OpenRaiser/Intern-Atlas huggingface dataset:
A hierarchical MPC scheme for interconnected systems
Venue: arXiv cs.SY 2017
Year: 2017

This paper describes a hierarchical control scheme for interconnected systems. The higher layer of the control structure is designed with robust Model Predictive Control (MPC) based on a reduced order dynamic model of the overall system and is aimed at optimizing long-term performance, while at the lower layer local regulators acting at a higher frequency are designed for the full order models of the subsystems to refine the control action. A simulation experiment concerning the control of the temperature inside a building is reported to witness the potentialities of the proposed approach.
Wirelessly Powered Backscatter Communications: Waveform Design and SNR-Energy Tradeoff
Venue: arXiv cs.IT 2017
Year: 2017

This paper shows that wirelessly powered backscatter communications is subject to a fundamental tradeoff between the harvested energy at the tag and the reliability of the backscatter communication, measured in terms of SNR at the reader. Assuming the RF transmit signal is a multisine waveform adaptive to the channel state information, we derive a systematic approach to optimize the transmit waveform weights (amplitudes and phases) in order to enlarge as much as possible the SNRenergy region. Performance evaluations confirm the significant benefits of using multiple frequency components in the adaptive transmit multisine waveform to exploit the nonlinearity of the rectifier and a frequency diversity gain.
A Low-Complexity Adaptive Multisine Waveform Design for Wireless Power Transfer
Venue: arXiv cs.IT 2017
Year: 2017

Far-field Wireless Power Transfer (WPT) has attracted significant attention in the last decade. Recently, channel-adaptive waveforms have been shown to significantly increase the DC power level at the output of the rectifier. However the design of those waveforms is generally computationally complex and does not lend itself easily to practical implementation. We here propose a low-complexity channel-adaptive multisine waveform design whose performance is very close to that of the optimal design. Performance evaluations confirm the benefits of the new design in various rectifier topologies.
On the Importance of Correlations in Rational Choice: A Case for Non-Nashian Game Theory
Venue: arXiv cs.GT 2017
Year: 2017

The Nash equilibrium paradigm, and Rational Choice Theory in general, rely on agents acting independently from each other. This note shows how this assumption is crucial in the definition of Rational Choice Theory. It explains how a consistent Alternate Rational Choice Theory, as suggested by Jean-Pierre Dupuy, can be built on the exact opposite assumption, and how it provides a viable account for alternate, actually observed behavior of rational agents that is based on correlations between their decisions. The end goal of this note is three-fold: (i) to motivate that the Perfect Prediction Equilibrium, implementing Dupuy's notion of projected time and previously called "projected equilibrium", is a reasonable approach in certain real situations and a meaningful complement to the Nash paradigm, (ii) to summarize common misconceptions about this equilibrium, and (iii) to give a concise motivation for future research on non-Nashian game theory.
Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji
Venue: arXiv cs.CL 2017
Year: 2017

Emojis, as a new way of conveying nonverbal cues, are widely adopted in computer-mediated communications. In this paper, first from a message sender perspective, we focus on people's motives in using four types of emojis -- positive, neutral, negative, and non-facial. We compare the willingness levels of using these emoji types for seven typical intentions that people usually apply nonverbal cues for in communication. The results of extensive statistical hypothesis tests not only report the popularities of the intentions, but also uncover the subtle differences between emoji types in terms of intended uses. Second, from a perspective of message recipients, we further study the sentiment effects of emojis, as well as their duplications, on verbal messages. Different from previous studies in emoji sentiment, we study the sentiments of emojis and their contexts as a whole. The experiment results indicate that the powers of conveying sentiment are different between four emoji types, and the sentiment effects of emojis vary in the contexts of different valences.
Context-Aware Recursive Bayesian Graph Traversal in BCIs
Venue: arXiv cs.HC 2017
Year: 2017

Noninvasive brain computer interfaces (BCI), and more specifically Electroencephalography (EEG) based systems for intent detection need to compensate for the low signal to noise ratio of EEG signals. In many applications, the temporal dependency information from consecutive decisions and contextual data can be used to provide a prior probability for the upcoming decision. In this study we proposed two probabilistic graphical models (PGMs), using context information and previously observed EEG evidences to estimate a probability distribution over the decision space in graph based decision-making mechanism. In this approach, user moves a pointer to the desired vertex in the graph in which each vertex represents an action. To select a vertex, a Select command, or a proposed probabilistic Selection criterion (PSC) can be used to automatically detect the user intended vertex. Performance of different PGMs and Selection criteria combinations are compared over a keyboard based on a graph layout. Based on the simulation results, probabilistic Selection criterion along with the probabilistic graphical model provides the highest performance boost for individuals with pour calibration performance and achieving the same performance for individuals with high calibration performance.
QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
Venue: arXiv cs.CV 2017
Year: 2017

Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise. This paper introduces a spatio-temporal denoising algorithm for OCT data on a B-scan level using a novel quantile sparse image (QuaSI) prior. To remove speckle noise while preserving image structures of diagnostic relevance, we implement our QuaSI prior via median filter regularization coupled with a Huber data fidelity model in a variational approach. For efficient energy minimization, we develop an alternating direction method of multipliers (ADMM) scheme using a linearization of median filtering. Our spatio-temporal method can handle both, denoising of single B-scans and temporally consecutive B-scans, to gain volumetric OCT data with enhanced signal-to-noise ratio. Our algorithm based on 4 B-scans only achieved comparable performance to averaging 13 B-scans and outperformed other current denoising methods.
Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models
Venue: arXiv cs.LG 2017
Year: 2017

The emergence and development of cancer is a consequence of the accumulation over time of genomic mutations involving a specific set of genes, which provides the cancer clones with a functional selective advantage. In this work, we model the order of accumulation of such mutations during the progression, which eventually leads to the disease, by means of probabilistic graphic models, i.e., Bayesian Networks (BNs). We investigate how to perform the task of learning the structure of such BNs, according to experimental evidence, adopting a global optimization meta-heuristics. In particular, in this work we rely on Genetic Algorithms, and to strongly reduce the execution time of the inference -- which can also involve multiple repetitions to collect statistically significant assessments of the data -- we distribute the calculations using both multi-threading and a multi-node architecture. The results show that our approach is characterized by good accuracy and specificity; we also demonstrate its feasibility, thanks to a 84x reduction of the overall execution time with respect to a traditional sequential implementation.
SRMCA: A Scalable and Resilient Real-time Multi-party Communication Architecture
Venue: arXiv cs.NI 2017
Year: 2017

This paper proposes a scalable and resilient real-time multi-party communication architecture for the delivery of mixed media streams, for which content centric networking, with its intelligent network layer, is chosen for implementation to address the shortcomings of the current IP-based Internet architecture. Content centric networking (CCN) represents one of the major proposals targeting future Internet architecture, and is typically optimized for non-realtime content delivery. Proposed research in this paper addresses the architectural challenges for large-scale deployment of CCN to serve real-time applications from the perspective of a multi-party video conferencing framework, with the necessary architectural components to support application- and system-level objectives, in regards to quality of experience, resource utilization, and scalability. We present an in-depth analysis of the proposed architecture by first providing an analytical driven study for the system, and then demonstrating its performance by emulating the architecture over a test-bed with a large number of participants involved in many-to-many communication sessions. The results suggest that the proposed architecture can scale well above 50 participants without incurring significant penalty in signaling, communication, and computing overheads, with capability to support 100 or more participants.
Long quasi-polycyclic $t-$CIS codes
Venue: arXiv cs.IT 2017
Year: 2017

We study complementary information set codes of length $tn$ and dimension $n$ of order $t$ called ($t-$CIS code for short). Quasi-cyclic and quasi-twisted $t$-CIS codes are enumerated by using their concatenated structure. Asymptotic existence results are derived for one-generator and have co-index $n$ by Artin's conjecture for quasi cyclic and special case for quasi twisted. This shows that there are infinite families of long QC and QT $t$-CIS codes with relative distance satisfying a modified Varshamov-Gilbert bound for rate $1/t$ codes. Similar results are defined for the new and more general class of quasi-polycyclic codes introduced recently by Berger and Amrani.
Technical Report: Outage Performance of Full-Duplex MIMO DF Relaying using Zero-Forcing Beamforming
Venue: arXiv cs.IT 2017
Year: 2017

In this paper, we deal with the performance analysis of full-duplex relaying in decode-&-forward cooperative networks with multiple-antenna terminals. More specifically, by analyzing the end-to-end statistics, we derive the accurate closed-form expressions of the end-to-end outage probability for both transmit and receive ZFBF scheme over Rayleigh fading environments. Some selected results show some interesting observations useful for system designers. Specifically, we observe that the outage performance can be improved by adopting the joint ZF-based precoding with different antenna configurations.
Segmenting Dermoscopic Images
Venue: arXiv cs.CV 2017
Year: 2017

