OpenRaiser/Intern-Atlas huggingface dataset:
Robust Preamble Design for Synchronization, Signaling Transmission and Channel Estimation
Venue: arXiv cs.IT 2015
Year: 2015

The European second generation digital video broadcasting standard (DVB-T2) introduces a P1 symbol. This P1 symbol facilitates the coarse synchronization and carries 7-bit transmission parameter signaling (TPS), including the fast Fourier transform size, single-input/single-output and multiple-input/single-output transmission modes, etc. However, this P1 symbol suffers from obvious performance loss over fading channels. In this paper, an improved preamble scheme is proposed, where a pair of optimal m sequences are inserted into the frequency domain. One sequence is used for carrier frequency offset (CFO) estimation, and the other carries TPS to inform the receiver about the transmission configuration parameters. Compared with the conventional preamble scheme, the proposed preamble improves CFO estimation performance and the signaling capacity. Meanwhile, without additional overhead, the proposed scheme exploits more active pilots than the conventional schemes. In this way, it can facilitate the channel estimation, improve the frame synchronization accuracy as well as enhance its robustness to frequency selective fading channels.
Priori-Information Aided Iterative Hard Threshold: A Low-Complexity High-Accuracy Compressive Sensing Based Channel Estimation for TDS-OFDM
Venue: arXiv cs.IT 2015
Year: 2015

This paper develops a low-complexity channel estimation (CE) scheme based on compressive sensing (CS) for time-domain synchronous (TDS) orthogonal frequency-division multiplexing (OFDM) to overcome the performance loss under doubly selective fading channels. Specifically, an overlap-add method of the time-domain training sequence is first proposed to obtain the coarse estimates of the channel length, path delays and path gains of the wireless channel, by exploiting the channel's temporal correlation to improve the robustness of the coarse CE under the severe fading channel with long delay spread. We then propose the priori-information aided (PA) iterative hard threshold (IHT) algorithm, which utilizes the priori information of the acquired coarse estimate for the wireless channel and therefore is capable of obtaining an accurate channel estimate of the doubly selective fading channel. Compared with the classical IHT algorithm whose convergence requires the $l_2$ norm of the measurement matrix being less than 1, the proposed PA-IHT algorithm exploits the priori information acquired to remove such a limitation as well as to reduce the number of required iterations. Compared with the existing CS based CE method for TDS-OFDM, the proposed PA-IHT algorithm significantly reduces the computational complexity of CE as well as enhances the CE accuracy. Simulation results demonstrate that, without sacrificing spectral efficiency and changing the current TDS-OFDM signal structure, the proposed scheme performs better than the existing CE schemes for TDS-OFDM in various scenarios, especially under severely doubly selective fading channels.
On Computing the Galois Lattice of Bipartite Distance Hereditary Graphs
Venue: arXiv cs.DM 2015
Year: 2015

The class of Bipartite Distance Hereditary (BDH) graphs is the intersection between bipartite domino-free and chordal bipartite graphs.\ Graphs in both the latter classes have linearly many maximal bicliques, implying the existence of polynomial-time algorithms for computing the associated Galois lattice.\ Such a lattice can indeed be built in $O(m\times n)$ worst case-time for a domino-free graph with $m$ edges and $n$ vertices.\ In this paper we give a sharp estimate on the number of the maximal bicliques of BDH graphs and exploit such result to give an $O(m)$ worst case time algorithm for computing the Galois lattice of BDH graphs. By relying on the fact that neighborhoods of vertices of BDH graphs can be realized as directed paths in a arborescence, we give an $O(n)$ worst-case space and time encoding of both the input graph and its Galois lattice, provided that the reverse of a Bandelt and Mulder building sequence is given.
Combine CRF and MMSEG to Boost Chinese Word Segmentation in Social Media
Venue: arXiv cs.CL 2015
Year: 2015

In this paper, we propose a joint algorithm for the word segmentation on Chinese social media. Previous work mainly focus on word segmentation for plain Chinese text, in order to develop a Chinese social media processing tool, we need to take the main features of social media into account, whose grammatical structure is not rigorous, and the tendency of using colloquial and Internet terms makes the existing Chinese-processing tools inefficient to obtain good performance on social media. In our approach, we combine CRF and MMSEG algorithm and extend features of traditional CRF algorithm to train the model for word segmentation, We use Internet lexicon in order to improve the performance of our model on Chinese social media. Our experimental result on Sina Weibo shows that our approach outperforms the state-of-the-art model.
Design and Development of a Burst Acquisition System for Geosynchronous Satcom Channels
Venue: arXiv cs.IT 2015
Year: 2015

