OpenRaiser/Intern-Atlas huggingface dataset:
Cross-Layer Control for Worse Case Delay Guarantees in Heterogeneous Powered Wireless Sensor Network via Lyapunov Optimization
Venue: arXiv cs.NI 2014
Year: 2014

The delay guarantee is a challenge in wireless sensor networks (WSNs), where energy constraints must be considered. The coexistence of renewable energy and electricity grid is expected as a promising energy supply manner for WSNs to remain function for a potentially infinite lifetime. In this paper, we address cross-layer control to guarantee worse case delay for Heterogeneous Powered (HP) WSNs. We design a novel virtual delay queue structure, and apply the Lyapunov optimization technique to develop cross-layer control algorithm only requiring knowledge of the instantaneous system state, which provides efficient throughput-utility, and guarantees bounded worst-case delay. We analyze the performance of the proposed algorithm and verify the theoretic claims through the simulation results. Compared to the existing work, the algorithm presented in this paper achieves much higher optimal objective value with ultralow data drop due to the proposed novel virtual queue structure.
Phase-Optimized K-SVD for Signal Extraction from Underdetermined Multichannel Sparse Mixtures
Venue: arXiv cs.SD 2014
Year: 2014

We propose a novel sparse representation for heavily underdetermined multichannel sound mixtures, i.e., with much more sources than microphones. The proposed approach operates in the complex Fourier domain, thus preserving spatial characteristics carried by phase differences. We derive a generalization of K-SVD which jointly estimates a dictionary capturing both spectral and spatial features, a sparse activation matrix, and all instantaneous source phases from a set of signal examples. The dictionary can then be used to extract the learned signal from a new input mixture. The method is applied to the challenging problem of ego-noise reduction for robot audition. We demonstrate its superiority relative to conventional dictionary-based techniques using recordings made in a real room.
Realizing RCC8 networks using convex regions
Venue: arXiv cs.AI 2014
Year: 2014

RCC8 is a popular fragment of the region connection calculus, in which qualitative spatial relations between regions, such as adjacency, overlap and parthood, can be expressed. While RCC8 is essentially dimensionless, most current applications are confined to reasoning about two-dimensional or three-dimensional physical space. In this paper, however, we are mainly interested in conceptual spaces, which typically are high-dimensional Euclidean spaces in which the meaning of natural language concepts can be represented using convex regions. The aim of this paper is to analyze how the restriction to convex regions constrains the realizability of networks of RCC8 relations. First, we identify all ways in which the set of RCC8 base relations can be restricted to guarantee that consistent networks can be convexly realized in respectively 1D, 2D, 3D, and 4D. Most surprisingly, we find that if the relation 'partially overlaps' is disallowed, all consistent atomic RCC8 networks can be convexly realized in 4D. If instead refinements of the relation 'part of' are disallowed, all consistent atomic RCC8 relations can be convexly realized in 3D. We furthermore show, among others, that any consistent RCC8 network with 2n+1 variables can be realized using convex regions in the n-dimensional Euclidean space.
Computational Beauty: Aesthetic Judgment at the Intersection of Art and Science
Venue: arXiv cs.CV 2014
Year: 2014

In part one of the Critique of Judgment, Immanuel Kant wrote that "the judgment of taste...is not a cognitive judgment, and so not logical, but is aesthetic."\cite{Kant} While the condition of aesthetic discernment has long been the subject of philosophical discourse, the role of the arbiters of that judgment has more often been assumed than questioned. The art historian, critic, connoisseur, and curator have long held the esteemed position of the aesthetic judge, their training, instinct, and eye part of the inimitable subjective processes that Kant described as occurring upon artistic evaluation. Although the concept of intangible knowledge in regard to aesthetic theory has been much explored, little discussion has arisen in response to the development of new types of artificial intelligence as a challenge to the seemingly ineffable abilities of the human observer. This paper examines the developments in the field of computer vision analysis of paintings from canonical movements with the history of Western art and the reaction of art historians to the application of this technology in the field. Through an investigation of the ethical consequences of this innovative technology, the unquestioned authority of the art expert is challenged and the subjective nature of aesthetic judgment is brought to philosophical scrutiny once again.
Unbeatable Consensus
Venue: arXiv cs.DC 2014
Year: 2014

