OpenRaiser/Intern-Atlas huggingface dataset:
Transmit Power Minimization for Wireless Networks with Energy Harvesting Relays
Venue: arXiv cs.IT 2016
Year: 2016

Energy harvesting (EH) has recently emerged as a key technology for green communications as it can power wireless networks with renewable energy sources. However, directly replacing the conventional non-EH transmitters by EH nodes will be a challenge. In this paper, we propose to deploy extra EH nodes as relays over an existing non-EH network. Specifically, the considered non-EH network consists of multiple source-destination (S-D) pairs. The deployed EH relays will take turns to assist each S-D pair, and energy diversity can be achieved to combat the low EH rate of each EH relay. To make the best of these EH relays, with the source transmit power minimization as the design objective, we formulate a joint power assignment and relay selection problem, which, however, is NP-hard. We thus propose a general framework to develop efficient sub-optimal algorithms, which is mainly based on a sufficient condition for the feasibility of the optimization problem. This condition yields useful design insights and also reveals an energy hardening effect, which provides the possibility to exempt the requirement of non-causal EH information. Simulation results will show that the proposed cooperation strategy can achieve near-optimal performance and provide significant power savings. Compared to the greedy cooperation method that only optimizes the performance of the current transmission block, the proposed strategy can achieve the same performance with much fewer relays, and the performance gap increases with the number of S-D pairs.
Face-space Action Recognition by Face-Object Interactions
Venue: arXiv cs.CV 2016
Year: 2016

Action recognition in still images has seen major improvement in recent years due to advances in human pose estimation, object recognition and stronger feature representations. However, there are still many cases in which performance remains far from that of humans. In this paper, we approach the problem by learning explicitly, and then integrating three components of transitive actions: (1) the human body part relevant to the action (2) the object being acted upon and (3) the specific form of interaction between the person and the object. The process uses class-specific features and relations not used in the past for action recognition and which use inherently two cycles in the process unlike most standard approaches. We focus on face-related actions (FRA), a subset of actions that includes several currently challenging categories. We present an average relative improvement of 52% over state-of-the art. We also make a new benchmark publicly available.
A Comparative Study of Object Trackers for Infrared Flying Bird Tracking
Venue: arXiv cs.CV 2016
Year: 2016

Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation. Computer vision based technology has been proposed to automatically detect birds, determine bird flying trajectories, and predict aircraft takeoff delays. However, the characteristics of bird flight using imagery and the performance of existing methods applied to flying bird task are not well known. Therefore, we perform infrared flying bird tracking experiments using 12 state-of-the-art algorithms on a real BIRDSITE-IR dataset to obtain useful clues and recommend feature analysis. We also develop a Struck-scale method to demonstrate the effectiveness of multiple scale sampling adaption in handling the object of flying bird with varying shape and scale. The general analysis can be used to develop specialized bird tracking methods for airport safety, wildness and urban bird population studies.
Lossless Intra Coding in HEVC with 3-tap Filters
Venue: arXiv cs.MM 2016
Year: 2016

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for prediction, based on the angular projection idea borrowed from block-based intra prediction in lossy coding. This paper explores a method which uses three neighboring pixels for prediction according to a two-dimensional correlation model, and the used neighbor pixels and prediction weights change depending on intra mode. To find the best prediction weights for each intra mode, a two-stage offline optimization algorithm is used and a number of implementation aspects are discussed to simplify the proposed prediction method. The proposed method is implemented in the HEVC reference software and experimental results show that the explored 3-tap filtering method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC. The proposed method also decreases average decoding time by 12.7% while it increases average encoding time by 9.7%
Dynamic Information Retrieval: Theoretical Framework and Application
Venue: arXiv cs.IR 2016
Year: 2016

Theoretical frameworks like the Probability Ranking Principle and its more recent Interactive Information Retrieval variant have guided the development of ranking and retrieval algorithms for decades, yet they are not capable of helping us model problems in Dynamic Information Retrieval which exhibit the following three properties; an observable user signal, retrieval over multiple stages and an overall search intent. In this paper a new theoretical framework for retrieval in these scenarios is proposed. We derive a general dynamic utility function for optimizing over these types of tasks, that takes into account the utility of each stage and the probability of observing user feedback. We apply our framework to experiments over TREC data in the dynamic multi page search scenario as a practical demonstration of its effectiveness and to frame the discussion of its use, its limitations and to compare it against the existing frameworks.
Proactive Message Passing on Memory Factor Networks
Venue: arXiv cs.AI 2016
Year: 2016