The key contribution of this work is to develop transmitter and receiver algorithms in discrete-time for turbo- coded offset QPSK signals. The proposed synchronization and detection techniques perform effectively at an SNR per bit close to 1.5 dB, in the presence of a frequency offset as large as 30 % of the symbol-rate and a clock offset of 25 ppm (parts per million). Due to the use of up-sampling and matched filtering and a feedforward approach, the acquisition time for clock recovery is just equal to the length of the preamble. The carrier recovery algorithm does not exhibit any phase ambiguity, alleviating the need for differentially encoding the data at the transmitter. The proposed techniques are well suited for discrete-time implementation.
On the Effect of Fronthaul Latency on ARQ in C-RAN Systems
Venue: arXiv cs.IT 2015
Year: 2015

In the Cloud Radio Access Network (C-RAN) architecture, a Control Unit (CU) implements the baseband processing functionalities of a cluster of Base Stations (BSs), which are connected to it through a fronthaul network. This architecture enables centralized processing at the CU, and hence the implementation of enhanced interference mitigation strategies, but it also entails an increased decoding latency due to the transport on the fronthaul network. The fronthaul latency may offset the benefits of centralized processing when considering the performance of protocols at layer 2 and above. This letter studies the impact of fronthaul latency on the performance of standard Automatic Retransmission reQuest (ARQ) protocols, namely Stop and Wait, Go-Back-N and Selective Repeat. The performance of the C-RAN architecture in terms of throughput and efficiency is compared to the that of a conventional cellular system with local processing, as well as with that of a proposed hybrid C-RAN system in which BSs can perform decoding. The dynamics of the system are modeled as a multi-dimensional Markov process that includes sub-chains to capture the temporal correlation of interference and channel gains. Numerical results yield insights into the impact of system parameters such as fronthaul latency and signal-to-interference ratio on different ARQ protocols.
Computational models of attention
Venue: arXiv cs.CV 2015
Year: 2015

This chapter reviews recent computational models of visual attention. We begin with models for the bottom-up or stimulus-driven guidance of attention to salient visual items, which we examine in seven different broad categories. We then examine more complex models which address the top-down or goal-oriented guidance of attention towards items that are more relevant to the task at hand.
Memory-Adjustable Navigation Piles with Applications to Sorting and Convex Hulls
Venue: arXiv cs.DS 2015
Year: 2015

We consider space-bounded computations on a random-access machine (RAM) where the input is given on a read-only random-access medium, the output is to be produced to a write-only sequential-access medium, and the available workspace allows random reads and writes but is of limited capacity. The length of the input is $N$ elements, the length of the output is limited by the computation, and the capacity of the workspace is $O(S)$ bits for some predetermined parameter $S$. We present a state-of-the-art priority queue---called an adjustable navigation pile---for this restricted RAM model. Under some reasonable assumptions, our priority queue supports $\mathit{minimum}$ and $\mathit{insert}$ in $O(1)$ worst-case time and $\mathit{extract}$ in $O(N/S + \lg{} S)$ worst-case time for any $S \geq \lg{} N$. We show how to use this data structure to sort $N$ elements and to compute the convex hull of $N$ points in the two-dimensional Euclidean space in $O(N^2/S + N \lg{} S)$ worst-case time for any $S \geq \lg{} N$. Following a known lower bound for the space-time product of any branching program for finding unique elements, both our sorting and convex-hull algorithms are optimal. The adjustable navigation pile has turned out to be useful when designing other space-efficient algorithms, and we expect that it will find its way to yet other applications.
Multiuser Detection by MAP Estimation with Sum-of-Absolute-Values Relaxation
Venue: arXiv cs.IT 2015
Year: 2015

In this article, we consider multiuser detection that copes with multiple access interference caused in star-topology machine-to-machine (M2M) communications. We assume that the transmitted signals are discrete-valued (e.g. binary signals taking values of $\pm 1$), which is taken into account as prior information in detection. We formulate the detection problem as the maximum a posteriori (MAP) estimation, which is relaxed to a convex optimization called the sum-of-absolute-values (SOAV) optimization. The SOAV optimization can be efficiently solved by a proximal splitting algorithm, for which we give the proximity operator in a closed form. Numerical simulations are shown to illustrate the effectiveness of the proposed approach compared with the linear minimum mean-square-error (LMMSE) and the least absolute shrinkage and selection operator (LASSO) methods.
Geometric Context from Videos
Venue: arXiv cs.CV 2015
Year: 2015