The unbeatability of a consensus protocol, introduced by Halpern, Moses and Waarts in 2001, is a stronger notion of optimality than the accepted notion of early stopping protocols. Using a novel knowledge-based analysis, this paper derives the first practical unbeatable consensus protocols in the literature, for the standard synchronous message-passing model with crash failures. These protocols strictly dominate the best known protocols for uniform and for non-uniform consensus, in some case beating them by a large margin. The analysis provides a new understanding of the logical structure of consensus, and of the distinction between uniform and nonuniform consensus. Finally, the first (early stopping and) unbeatable protocol that treats decision values "fairly" is presented. All of these protocols have very concise descriptions, and are shown to be efficiently implementable.
Novel energy detection using uniform noise distribution
Venue: arXiv cs.IT 2014
Year: 2014

Energy detection is widely used in cognitive radio due to its low complexity. One fundamental challenge is that its performance degrades in the presence of noise uncertainty, which inevitably occurs in practical implementations. In this work, three novel detectors based on uniformly distributed noise uncertainty as the worst-case scenario are proposed. Numerical results show that the new detectors outperform the conventional energy detector with considerable performance gains.
Algorithm engineering for a quantum annealing platform
Venue: arXiv cs.DS 2014
Year: 2014

Recent advances bring within reach the viability of solving combinatorial problems using a quantum annealing algorithm implemented on a purpose-built platform that exploits quantum properties. However, the question of how to tune the algorithm for most effective use in this framework is not well understood. In this paper we describe some operational parameters that drive performance, discuss approaches for mitigating sources of error, and present experimental results from a D-Wave Two quantum annealing processor.
Second-Order Coding Rates for Conditional Rate-Distortion
Venue: arXiv cs.IT 2014
Year: 2014

This paper characterizes the second-order coding rates for lossy source coding with side information available at both the encoder and the decoder. We first provide non-asymptotic bounds for this problem and then specialize the non-asymptotic bounds for three different scenarios: discrete memoryless sources, Gaussian sources, and Markov sources. We obtain the second-order coding rates for these settings. It is interesting to observe that the second-order coding rate for Gaussian source coding with Gaussian side information available at both the encoder and the decoder is the same as that for Gaussian source coding without side information. Furthermore, regardless of the variance of the side information, the dispersion is $1/2$ nats squared per source symbol.
A note on a sports league scheduling problem
Venue: arXiv cs.DS 2014
Year: 2014

Sports league scheduling is a difficult task in the general case. In this short note, we report two improvements to an existing enumerative search algorithm for a NP-hard sports league scheduling problem known as "prob026" in CSPLib. These improvements are based on additional rules to constraint and accelerate the enumeration process. The proposed approach is able to find a solution (schedule) for all prob026 instances for a number T of teams ranging from 12 to 70, including several T values for which a solution is reported for the first time.
Area Versus Speed Trade-off Analysis of a WiMAX Deinterleaver Circuit Design
Venue: arXiv cs.OH 2014
Year: 2014

