OpenRaiser/Intern-Atlas huggingface dataset:
An OvS-MultiObjective Algorithm Approach for Lane Reversal Problem
Venue: arXiv cs.NE 2014
Year: 2014

The lane reversal has proven to be a useful method to mitigate traffic congestion during rush hour or in case of specific events that affect high traffic volumes. In this work we propose a methodology that is placed within optimization via Simulation, by means of which a multi-objective genetic algorithm and simulations of traffic are used to determine the configuration of ideal lane reversal.
From Attention to Citation, What and How Does Altmetrics Work?
Venue: arXiv cs.DL 2014
Year: 2014

Scholarly and social impacts of scientific publications could be measured by various metrics. In this study, the relationship between various metrics of 63,805 PLOS research articles are studied. Generally, article views correlate well with citation, however, different types of article view have different levels of correlation with citation, when pdf download correlates the citation most significantly. It's necessary for publishers and journals to provide detailed and comprehensive article metrics. Although the low correlation between social attention and citation is confirmed by this study and previous studies, more than ever, we find that social attention is highly correlated with article view, especially the browser html view. Social attention is the important source that bringing network traffic to browser html view and may lead to citation subsequently. High altmetric score has the potential role in promoting the long-term academic impact of articles, when a conceptual model is proposed to interpret the conversion from social attention to article view, and to citation finally.
Planar Embeddings with Small and Uniform Faces
Venue: arXiv cs.CG 2014
Year: 2014

Motivated by finding planar embeddings that lead to drawings with favorable aesthetics, we study the problems MINMAXFACE and UNIFORMFACES of embedding a given biconnected multi-graph such that the largest face is as small as possible and such that all faces have the same size, respectively. We prove a complexity dichotomy for MINMAXFACE and show that deciding whether the maximum is at most $k$ is polynomial-time solvable for $k \leq 4$ and NP-complete for $k \geq 5$. Further, we give a 6-approximation for minimizing the maximum face in a planar embedding. For UNIFORMFACES, we show that the problem is NP-complete for odd $k \geq 7$ and even $k \geq 10$. Moreover, we characterize the biconnected planar multi-graphs admitting 3- and 4-uniform embeddings (in a $k$-uniform embedding all faces have size $k$) and give an efficient algorithm for testing the existence of a 6-uniform embedding.
Optimal Sizing of Voltage Control Devices for Distribution Circuit with Intermittent Load
Venue: arXiv cs.SY 2014
Year: 2014

We consider joint control of a switchable capacitor and a D-STATCOM for voltage regulation in a distribution circuit with intermittent load. The control problem is formulated as a two-timescale optimal power flow problem with chance constraints, which minimizes power loss while limiting the probability of voltage violations due to fast changes in load. The control problem forms the basis of an optimization problem which determines the sizes of the control devices by minimizing sum of the expected power loss cost and the capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments on a circuit with high-performance computing (HPC) load show that the proposed sizing and control schemes significantly improve the reliability of voltage regulation on the expense of only a moderate increase in cost.
Pricing Mobile Data Offloading: A Distributed Market Framework
Venue: arXiv cs.NI 2014
Year: 2014

Mobile data offloading is an emerging technology to avoid congestion in cellular networks and improve the level of user satisfaction. In this paper, we develop a distributed market framework to price the offloading service, and conduct a detailed analysis of the incentives for offloading service providers and conflicts arising from the interactions of different participators. Specifically, we formulate a multi-leader multi-follower Stackelberg game (MLMF-SG) to model the interactions between the offloading service providers and the offloading service consumers in the considered market framework, and investigate the cases where the offloading capacity of APs is unlimited and limited, respectively. For the case without capacity limit, we decompose the followers' game of the MLMF-SG (FG-MLMF-SG) into a number of simple follower games (FGs), and prove the existence and uniqueness of the equilibrium of the FGs from which the existence and uniqueness of the FG-MLMF-SG also follows. For the leaders' game of the MLMF-SG, we also prove the existence and uniqueness of the equilibrium. For the case with capacity limit, by considering a symmetric strategy profile, we establish the existence and uniqueness of the equilibrium of the corresponding MLMF-SG, and present a distributed algorithm that allows the leaders to achieve the equilibrium. Finally, extensive numerical experiments demonstrate that the Stackelberg equilibrium is very close to the corresponding social optimum for both considered cases.
A new Watermarking Technique for Medical Image using Hierarchical Encryption
Venue: arXiv cs.MM 2014
Year: 2014

