pwc-archive/papers-with-abstracts huggingface dataset:
Channel Static Antennas for Mobile Devices
Date: 2019-05-27 00:00:00

Channel static antennas are considered for mobile devices. The antenna keeps
the wireless communication channel static by performing a counter-movement that
is opposed to movements of the device that might be caused by a user. The
feasibility of the concept is demonstrated for linear movement in an office
environment. Channel measurements are performed with quarter wavelength
monopole antennas in the 2.4GHz ISM frequency band. A channel model for the
wireless communication channel of mobile devices with channel static antennas
is proposed based on these measurement results.
Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey
Date: 2019-09-26 00:00:00
Tasks: Autonomous Driving, Autonomous Vehicles, Decision Making, Survey

The literature suggests that autonomous vehicles (AVs) may drastically change
the user experience of private automobile travel by allowing users to engage in
productive or relaxing activities while travelling. As a consequence, the
generalised cost of car travel may decrease, and car users may become less
sensitive to travel time. By facilitating private motorised mobility, AVs may
eventually impact land use and households' residential location choices. This
paper seeks to advance the understanding of the potential impacts of AVs on
travel behaviour and land use by investigating stated preferences for
combinations of residential locations and travel options for the commute in the
context of autonomous automobile travel. Our analysis draws from a stated
preference survey, which was completed by 512 commuters from the Sydney
metropolitan area in Australia and provides insights into travel time
valuations in a long-term decision-making context. For the analysis of the
stated choice data, mixed logit models are estimated. Based on the empirical
results, no changes in the valuation of travel time due to the advent of AVs
should be expected. However, given the hypothetical nature of the stated
preference survey, the results may be affected by methodological limitations.
Age Based Task Scheduling and Computation Offloading in Mobile-Edge Computing Systems
Date: 2019-05-28 00:00:00
Tasks: Edge-computing, Scheduling

To support emerging real-time monitoring and control applications, the
timeliness of computation results is of critical importance to mobile-edge
computing (MEC) systems. We propose a performance metric called age of task
(AoT) based on the concept of age of information (AoI), to evaluate the
temporal value of computation tasks. In this paper, we consider a system
consisting of a single MEC server and one mobile device running several
applications. We study an age minimization problem by jointly considering task
scheduling, computation offloading and energy consumption. To solve the problem
efficiently, we propose a light-weight task scheduling and computation
offloading algorithm. Through performance evaluation, we show that our proposed
age-based solution is competitive when compared with traditional strategies.
Perceived Advantage in Perspective Application of Integrated Choice and Latent Variable Model to Capture Electric Vehicles Perceived Advantage from Consumers Perspective
Date: 2019-11-28 00:00:00

Relative advantage, or the degree to which a new technology is perceived to
be better over the existing technology it supersedes, has a significant impact
on individuals decision of adopting to the new technology. This paper
investigates the impact of electric vehicles perceived advantage over the
conventional internal combustion engine vehicles, from consumers perspective,
on their decision to select electric vehicles. Data is obtained from a stated
preference survey from 1176 residents in New South Wales, Australia. The
collected data is used to estimate an integrated choice and latent variable
model of electric vehicle choice, which incorporates the perceived advantage of
electric vehicles in the form of latent variables in the utility function. The
design of the electric vehicle, impact on the environment, and safety are three
identified advantages from consumers point of view. The model is used to
simulate the effectiveness of various policies to promote electric vehicles on
different cohorts. Rebate on the purchase price is found to be the most
effective strategy to promote electric vehicles adoption.
AmoebaContact and GDFold: a new pipeline for rapid prediction of protein structures
Date: 2019-05-28 00:00:00
Tasks: Prediction, Protein Structure Prediction

Native contacts between residues could be predicted from the amino acid
sequence of proteins, and the predicted contact information could assist the de
novo protein structure prediction. Here, we present a novel pipeline of a
residue contact predictor AmoebaContact and a contact-assisted folder GDFold
for rapid protein structure prediction. Unlike mainstream contact predictors
that utilize human-designed neural networks, AmoebaContact adopts a set of
network architectures that are found as optimal for contact prediction through
automatic searching and predicts the residue contacts at a series of cutoffs.
Different from conventional contact-assisted folders that only use top-scored
contact pairs, GDFold considers all residue pairs from the prediction results
of AmoebaContact in a differentiable loss function and optimizes the atom
coordinates using the gradient descent algorithm. Combination of AmoebaContact
and GDFold allows quick reconstruction of the protein structure, with
comparable model quality to the state-of-the-art protein structure prediction
methods.
Online Measurement-Based Estimation of Dynamic System State Matrix in Ambient Conditions
Date: 2019-05-28 00:00:00