Trade-off is one of the main design parameters in the field of electronic circuit design. Whereas smaller electronics devices which use less hardware due to techniques like hardware multiplexing or due to smaller devices created due to techniques developed by nanotechnology and MEMS, are more appealing, a trade-off between area, power and speed is inevitable. This paper analyses the trade-off in the design of WiMAX deinterleaver. The main aim is to reduce the hardware utilization in a deinterleaver but speed and power consumption are important parameters which cannot be overlooked.
Q-learning for Optimal Control of Continuous-time Systems
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, two Q-learning (QL) methods are proposed and their convergence theories are established for addressing the model-free optimal control problem of general nonlinear continuous-time systems. By introducing the Q-function for continuous-time systems, policy iteration based QL (PIQL) and value iteration based QL (VIQL) algorithms are proposed for learning the optimal control policy from real system data rather than using mathematical system model. It is proved that both PIQL and VIQL methods generate a nonincreasing Q-function sequence, which converges to the optimal Q-function. For implementation of the QL algorithms, the method of weighted residuals is applied to derived the parameters update rule. The developed PIQL and VIQL algorithms are essentially off-policy reinforcement learning approachs, where the system data can be collected arbitrary and thus the exploration ability is increased. With the data collected from the real system, the QL methods learn the optimal control policy offline, and then the convergent control policy will be employed to real system. The effectiveness of the developed QL algorithms are verified through computer simulation.
Whole counting vs. whole-normalized counting: A country level comparative study of internationally collaborated papers on Tribology
Venue: arXiv cs.DL 2014
Year: 2014

The purpose of this study is to compare the changing behavior of two counting methods (whole counting and whole-normalized counting) and inflation rate at country level research productivity and impact. For this, publication data on tribology research published between 1998 and 2012 from SCOPUS has been used. Only internationally collaborated papers are considered for comparison between two counting methods. The result of correlation tests shows that there is highly correlation in all the four indicators between the two counting methods. However, the result of t-test shows that there is significant difference in the three indicators (paper count, citation count and h-index) between the two counting methods. This study concludes that whole-normalized counting (fractional) is the better choice for publication and citations counting at the country level assessment.
A mathematical design and evaluation of Bernstein-Bezier curves' shape features using the laws of technical aesthetics
Venue: arXiv cs.GR 2014
Year: 2014

We present some notes on the definition of mathematical design as well as on the methods of mathematical modeling which are used in the process of the artistic design of the environment and its components. For the first time in the field of geometric modeling, we perform an aesthetic analysis of planar Bernstein-Bezier curves from the standpoint of the laws of technical aesthetics. The shape features of the curve segments' geometry were evaluated using the following criteria: conciseness-integrity, expressiveness, proportional consistency, compositional balance, structural organization, imagery, rationality, dynamism, scale, flexibility and harmony. In the non-Russian literature, Bernstein-Bezier curves using a monotonic curvature function (i.e., a class A Bezier curve) are considered to be fair (i.e., beautiful) curves, but their aesthetic analysis has never been performed. The aesthetic analysis performed by the authors of this work means that this is no longer the case. To confirm the conclusions of the authors' research, a survey of the "aesthetic appropriateness" of certain Bernstein-Bezier curve segments was conducted among 240 children, aged 14-17. The results of this survey have shown themselves to be in full accordance with the authors' results.
Tree-Structure Bayesian Compressive Sensing for Video
Venue: arXiv cs.CV 2014
Year: 2014

A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system. By exploiting the three dimension (3D) tree structure of the wavelet and Discrete Cosine Transformation (DCT) coefficients, a Bayesian compressive sensing inversion algorithm is derived to reconstruct (up to 22) color video frames from a single monochromatic compressive measurement. Both simulated and real datasets are adopted to verify the performance of the proposed algorithm.
Content and Network Dynamics Behind Egyptian Political Polarization on Twitter
Venue: arXiv cs.SI 2014
Year: 2014