We propose an automatic algorithm, named SDI, for the segmentation of skin lesions in dermoscopic images, articulated into three main steps: selection of the image ROI, selection of the segmentation band, and segmentation. We present extensive experimental results achieved by the SDI algorithm on the lesion segmentation dataset made available for the ISIC 2017 challenge on Skin Lesion Analysis Towards Melanoma Detection, highlighting its advantages and disadvantages.
Reconsidering the gold open access citation advantage postulate in a multidisciplinary context: an analysis of the subject categories in the Web of Science database 2009-2014
Venue: arXiv cs.DL 2017
Year: 2017

Since Lawrence in 2001 proposed the open access (OA) citation advantage, the potential benefit of OA in relation to the citation impact has been discussed in depth. The methodology to test this postulate ranges from comparing the impact factors of OA journals versus traditional ones, to comparing citations of OA versus non-OA articles published in the same non-OA journals. However, conclusions are not entirely consistent among fields, and two possible explications have been suggested in those fields where a citation advantage has been observed for OA: the early view and the selection bias postulates. In this study, a longitudinal and multidisciplinary analysis of the gold OA citation advantage is developed. All research articles in all journals for all subject categories in the multidisciplinary database Web of Science are considered. A total of 1,137,634 articles - 86,712 OA articles (7.6%) and 1,050,922 non-OA articles (92.4%)- published in 2009 are analysed. The citation window considered goes from 2009 to 2014, and data are aggregated for the 249 disciplines (subject categories). At journal level, we also study the evolution of journal impact factors for OA and non-OA journals in those disciplines whose OA prevalence is higher (top 36 subject categories). As the main conclusion, there is no generalizable gold OA citation advantage, neither at article nor at journal level.
Maximum Likelihood Decoder for Index Coded PSK Modulation for Priority Ordered Receivers
Venue: arXiv cs.IT 2017
Year: 2017

Index coded PSK modulation over an AWGN broadcast channel, for a given index coding problem (ICP) is studied. For a chosen index code and an arbitrary mapping (of broadcast vectors to PSK signal points), we have derived a decision rule for the maximum likelihood (ML) decoder. The message error performance of a receiver at high SNR is characterized by a parameter called PSK Index Coding Gain (PSK-ICG). The PSK-ICG of a receiver is determined by a metric called minimum inter-set distance. For a given ICP with an order of priority among the receivers, and a chosen $2^N$-PSK constellation we propose an algorithm to find (index code, mapping) pairs, each of which gives the best performance in terms of PSK-ICG of the receivers. No other pair of index code (of length $N$ with $2^N$ broadcast vectors) and mapping can give a better PSK-ICG for the highest priority receiver. Also, given that the highest priority receiver achieves its best performance, the next highest priority receiver achieves its maximum gain possible and so on in the specified order or priority.
Anomaly Detection and Redundancy Elimination of Big Sensor Data in Internet of Things
Venue: arXiv cs.DC 2017
Year: 2017

In the era of big data and Internet of things, massive sensor data are gathered with Internet of things. Quantity of data captured by sensor networks are considered to contain highly useful and valuable information. However, for a variety of reasons, received sensor data often appear abnormal. Therefore, effective anomaly detection methods are required to guarantee the quality of data collected by those sensor nodes. Since sensor data are usually correlated in time and space, not all the gathered data are valuable for further data processing and analysis. Preprocessing is necessary for eliminating the redundancy in gathered massive sensor data. In this paper, the proposed work defines a sensor data preprocessing framework. It is mainly composed of two parts, i.e., sensor data anomaly detection and sensor data redundancy elimination. In the first part, methods based on principal statistic analysis and Bayesian network is proposed for sensor data anomaly detection. Then, approaches based on static Bayesian network (SBN) and dynamic Bayesian networks (DBNs) are proposed for sensor data redundancy elimination. Static sensor data redundancy detection algorithm (SSDRDA) for eliminating redundant data in static datasets and real-time sensor data redundancy detection algorithm (RSDRDA) for eliminating redundant sensor data in real-time are proposed. The efficiency and effectiveness of the proposed methods are validated using real-world gathered sensor datasets.
Efficiency Optimizations on Yao's Garbled Circuits and Their Practical Applications
Venue: arXiv cs.CR 2017
Year: 2017

