OpenRaiser/Intern-Atlas huggingface dataset:
Intersection-Link Representations of Graphs
Venue: arXiv cs.DS 2015
Year: 2015

We consider drawings of graphs that contain dense subgraphs. We introduce intersection-link representations for such graphs, in which each vertex $u$ is represented by a geometric object $R(u)$ and in which each edge $(u,v)$ is represented by the intersection between $R(u)$ and $R(v)$ if it belongs to a dense subgraph or by a curve connecting the boundaries of $R(u)$ and $R(v)$ otherwise. We study a notion of planarity, called Clique Planarity, for intersection-link representations of graphs in which the dense subgraphs are cliques.
Outage Analysis of Spectrum Sharing Energy Harvesting Cognitive Relays in Nakagami-$m$ Channels
Venue: arXiv cs.IT 2015
Year: 2015

Energy harvesting (EH) cognitive relays are an exciting solution to the problem of inefficient use of spectrum while achieving green communications and spatial diversity. In a spectrum sharing scenario, we investigate the performance of a cognitive relay network, where a secondary source communicates with its destination over Nakagami-$m$ channels via decode-and-forward EH relays while maintaining the outage probability of the primary user below a predefined threshold. Specifically, we derive a closed-form expression for the secondary outage probability and show that it is a function of the probability of an EH relay having sufficient energy for relaying, which in turn, depends on the energy harvesting and consumption rates of the EH relay and the primary outage probability threshold. We also show that relaxing the primary outage constraint may not always benefit the cognitive EH relay network due to the limitations imposed on the relay's transmit power by the energy constraint.
SDL based validation of a node monitoring protocol
Venue: arXiv cs.NI 2015
Year: 2015

Mobile ad hoc network is a wireless, self-configured, infrastructureless network of mobile nodes. The nodes are highly mobile, which makes the application running on them face network related problems like node failure, link failure, network level disconnection, scarcity of resources, buffer degradation, and intermittent disconnection etc. Node failure and Network fault are need to be monitored continuously by supervising the network status. Node monitoring protocol is crucial, so it is required to test the protocol exhaustively to verify and validate the functionality and accuracy of the designed protocol. This paper presents a validation model for Node Monitoring Protocol using Specification and Description Llanguage (SDL) using both Static Agent (SA) and Mobile Agent (MA). We have verified properties of the Node Monitoring Protocol (NMP) based on the global states with no exits, deadlock states or proper termination states using reachability graph. Message Sequence Chart (MSC) gives an intuitive understanding of the described system behavior with varying node density and complex behavior etc.
Sequent Calculus for Intuitionistic Epistemic Logic
Venue: arXiv cs.LO 2015
Year: 2015

The formal system of intuitionistic epistemic logic IEL was proposed by S. Artemov and T. Protopopescu. It provides the formal foundation for the study of knowledge from an intuitionistic point of view based on Brouwer-Hayting-Kolmogorov semantics of intuitionism. We construct a cut-free sequent calculus for IEL and establish that polynomial space is sufficient for the proof search in it. So, we prove that IEL is PSPACE-complete.
Multi-Projector Color Structured-Light Vision
Venue: arXiv cs.CV 2015
Year: 2015

Research interest in rapid structured-light imaging has grown increasingly for the modeling of moving objects, and a number of methods have been suggested for the range capture in a single video frame. The imaging area of a 3D object using a single projector is restricted since the structured light is projected only onto a limited area of the object surface. Employing additional projectors to broaden the imaging area is a challenging problem since simultaneous projection of multiple patterns results in their superposition in the light-intersected areas and the recognition of original patterns is by no means trivial. This paper presents a novel method of multi-projector color structured-light vision based on projector-camera triangulation. By analyzing the behavior of superposed-light colors in a chromaticity domain, we show that the original light colors cannot be properly extracted by the conventional direct estimation. We disambiguate multiple projectors by multiplexing the orientations of projector patterns so that the superposed patterns can be separated by explicit derivative computations. Experimental studies are carried out to demonstrate the validity of the presented method. The proposed method increases the efficiency of range acquisition compared to conventional active stereo using multiple projectors.
GCC-Plugin for Automated Accelerator Generation and Integration on Hybrid FPGA-SoCs
Venue: arXiv cs.OH 2015
Year: 2015