There is little doubt about whether social networks play a role in modern protests. This agreement has triggered an entire research avenue, in which social structure and content analysis have been central --but are typically exploited separately. Here, we combine these two approaches to shed light on the opinion evolution dynamics in Egypt during the summer of 2013 along two axes (Islamist/Secularist, pro/anti-military intervention). We intend to find traces of opinion changes in Egypt's population, paralleling those in the international community --which oscillated from sympathetic to condemnatory as civil clashes grew. We find little evidence of people "switching" sides, along with clear changes in volume in both pro- and anti-military camps. Our work contributes new insights into the dynamics of large protest movements, specially in the aftermath of the main events --rather unattended previously. It questions the standard narrative concerning a simplistic mapping between Secularist/pro-military and Islamist/anti-military. Finally, our conclusions provide empirical validation to sociological models regarding the behavior of individuals in conflictive contexts.
Secure Erasure Codes With Partial Decodability
Venue: arXiv cs.IT 2014
Year: 2014

The MDS property (aka the $k$-out-of-$n$ property) requires that if a file is split into several symbols and subsequently encoded into $n$ coded symbols, each being stored in one storage node of a distributed storage system (DSS), then an user can recover the file by accessing any $k$ nodes. We study the so-called $p$-decodable $μ$-secure erasure coding scheme $(1 \leq p \leq k - μ, 0 \leq μ< k, p | (k-μ))$, which satisfies the MDS property and the following additional properties: (P1) strongly secure up to a threshold: an adversary which eavesdrops at most $μ$ storage nodes gains no information (in Shannon's sense) about the stored file, (P2) partially decodable: a legitimate user can recover a subset of $p$ file symbols by accessing some $μ+ p$ storage nodes. The scheme is perfectly $p$-decodable $μ$-secure if it satisfies the following additional property: (P3) weakly secure up to a threshold: an adversary which eavesdrops more than $μ$ but less than $μ+p$ storage nodes cannot reconstruct any part of the file. Most of the related work in the literature only focused on the case $p = k - μ$. In other words, no partial decodability is provided: an user cannot retrieve any part of the file by accessing less than $k$ nodes. We provide an explicit construction of $p$-decodable $μ$-secure coding schemes over small fields for all $μ$ and $p$. That construction also produces perfectly $p$-decodable $μ$-secure schemes over small fields when $p = 1$ (for every $μ$), and when $μ= 0, 1$ (for every $p$). We establish that perfect schemes exist over \emph{sufficiently large} fields for almost all $μ$ and $p$.
Philosophy of science viewed through the lense of "References Publication Years spectrosopy" (RPYS)
Venue: arXiv cs.DL 2014
Year: 2014

We examine the sub-field of philosophy of science using a new method developed in information science, Referenced Publication Years Spectroscopy (RPYS). RPYS allows us to identify peak years in citations in a field, which promises to help scholars identify the key contributions to a field, and revolutionary discoveries in a field. We discovered that philosophy of science, a sub-field in the humanities, differs significantly from other fields examined with this method. Books play a more important role in philosophy of science than in the sciences. Further, Einstein's famous 1905 papers created a citation peak in the philosophy of science literature. But rather than being a contribution to the philosophy of science, their importance lies in the fact that they are revolutionary contributions to physics with important implications for philosophy of science.
Tag Relevance Fusion for Social Image Retrieval
Venue: arXiv cs.IR 2014
Year: 2014

Due to the subjective nature of social tagging, measuring the relevance of social tags with respect to the visual content is crucial for retrieving the increasing amounts of social-networked images. Witnessing the limit of a single measurement of tag relevance, we introduce in this paper tag relevance fusion as an extension to methods for tag relevance estimation. We present a systematic study, covering tag relevance fusion in early and late stages, and in supervised and unsupervised settings. Experiments on a large present-day benchmark set show that tag relevance fusion leads to better image retrieval. Moreover, unsupervised tag relevance fusion is found to be practically as effective as supervised tag relevance fusion, but without the need of any training efforts. This finding suggests the potential of tag relevance fusion for real-world deployment.
Understanding News Geography and Major Determinants of Global News Coverage of Disasters
Venue: arXiv cs.CY 2014
Year: 2014

