is the fact that the learning rate needs to vary according to conditions such as double-talk and echo path change. In this paper we propose a new method of varying the learning rate of a frequency-domain echo canceller. This method is based on the derivation of the optimal learning rate of the NLMS algorithm in the presence of noise. The method is evaluated in conjunction with the multidelay block frequency domain (MDF) adaptive filter. We demonstrate that it performs better than current double-talk detection techniques and is simple to implement.
Optimal Bounds for the No-Show Paradox via SAT Solving
Venue: arXiv cs.GT 2016
Year: 2016

Voting rules allow multiple agents to aggregate their preferences in order to reach joint decisions. Perhaps one of the most important desirable properties in this context is Condorcet-consistency, which requires that a voting rule should return an alternative that is preferred to any other alternative by some majority of voters. Another desirable property is participation, which requires that no voter should be worse off by joining an electorate. A seminal result in social choice theory by Moulin (1998) has shown that Condorcet-consistency and participation are incompatible whenever there are at least 4 alternatives and 25 voters. We leverage SAT solving to obtain an elegant human-readable proof of Moulin's result that requires only 12 voters. Moreover, the SAT solver is able to construct a Condorcet-consistent voting rule that satisfies participation as well as a number of other desirable properties for up to 11 voters, proving the optimality of the above bound. We also obtain tight results for set-valued and probabilistic voting rules, which complement and significantly improve existing theorems.
Robust Max-Min Fairness Energy Harvesting in Secure MISO Cognitive Radio With SWIPT
Venue: arXiv cs.IT 2016
Year: 2016

A multiple-input single-output cognitive radio downlink network is studied with simultaneous wireless information and power transfer. In this network, a secondary user coexists with multiple primary users and multiple energy harvesting receivers. In order to guarantee secure communication and energy harvesting, the problem of robust secure artificial noise-aided beamforming and power splitting design is investigated under imperfect channel state information. Specifically, the max-min fairness energy harvesting problem is formulated under the bounded channel state information error model. A one-dimensional search algorithm based on ${\cal S}\text{-Procedure} $ is proposed to solve the problem. It is shown that the optimal robust secure beamforming can be achieved. A tradeoff is elucidated between the secrecy rate of the secondary user receiver and the energy harvested by the energy harvesting receivers under a max-min fairness criterion.
Extension spectrale d'un signal de parole de la bande téléphonique à la bande AM
Venue: arXiv cs.SD 2016
Year: 2016

This document proposes a bandwidth extension system producing a wideband signal from a narrowband speech signal. The extension is performed independently for high and low frequencies. High-frequency extension uses the excitation-filter model. Extension of the excitation is performed in the time domain using a non-linear function, while the spectral envelope is extended in the cepstral domain using a multi-layer perceptron. Low-band extension is based on the sinusoidal model. The amplitude of sinusoids is also estimated using a multi-layer perceptron. The results show that the sound quality after extension is higher than that of narrowband speech, with a significant variation across listeners. Some of the techniques, including excitation extension, are of interest in the field of speech coding. ----- Le présent mémoire propose un système d'extension de la bande permettant de produire un signal en bande AM à partir d'un signal de parole en bande téléphonique. L'extension est effectuée de façon indépendante pour les hautes fréquences et les basses fréquences. L'extension des hautes fréquences utilise le modèle filtre-excitation. L'extension de l'excitation est réalisée dans le domaine temporel par une fonction non linéaire, alors que l'extension de l'enveloppe spectrale s'effectue dans le domaine cepstral par un perceptron multi-couches. L'extension de la bande basse utilise le modèle sinusoïdal. L'amplitude des sinusoïdes est aussi estimée par un perceptron multi-couches. Les résultats obtenus montrent que la qualité sonore après extension est supérieure à celle de la bande téléphonique, avec une importante différence entre les auditeurs. Certaines techniques développées, dont l'extension de l'excitation, présentent un certain intérêt pour le domaine du codage de la parole.
Relational lattices via duality
Venue: arXiv cs.LO 2016
Year: 2016

The natural join and the inner union combine in different ways tables of a relational database. Tropashko [18] observed that these two operations are the meet and join in a class of lattices-called the relational lattices- and proposed lattice theory as an alternative algebraic approach to databases. Aiming at query optimization, Litak et al. [12] initiated the study of the equational theory of these lattices. We carry on with this project, making use of the duality theory developed in [16]. The contributions of this paper are as follows. Let A be a set of column's names and D be a set of cell values; we characterize the dual space of the relational lattice R(D, A) by means of a generalized ultrametric space, whose elements are the functions from A to D, with the P (A)-valued distance being the Hamming one but lifted to subsets of A. We use the dual space to present an equational axiomatization of these lattices that reflects the combinatorial properties of these generalized ultrametric spaces: symmetry and pairwise completeness. Finally, we argue that these equations correspond to combinatorial properties of the dual spaces of lattices, in a technical sense analogous of correspondence theory in modal logic. In particular, this leads to an exact characterization of the finite lattices satisfying these equations.
Alpaka - An Abstraction Library for Parallel Kernel Acceleration
Venue: arXiv cs.DC 2016
Year: 2016