In recent years, architectures combining a reconfigurable fabric and a general purpose processor on a single chip became increasingly popular. Such hybrid architectures allow extending embedded software with application specific hardware accelerators to improve performance and/or energy efficiency. Aiding system designers and programmers at handling the complexity of the required process of hardware/software (HW/SW) partitioning is an important issue. Current methods are often restricted, either to bare-metal systems, to subsets of mainstream programming languages, or require special coding guidelines, e.g., via annotations. These restrictions still represent a high entry barrier for the wider community of programmers that new hybrid architectures are intended for. In this paper we revisit HW/SW partitioning and present a seamless programming flow for unrestricted, legacy C code. It consists of a retargetable GCC plugin that automatically identifies code sections for hardware acceleration and generates code accordingly. The proposed workflow was evaluated on the Xilinx Zynq platform using unmodified code from an embedded benchmark suite.
Automatic Nested Loop Acceleration on FPGAs Using Soft CGRA Overlay
Venue: arXiv cs.AR 2015
Year: 2015

Offloading compute intensive nested loops to execute on FPGA accelerators have been demonstrated by numerous researchers as an effective performance enhancement technique across numerous application domains. To construct such accelerators with high design productivity, researchers have increasingly turned to the use of overlay architectures as an intermediate generation target built on top of off-the-shelf FPGAs. However, achieving the desired performance-overhead trade-off remains a major productivity challenge as complex application-specific customizations over a large design space covering multiple architectural parameters are needed. In this work, an automatic nested loop acceleration framework utilizing a regular soft coarse-grained reconfigurable array (SCGRA) overlay is presented. Given high-level resource constraints, the framework automatically customizes the overlay architectural design parameters, high-level compilation options as well as communication between the accelerator and the host processor for optimized performance specifically to the given application. In our experiments, at a cost of 10 to 20 minutes additional tools run time, the proposed customization process resulted in up to 5 times additional speedup over a baseline accelerator generated by the same framework without customization. Overall, when compared to the equivalent software running on the host ARM processor alone on the Zedboard, the resulting accelerators achieved up to 10 times speedup.
Brewing Analytics Quality for Cloud Performance
Venue: arXiv cs.PF 2015
Year: 2015

Cloud computing has become increasingly popular. Many options of cloud deployments are available. Testing cloud performance would enable us to choose a cloud deployment based on the requirements. In this paper, we present an innovative process, implemented in software, to allow us to assess the quality of the cloud performance data. The process combines performance data from multiple machines, spanning across user experience data, workload performance metrics, and readily available system performance data. Furthermore, we discuss the major challenges of bringing raw data into tidy data formats in order to enable subsequent analysis, and describe how our process has several layers of assessment to validate the quality of the data processing procedure. We present a case study to demonstrate the effectiveness of our proposed process, and conclude our paper with several future research directions worth investigating.
Community detection in networks with unequal groups
Venue: arXiv cs.SI 2015
Year: 2015

Recently, a phase transition has been discovered in the network community detection problem below which no algorithm can tell which nodes belong to which communities with success any better than a random guess. This result has, however, so far been limited to the case where the communities have the same size or the same average degree. Here we consider the case where the sizes or average degrees are different. This asymmetry allows us to assign nodes to communities with better-than- random success by examining their local neighborhoods. Using the cavity method, we show that this removes the detectability transition completely for networks with four groups or fewer, while for more than four groups the transition persists up to a critical amount of asymmetry but not beyond. The critical point in the latter case coincides with the point at which local information percolates, causing a global transition from a less-accurate solution to a more-accurate one.
Analysis of Hannan Consistent Selection for Monte Carlo Tree Search in Simultaneous Move Games
Venue: arXiv cs.GT 2015
Year: 2015

