OpenRaiser/Intern-Atlas huggingface dataset:
Universal Dependencies to Logical Forms with Negation Scope
Venue: arXiv cs.CL 2017
Year: 2017

Many language technology applications would benefit from the ability to represent negation and its scope on top of widely-used linguistic resources. In this paper, we investigate the possibility of obtaining a first-order logic representation with negation scope marked using Universal Dependencies. To do so, we enhance UDepLambda, a framework that converts dependency graphs to logical forms. The resulting UDepLambda$\lnot$ is able to handle phenomena related to scope by means of an higher-order type theory, relevant not only to negation but also to universal quantification and other complex semantic phenomena. The initial conversion we did for English is promising, in that one can represent the scope of negation also in the presence of more complex phenomena such as universal quantifiers.
Forward Collision Vehicular Radar with IEEE 802.11: Feasibility Demonstration through Measurements
Venue: arXiv cs.NI 2017
Year: 2017

Increasing safety and automation in transportation systems has led to the proliferation of radar and IEEE 802.11 dedicated short range communication (DSRC) in vehicles. Current implementations of vehicular radar devices, however, are expensive, use a substantial amount of bandwidth, and are susceptible to multiple security risks. Consider the feasibility of using an IEEE 802.11 orthogonal frequency division multiplexing (OFDM) communications waveform to perform radar functions. In this paper, we present an approach that determines the mean-normalized channel energy from frequency domain channel estimates and models it as a direct sinusoidal function of target range, enabling closest target range estimation. In addition, we propose an alternative to vehicular forward collision detection by extending IEEE 802.11 dedicated short-range communications (DSRC) and WiFi technology to radar, providing a foundation for joint communications and radar framework. Furthermore, we perform an experimental demonstration using existing IEEE 802.11 devices with minimal modification through algorithm processing on frequency-domain channel estimates. The results of this paper show that our solution delivers similar accuracy and reliability to mmWave radar devices with as little as 20 MHz of spectrum (doubling DSRC's 10 MHz allocation), indicating significant potential for industrial devices with joint vehicular communications and radar capabilities.
On the Global-Local Dichotomy in Sparsity Modeling
Venue: arXiv cs.IT 2017
Year: 2017

The traditional sparse modeling approach, when applied to inverse problems with large data such as images, essentially assumes a sparse model for small overlapping data patches. While producing state-of-the-art results, this methodology is suboptimal, as it does not attempt to model the entire global signal in any meaningful way - a nontrivial task by itself. In this paper we propose a way to bridge this theoretical gap by constructing a global model from the bottom up. Given local sparsity assumptions in a dictionary, we show that the global signal representation must satisfy a constrained underdetermined system of linear equations, which can be solved efficiently by modern optimization methods such as Alternating Direction Method of Multipliers (ADMM). We investigate conditions for unique and stable recovery, and provide numerical evidence corroborating the theory.
RSPP: A Reliable, Searchable and Privacy-Preserving e-Healthcare System for Cloud-Assisted Body Area Networks
Venue: arXiv cs.CR 2017
Year: 2017

The integration of cloud computing and Internet of Things (IoT) is quickly becoming the key enabler for the digital transformation of the healthcare industry by offering comprehensive improvements in patient engagements, productivity and risk mitigation. This paradigm shift, while bringing numerous benefits and new opportunities to healthcare organizations, has raised a lot of security and privacy concerns. In this paper, we present a reliable, searchable and privacy-preserving e-healthcare system, which takes advantage of emerging cloud storage and IoT infrastructure and enables healthcare service providers (HSPs) to realize remote patient monitoring in a secure and regulatory compliant manner. Our system is built upon a novel dynamic searchable symmetric encryption scheme with forward privacy and delegated verifiability for periodically generated healthcare data. While the forward privacy is achieved by maintaining an increasing counter for each keyword at an IoT gateway, the data owner delegated verifiability comes from the combination of the Bloom filter and aggregate message authentication code. Moreover, our system is able to support multiple HSPs through either data owner assistance or delegation. The detailed security analysis as well as the extensive simulations on a large data set with millions of records demonstrate the practical efficiency of the proposed system for real world healthcare applications.
Octopus: A Framework for Cost-Quality-Time Optimization in Crowdsourcing
Venue: arXiv cs.AI 2017
Year: 2017

We present Octopus, an AI agent to jointly balance three conflicting task objectives on a micro-crowdsourcing marketplace - the quality of work, total cost incurred, and time to completion. Previous control agents have mostly focused on cost-quality, or cost-time tradeoffs, but not on directly controlling all three in concert. A naive formulation of three-objective optimization is intractable; Octopus takes a hierarchical POMDP approach, with three different components responsible for setting the pay per task, selecting the next task, and controlling task-level quality. We demonstrate that Octopus significantly outperforms existing state-of-the-art approaches on real experiments. We also deploy Octopus on Amazon Mechanical Turk, showing its ability to manage tasks in a real-world dynamic setting.
A better model of computation for digital physics?
Venue: arXiv cs.LO 2017
Year: 2017