We present a novel algorithm for estimating the broad 3D geometric structure of outdoor video scenes. Leveraging spatio-temporal video segmentation, we decompose a dynamic scene captured by a video into geometric classes, based on predictions made by region-classifiers that are trained on appearance and motion features. By examining the homogeneity of the prediction, we combine predictions across multiple segmentation hierarchy levels alleviating the need to determine the granularity a priori. We built a novel, extensive dataset on geometric context of video to evaluate our method, consisting of over 100 ground-truth annotated outdoor videos with over 20,000 frames. To further scale beyond this dataset, we propose a semi-supervised learning framework to expand the pool of labeled data with high confidence predictions obtained from unlabeled data. Our system produces an accurate prediction of geometric context of video achieving 96% accuracy across main geometric classes.
Towards Electronics-based Emergency Control in Power Grids with High Renewable Penetration
Venue: arXiv cs.SY 2015
Year: 2015

Traditional emergency control schemes in power systems usually accompany with power interruption yielding severely economic damages to customers. This paper sketches the ideas of a viable alternative for traditional remedial controls for power grids with high penetration of renewables, in which the renewables are integrated with synchronverters to mimic the dynamics of conventional generators. In this novel emergency control scheme, the power electronics resources are exploited to control the inertia and damping of the imitated generators in order to quickly compensate for the deviations caused by fault and thereby bound the fault-on dynamics and stabilize the power system under emergency situations. This emergency control not only saves investments and operating costs for modern and future power systems, but also helps to offer seamless electricity service to customers. Simple numerical simulation will be used to illustrate the concept of this paper.
An Inverse Problem Approach for Content Popularity Estimation
Venue: arXiv cs.NI 2015
Year: 2015

The Internet increasingly focuses on content, as exemplified by the now popular Information Centric Networking paradigm. This means, in particular, that estimating content popularities becomes essential to manage and distribute content pieces efficiently. In this paper, we show how to properly estimate content popularities from a traffic trace. Specifically, we consider the problem of the popularity inference in order to tune content-level performance models, e.g. caching models. In this context, special care must be brought on the fact that an observer measures only the flow of requests, which differs from the model parameters, though both quantities are related by the model assumptions. Current studies, however, ignore this difference and use the observed data as model parameters. In this paper, we highlight the inverse problem that consists in determining parameters so that the flow of requests is properly predicted by the model. We then show how such an inverse problem can be solved using Maximum Likelihood Estimation. Based on two large traces from the Orange network and two synthetic datasets, we eventually quantify the importance of this inversion step for the performance evaluation accuracy.
A light-weight, multi-axis compliant tensegrity joint
Venue: arXiv cs.RO 2015
Year: 2015

In this paper, we present a light-weight, multi- axis compliant tenegrity joint that is biologically inspired by the human elbow. This tensegrity elbow actuates by shortening and lengthening cable in a method inspired by muscular actuation in a person. Unlike many series elastic actuators, this joint is structurally compliant not just along each axis of rotation, but along other axes as well. Compliant robotic joints are indispensable in unpredictable environments, including ones where the robot must interface with a person. The joint also addresses the need for functional redundancy and flexibility, traits which are required for many applications that investigate the use of biologically accurate robotic models.
Fast Compatibility Testing for Rooted Phylogenetic Trees
Venue: arXiv cs.DS 2015
Year: 2015

We consider the following basic problem in phylogenetic tree construction. Let $\mathcal{P} = \{T_1, \ldots, T_k\}$ be a collection of rooted phylogenetic trees over various subsets of a set of species. The tree compatibility problem asks whether there is a tree $T$ with the following property: for each $i \in \{1, \dots, k\}$, $T_i$ can be obtained from the restriction of $T$ to the species set of $T_i$ by contracting zero or more edges. If such a tree $T$ exists, we say that $\mathcal{P}$ is compatible. We give a $\tilde{O}(M_\mathcal{P})$ algorithm for the tree compatibility problem, where $M_\mathcal{P}$ is the total number of nodes and edges in $\mathcal{P}$. Unlike previous algorithms for this problem, the running time of our method does not depend on the degrees of the nodes in the input trees. Thus, it is equally fast on highly resolved and highly unresolved trees.
Defect Detection Techniques for Airbag Production Sewing Stages
Venue: arXiv cs.CV 2015
Year: 2015

Airbags are subject to strict quality control in order to ensure passengers safety. The quality of fabric and sewing thread influence the final product and therefore, sewing defects must be early and accurately detected, in order to remove the item from production. Airbag seams assembly can take various forms, using linear and circle primitives, with threads of different colors and length densities, creating lockstitch or double threads chainstitch. The paper presents a framework for the automatic detection of defects occurring during the airbag sewing stage. Types of defects as skipped stitch, missed stitch or superimposed seam for lockstitch and two threads chainstitch are detected and marked. Using image processing methods, the proposed framework follows the seams path and determines if a color pattern of the considered stitches is valid.
Multihop Relaying in Millimeter Wave Networks: A Proportionally Fair Cooperative Network Formation Game
Venue: arXiv cs.GT 2015
Year: 2015