Monte Carlo Tree Search (MCTS) has recently been successfully used to create strategies for playing imperfect-information games. Despite its popularity, there are no theoretic results that guarantee its convergence to a well-defined solution, such as Nash equilibrium, in these games. We partially fill this gap by analysing MCTS in the class of zero-sum extensive-form games with simultaneous moves but otherwise perfect information. The lack of information about the opponent's concurrent moves already causes that optimal strategies may require randomization. We present theoretic as well as empirical investigation of the speed and quality of convergence of these algorithms to the Nash equilibria. Primarily, we show that after minor technical modifications, MCTS based on any (approximately) Hannan consistent selection function always converges to an (approximate) subgame perfect Nash equilibrium. Without these modifications, Hannan consistency is not sufficient to ensure such convergence and the selection function must satisfy additional properties, which empirically hold for the most common Hannan consistent algorithms.
Analysis of Dynamic Channel Bonding in Dense Networks of WLANs
Venue: arXiv cs.NI 2015
Year: 2015

Dynamic Channel Bonding (DCB) allows for the dynamic selection and use of multiple contiguous basic channels in Wireless Local Area Networks (WLANs). A WLAN operating under DCB can enjoy a larger bandwidth, when available, and therefore achieve a higher throughput. However, the use of larger bandwidths also increases the contention with adjacent WLANs, which can result in longer delays in accessing the channel and consequently, a lower throughput. In this paper, a scenario consisting of multiple WLANs using DCB and operating within carrier-sensing range of one another is considered. An analytical framework for evaluating the performance of such networks is presented. The analysis is carried out using a Markov chain model that characterizes the interactions between adjacent WLANs with overlapping channels. An algorithm is proposed for systematically constructing the Markov chain corresponding to any given scenario. The analytical model is then used to highlight and explain the key properties that differentiate DCB networks of WLANs from those operating on a single shared channel. Furthermore, the analysis is applied to networks of IEEE 802.11ac WLANs operating under DCB--which do not fully comply with some of the simplifying assumptions in our analysis--to show that the analytical model can give accurate results in more realistic scenarios.
A Number-Theoretic Error-Correcting Code
Venue: arXiv cs.IT 2015
Year: 2015

In this paper we describe a new error-correcting code (ECC) inspired by the Naccache-Stern cryptosystem. While by far less efficient than Turbo codes, the proposed ECC happens to be more efficient than some established ECCs for certain sets of parameters. The new ECC adds an appendix to the message. The appendix is the modular product of small primes representing the message bits. The receiver recomputes the product and detects transmission errors using modular division and lattice reduction.
28 GHz and 73 GHz Millimeter-Wave Indoor Propagation Measurements and Path Loss Models
Venue: arXiv cs.IT 2015
Year: 2015

This paper presents 28 GHz and 73 GHz millimeter- wave propagation measurements performed in a typical office environment using a 400 Megachip-per-second broadband sliding correlator channel sounder and highly directional steerable 15 dBi (30 degrees beamwidth) and 20 dBi (15 degrees beamwidth) horn antennas. Power delay profiles were acquired for 48 transmitter-receiver location combinations over distances ranging from 3.9 m to 45.9 m with maximum transmit powers of 24 dBm and 12.3 dBm at 28 GHz and 73 GHz, respectively. Directional and omnidirectional path loss models and RMS delay spread statistics are presented for line-of-sight and non-line-of-sight environments for both co- and cross-polarized antenna configurations. The LOS omnidirectional path loss exponents were 1.1 and 1.3 at 28 GHz and 73 GHz, and 2.7 and 3.2 in NLOS at 28 GHz and 73 GHz, respectively, for vertically-polarized antennas. The mean directional RMS delay spreads were 18.4 ns and 13.3 ns, with maximum values of 193 ns and 288 ns at 28 GHz and 73 GHz, respectively.
73 GHz Wideband Millimeter-Wave Foliage and Ground Reflection Measurements and Models
Venue: arXiv cs.IT 2015
Year: 2015