In recent years, characterized by the innovation of technology and the digital revolution, the field of media has become important. The transfer and exchange of multimedia data and duplication have become major concerns of researchers. Consequently, protecting copyrights and ensuring service safety is needed. Cryptography has a specific role, is to protect secret files against unauthorized access. In this paper, a hierarchical cryptosystem algorithm based on Logistic Map chaotic systems is proposed. The results show that the proposed method improves the security of the image. Experimental results on a database of 200 medical images show that the proposed method significantly gives better results.
Nonzero bound on Fiedler eigenvalue causes exponential growth of H-infinity norm of vehicular platoon
Venue: arXiv cs.SY 2014
Year: 2014

We consider platoons composed of identical vehicles and controlled in a distributed way, that is, each vehicle has its own onboard controller. The regulation errors in spacing to the immediately preceeding and following vehicles are weighted differently by the onboard controller, which thus implements an asymmetric bidirectional control scheme. The weights can vary along the platoon. We prove that such platoons have a nonzero uniform bound on the second smallest eigenvalue of the graph Laplacian matrix - the Fiedler eigenvalue. Furthermore, it is shown that existence of this bound always signals undesirable scaling properties of the platoon. Namely, the H-infinity norm of the transfer function of the platoon grows exponentially with the number of vehicles regardless of the controllers used. Hence the benefits of a uniform gap in the spectrum of a Laplacian with an asymetric distributed controller are paid for by poor scaling as the number of vehicles grows.
Robot Monitoring for the Detection and Confirmation of Stochastic Events
Venue: arXiv cs.RO 2014
Year: 2014

In this paper we consider a robot patrolling problem in which events arrive randomly over time at the vertices of a graph. When an event arrives it remains active for a random amount of time. If that time active exceeds a certain threshold, then we say that the event is a true event; otherwise it is a false event. The robot(s) can traverse the graph to detect newly arrived events, and can revisit these events in order to classify them as true or false. The goal is to plan robot paths that maximize the number of events that are correctly classified, with the constraint that there are no false positives. We show that the offline version of this problem is NP-hard. We then consider a simple patrolling policy based on the traveling salesman tour, and characterize the probability of correctly classifying an event. We investigate the problem when multiple robots follow the same path, and we derive the optimal (and not necessarily uniform) spacing between robots on the path.
Reducing the Complexity of the Linear Programming Decoding
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we show how the complexity of Linear Programming (LP) decoder can decrease. We use the degree 3 check equation to model all variation check degrees. The complexity of LP decoding is directed relative to the number of constraint. Number of constraint for original LP decoder is O(n*(2^n)). Our method decrease the number of the constraint to O(n).
Developing a Video Steganography Toolkit
Venue: arXiv cs.MM 2014
Year: 2014

Although techniques for separate image and audio steganography are widely known, relatively little has been described concerning the hiding of information within video streams ("video steganography"). In this paper we review the current state of the art in this field, and describe the key issues we have encountered in developing a practical video steganography system. A supporting video is also available online at http://www.youtube.com/watch?v=YhnlHmZolRM
The Generation of Large Networks from Web-of-Science Data
Venue: arXiv cs.DL 2014
Year: 2014