This note is meant to invite the reader to consider interaction nets, a relatively recently discovered model of computation, as a possible alternative for cellular automata which are often employed as the basis for digital physics. Defined as graph-like structures (in contrast to the grids for cellular automata), interaction nets possess a set of interesting properties, such as locality, linearity, and strong confluence, which together result in so-called clockless computation in the sense that they do not require any global clock in order to operate. We believe that an attempt of using interaction nets as a replacement for cellular automata may lead to a new view in digital physics.
Evaluation of Temporal Formulas Based on "Checking By Spheres"
Venue: arXiv cs.SE 2017
Year: 2017

Classical algorithms of evaluation of temporal CTL formulas are constructed "bottom-up". A formula must be evaluated completely to give the result. In the paper, a new concept of "top-down" evaluation of temporal QsCTL (CTL with state quantifiers) formulas, called "Checking By Spheres" is presented. The new algorithm has two general advantages: the evaluation may be stopped on certain conditions in early steps of the algorithm (not the whole formula and not whole state space should be analyzed), and state quantification may be used in formulas (even if a range of a quantifier is not statically obtainable).
Subspace-Aware Index Codes
Venue: arXiv cs.IT 2017
Year: 2017

In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications, the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unaware cases. Our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.
Multitask diffusion adaptation over networks with common latent representations
Venue: arXiv cs.MA 2017
Year: 2017

Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications. This topic has been receiving considerable attention in recent years with emphasis on both single-task and multitask scenarios. In single-task adaptation, agents cooperate to track an objective of common interest, while in multitask adaptation agents track multiple objectives simultaneously. Regularization is one useful technique to promote and exploit similarity among tasks in the latter scenario. This work examines an alternative way to model relations among tasks by assuming that they all share a common latent feature representation. As a result, a new multitask learning formulation is presented and algorithms are developed for its solution in a distributed online manner. We present a unified framework to analyze the mean-square-error performance of the adaptive strategies, and conduct simulations to illustrate the theoretical findings and potential applications.
Trie Compression for GPU Accelerated Multi-Pattern Matching
Venue: arXiv cs.DS 2017
Year: 2017

Graphics Processing Units allow for running massively parallel applications offloading the CPU from computationally intensive resources, however GPUs have a limited amount of memory. In this paper a trie compression algorithm for massively parallel pattern matching is presented demonstrating 85% less space requirements than the original highly efficient parallel failure-less aho-corasick, whilst demonstrating over 22 Gbps throughput. The algorithm presented takes advantage of compressed row storage matrices as well as shared and texture memory on the GPU.
Discrete Cosserat Approach for Multi-Section Soft Robots Dynamics
Venue: arXiv cs.RO 2017
Year: 2017

In spite of recent progress, soft robotics still suffers from a lack of unified modeling framework. Nowadays, the most adopted model for the design and control of soft robots is the piece-wise constant curvature model, with its consolidated benefits and drawbacks. In this work, an alternative model for multisection soft robots dynamics is presented based on a discrete Cosserat approach, which, not only takes into account shear and torsional deformations, essentials to cope with out-of-plane external loads, but also inherits the geometrical and mechanical properties of the continuous Cosserat model, making it the natural soft robotics counterpart of the traditional rigid robotics dynamics model. The soundness of the model is demonstrated through extensive simulation and experimental results for both plane and out-of-plane motions.
Unified Analysis of SWIPT Relay Networks with Noncoherent Modulation
Venue: arXiv cs.IT 2017
Year: 2017

Simultaneous wireless information and power transfer (SWIPT) relay networks represent a paradigm shift in the development of wireless networks, enabling simultaneous radio frequency (RF) energy harvesting (EH) and information processing. Different from conventional SWIPT relaying schemes, which typically assume the availability of perfect channel state information (CSI), here we consider the application of noncoherent modulation in order to avoid the need of instantaneous CSI estimation/tracking and minimise the energy consumption. We propose a unified and comprehensive analytical framework for the analysis of time switching (TS) and power splitting (PS) receiver architectures with the amplify-and-forward (AF) protocol. In particular, we adopt a moments-based approach to derive novel expressions for the outage probability, achievable throughput, and average symbol error rate (ASER) of the considered SWIPT system. We quantify the impact of several system parameters, involving relay location, energy conversion efficiency, and TS and PS ratio assumptions, imposed on the EH relay terminal. Our results reveal that the throughput performance of the TS protocol is superior to that of the PS protocol at lower receive signal-to-noise (SNR) values, which is in contrast to the point-to-point SWIPT systems. An extensive Monte Carlo simulation study is presented to corroborate the proposed analysis.
Adaptive beamforming method based on recursive maximum correntropy in impulsive noise with alpha-stable process
Venue: arXiv cs.SY 2017
Year: 2017