This paper presents 73 GHz wideband outdoor foliage and ground reflection measurements. Propagation measurements were made with a 400 Megachip-per-second sliding correlator channel sounder, with rotatable 27 dBi (7 degrees half- power beamwidth) horn antennas at both the transmitter and receiver, to study foliage-induced scattering and de-polarization effects, to assist in developing future wireless systems that will use adaptive array antennas. Signal attenuation through foliage was measured to be 0.4 dB/m for both co- and cross-polarized antenna configurations. Measured ground reflection coefficients for dirt and gravel ranged from 0.02 to 0.34, for incident angles ranging from 60 degrees to 81 degrees (with respect to the normal incidence of the surface). These data are useful for link budget design and site-specific (ray-tracing) models for future millimeter-wave communication systems.
PLC-to-DSL Interference: Statistical Model and Impact on DSL
Venue: arXiv cs.IT 2015
Year: 2015

Newly available standards for broadband access using Digital Subscriber Lines (DSL) have a high degree of spectrum overlap with home networking technologies using broadband Power Line Communications (BB-PLC) and this overlap leads to Electromagnetic Compatibility issues that may cause performance degradation in DSL systems. This paper studies the characteristics of measured PLC-to-DSL interference and presents novel results on its statistical characterization. The frequency-dependent couplings between power line cables and twisted-pairs are estimated from measurements and a statistical model based on a mixture of two truncated Gaussian distributions is set forth. The proposed statistical model allows the accurate evaluation of the impact of BB-PLC interference on various DSL technologies, in terms of both average and worst-case impacts on data rate. This paper further provides an extensive assessment of the impact of PLC-to-DSL interference at various loop lengths and for multiple profiles of Very-high rate Digital Subscriber Lines (VDSL2), Vectored VDSL2 (V-VDSL2), and G.fast. The results of this paper confirm that the impact of PLC interference varies with loop length and whether vectoring is used or not. Furthermore, the average impact is found to be generally small but worst-case couplings can lead to substantial degradation of DSL.
Leveraging One-hop Information in Massive MIMO Full-Duplex Wireless Systems
Venue: arXiv cs.IT 2015
Year: 2015

We consider a single-cell massive MIMO full-duplex wireless communication system, where the base-station (BS) is equipped with a large number of antennas. We consider the setup where the single-antenna mobile users operate in half- duplex, while each antenna at the BS is capable of full-duplex transmissions, i.e., it can transmit and receive simultaneously using the same frequency spectrum. The fundamental challenge in this system is intra-cell inter-node interference, generated by the transmissions of uplink users to the receptions at the downlink users. The key operational challenge is estimating and aggregating inter-mobile channel estimates, which can potentially overwhelm any gains from full-duplex operation. In this work, we propose a scalable and distributed scheme to optimally manage the inter-node interference by utilizing a "one- hop information architecture". In this architecture, the BS only needs to know the signal-to-interference-plus-noise ratio (SINR) from the downlink users. Each uplink user needs its own SINR, along with a weighted signal-plus-noise metric from its one-hop neighboring downlink users, which are the downlink users that it interferes with. The proposed one-hop information architecture does not require any network devices to comprehensively gather the vast inter-node interference channel knowledge, and hence significantly reduces the overhead. Based on the one-hop information architecture, we design a distributed power control algorithm and implement such architecture using overheard feedback information. We show that, in typical asymptotic regimes with many users and antennas, the proposed distributed power control scheme improves the overall network utility and reduces the transmission power of the uplink users.
DAG-Recurrent Neural Networks For Scene Labeling
Venue: arXiv cs.CV 2015
Year: 2015