During the 1990s, one of us developed a series of freeware routines (http://www.leydesdorff.net/indicators) that enable the user to organize downloads from the Web-of-Science (Thomson Reuters) into a relational database, and then to export matrices for further analysis in various formats (for example, for co-author analysis). The basic format of the matrices displays each document as a case in a row that can be attributed different variables in the columns. One limitation to this approach was hitherto that relational databases typically have an upper limit for the number of variables, such as 256 or 1024. In this brief communication, we report on a way to circumvent this limitation by using txt2Pajek.exe, available as freeware from http://www.pfeffer.at/txt2pajek/.
A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping
Venue: arXiv cs.LG 2014
Year: 2014

A survey of existing methods for stopping active learning (AL) reveals the needs for methods that are: more widely applicable; more aggressive in saving annotations; and more stable across changing datasets. A new method for stopping AL based on stabilizing predictions is presented that addresses these needs. Furthermore, stopping methods are required to handle a broad range of different annotation/performance tradeoff valuations. Despite this, the existing body of work is dominated by conservative methods with little (if any) attention paid to providing users with control over the behavior of stopping methods. The proposed method is shown to fill a gap in the level of aggressiveness available for stopping AL and supports providing users with control over stopping behavior.
A Tabu Search Algorithm for the Multi-period Inspector Scheduling Problem
Venue: arXiv cs.AI 2014
Year: 2014

This paper introduces a multi-period inspector scheduling problem (MPISP), which is a new variant of the multi-trip vehicle routing problem with time windows (VRPTW). In the MPISP, each inspector is scheduled to perform a route in a given multi-period planning horizon. At the end of each period, each inspector is not required to return to the depot but has to stay at one of the vertices for recuperation. If the remaining time of the current period is insufficient for an inspector to travel from his/her current vertex $A$ to a certain vertex B, he/she can choose either waiting at vertex A until the start of the next period or traveling to a vertex C that is closer to vertex B. Therefore, the shortest transit time between any vertex pair is affected by the length of the period and the departure time. We first describe an approach of computing the shortest transit time between any pair of vertices with an arbitrary departure time. To solve the MPISP, we then propose several local search operators adapted from classical operators for the VRPTW and integrate them into a tabu search framework. In addition, we present a constrained knapsack model that is able to produce an upper bound for the problem. Finally, we evaluate the effectiveness of our algorithm with extensive experiments based on a set of test instances. Our computational results indicate that our approach generates high-quality solutions.
Minimum-Energy Distributed Filtering
Venue: arXiv cs.SY 2014
Year: 2014

The paper addresses the problem of distributed filtering with guaranteed convergence properties using minimum-energy filtering and $H_\infty$ filtering methodologies. A linear state space plant model is considered observed by a network of communicating sensors, in which individual sensor measurements may lead to an unobservable filtering problem. However, each filter locally shares estimates, that are subject to disturbances, with its respective neighboring filters to produce an estimate of the plant state. The minimum-energy strategy of the proposed local filter leads to a locally optimal time-varying filter gain facilitating the transient and the asymptotic convergence of the estimation error, with guaranteed $H_\infty$ performance. The filters are implementable using only the local measurements and information from the neighboring filters subject to disturbances. A key idea of the proposed algorithm is to locally approximate the neighboring estimates, that are not directly accessible, considering them as disturbance contaminated versions of the plant state. The proposed algorithm imposes minimal communication load on the network and is scalable to larger sensor networks.
Quality of Service in Network Creation Games
Venue: arXiv cs.GT 2014
Year: 2014