Millimeter wave channels suffer from considerable degradation in the channel quality when the signal is Non Line of Sight (NLOS) between the source and the destination. Multihop relaying is thus anticipated to improve the communi- cation between a source and its destination. This is achieved by transmitting the signal to a sequence of relays in which a Line of Sight (LOS) signal exists between two nodes along the path, or more generally when the signal is better than the transmitted signal directly from the source to the destination. In this paper, we consider a millimeter wave network composed of multiple source- destination pairs and a set of deployed relays. We formulate the problem of multihop relaying as a cooperative network formation game in which each relay chooses which source-destination pair to assist in order to improve the end-to-end performance, that is, the multihop delay between the source and the destination. Further, we present an algorithm based on the Nash Bargaining Solution to ensure fairness among the different source-destination pairs and assess its efficiency on numerical simulations.
An Application-Aware Spectrum Sharing Approach for Commercial Use of 3.5 GHz Spectrum
Venue: arXiv cs.NI 2015
Year: 2015

In this paper, we introduce an application-aware spectrum sharing approach for sharing the Federal under-utilized 3.5 GHz spectrum with commercial users. In our model, users are running elastic or inelastic traffic and each application running on the user equipment (UE) is assigned a utility function based on its type. Furthermore, each of the small cells users has a minimum required target utility for its application. In order for users located under the coverage area of the small cells' eNodeBs, with the 3.5 GHz band resources, to meet their minimum required quality of experience (QoE), the network operator makes a decision regarding the need for sharing the macro cell's resources to obtain additional resources. Our objective is to provide each user with a rate that satisfies its application's minimum required utility through spectrum sharing approach and improve the overall QoE in the network. We present an application-aware spectrum sharing algorithm that is based on resource allocation with carrier aggregation to allocate macro cell permanent resources and small cells' leased resources to UEs and allocate each user's application an aggregated rate that can at minimum achieves the application's minimum required utility. Finally, we present simulation results for the performance of the proposed algorithm.
Architectural Consistency Checking in Plugin-Based Software Systems
Venue: arXiv cs.SE 2015
Year: 2015

Manually ensuring that the implementation of a software system is consistent with the software architecture is a laborious and error-prone task. Thus, a variety of approaches towards automated consistency checking have been developed to counteract architecture erosion. However, these approaches lack means to define and check architectural restrictions concerning plugin dependencies, which is required for plugin-based software systems. In this paper, we propose a domain-specific language called Dependency Constraint Language (DepCoL) to facilitate the definition of constraints concerning plugin dependencies. Using DepCoL, it is possible to define constraints affecting groups of plugins, reducing the required specification effort, to formulate constraints for specific plugins only and to refine constraints. Moreover, we provide an Eclipse plugin, which checks whether the software system under development is consistent with the modeled constraints. This enables a seamless integration into the development process to effortless check consistency during development of the software system. In this way, developers are informed about dependency violations immediately and this supports developers in counteracting architecture erosion.
Learning with $\ell^{0}$-Graph: $\ell^{0}$-Induced Sparse Subspace Clustering
Venue: arXiv cs.LG 2015
Year: 2015

Sparse subspace clustering methods, such as Sparse Subspace Clustering (SSC) \cite{ElhamifarV13} and $\ell^{1}$-graph \cite{YanW09,ChengYYFH10}, are effective in partitioning the data that lie in a union of subspaces. Most of those methods use $\ell^{1}$-norm or $\ell^{2}$-norm with thresholding to impose the sparsity of the constructed sparse similarity graph, and certain assumptions, e.g. independence or disjointness, on the subspaces are required to obtain the subspace-sparse representation, which is the key to their success. Such assumptions are not guaranteed to hold in practice and they limit the application of sparse subspace clustering on subspaces with general location. In this paper, we propose a new sparse subspace clustering method named $\ell^{0}$-graph. In contrast to the required assumptions on subspaces for most existing sparse subspace clustering methods, it is proved that subspace-sparse representation can be obtained by $\ell^{0}$-graph for arbitrary distinct underlying subspaces almost surely under the mild i.i.d. assumption on the data generation. We develop a proximal method to obtain the sub-optimal solution to the optimization problem of $\ell^{0}$-graph with proved guarantee of convergence. Moreover, we propose a regularized $\ell^{0}$-graph that encourages nearby data to have similar neighbors so that the similarity graph is more aligned within each cluster and the graph connectivity issue is alleviated. Extensive experimental results on various data sets demonstrate the superiority of $\ell^{0}$-graph compared to other competing clustering methods, as well as the effectiveness of regularized $\ell^{0}$-graph.