We introduce a new type of graphical model that we call a "memory factor network" (MFN). We show how to use MFNs to model the structure inherent in many types of data sets. We also introduce an associated message-passing style algorithm called "proactive message passing"' (PMP) that performs inference on MFNs. PMP comes with convergence guarantees and is efficient in comparison to competing algorithms such as variants of belief propagation. We specialize MFNs and PMP to a number of distinct types of data (discrete, continuous, labelled) and inference problems (interpolation, hypothesis testing), provide examples, and discuss approaches for efficient implementation.
A Class of Low-Interference N-Continuous OFDM Schemes
Venue: arXiv cs.IT 2016
Year: 2016

N-continuous orthogonal frequency division multiplexing (NC-OFDM) was demonstrated to provide significant sidelobe suppression for baseband OFDM signals. However, it will introduce severe interference to the transmit signals. Hence in this letter, we specifically design a class of low-interference NC-OFDM schemes for alleviating the introduced interference. Meanwhile, we also obtain an asymptotic spectrum analysis by a closed-form expression. It is shown that the proposed scheme is capable of reducing the interference to a negligible level, and hence to save the high complexity of signal recovery at the receiver, while maintaining similar sidelobe suppression performance compared to traditional NC-OFDM.
Crowdsourced, Actionable and Verifiable Contextual Informational Norms
Venue: arXiv cs.CY 2016
Year: 2016

There is often a fundamental mismatch between programmable privacy frameworks, on the one hand, and the ever shifting privacy expectations of computer system users, on the other hand. Based on the theory of contextual integrity (CI), our paper addresses this problem by proposing a privacy framework that translates users' privacy expectations (norms) into a set of actionable privacy rules that are rooted in the language of CI. These norms are then encoded using Datalog logic specification to develop an information system that is able to verify whether information flows are appropriate and the privacy of users thus preserved. A particular benefit of our framework is that it can automatically adapt as users' privacy expectations evolve over time. To evaluate our proposed framework, we conducted an extensive survey involving more than 450 participants and 1400 questions to derive a set of privacy norms in the educational context. Based on the crowdsourced responses, we demonstrate that our framework can derive a compact Datalog encoding of the privacy norms which can in principle be directly used for enforcing privacy of information flows within this context. In addition, our framework can automatically detect logical inconsistencies between individual users' privacy expectations and the derived privacy logic.
Constrained Multi-user Multi-server Max-Min Fair Queuing
Venue: arXiv cs.NI 2016
Year: 2016

In this paper, a multi-user multi-server queuing system is studied in which each user is constrained to get service from a subset of servers. In the studied system, rate allocation in the sense of max-min fairness results in multi-level fair rates. To achieve such fair rates, we propose $CM^4FQ$ algorithm. In this algorithm users are chosen for service on a packet by packet basis. The priority of each user $i$ to be chosen at time $t$ is determined based on a parameter known as service tag (representing the amount of work counted for user $i$ till time $t$). Hence, a free server will choose to serve an eligible user with the minimum service tag. Based on such simple selection criterion, $CM^4FQ$ aims at guaranteed fair throughput for each demanding user without explicit knowledge of each server service rate. We argue that $CM^4FQ$ can be applied in a variety of practical queuing systems specially in mobile cloud computing architecture.
Defeating the Ben-Zvi, Blackburn, and Tsaban Attack on the Algebraic Eraser
Venue: arXiv cs.CR 2016
Year: 2016

The Algebraic Eraser Diffie-Hellman (AEDH) protocol was introduced in 2005 and published in 2006 by Anshel-Anshel-Goldfeld-Lemieux as a protocol suitable for use on platforms with constrained computational resources, such as FPGAs, ASICs, and wireless sensors. It is a group-theoretic cryptographic protocol that allows two users to construct a shared secret via a Diffie-Hellman-type scheme over an insecure channel. Building on the refuted 2012 permutation-based attack of Kalka-Teichner-Tsaban, in 2015 Ben-Zvi-Blackburn-Tsaban (BBT) presented a heuristic attack that attempts to recover the AEDH shared secret. In their paper BBT reference the AEDH protocol as presented to ISO for certification (ISO 29167-20) by SecureRF. The ISO draft contains two profiles using the Algebraic Eraser. One profile is unaffected by this attack; the second profile is subject to their attack provided the attack runs in real time. This is not the case in most practical deployments. The BBT attack is simply a targeted attack that does not attempt to break the method, system parameters, or recover any private keys. Rather, its limited focus is to recover the shared secret in a single transaction. In addition, the BBT attack is based on several conjectures that are assumed to hold when parameters are chosen according to standard distributions, which can be mitigated, if not avoided. This paper shows how to choose special distributions so that these conjectures do not hold making the BBT attack ineffective for braid groups with sufficiently many strands. Further, the BBT attack assumes that certain data is available to an attacker, but there are realistic deployment scenarios where this is not the case, making the attack fail completely. In summary, the BBT attack is flawed (with respect to the SecureRF ISO draft) and, at a minimum, over-reaches as to its applicability.
Interpolation synthesis for quadratic polynomial inequalities and combination with EUF
Venue: arXiv cs.LO 2016
Year: 2016