In this paper, a purely measurement-based method is proposed to estimate the
dynamic system state matrix by applying the regression theorem of the
multivariate Ornstein-Uhlenbeck process. The proposed method employs a
recursive algorithm to minimize the required computational effort, making it
applicable to the real-time environment. One main advantage of the proposed
method is model independence, i.e., it is independent of the network model and
the dynamic model of generators. Among various applications of the estimated
matrix, detecting and locating unexpected network topology change is
illustrated in details. Simulation studies have shown that the proposed
measurement-based method can provide an accurate and efficient estimation of
the dynamic system state matrix under the occurrence of unexpected topology
change. Besides, various implementation conditions are tested to show that the
proposed method can provide accurate approximation despite measurement noise,
missing PMUs, and the implementation of higher-order generator models with
control devices.
Many-player games of optimal consumption and investment under relative performance criteria
Date: 2019-05-28 00:00:00
Tasks: Portfolio Optimization

We study a portfolio optimization problem for competitive agents with CRRA
utilities and a common finite time horizon. The utility of an agent depends not
only on her absolute wealth and consumption but also on her relative wealth and
consumption when compared to the averages among the other agents. We derive a
closed form solution for the $n$-player game and the corresponding mean field
game. This solution is unique in the class of equilibria with constant
investment and continuous time-dependent consumption, both independent of the
wealth of the agent. Compared to the classical Merton problem with one agent,
the competitive model exhibits a wide range of highly nonlinear and
non-monotone dependence on the agents' risk tolerance and competitiveness
parameters. Counter-intuitively, competitive agents with high risk tolerance
may behave like non-competitive agents with low risk tolerance.
Automatic Quality Control and Enhancement for Voice-Based Remote Parkinson's Disease Detection
Date: 2019-05-31 00:00:00

The performance of voice-based Parkinson's disease (PD) detection systems
degrades when there is an acoustic mismatch between training and operating
conditions caused mainly by degradation in test signals. In this paper, we
address this mismatch by considering three types of degradation commonly
encountered in remote voice analysis, namely background noise, reverberation
and nonlinear distortion, and investigate how these degradations influence the
performance of a PD detection system. Given that the specific degradation is
known, we explore the effectiveness of a variety of enhancement algorithms in
compensating this mismatch and improving the PD detection accuracy. Then, we
propose two approaches to automatically control the quality of recordings by
identifying the presence and type of short-term and long-term degradations and
protocol violations in voice signals. Finally, we experiment with using the
proposed quality control methods to inform the choice of enhancement algorithm.
Experimental results using the voice recordings of the mPower mobile PD data
set under different degradation conditions show the effectiveness of the
quality control approaches in selecting an appropriate enhancement method and,
consequently, in improving the PD detection accuracy. This study is a step
towards the development of a remote PD detection system capable of operating in
unseen acoustic environments.
Credit Scoring by Incorporating Dynamic Networked Information
Date: 2019-10-31 00:00:00
Tasks: Management

In this paper, the credit scoring problem is studied by incorporating
networked information, where the advantages of such incorporation are
investigated theoretically in two scenarios. Firstly, a Bayesian optimal filter
is proposed to provide risk prediction for lenders assuming that published
credit scores are estimated merely from structured financial data. Such
prediction can then be used as a monitoring indicator for the risk management
in lenders' future decisions. Secondly, a recursive Bayes estimator is further
proposed to improve the precision of credit scoring by incorporating the
dynamic interaction topology of clients. It is shown that under the proposed
evolution framework, the designed estimator has a higher precision than any
efficient estimator, and the mean square errors are strictly smaller than the
Cram\'er-Rao lower bound for clients within a certain range of scores. Finally,
simulation results for a special case illustrate the feasibility and
effectiveness of the proposed algorithms.
Graph-based era segmentation of international financial integration
Date: 2019-05-28 00:00:00
Tasks: Time Series, Time Series Analysis

Assessing world-wide financial integration constitutes a recurrent challenge
in macroeconometrics, often addressed by visual inspections searching for data
patterns. Econophysics literature enables us to build complementary,
data-driven measures of financial integration using graphs. The present
contribution investigates the potential and interests of a novel 3-step
approach that combines several state-of-the-art procedures to i) compute
graph-based representations of the multivariate dependence structure of asset
prices time series representing the financial states of 32 countries world-wide
(1955-2015); ii) compute time series of 5 graph-based indices that characterize
the time evolution of the topologies of the graph; iii) segment these time
evolutions in piece-wise constant eras, using an optimization framework
constructed on a multivariate multi-norm total variation penalized functional.
The method shows first that it is possible to find endogenous stable eras of
world-wide financial integration. Then, our results suggest that the most
relevant globalization eras would be based on the historical patterns of global
capital flows, while the major regulatory events of the 1970s would only appear
as a cause of sub-segmentation.
Monetary Stabilization in Cryptocurrencies - Design Approaches and Open Questions
Date: 2019-05-28 00:00:00