In image labeling, local representations for image units are usually generated from their surrounding image patches, thus long-range contextual information is not effectively encoded. In this paper, we introduce recurrent neural networks (RNNs) to address this issue. Specifically, directed acyclic graph RNNs (DAG-RNNs) are proposed to process DAG-structured images, which enables the network to model long-range semantic dependencies among image units. Our DAG-RNNs are capable of tremendously enhancing the discriminative power of local representations, which significantly benefits the local classification. Meanwhile, we propose a novel class weighting function that attends to rare classes, which phenomenally boosts the recognition accuracy for non-frequent classes. Integrating with convolution and deconvolution layers, our DAG-RNNs achieve new state-of-the-art results on the challenging SiftFlow, CamVid and Barcelona benchmarks.
Identification of Source of Rumors in Social Networks with Incomplete Information
Venue: arXiv cs.SI 2015
Year: 2015

Rumor source identification in large social networks has received significant attention lately. Most recent works deal with the scale of the problem by observing a subset of the nodes in the network, called sensors, to estimate the source. This paper addresses the problem of locating the source of a rumor in large social networks where some of these sensor nodes have failed. We estimate the missing information about the sensors using doubly non-negative (DN) matrix completion and compressed sensing techniques. This is then used to identify the actual source by using a maximum likelihood estimator we developed earlier, on a large data set from Sina Weibo. Results indicate that the estimation techniques result in almost as good a performance of the ML estimator as for the network for which complete information is available. To the best of our knowledge, this is the first research work on source identification with incomplete information in social networks.
Overlap Frequency Domain Equalization for Faster-than-Nyquist Signaling
Venue: arXiv cs.IT 2015
Year: 2015

This letter proposes the Faster-than-Nyquist signaling (FTNS) using overlap frequency domain equalization (FDE), which compensates the inter-symbol interference (ISI) due to band limiting filters of the FTNS at the transmitter and the receiver as well as the frequency selective fading channel. Since overlap FDE does not require any guard interval (GI) at the transmitter such as cyclic prefix (CP), higher spectral efficiency can be achieved compared to FTNS scheme using the conventional FDE. In the proposed method, the equalizer weight is derived based on minimum mean square error (MMSE) criterion taking the colored noise due to the receiving filter into consideration. Moreover, we also give an approximated FDE weight in order to reduce the computational complexity. The performance of the proposed scheme is demonstrated via computer simulations.
Exploring Online Ad Images Using a Deep Convolutional Neural Network Approach
Venue: arXiv cs.CV 2015
Year: 2015

Online advertising is a huge, rapidly growing advertising market in today's world. One common form of online advertising is using image ads. A decision is made (often in real time) every time a user sees an ad, and the advertiser is eager to determine the best ad to display. Consequently, many algorithms have been developed that calculate the optimal ad to show to the current user at the present time. Typically, these algorithms focus on variations of the ad, optimizing among different properties such as background color, image size, or set of images. However, there is a more fundamental layer. Our study looks at new qualities of ads that can be determined before an ad is shown (rather than online optimization) and defines which ads are most likely to be successful. We present a set of novel algorithms that utilize deep-learning image processing, machine learning, and graph theory to investigate online advertising and to construct prediction models which can foresee an image ad's success. We evaluated our algorithms on a dataset with over 260,000 ad images, as well as a smaller dataset specifically related to the automotive industry, and we succeeded in constructing regression models for ad image click rate prediction. The obtained results emphasize the great potential of using deep-learning algorithms to effectively and efficiently analyze image ads and to create better and more innovative online ads. Moreover, the algorithms presented in this paper can help predict ad success and can be applied to analyze other large-scale image corpora.
Termination of rewrite relations on $λ$-terms based on Girard's notion of reducibility
Venue: arXiv cs.LO 2015
Year: 2015

In this paper, we show how to extend the notion of reducibility introduced by Girard for proving the termination of $β$-reduction in the polymorphic $λ$-calculus, to prove the termination of various kinds of rewrite relations on $λ$-terms, including rewriting modulo some equational theory and rewriting with matching modulo $β$$η$, by using the notion of computability closure. This provides a powerful termination criterion for various higher-order rewriting frameworks, including Klop's Combinatory Reductions Systems with simple types and Nipkow's Higher-order Rewrite Systems.