An algorithm for generating interpolants for formulas which are conjunctions of quadratic polynomial inequalities (both strict and nonstrict) is proposed. The algorithm is based on a key observation that quadratic polynomial inequalities can be linearized if they are concave. A generalization of Motzkin's transposition theorem is proved, which is used to generate an interpolant between two mutually contradictory conjunctions of polynomial inequalities, using semi-definite programming in time complexity $\mathcal{O}(n^3+nm))$, where $n$ is the number of variables and $m$ is the number of inequalities. Using the framework proposed by \cite{SSLMCS2008} for combining interpolants for a combination of quantifier-free theories which have their own interpolation algorithms, a combination algorithm is given for the combined theory of concave quadratic polynomial inequalities and the equality theory over uninterpreted functions symbols (\textit{EUF}). The proposed approach is applicable to all existing abstract domains like \emph{octagon}, \emph{polyhedra}, \emph{ellipsoid} and so on, therefore it can be used to improve the scalability of existing verification techniques for programs and hybrid systems. In addition, we also discuss how to extend our approach to formulas beyond concave quadratic polynomials using Gröbner basis.
The Structure of Z_2[u]Z_2[u, v]-additive Codes
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we study the algebraic structure of Z_2[u]Z_2[u, v]-additive codes which are Z_2[u, v]-submodules where u^2 = v^2 = 0 and uv = vu. In particular, we determine a Gray map from Z_2[u]Z_2 [u, v] to Z_2^{2α+8\b{eta}} and study generator and parity check matrices for these codes. Further we study the structure of Z_2[u]Z_2[u, v]-additive cyclic codes and constacyclic codes.
Eye detection in digital images: challenges and solutions
Venue: arXiv cs.CV 2016
Year: 2016

Eye Detection has an important role in the field of biometric identification and known as one method of person's identification. In recent years, many efforts have been done which can detect eye automatically and with different image conditions. However, each method has its own drawbacks which can control some of these conditions. In this paper, different methods of eye detection will be categorized and explained. In each category, the advantages and disadvantages of each method will be presented.
Women Through the Glass Ceiling: Gender Asymmetries in Wikipedia
Venue: arXiv cs.SI 2016
Year: 2016

Contributing to the writing of history has never been as easy as it is today thanks to Wikipedia, a community-created encyclopedia that aims to document the world's knowledge from a neutral point of view. Though everyone can participate it is well known that the editor community has a narrow diversity, with a majority of white male editors. While this participatory \emph{gender gap} has been studied extensively in the literature, this work sets out to \emph{assess potential gender inequalities in Wikipedia articles} along different dimensions: notability, topical focus, linguistic bias, structural properties, and meta-data presentation. We find that (i) women in Wikipedia are more notable than men, which we interpret as the outcome of a subtle glass ceiling effect; (ii) family-, gender-, and relationship-related topics are more present in biographies about women; (iii) linguistic bias manifests in Wikipedia since abstract terms tend to be used to describe positive aspects in the biographies of men and negative aspects in the biographies of women; and (iv) there are structural differences in terms of meta-data and hyperlinks, which have consequences for information-seeking activities. While some differences are expected, due to historical and social contexts, other differences are attributable to Wikipedia editors. The implications of such differences are discussed having Wikipedia contribution policies in mind. We hope that the present work will contribute to increased awareness about, first, gender issues in the content of Wikipedia, and second, the different levels on which gender biases can manifest on the Web.
Bounds on the Lambert function and their application to the outage analysis of user cooperation
Venue: arXiv cs.IT 2016
Year: 2016

Problems formulated in terms of logarithmic or exponential equations often use the Lambert $W$ function in their solutions. Expansions, approximations and bounds on $W$ have been derived in an effort to gain a better understanding of the relationship between equation parameters. In this paper, we focus on one of the branches of $W$, denoted as $W_{-1}$, we derive tractable upper and lower bounds and we illustrate their usefulness in identifying conditions under which user cooperation can yield a lower outage probability than non-cooperative transmission.
PupilNet: Convolutional Neural Networks for Robust Pupil Detection
Venue: arXiv cs.CV 2016
Year: 2016

Real-time, accurate, and robust pupil detection is an essential prerequisite for pervasive video-based eye-tracking. However, automated pupil detection in real-world scenarios has proven to be an intricate challenge due to fast illumination changes, pupil occlusion, non centered and off-axis eye recording, and physiological eye characteristics. In this paper, we propose and evaluate a method based on a novel dual convolutional neural network pipeline. In its first stage the pipeline performs coarse pupil position identification using a convolutional neural network and subregions from a downscaled input image to decrease computational costs. Using subregions derived from a small window around the initial pupil position estimate, the second pipeline stage employs another convolutional neural network to refine this position, resulting in an increased pupil detection rate up to 25% in comparison with the best performing state-of-the-art algorithm. Annotated data sets can be made available upon request.
H2 Optimal Coordination of Homogeneous Agents Subject to Limited Information Exchange
Venue: arXiv cs.SY 2016
Year: 2016