Porting applications to new hardware or programming models is a tedious and error prone process. Every help that eases these burdens is saving developer time that can then be invested into the advancement of the application itself instead of preserving the status-quo on a new platform. The Alpaka library defines and implements an abstract hierarchical redundant parallelism model. The model exploits parallelism and memory hierarchies on a node at all levels available in current hardware. By doing so, it allows to achieve platform and performance portability across various types of accelerators by ignoring specific unsupported levels and utilizing only the ones supported on a specific accelerator. All hardware types (multi- and many-core CPUs, GPUs and other accelerators) are supported for and can be programmed in the same way. The Alpaka C++ template interface allows for straightforward extension of the library to support other accelerators and specialization of its internals for optimization. Running Alpaka applications on a new (and supported) platform requires the change of only one source code line instead of a lot of \#ifdefs.
Occupancy Estimation in Smart Buildings using Audio-Processing Techniques
Venue: arXiv cs.SD 2016
Year: 2016

In the past few years, several case studies have illustrated that the use of occupancy information in buildings leads to energy-efficient and low-cost HVAC operation. The widely presented techniques for occupancy estimation include temperature, humidity, CO2 concentration, image camera, motion sensor and passive infrared (PIR) sensor. So far little studies have been reported in literature to utilize audio and speech processing as indoor occupancy prediction technique. With rapid advances of audio and speech processing technologies, nowadays it is more feasible and attractive to integrate audio-based signal processing component into smart buildings. In this work, we propose to utilize audio processing techniques (i.e., speaker recognition and background audio energy estimation) to estimate room occupancy (i.e., the number of people inside a room). Theoretical analysis and simulation results demonstrate the accuracy and effectiveness of this proposed occupancy estimation technique. Based on the occupancy estimation, smart buildings will adjust the thermostat setups and HVAC operations, thus, achieving greater quality of service and drastic cost savings.
Improving on the Cut-Set Bound via Geometric Analysis of Typical Sets
Venue: arXiv cs.IT 2016
Year: 2016

We consider the discrete memoryless symmetric primitive relay channel, where, a source $X$ wants to send information to a destination $Y$ with the help of a relay $Z$ and the relay can communicate to the destination via an error-free digital link of rate $R_0$, while $Y$ and $Z$ are conditionally independent and identically distributed given $X$. We develop two new upper bounds on the capacity of this channel that are tighter than existing bounds, including the celebrated cut-set bound. Our approach significantly deviates from the standard information-theoretic approach for proving upper bounds on the capacity of multi-user channels. We build on the blowing-up lemma to analyze the probabilistic geometric relations between the typical sets of the $n$-letter random variables associated with a reliable code for communicating over this channel. These relations translate to new entropy inequalities between the $n$-letter random variables involved. As an application of our bounds, we study an open question posed by (Cover, 1987), namely, what is the minimum needed $Z$-$Y$ link rate $R_0^*$ in order for the capacity of the relay channel to be equal to that of the broadcast cut. We consider the special case when the $X$-$Y$ and $X$-$Z$ links are both binary symmetric channels. Our tighter bounds on the capacity of the relay channel immediately translate to tighter lower bounds for $R_0^*$. More interestingly, we show that when $p\to 1/2$, $R_0^*\geq 0.1803$; even though the broadcast channel becomes completely noisy as $p\to 1/2$ and its capacity, and therefore the capacity of the relay channel, goes to zero, a strictly positive rate $R_0$ is required for the relay channel capacity to be equal to the broadcast bound.
Filtering Video Noise as Audio with Motion Detection to Form a Musical Instrument
Venue: arXiv cs.HC 2016
Year: 2016

Even though they differ in the physical domain, digital video and audio share many characteristics. Both are temporal data streams often stored in buffers with 8-bit values. This paper investigates a method for creating harmonic sounds with a video signal as input. A musical instrument is proposed, that utilizes video in both a sound synthesis method, and in a controller interface for selecting musical notes at specific velocities. The resulting instrument was informally determined by the author to sound both pleasant and interesting, but hard to control, and therefore suited for synth pad sounds.
Investigating practical linear temporal difference learning
Venue: arXiv cs.LG 2016
Year: 2016

