OpenRaiser/Intern-Atlas huggingface dataset:
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network
Venue: arXiv cs.LG 2013
Year: 2013

Effectively modelling hidden structures in a network is very practical but theoretically challenging. Existing relational models only involve very limited information, namely the binary directional link data, embedded in a network to learn hidden networking structures. There is other rich and meaningful information (e.g., various attributes of entities and more granular information than binary elements such as "like" or "dislike") missed, which play a critical role in forming and understanding relations in a network. In this work, we propose an informative relational model (InfRM) framework to adequately involve rich information and its granularity in a network, including metadata information about each entity and various forms of link data. Firstly, an effective metadata information incorporation method is employed on the prior information from relational models MMSB and LFRM. This is to encourage the entities with similar metadata information to have similar hidden structures. Secondly, we propose various solutions to cater for alternative forms of link data. Substantial efforts have been made towards modelling appropriateness and efficiency, for example, using conjugate priors. We evaluate our framework and its inference algorithms in different datasets, which shows the generality and effectiveness of our models in capturing implicit structures in networks.
Congestion Control using FEC for Conversational Multimedia Communication
Venue: arXiv cs.NI 2013
Year: 2013

In this paper, we propose a new rate control algorithm for conversational multimedia flows. In our approach, along with Real-time Transport Protocol (RTP) media packets, we propose sending redundant packets to probe for available bandwidth. These redundant packets are Forward Error Correction (FEC) encoded RTP packets. A straightforward interpretation is that if no losses occur, the sender can increase the sending rate to include the FEC bit rate, and in the case of losses due to congestion the redundant packets help in recovering the lost packets. We also show that by varying the FEC bit rate, the sender is able to conservatively or aggressively probe for available bandwidth. We evaluate our FEC-based Rate Adaptation (FBRA) algorithm in a network simulator and in the real-world and compare it to other congestion control algorithms.
Ethical Considerations when Employing Fake Identities in OSN for Research
Venue: arXiv cs.CY 2013
Year: 2013

Online Social Networks (OSNs) have rapidly become a prominent and widely used service, offering a wealth of personal and sensitive information with significant security and privacy implications. Hence, OSNs are also an important - and popular - subject for research. To perform research based on real-life evidence, however, researchers may need to access OSN data, such as texts and files uploaded by users and connections among users. This raises significant ethical problems. Currently, there are no clear ethical guidelines, and researchers may end up (unintentionally) performing ethically questionable research, sometimes even when more ethical research alternatives exist. For example, several studies have employed `fake identities` to collect data from OSNs, but fake identities may be used for attacks and are considered a security issue. Is it legitimate to use fake identities for studying OSNs or for collecting OSN data for research? We present a taxonomy of the ethical challenges facing researchers of OSNs and compare different approaches. We demonstrate how ethical considerations have been taken into account in previous studies that used fake identities. In addition, several possible approaches are offered to reduce or avoid ethical misconducts. We hope this work will stimulate the development and use of ethical practices and methods in the research of online social networks.
Beyond AMT: An Analysis of Crowd Work Platforms
Venue: arXiv cs.CY 2013
Year: 2013

While Amazon's Mechanical Turk (AMT) helped launch the paid crowd work industry eight years ago, many new vendors now offer a range of alternative models. Despite this, little crowd work research has explored other platforms. Such near-exclusive focus risks letting AMT's particular vagaries and limitations overly shape our understanding of crowd work and the research questions and directions being pursued. To address this, we present a cross-platform content analysis of seven crowd work platforms. We begin by reviewing how AMT assumptions and limitations have influenced prior research. Next, we formulate key criteria for characterizing and differentiating crowd work platforms. Our analysis of platforms contrasts them with AMT, informing both methodology of use and directions for future research. Our cross-platform analysis represents the only such study by researchers for researchers, intended to further enrich the diversity of research on crowd work and accelerate progress.
General inner approximation of vector-valued functions
Venue: arXiv cs.NA 2013
Year: 2013

This paper addresses the problem of evaluating a subset of the range of a vector-valued function. It is based on a work by Gold- sztejn and Jaulin which provides methods based on interval analysis to address this problem when the dimension of the domain and co-domain of the function are equal. This paper extends this result to vector-valued functions with domain and co-domain of different dimensions. This ex- tension requires the knowledge of the rank of the Jacobian function on the whole domain. This leads to the sub-problem of extracting an in- terval sub-matrix of maximum rank from a given interval matrix. Three different techniques leading to approximate solutions of this extraction are proposed and compared.
Mobility Diversity in Mobile Wireless Networks
Venue: arXiv cs.NI 2013
Year: 2013