Controllers with a diagonal-plus-low-rank structure constitute a scalable class of controllers for multi-agent systems. Previous research has shown that diagonal-plus-low-rank control laws appear as the optimal solution to a class of multi-agent H2 coordination problems, which arise in the control of wind farms. In this paper we show that this result extends to the case where the information exchange between agents is subject to limitations. We also show that the computational effort required to obtain the optimal controller is independent of the number of agents and provide analytical expressions that quantify the usefulness of information exchange.
Simplifying Wireless Social Caching
Venue: arXiv cs.IT 2016
Year: 2016

Social groups give the opportunity for a new form of caching. In this paper, we investigate how a social group of users can jointly optimize bandwidth usage, by each caching parts of the data demand, and then opportunistically share these parts among themselves upon meeting. We formulate this problem as a Linear Program (LP) with exponential complexity. Based on the optimal solution, we propose a simple heuristic inspired by the bipartite set-cover problem that operates in polynomial time. Furthermore, we prove a worst case gap between the heuristic and the LP solutions. Finally, we assess the performance of our algorithm using real-world mobility traces from the MIT Reality Mining project dataset and two mobility traces that were synthesized using the SWIM model. Our heuristic performs closely to the optimal in most cases, showing a better performance with respect to alternative solutions.
Medium Access Control for Dynamic Spectrum Sharing in Cognitive Radio Networks
Venue: arXiv cs.NI 2016
Year: 2016

The proliferation of wireless services and applications over the past decade has led to the rapidly increasing demand in wireless spectrum. Hence, we have been facing a critical spectrum shortage problem even though several measurements have indicated that most licensed radio spectrum is very underutilized. These facts have motivated the development of dynamic spectrum access (DSA) and cognitive radio techniques to enhance the efficiency and flexibility of spectrum utilization. In this dissertation, we investigate design, analysis, and optimization issues for joint spectrum sensing and cognitive medium access control (CMAC) protocol engineering for cognitive radio networks (CRNs). The joint spectrum sensing and CMAC design is considered under the interweave spectrum sharing paradigm and different communications settings. Our research has resulted in four major research contributions, namely, the CMAC protocol design with parallel spectrum sensing, the CMAC protocol with sequential sensing, the CMAC protocol with cooperative sensing and the asynchronous Full-Duplex cognitive MAC. We develop various analytical models for throughput performance analysis of our proposed CMAC protocol designs. Based on these analytical models, we develop different efficient algorithms to configure the CMAC protocol including channel allocation, sensing time, transmit power, contention window to maximize the total throughput of the secondary network. Furthermore, extensive numerical results are presented to gain further insights and to evaluate the performance of our CMAC protocol designs. Both the numerical and simulation results confirm that our proposed CMAC protocols can achieve efficient spectrum utilization and significant performance gains compared to existing and unoptimized designs.
Value Function Approximation for Direct Control of Switched Power Converters
Venue: arXiv cs.SY 2016
Year: 2016

We consider the problem of controlling switched-mode power converters using model predictive control. Model predictive control requires solving optimization problems in real time, limiting its application to systems with small numbers of switches and a short horizon. We propose a technique for using off-line computation to approximate the model predictive controller. This is done by dividing the planning horizon into two segments, and using a quadratic function to approximate the optimal cost over the second segment. The approximate model predictive algorithm minimizes the true cost over the first segment, and the approximate cost over the second segment, allowing the user to adjust the computational requirements by changing the length of the first segment. We conclude with two simulated examples.
The DARPA Twitter Bot Challenge
Venue: arXiv cs.SI 2016
Year: 2016

A number of organizations ranging from terrorist groups such as ISIS to politicians and nation states reportedly conduct explicit campaigns to influence opinion on social media, posing a risk to democratic processes. There is thus a growing need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussion on sites like Twitter and Facebook - before they get too influential. Spurred by such events, DARPA held a 4-week competition in February/March 2015 in which multiple teams supported by the DARPA Social Media in Strategic Communications program competed to identify a set of previously identified "influence bots" serving as ground truth on a specific topic within Twitter. Past work regarding influence bots often has difficulty supporting claims about accuracy, since there is limited ground truth (though some exceptions do exist [3,7]). However, with the exception of [3], no past work has looked specifically at identifying influence bots on a specific topic. This paper describes the DARPA Challenge and describes the methods used by the three top-ranked teams.