As a well-established adaptation criterion, the maximum correntropy criterion (MCC) has been receiving increasing attention due to its robust against outliers. In this paper, a new complex recursive maximum correntropy (CRMC) algorithm without any priori information on the noise characteristics, is proposed under the MCC. The proposed algorithm is useful for adaptive beamforming, when the desired signal is contaminated by the impulsive noises. Moreover, the analysis of convergence property of the CRMC algorithm is performed. The results obtained from simulation study establish the effectiveness of this new beamformer.
An oracle-based attack on CAPTCHAs protected against oracle attacks
Venue: arXiv cs.CR 2017
Year: 2017

CAPTCHAs/HIPs are security mechanisms that try to prevent automatic abuse of services. They are susceptible to learning attacks in which attackers can use them as oracles. Kwon and Cha presented recently a novel algorithm that intends to avoid such learning attacks and "detect all bots". They add uncertainties to the grading of challenges, and also use trap images designed to detect bots. The authors suggest that a major IT corporation is studying their proposal for mainstream implementation. We present here two fundamental design flaws regarding their trap images and uncertainty grading. These leak information regarding the correct grading of images. Exploiting them, an attacker can use an UTS-CAPTCHA as an oracle, and perform a learning attack. Our testing has shown that we can increase any reasonable initial success rate up to 100%.
Data-Intensive Supercomputing in the Cloud: Global Analytics for Satellite Imagery
Venue: arXiv cs.DC 2017
Year: 2017

We present our experiences using cloud computing to support data-intensive analytics on satellite imagery for commercial applications. Drawing from our background in high-performance computing, we draw parallels between the early days of clustered computing systems and the current state of cloud computing and its potential to disrupt the HPC market. Using our own virtual file system layer on top of cloud remote object storage, we demonstrate aggregate read bandwidth of 230 gigabytes per second using 512 Google Compute Engine (GCE) nodes accessing a USA multi-region standard storage bucket. This figure is comparable to the best HPC storage systems in existence. We also present several of our application results, including the identification of field boundaries in Ukraine, and the generation of a global cloud-free base layer from Landsat imagery.
On the Courtade-Kumar conjecture for certain classes of Boolean functions
Venue: arXiv cs.IT 2017
Year: 2017

We prove the Courtade-Kumar conjecture, for certain classes of $n$-dimensional Boolean functions, $\forall n\geq 2$ and for all values of the error probability of the binary symmetric channel, $\forall 0 \leq p \leq \frac{1}{2}$. Let $\mathbf{X}=[X_1...X_n]$ be a vector of independent and identically distributed Bernoulli$(\frac{1}{2})$ random variables, which are the input to a memoryless binary symmetric channel, with the error probability in the interval $0 \leq p \leq \frac{1}{2}$, and $\mathbf{Y}=[Y_1...Y_n]$ the corresponding output. Let $f:\{0,1\}^n \rightarrow \{0,1\}$ be an $n$-dimensional Boolean function. Then, the Courtade-Kumar conjecture states that the mutual information $\operatorname{MI}(f(\mathbf{X}),\mathbf{Y}) \leq 1-\operatorname{H}(p)$, where $\operatorname{H}(p)$ is the binary entropy function.
Time-Assisted Authentication Protocol
Venue: arXiv cs.CR 2017
Year: 2017

Authentication is the first step toward establishing a service provider and customer (C-P) association. In a mobile network environment, a lightweight and secure authentication protocol is one of the most significant factors to enhance the degree of service persistence. This work presents a secure and lightweight keying and authentication protocol suite termed TAP (Time-Assisted Authentication Protocol). TAP improves the security of protocols with the assistance of time-based encryption keys and scales down the authentication complexity by issuing a re-authentication ticket. While moving across the network, a mobile customer node sends a re-authentication ticket to establish new sessions with service-providing nodes. Consequently, this reduces the communication and computational complexity of the authentication process. In the keying protocol suite, a key distributor controls the key generation arguments and time factors, while other participants independently generate a keychain based on key generation arguments. We undertake a rigorous security analysis and prove the security strength of TAP using CSP and rank function analysis.
A Cache Management Scheme for Efficient Content Eviction and Replication in Cache Networks
Venue: arXiv cs.NI 2017
Year: 2017