We introduce the novel concept of mobility diversity for mobile sensor or communication networks as the diversity introduced by transmitting data over different topologies of the network. We show how node mobility can provide diversity by changing the topology of the network. More specifically, we consider a mobile network of a sensor node and a number of sink nodes which are all moving randomly according to different Wiener process mobility models. Assuming that the network topology evolves with time and assuming that the connectivity of the sensor node to at least one sink node is needed for successful communication, we calculate three performance measures for this network, i) the expected number of time instants, where the sensor node is connected to at least one sink node, ii) the probability of outage, being the probability that no sink node is in the vicinity of the sensor node during the observation interval, and finally, iii) the maximum number of consequent failures in the communication. Our theoretical and numerical analysis show that increasing the mobility parameter of the sensor node increases the average number of successful transmissions, decreases the probability of outage, and reduces the maximum delay in the senor-sink communication.
On triangulating k-outerplanar graphs
Venue: arXiv cs.DM 2013
Year: 2013

A k-outerplanar graph is a graph that can be drawn in the plane without crossing such that after k-fold removal of the vertices on the outer-face there are no vertices left. In this paper, we study how to triangulate a k-outerplanar graph while keeping its outerplanarity small. Specifically, we show that not all k-outerplanar graphs can be triangulated so that the result is k-outerplanar, but they can be triangulated so that the result is (k+1)-outerplanar.
First Author Advantage: Citation Labeling in Research
Venue: arXiv cs.DL 2013
Year: 2013

Citations among research papers, and the networks they form, are the primary object of study in scientometrics. The act of making a citation reflects the citer's knowledge of the related literature, and of the work being cited. We aim to gain insight into this process by studying citation keys: user-chosen labels to identify a cited work. Our main observation is that the first listed author is disproportionately represented in such labels, implying a strong mental bias towards the first author.
The role of RGB-D benchmark datasets: an overview
Venue: arXiv cs.CV 2013
Year: 2013

The advent of the Microsoft Kinect three years ago stimulated not only the computer vision community for new algorithms and setups to tackle well-known problems in the community but also sparked the launch of several new benchmark datasets to which future algorithms can be compared 019 to. This review of the literature and industry developments concludes that the current RGB-D benchmark datasets can be useful to determine the accuracy of a variety of applications of a single or multiple RGB-D sensors.
Distributed Linear Convolutional Space-Time Coding for Two-Relay Full-Duplex Asynchronous Cooperative Networks
Venue: arXiv cs.IT 2013
Year: 2013

In this paper, a two-relay full-duplex asynchronous cooperative network with the amplify-and-forward (AF) protocol is considered. We propose two distributed space-time coding schemes for the cases with and without cross-talks, respectively. In the first case, each relay can receive the signal sent by the other through the cross-talk link. We first study the feasibility of cross-talk cancellation in this network and show that the cross-talk interference cannot be removed well. For this reason, we design space-time codes by utilizing the cross-talk signals instead of removing them. In the other case, the self-coding is realized individually through the loop channel at each relay node and the signals from the two relay nodes form a space-time code. The achievable cooperative diversity of both cases is investigated and the conditions to achieve full cooperative diversity are presented. Simulation results verify the theoretical analysis.
An Iterative Method Applied to Correct the Actual Compressor Performance to the Equivalent Performance under the Specified Reference Conditions
Venue: arXiv cs.SY 2013
Year: 2013

This paper proposes a correction method, which corrects the actual compressor performance in real operating conditions to the equivalent performance under specified reference condition. The purpose is to make fair comparisons between actual performance against design performance or reference maps under the same operating conditions. Then the abnormal operating conditions or early failure indications can be identified through condition monitoring, which helps to avoid mandatory shutdown and reduces maintenance costs. The corrections are based on an iterative scheme, which simultaneously correct the main performance parameters known as the polytropic head, the gas power, and the polytropic efficiency. The excellent performance of the method is demonstrated by performing the corrections over real industrial measurements.
Towards Internet of Things (IOTS):Integration of Wireless Sensor Network to Cloud Services for Data Collection and Sharing
Venue: arXiv cs.NI 2013
Year: 2013

Cloud computing provides great benefits for applications hosted on the Web that also have special computational and storage requirements. This paper proposes an extensible and flexible architecture for integrating Wireless Sensor Networks with the Cloud. We have used REST based Web services as an interoperable application layer that can be directly integrated into other application domains for remote monitoring such as e-health care services, smart homes, or even vehicular area networks (VAN). For proof of concept, we have implemented a REST based Web services on an IP based low power WSN test bed, which enables data access from anywhere. The alert feature has also been implemented to notify users via email or tweets for monitoring data when they exceed values and events of interest.
Development of Biofeedback Mechanisms in a Procedural Environment Using Biometric Sensors
Venue: arXiv cs.HC 2013
Year: 2013