The advance of cloud computing and big data technologies brings out major changes in the ways that people make use of information systems. While those technologies extremely ease our lives, they impose the danger of compromising privacy and security of data due to performing the computation on an untrusted remote server. Moreover, there are also many other real-world scenarios requiring two or more (possibly distrustful) parties to securely compute a function without leaking their respective inputs to each other. In this respect, various secure computation mechanisms have been proposed in order to protect users' data privacy. Yao's garbled circuit protocol is one of the most powerful solutions for this problem. In this thesis, we first describe the Yao's protocol in detail, and include the complete list of optimizations over the Yao's protocol. We also compare their advantages in terms of communication and computation complexities, and analyse their compatibility with each other. We also look into generic Yao implementations (including garbled RAM) to demonstrate the use of this powerful tool in practice. We compare those generic implementations in terms of their use of garbled circuit optimizations. We also cover the specific real-world applications for further illustration. Moreover, in some scenarios, the functionality itself may also need to be kept private which leads to an ideal solution of secure computation problem. In this direction, we finally cover the problem of Private Function Evaluation, in particular for the 2-party case where garbled circuits have an important role. We finally analyse the generic mechanism of Mohassel et al. and contribute to it by proposing a new technique for the computation of the number of possible circuit mappings.
Implicit Sensor-based Authentication of Smartphone Users with Smartwatch
Venue: arXiv cs.CR 2017
Year: 2017

Smartphones are now frequently used by end-users as the portals to cloud-based services, and smartphones are easily stolen or co-opted by an attacker. Beyond the initial log-in mechanism, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data, whether in the cloud or in the smartphone. But attackers who have gained access to a logged-in smartphone have no incentive to re-authenticate, so this must be done in an automatic, non-bypassable way. Hence, this paper proposes a novel authentication system, iAuth, for implicit, continuous authentication of the end-user based on his or her behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We design a system that gives accurate authentication using machine learning and sensor data from multiple mobile devices. Our system can achieve 92.1% authentication accuracy with negligible system overhead and less than 2% battery consumption.
Interactive Program Synthesis
Venue: arXiv cs.PL 2017
Year: 2017

Program synthesis from incomplete specifications (e.g. input-output examples) has gained popularity and found real-world applications, primarily due to its ease-of-use. Since this technology is often used in an interactive setting, efficiency and correctness are often the key user expectations from a system based on such technologies. Ensuring efficiency is challenging since the highly combinatorial nature of program synthesis algorithms does not fit in a 1-2 second response expectation of a user-facing system. Meeting correctness expectations is also difficult, given that the specifications provided are incomplete, and that the users of such systems are typically non-programmers. In this paper, we describe how interactivity can be leveraged to develop efficient synthesis algorithms, as well as to decrease the cognitive burden that a user endures trying to ensure that the system produces the desired program. We build a formal model of user interaction along three dimensions: incremental algorithm, step-based problem formulation, and feedback-based intent refinement. We then illustrate the effectiveness of each of these forms of interactivity with respect to synthesis performance and correctness on a set of real-world case studies.
Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A Survey, Classification and Challenges
Venue: arXiv cs.IT 2017
Year: 2017

Precoding has been conventionally considered as an effective means of mitigating the interference and efficiently exploiting the available in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block- and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast-/multicast-/broadcast- precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area.
A Study of Metrics of Distance and Correlation Between Ranked Lists for Compositionality Detection
Venue: arXiv cs.CL 2017
Year: 2017

Compositionality in language refers to how much the meaning of some phrase can be decomposed into the meaning of its constituents and the way these constituents are combined. Based on the premise that substitution by synonyms is meaning-preserving, compositionality can be approximated as the semantic similarity between a phrase and a version of that phrase where words have been replaced by their synonyms. Different ways of representing such phrases exist (e.g., vectors [1] or language models [2]), and the choice of representation affects the measurement of semantic similarity. We propose a new compositionality detection method that represents phrases as ranked lists of term weights. Our method approximates the semantic similarity between two ranked list representations using a range of well-known distance and correlation metrics. In contrast to most state-of-the-art approaches in compositionality detection, our method is completely unsupervised. Experiments with a publicly available dataset of 1048 human-annotated phrases shows that, compared to strong supervised baselines, our approach provides superior measurement of compositionality using any of the distance and correlation metrics considered.
Comparison of SMT and RBMT; The Requirement of Hybridization for Marathi-Hindi MT
Venue: arXiv cs.CL 2017
Year: 2017

We present in this paper our work on comparison between Statistical Machine Translation (SMT) and Rule-based machine translation for translation from Marathi to Hindi. Rule Based systems although robust take lots of time to build. On the other hand statistical machine translation systems are easier to create, maintain and improve upon. We describe the development of a basic Marathi-Hindi SMT system and evaluate its performance. Through a detailed error analysis, we, point out the relative strengths and weaknesses of both systems. Effectively, we shall see that even with a small amount of training corpus a statistical machine translation system has many advantages for high quality domain specific machine translation over that of a rule-based counterpart.