Network creation games model the creation and usage costs of networks formed by n selfish nodes. Each node v can buy a set of edges, each for a fixed price α> 0. Its goal is to minimize its private costs, i.e., the sum (SUM-game, Fabrikant et al., PODC 2003) or maximum (MAX-game, Demaine et al., PODC 2007) of distances from $v$ to all other nodes plus the prices of the bought edges. The above papers show the existence of Nash equilibria as well as upper and lower bounds for the prices of anarchy and stability. In several subsequent papers, these bounds were improved for a wide range of prices α. In this paper, we extend these models by incorporating quality-of-service aspects: Each edge cannot only be bought at a fixed quality (edge length one) for a fixed price α. Instead, we assume that quality levels (i.e., edge lengths) are varying in a fixed interval [β,B], 0 < β<= B. A node now cannot only choose which edge to buy, but can also choose its quality x, for the price p(x), for a given price function p. For both games and all price functions, we show that Nash equilibria exist and that the price of stability is either constant or depends only on the interval size of available edge lengths. Our main results are bounds for the price of anarchy. In case of the SUM-game, we show that they are tight if price functions decrease sufficiently fast.
Deformable Part Models are Convolutional Neural Networks
Venue: arXiv cs.CV 2014
Year: 2014

Deformable part models (DPMs) and convolutional neural networks (CNNs) are two widely used tools for visual recognition. They are typically viewed as distinct approaches: DPMs are graphical models (Markov random fields), while CNNs are "black-box" non-linear classifiers. In this paper, we show that a DPM can be formulated as a CNN, thus providing a novel synthesis of the two ideas. Our construction involves unrolling the DPM inference algorithm and mapping each step to an equivalent (and at times novel) CNN layer. From this perspective, it becomes natural to replace the standard image features used in DPM with a learned feature extractor. We call the resulting model DeepPyramid DPM and experimentally validate it on PASCAL VOC. DeepPyramid DPM significantly outperforms DPMs based on histograms of oriented gradients features (HOG) and slightly outperforms a comparable version of the recently introduced R-CNN detection system, while running an order of magnitude faster.
Windows into Geometric Events: Data Structures for Time-Windowed Querying of Temporal Point Sets
Venue: arXiv cs.DS 2014
Year: 2014

We study geometric data structures for sets of point-based temporal events, answering time-windowed queries, i.e., given a contiguous time interval we answer common geometric queries about the point events with time stamps in this interval. The geometric queries we consider include queries based on the skyline, convex hull, and proximity relations of the point set. We provide space efficient data structures which answer queries in polylogarithmic time.
Linear Degrees of Freedom of MIMO Broadcast Channels with Reconfigurable Antennas in the Absence of CSIT
Venue: arXiv cs.IT 2014
Year: 2014

The K-user multiple-input and multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter (CSIT) is considered, where each receiver is assumed to be equipped with reconfigurable antennas capable of choosing a subset of receiving modes from several preset modes. Under general antenna configurations, the sum linear degrees of freedom (LDoF) of the K-user MIMO BC with reconfigurable antennas is completely characterized, which corresponds to the maximum sum DoF achievable by linear coding strategies. The LDoF region is further characterized for a class of antenna configurations. Similar analysis is extended to the K-user MIMO interference channels with reconfigurable antennas and the sum LDoF is characterized for a class of antenna configurations.
Profiling underprivileged residents with mid-term public transit smartcard data of Beijing
Venue: arXiv cs.OH 2014
Year: 2014

Mobility of economically underprivileged residents in China has seldom been well profiled due to privacy issue and the characteristics of Chinese over poverty. In this paper, we identify and characterize underprivileged residents in Beijing using ubiquitous public transport smartcard transactions in 2008 and 2010, respectively. We regard these frequent bus/metro riders (FRs) in China, especially in Beijing, as economically underprivileged residents. Our argument is tested against (1) the household travel survey in 2010, (2) a small-scale survey in 2012, as well as (3) our interviews with local residents in Beijing. Cardholders' job and residence locations are identified using Smart Card Data (SCD) in 2008 and 2010. Our analysis is restricted to cardholders that use the same cards in both years. We then classify all identified FRs into 20 groups by residence changes (change, no change), workplace changes (change, no change, finding a job, losing a job, and all-time employed) during 2008-2010 and housing place in 2010 (within the fourth ring road or not). The underprivileged degree of each FR is then evaluated using the 2014 SCD. To the best of our knowledge, this is one of the first studies for understanding long- or mid-term urban dynamics using immediate "big data", and also for profiling underprivileged residents in Beijing in a fine-scale.
Completely Independent Spanning Trees in Some Regular Graphs
Venue: arXiv cs.DM 2014
Year: 2014