To cope with the ongoing changing demands of the internet, 'in-network caching' has been presented as an application solution for two decades. With the advent of information-centric network (ICN) architecture, 'in-network caching' becomes a network level solution. Some unique features of ICNs, e.g., rapidly changing cache states, higher request arrival rates, smaller cache sizes, and other factors, impose diverse requirements on the content eviction policies. In particular, eviction policies should be fast and lightweight. In this study, we propose cache replication and eviction schemes, Conditional Leave Cope Everywhere (CLCE) and Least Frequent Recently Used (LFRU), which are well suited for the ICN type of cache networks (CNs). The CLCE replication scheme reduces the redundant caching of contents; hence improves the cache space utilization. LFRU approximates the Least Frequently Used (LFU) scheme coupled with the Least Recently Used (LRU) scheme and is practically implementable for rapidly changing cache networks like ICNs.
Circular Buffer Rate-Matched Polar Codes
Venue: arXiv cs.IT 2017
Year: 2017

A practical rate-matching system for constructing rate-compatible polar codes is proposed. The proposed polar code circular buffer rate-matching is suitable for transmissions on communication channels that support hybrid automatic repeat request (HARQ) communications, as well as for flexible resource-element rate-matching on single transmission channels. Our proposed circular buffer rate matching scheme also incorporates a bit-mapping scheme for transmission on bit-interleaved coded modulation (BICM) channels using higher order modulations. An interleaver is derived from a puncturing order obtained with a low complexity progressive puncturing search algorithm on a base code of short length, and has the flexibility to achieve any desired rate at the desired code length, through puncturing or repetition. The rate-matching scheme is implied by a two-stage polarization, for transmission at any desired code length, code rate, and modulation order, and is shown to achieve the symmetric capacity of BICM channels. Numerical results on AWGN and fast fading channels show that the rate-matched polar codes have a competitive performance when compared to the spatially-coupled quasi-cyclic LDPC codes or LTE turbo codes, while having similar rate-dematching storage and computational complexities.
EGC Reception for FSO Systems Under Mixture-Gamma Fading Channels and Pointing Errors
Venue: arXiv cs.IT 2017
Year: 2017

The performance of equal gain combining reception at free-space optical communication systems is analytically studied and evaluated. We consider the case when the total received signal undergoes independent and not necessarily identically distributed channel fading, modeled by the versatile mixture-Gamma distribution. Also, the misalignment-induced fading due to the presence of pointing errors is jointly considered in the enclosed analysis. New closed-form expressions in terms of finite sum series of the Meijer's $G$-function are derived regarding some key performance metrics of the considered system; namely, the scintillation index, outage probability, and average bit-error rate. Based on these results, some useful outcomes are manifested, such as the system diversity order, the crucial role of diversity branches, and the impact of composite channel fading/pointing error effect onto the system performance.
Graph Based Over-Segmentation Methods for 3D Point Clouds
Venue: arXiv cs.CV 2017
Year: 2017

Over-segmentation, or super-pixel generation, is a common preliminary stage for many computer vision applications. New acquisition technologies enable the capturing of 3D point clouds that contain color and geometrical information. This 3D information introduces a new conceptual change that can be utilized to improve the results of over-segmentation, which uses mainly color information, and to generate clusters of points we call super-points. We consider a variety of possible 3D extensions of the Local Variation (LV) graph based over-segmentation algorithms, and compare them thoroughly. We consider different alternatives for constructing the connectivity graph, for assigning the edge weights, and for defining the merge criterion, which must now account for the geometric information and not only color. Following this evaluation, we derive a new generic algorithm for over-segmentation of 3D point clouds. We call this new algorithm Point Cloud Local Variation (PCLV). The advantages of the new over-segmentation algorithm are demonstrated on both outdoor and cluttered indoor scenes. Performance analysis of the proposed approach compared to state-of-the-art 2D and 3D over-segmentation algorithms shows significant improvement according to the common performance measures.
Coordination of Mobile Mules via Facility Location Strategies
Venue: arXiv cs.NI 2017
Year: 2017

In this paper, we study the problem of wireless sensor network (WSN) maintenance using mobile entities called mules. The mules are deployed in the area of the WSN in such a way that would minimize the time it takes them to reach a failed sensor and fix it. The mules must constantly optimize their collective deployment to account for occupied mules. The objective is to define the optimal deployment and task allocation strategy for the mules, so that the sensors' downtime and the mules' traveling distance are minimized. Our solutions are inspired by research in the field of computational geometry and the design of our algorithms is based on state of the art approximation algorithms for the classical problem of facility location. Our empirical results demonstrate how cooperation enhances the team's performance, and indicate that a combination of k-Median based deployment with closest-available task allocation provides the best results in terms of minimizing the sensors' downtime but is inefficient in terms of the mules' travel distance. A k-Centroid based deployment produces good results in both criteria.