Off-policy reinforcement learning has many applications including: learning from demonstration, learning multiple goal seeking policies in parallel, and representing predictive knowledge. Recently there has been an proliferation of new policy-evaluation algorithms that fill a longstanding algorithmic void in reinforcement learning: combining robustness to off-policy sampling, function approximation, linear complexity, and temporal difference (TD) updates. This paper contains two main contributions. First, we derive two new hybrid TD policy-evaluation algorithms, which fill a gap in this collection of algorithms. Second, we perform an empirical comparison to elicit which of these new linear TD methods should be preferred in different situations, and make concrete suggestions about practical use.
The BigDAWG Architecture
Venue: arXiv cs.DB 2016
Year: 2016

BigDAWG is a polystore system designed to work on complex problems that naturally span across different processing or storage engines. BigDAWG provides an architecture that supports diverse database systems working with different data models, support for the competing notions of location transparency and semantic completeness via islands of information and a middleware that provides a uniform multi-island interface. In this article, we describe the current architecture of BigDAWG, its application on the MIMIC II medical dataset, and our plans for the mechanics of cross-system queries. During the presentation, we will also deliver a brief demonstration of the current version of BigDAWG.
Characterization of maximum hands-off control
Venue: arXiv cs.SY 2016
Year: 2016

Maximum hands-off control aims to maximize the length of time over which zero actuator values are applied to a system when executing specified control tasks. To tackle such problems, recent literature has investigated optimal control problems which penalize the size of the support of the control function and thereby lead to desired sparsity properties. This article gives the exact set of necessary conditions for a maximum hands-off optimal control problem using an $L_0$-(semi)norm, and also provides sufficient conditions for the optimality of such controls. Numerical example illustrates that adopting an $L_0$ cost leads to a sparse control, whereas an $L_1$-relaxation in singular problems leads to a non-sparse solution.
Alternating Set Quantifiers in Modal Logic
Venue: arXiv cs.LO 2016
Year: 2016

We establish the strictness of several set quantifier alternation hierarchies that are based on modal logic, evaluated on various classes of finite graphs. This extends to the modal setting a celebrated result of Matz, Schweikardt and Thomas (2002), which states that the analogous hierarchy of monadic second-order logic is strict. Thereby, the present paper settles a question raised by van Benthem (1983), revived by ten Cate (2006), and partially answered by Kuusisto (2008, 2015).
Even Trolls Are Useful: Efficient Link Classification in Signed Networks
Venue: arXiv cs.LG 2016
Year: 2016

We address the problem of classifying the links of signed social networks given their full structural topology. Motivated by a binary user behaviour assumption, which is supported by decades of research in psychology, we develop an efficient and surprisingly simple approach to solve this classification problem. Our methods operate both within the active and batch settings. We demonstrate that the algorithms we developed are extremely fast in both theoretical and practical terms. Within the active setting, we provide a new complexity measure and a rigorous analysis of our methods that hold for arbitrary signed networks. We validate our theoretical claims carrying out a set of experiments on three well known real-world datasets, showing that our methods outperform the competitors while being much faster.
Proof of Control of a UAV and a UGV Cooperating to Manipulate an Object
Venue: arXiv cs.SY 2016
Year: 2016

This paper focuses on the control of a system composed of an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) which cooperate to manipulate an object. The two units are subject to actuator saturations and cooperate to move the object to a desired pose, characterized by its position and inclination. The paper proposes a control strategy where the ground vehicle is tasked to deploy the object to a certain position, whereas the aerial vehicle adjusts its inclination. The ground vehicle is governed by a saturated proportional-derivative control law. The aerial vehicle is regulated by means of a cascade control specifically designed for this problem that is able to exploit the mechanical interconnection. The stability of the overall system is proved through Input-to-State Stability and Small Gain theorem arguments. To solve the problem of constraints satisfaction, a nonlinear Reference Governor scheme is implemented. Numerical simulations are provided to demonstrate the effectiveness of the proposed method.
A Day of Your Days: Estimating Individual Daily Journeys Using Mobile Data to Understand Urban Flow
Venue: arXiv cs.SI 2016
Year: 2016

Nowadays, travel surveys provide rich information about urban mobility and commuting patterns. But, at the same time, they have drawbacks: they are static pictures of a dynamic phenomena, are expensive to make, and take prolonged periods of time to finish. However, the availability of mobile usage data (Call Detail Records) makes the study of urban mobility possible at levels not known before. This has been done in the past with good results--mobile data makes possible to find and understand aggregated mobility patterns. In this paper, we propose to analyze mobile data at individual level by estimating daily journeys, and use those journeys to build Origin-Destiny matrices to understand urban flow. We evaluate this approach with large anonymized CDRs from Santiago, Chile, and find that our method has a high correlation ($ρ= 0.89$) with the current travel survey, and that it captures external anomalies in daily travel patterns, making our method suitable for inclusion into urban computing applications.
State-of-the-art in Power Line Communications: from the Applications to the Medium
Venue: arXiv cs.NI 2016
Year: 2016

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.