In this work, we reveal the structure of global news coverage of disasters and its determinants by using a large-scale news coverage dataset collected by the GDELT (Global Data on Events, Location, and Tone) project that monitors news media in over 100 languages from the whole world. Significant variables in our hierarchical (mixed-effect) regression model, such as the number of population, the political stability, the damage, and more, are well aligned with a series of previous research. Yet, strong regionalism we found in news geography highlights the necessity of the comprehensive dataset for the study of global news coverage.
What is known about the Value 1 Problem for Probabilistic Automata?
Venue: arXiv cs.FL 2014
Year: 2014

The value 1 problem is a decision problem for probabilistic automata over finite words: are there words accepted by the automaton with arbitrarily high probability? Although undecidable, this problem attracted a lot of attention over the last few years. The aim of this paper is to review and relate the results pertaining to the value 1 problem. In particular, several algorithms have been proposed to partially solve this problem. We show the relations between them, leading to the following conclusion: the Markov Monoid Algorithm is the most correct algorithm known to (partially) solve the value 1 problem.
Prioritized motion-force control of constrained fully-actuated robots: "Task Space Inverse Dynamics"
Venue: arXiv cs.RO 2014
Year: 2014

We present a new framework for prioritized multi-task motion-force control of fully-actuated robots. This work is established on a careful review and comparison of the state of the art. Some control frameworks are not optimal, that is they do not find the optimal solution for the secondary tasks. Other frameworks are optimal, but they tackle the control problem at kinematic level, hence they neglect the robot dynamics and they do not allow for force control. Still other frameworks are optimal and consider force control, but they are computationally less efficient than ours. Our final claim is that, for fully-actuated robots, computing the operational-space inverse dynamics is equivalent to computing the inverse kinematics (at acceleration level) and then the joint-space inverse dynamics. Thanks to this fact, our control framework can efficiently compute the optimal solution by decoupling kinematics and dynamics of the robot. We take into account: motion and force control, soft and rigid contacts, free and constrained robots. Tests in simulation validate our control framework, comparing it with other state-of-the-art equivalent frameworks and showing remarkable improvements in optimality and efficiency.
Efficient Image Categorization with Sparse Fisher Vector
Venue: arXiv cs.CV 2014
Year: 2014

In object recognition, Fisher vector (FV) representation is one of the state-of-art image representations ways at the expense of dense, high dimensional features and increased computation time. A simplification of FV is attractive, so we propose Sparse Fisher vector (SFV). By incorporating locality strategy, we can accelerate the Fisher coding step in image categorization which is implemented from a collective of local descriptors. Combining with pooling step, we explore the relationship between coding step and pooling step to give a theoretical explanation about SFV. Experiments on benchmark datasets have shown that SFV leads to a speedup of several-fold of magnitude compares with FV, while maintaining the categorization performance. In addition, we demonstrate how SFV preserves the consistence in representation of similar local features.
Privacy4ICTD in India: Exploring Perceptions, Attitudes and Awareness about ICT Use
Venue: arXiv cs.CY 2014
Year: 2014

Several ICT studies give anecdotal evidences showing privacy to be an area of concern that can influence adoption of technology in the developing world. However, in-depth understanding of end users' privacy attitudes and awareness is largely unexplored in developing countries such as India. We conducted a survey with 10,427 Indian citizens to bring forth various insights on privacy expectations and perceptions of end users. Our study explores end-users' privacy expectations on three ICT platforms - mobile phones, OSN (Online Social Network), and government projects. Our results, though preliminary, show that users disproportionately consider financial details as personal information in comparison to medical records. Users heavily use mobile phones to store personal details and show high trust in mobile service providers for protecting the private data. However, users show concerns that mobile service provider may allow improper access of their personal information to third parties and government. We also find that female participants in the study were marginally more conscious of their privacy than males. To the best of our knowledge, this work presents the largest privacy study which benchmarks privacy perceptions among Indian citizens. Understanding users' privacy perceptions can help improve technology adoption and develop policies and laws for improving technology experience and enabling development for a better life in India.