The price volatility of cryptocurrencies is often cited as a major hindrance
to their wide-scale adoption. Consequently, during the last two years, multiple
so called stablecoins have surfaced---cryptocurrencies focused on maintaining
stable exchange rates. In this paper, we systematically explore and analyze the
stablecoin landscape. Based on a survey of 24 specific stablecoin projects, we
go beyond individual coins for extracting general concepts and approaches. We
combine our findings with learnings from classical monetary policy, resulting
in a comprehensive taxonomy of cryptocurrency stabilization. We use our
taxonomy to highlight the current state of development from different
perspectives and show blank spots. For instance, while over 91% of projects
promote 1-to-1 stabilization targets to external assets, monetary policy
literature suggests that the smoothing of short term volatility is often a more
sustainable alternative. Our taxonomy bridges computer science and economics,
fostering the transfer of expertise. For example, we find that 38% of the
reviewed projects use a combination of exchange rate targeting and specific
stabilization techniques that can render them vulnerable to speculative
economic attacks - an avoidable design flaw.
Distributed Antenna Selection for Massive MIMO using Reversing Petri Nets
Date: 2019-05-28 00:00:00
Tasks: Diversity

Distributed antenna selection for Distributed Massive MIMO (Multiple Input
Multiple Output) communication systems reduces computational complexity
compared to centralised approaches, and provides high fault tolerance while
retaining diversity and spatial multiplexity. We propose a novel distributed
algorithm for antenna selection and show its advantage over existing
centralised and distributed solutions. The proposed algorithm is shown to
perform well with imperfect channel state information, and to execute a small
number of simple computational operations per node, converging fast to a steady
state. We base it on Reversing Petri Nets, a variant of Petri nets inspired by
reversible computation, capable of both forward and backward execution while
obeying conservation laws.
Downlink Coverage and Rate Analysis of an Aerial User in Vertical Heterogeneous Networks (VHetNets)
Authors: Nesrine Cherif, Mohamed Alzenad, Halim Yanikomeroglu, Abbas Yongacoglu
Date: 2019-05-24 00:00:00

In this paper, we analyze the downlink coverage probability and rate of an aerial user in vertical HetNets (VHetNets) comprising aerial base stations (aerial-BSs) and terrestrial-BSs. The locations of terrestrial-BSs are modeled as an infinite 2-D Poisson Point Process (PPP), while the locations of aerial-BSs are modeled as a finite 2-D Binomial Point Process (BPP). Our cellular-to-air (C2A) channel model incorporates line-of-sight (LoS) and non-LoS transmissions between terrestrial-BSs and a typical aerial user, while we assume LoS transmissions for all aerial links. We assume that the aerial user is associated with an aerial-BS or terrestrial-BS that provides the strongest average received power. Using stochastic geometry, we derive exact and approximate expressions of the coverage probability and rate in terms of interference power's Laplace transform. The expressions are simplified assuming only LoS transmissions for the C2A channels. This enables easy-to-compute equations with good accuracy at elevated aerial user heights. We find that aerial users hovering at low altitudes tend to connect to aerial-BSs in denser terrestrial environments. Employing directive beamforming at aerial-BSs guarantees an acceptable performance at the aerial user by reducing interference signals received from the aerial-BSs. In denser terrestrial networks, the performance at the aerial user degrades substantially despite beamforming.
Dynamics of T Cell Receptor Distributions Following Acute Thymic Atrophy and Resumption
Date: 2019-05-29 00:00:00