Before the computer age, games were played in the physical world where players would have to interact with real objects and each other, triggering a series of emotions. Nowadays, the computer games have become one of the most popular forms of entertainment due to their high-level of attraction and accessibility. However, the game industry is always trying to find new ways of making games more interactive and exciting in order to attract new players, and one of the recent trends on the area of human-computer interaction is Biofeedback. The goal of this dissertation is to study different approaches on the use of indirect biofeedback within videogames, with the purpose of creating a better human-computer interaction, and provide a more appealing and immersive user experience. For this, we focused on the development of a framework capable of testing different indirect biofeedback models within a specified game, in order to assess the effect of each of these variations on the user experience. This framework is game independent, with the intention of being used on further studies.
A Comparative Study of the Signal-to-Noise Ratios of Different Representations for Symbolic Sequences
Venue: arXiv cs.DM 2013
Year: 2013

Based on the numerical representations by T basic vectors of a symbolic sequence consisting of T symbols, first, we prove mathematical that the total Fourier spectrum of the sequence is the square of the length of the sequence. In the meantime, we define the indicator sequences vector. Using the orthogonal or row orthogonal transformations of the indicator sequences vector, we construct some special numerical representations of the symbolic sequence and characterize the signal-to-noise ratios of the power spectrum of the numerical representations. After calculating the discrete Fourier transform of those special numerical representations, the signal-to-noise ratios of them can be figured out. Mathematical theorems prove that the signal-to-noise ratio of the Fourier spectrum of those special representations of the symbolic sequence is T/(T-1) times the signal-to-noise ratio of the representation by T base vectors. The results are applied in analyzing the properties of the DNA sequences or protein sequences in the frequency domain, if one uses the signal-to-noise ratios of special representations as the distinguishing criterion, the distinguishing results only depend upon the distribution of the symbols in the symbolic sequence and their mathematical constructions of representations, but do not relate to the chemical or biological meanings of the representations.
Speculative Staging for Interpreter Optimization
Venue: arXiv cs.PL 2013
Year: 2013

Interpreters have a bad reputation for having lower performance than just-in-time compilers. We present a new way of building high performance interpreters that is particularly effective for executing dynamically typed programming languages. The key idea is to combine speculative staging of optimized interpreter instructions with a novel technique of incrementally and iteratively concerting them at run-time. This paper introduces the concepts behind deriving optimized instructions from existing interpreter instructions---incrementally peeling off layers of complexity. When compiling the interpreter, these optimized derivatives will be compiled along with the original interpreter instructions. Therefore, our technique is portable by construction since it leverages the existing compiler's backend. At run-time we use instruction substitution from the interpreter's original and expensive instructions to optimized instruction derivatives to speed up execution. Our technique unites high performance with the simplicity and portability of interpreters---we report that our optimization makes the CPython interpreter up to more than four times faster, where our interpreter closes the gap between and sometimes even outperforms PyPy's just-in-time compiler.
Gain scaling for multirate filter banks
Venue: arXiv cs.IT 2013
Year: 2013

Eliminating two trivial degrees of freedom corresponding to the lowpass DC response and the highpass Nyquist response in a two-channel multirate filter bank seems simple enough. Nonetheless, the ISO/IEC JPEG 2000 image coding standard manages to make this mundane task look totally mysterious. We reveal the true meaning behind JPEG 2000's arcane specifications for filter bank normalization and point out how the seemingly trivial matter of gain scaling leads to highly nontrivial issues concerning uniqueness of lifting factorizations.
Dejavu: An Accurate Energy-Efficient Outdoor Localization System
Venue: arXiv cs.CY 2013
Year: 2013

We present Dejavu, a system that uses standard cell-phone sensors to provide accurate and energy-efficient outdoor localization suitable for car navigation. Our analysis shows that different road landmarks have a unique signature on cell-phone sensors; For example, going inside tunnels, moving over bumps, going up a bridge, and even potholes all affect the inertial sensors on the phone in a unique pattern. Dejavu employs a dead-reckoning localization approach and leverages these road landmarks, among other automatically discovered abundant virtual landmarks, to reset the accumulated error and achieve accurate localization. To maintain a low energy profile, Dejavu uses only energy-efficient sensors or sensors that are already running for other purposes. We present the design of Dejavu and how it leverages crowd-sourcing to automatically learn virtual landmarks and their locations. Our evaluation results from implementation on different android devices in both city and highway driving show that Dejavu can localize cell phones to within 8.4m median error in city roads and 16.6m on highways. Moreover, compared to GPS and other state-of-the-art systems, Dejavu can extend the battery lifetime by 347%, achieving even better localization results than GPS in the more challenging in-city driving conditions.
Topological Interference Management with Alternating Connectivity: The Wyner-Type Three User Interference Channel
Venue: arXiv cs.IT 2013
Year: 2013