Let $k\ge 2$ be an integer and $T_1,\ldots, T_k$ be spanning trees of a graph $G$. If for any pair of vertices $(u,v)$ of $V(G)$, the paths from $u$ to $v$ in each $T_i$, $1\le i\le k$, do not contain common edges and common vertices, except the vertices $u$ and $v$, then $T_1,\ldots, T_k$ are completely independent spanning trees in $G$. For $2k$-regular graphs which are $2k$-connected, such as the Cartesian product of a complete graph of order $2k-1$ and a cycle and some Cartesian products of three cycles (for $k=3$), the maximum number of completely independent spanning trees contained in these graphs is determined and it turns out that this maximum is not always $k$.
A High-Level Model of Neocortical Feedback Based on an Event Window Segmentation Algorithm
Venue: arXiv cs.NE 2014
Year: 2014

The author previously presented an event window segmentation (EWS) algorithm [5] that uses purely statistical methods to learn to recognize recurring patterns in an input stream of events. In the following discussion, the EWS algorithm is first extended to make predictions about future events. Next, this extended algorithm is used to construct a high-level, simplified model of a neocortical hierarchy. An event stream enters at the bottom of the hierarchy, and drives processing activity upward in the hierarchy. Successively higher regions in the hierarchy learn to recognize successively deeper levels of patterns in these events as they propagate from the bottom of the hierarchy. The lower levels in the hierarchy use the predictions from the levels above to strengthen their own predictions. A C++ source code listing of the model implementation and test program is included as an appendix.
On tensor rank of conditional probability tables in Bayesian networks
Venue: arXiv cs.AI 2014
Year: 2014

A difficult task in modeling with Bayesian networks is the elicitation of numerical parameters of Bayesian networks. A large number of parameters is needed to specify a conditional probability table (CPT) that has a larger parent set. In this paper we show that, most CPTs from real applications of Bayesian networks can actually be very well approximated by tables that require substantially less parameters. This observation has practical consequence not only for model elicitation but also for efficient probabilistic reasoning with these networks.
Enhanced Pilot-Based Spectrum Sensing Algorithm
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we develop an enhanced pilot-based spectrum sensing algorithm for cognitive radio. Unlike conventional pilot-based detectors which merely detect the presence of pilot signals, the proposed detector also utilizes the presence of the signal that carries the actual information. We analytically compare the performance of the proposed detector with the conventional one, and we show that the detection performance is significantly improved.
HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we propose a novel method for fast face recognition called L1/2 Regularized Sparse Representation using Hierarchical Feature Selection (HSR). By employing hierarchical feature selection, we can compress the scale and dimension of global dictionary, which directly contributes to the decrease of computational cost in sparse representation that our approach is strongly rooted in. It consists of Gabor wavelets and Extreme Learning Machine Auto-Encoder (ELM-AE) hierarchically. For Gabor wavelets part, local features can be extracted at multiple scales and orientations to form Gabor-feature based image, which in turn improves the recognition rate. Besides, in the presence of occluded face image, the scale of Gabor-feature based global dictionary can be compressed accordingly because redundancies exist in Gabor-feature based occlusion dictionary. For ELM-AE part, the dimension of Gabor-feature based global dictionary can be compressed because high-dimensional face images can be rapidly represented by low-dimensional feature. By introducing L1/2 regularization, our approach can produce sparser and more robust representation compared to regularized Sparse Representation based Classification (SRC), which also contributes to the decrease of the computational cost in sparse representation. In comparison with related work such as SRC and Gabor-feature based SRC (GSRC), experimental results on a variety of face databases demonstrate the great advantage of our method for computational cost. Moreover, we also achieve approximate or even better recognition rate.