Interference management in a three-user interference channel with alternating connectivity with only topological knowledge at the transmitters is considered. The network has a Wyner-type channel flavor, i.e., for each connectivity state the receivers observe at most one interference signal in addition to their desired signal. Degrees of freedom (DoF) upper bounds and lower bounds are derived. The lower bounds are obtained from a scheme based on joint encoding across the alternating states. Given a uniform distribution among the connectivity states, it is shown that the channel has 2+ 1/9 DoF. This provides an increase in the DoF as compared to encoding over each state separately, which achieves 2 DoF only.
Practical Verification of Decision-Making in Agent-Based Autonomous Systems
Venue: arXiv cs.LO 2013
Year: 2013

We present a verification methodology for analysing the decision-making component in agent-based hybrid systems. Traditionally hybrid automata have been used to both implement and verify such systems, but hybrid automata based modelling, programming and verification techniques scale poorly as the complexity of discrete decision-making increases making them unattractive in situations where complex logical reasoning is required. In the programming of complex systems it has, therefore, become common to separate out logical decision-making into a separate, discrete, component. However, verification techniques have failed to keep pace with this development. We are exploring agent-based logical components and have developed a model checking technique for such components which can then be composed with a separate analysis of the continuous part of the hybrid system. Among other things this allows program model checkers to be used to verify the actual implementation of the decision-making in hybrid autonomous systems.
Interference Alignment via Message-Passing
Venue: arXiv cs.IT 2013
Year: 2013

We introduce an iterative solution to the problem of interference alignment (IA) over MIMO channels based on a message-passing formulation. We propose a parameterization of the messages that enables the computation of IA precoders by a min-sum algorithm over continuous variable spaces -- under this parameterization, suitable approximations of the messages can be computed in closed-form. We show that the iterative leakage minimization algorithm of Cadambe et al. is a special case of our message-passing algorithm, obtained for a particular schedule. Finally, we show that the proposed algorithm compares favorably to iterative leakage minimization in terms of convergence speed, and discuss a distributed implementation.
Discrete Sparse Signals: Compressed Sensing by Combining OMP and the Sphere Decoder
Venue: arXiv cs.IT 2013
Year: 2013

We study the reconstruction of discrete-valued sparse signals from underdetermined systems of linear equations. On the one hand, classical compressed sensing (CS) is designed to deal with real-valued sparse signals. On the other hand, algorithms known from MIMO communications, especially the sphere decoder (SD), are capable to reconstruct discrete-valued non-sparse signals from well- or overdefined system of linear equations. Hence, a combination of both approaches is required. We discuss strategies to include the knowledge of the discrete nature of the signal in the reconstruction process. For brevity, the exposition is done for combining the orthogonal matching pursuit (OMP) with the SD; design guidelines are derived. It is shown that by suitably combining OMP and SD an efficient low-complexity scheme for the detection of discrete sparse signals is obtained.
Clustering Memes in Social Media
Venue: arXiv cs.SI 2013
Year: 2013

The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme, or unit of information that can spread from person to person through the social network. Once a meme is identified, supervised learning methods can be applied to classify different types of communication. The appropriate granularity of a meme, however, is hardly captured from existing entities such as tags and keywords. Here we present a framework for the novel task of detecting memes by clustering messages from large streams of social data. We evaluate various similarity measures that leverage content, metadata, network features, and their combinations. We also explore the idea of pre-clustering on the basis of existing entities. A systematic evaluation is carried out using a manually curated dataset as ground truth. Our analysis shows that pre-clustering and a combination of heterogeneous features yield the best trade-off between number of clusters and their quality, demonstrating that a simple combination based on pairwise maximization of similarity is as effective as a non-trivial optimization of parameters. Our approach is fully automatic, unsupervised, and scalable for real-time detection of memes in streaming data.
New Families of $p$-ary Sequences of Period $\frac{p^n-1}{2}$ With Low Maximum Correlation Magnitude
Venue: arXiv cs.IT 2013
Year: 2013

Let $p$ be an odd prime such that $p \equiv 3\;{\rm mod}\;4$ and $n$ be an odd integer. In this paper, two new families of $p$-ary sequences of period $N = \frac{p^n-1}{2}$ are constructed by two decimated $p$-ary m-sequences $m(2t)$ and $m(dt)$, where $d = 4$ and $d = (p^n + 1)/2=N+1$. The upper bound on the magnitude of correlation values of two sequences in the family is derived using Weil bound. Their upper bound is derived as $\frac{3}{\sqrt{2}} \sqrt{N+\frac{1}{2}}+\frac{1}{2}$ and the family size is 4N, which is four times the period of the sequence.