Naive human T cells are produced in the thymus, which atrophies abruptly and
severely in response to physical or psychological stress. To understand how an
instance of stress affects the size and "diversity" of the peripheral naive T
cell pool, we derive a mean-field autonomous ODE model of T cell replenishment
that allows us to track the clone abundance distribution (the mean number of
different TCRs each represented by a specific number of cells). We identify
equilibrium solutions that arise at different rates of T cell production, and
derive analytic approximations to the dominant eigenvalues and eigenvectors of
the problem linearized about these equilibria. From the forms of the
eigenvalues and eigenvectors, we estimate rates at which counts of clones of
different sizes converge to and depart from equilibrium values--that is, how
the number of clones of different sizes "adjust" to the changing rate of T cell
production. Under most physiologically realistic realizations of our model, the
dominant eigenvalue (representing the slowest dynamics of the clone abundance
distribution) scales as a power law in the thymic output for low output levels,
but saturates at higher T cell production rates. Our analysis provides a
framework for quantitatively understanding how the clone abundance
distributions evolve under small changes in the overall T cell production rate
by the thymus.
Cumulative labelling with thymidine analogues when the steady-state assumption is violated
Authors: Darragh M Walsh
Date: 2019-05-29 00:00:00

We present modelling results that examine the consequences of implementing cumulative labelling with thymidine analogues, to estimate the cell cycle time and growth fraction of dividing cells, when the steady-state assumption is violated. We fix the value of the cell cycle time a priori and examine whether cumulative labelling can reproduce this value. We find that the cumulative labelling technique systematically overestimates the growth fraction and cell cycle time in non-steady cell populations. Our results suggest an explanation for discrepancies in experimental measurements of oligodendrocyte precursor cell properties using cumulative labelling. These results also emphasise the utility of using computational models to determine what violating the assumptions of experimental techniques would look like in the laboratory before experiments are undertaken.
Secrecy Outage Analysis Over Fluctuating Two-Ray Fading Channels
Date: 2019-05-29 00:00:00
Tasks: valid, Vocal Bursts Valence Prediction

In this letter, we analyze the secrecy outage probability (SOP) over
fluctuating two-ray fading channels but with a different definition from the
one adopted in [5]. Following the new defined SOP, we derive an analytical
closed-form expression for our proposed SOP, as well as an asymptotic formula
valid in the high signal-to-noise ratio region of the source to destination
link. In the numerical results section, we perform some Monte-Carlo simulations
to validate the accuracy of our derived expressions, and also present the
probability gap between our proposed SOP and the SOP in [5].
Review: dual benefits, compositions, recommended storage, and intake duration of mother's milk
Authors: Ammu Prasanna Kumar, Suryani Lukman
Date: 2019-05-28 00:00:00
Tasks: Literature Mining

Breastfeeding benefits both infants and mothers. Nutrients in mother's milk help protect infants from multiple diseases including infections, cancers, diabetes, gastrointestinal and respiratory diseases. We performed literature mining on 31,496 mother's-milk-related abstracts from PubMed and the results suggest the need for individualized mother's milk fortification and proper maternal supplementations (e.g. probiotics, vitamin D), because mother's milk compositions (e.g. fatty acids) vary according to maternal diet and responses to infection in mothers and/or infants. We review at details the variability observed in mother's milk compositions and its possible health effects in infants. We also review the effects of storage practices on mother's milk nutrients, recommended durations for mother's milk intake and the associated health benefits.
Statistical Modeling of the FSO Fronthaul Channel for UAV-based Communications
Date: 2020-03-16 00:00:00
Tasks: Position

In this paper, we investigate the statistics of the free space optics (FSO)
communication channel between a hovering unmanned aerial vehicle (UAV) and a
central unit. Two unique characteristics make UAV-based FSO systems
significantly different from conventional FSO systems with static transceivers.
First, for UAV-based FSO systems, the incident laser beam is not always
orthogonal to the receiver lens plane. Second, both position and orientation of
the UAV fluctuate over time due to dynamic wind load, inherent random air
fluctuations in the atmosphere around the UAV, and internal vibrations of the
UAV. On the contrary, for conventional FSO systems, the laser beam is always
perpendicular to the receiver lens plane and the relative movement of the
transceivers is limited. In this paper, we develop a novel channel model for
UAV-based FSO systems by quantifying the corresponding geometric and
misalignment losses (GML), while taking into account the non-orthogonality of
the laser beam and the random fluctuations of the position and orientation of
the UAV. In particular, for diverse weather conditions, we propose different
fluctuation models for the position and orientation of the UAV and derive
corresponding statistical models for the GML. We further analyze the
performance of a UAV-based FSO link in terms of outage probability and ergodic
rate and simplify the resulting analytical expressions for the high
signal-to-noise ratio (SNR) regime. Finally, simulations validate the accuracy
of the presented analysis and provide important insights for system design. For
instance, we show that for a given variance of the fluctuations, the beam width
should be properly adjusted to minimize the outage probability.
An assets-liabilities dynamical model of banking system and systemic risk governance
Date: 2019-05-29 00:00:00

We consider the problem of governing systemic risk in an assets-liabilities
dynamical model of banking system. In the model considered each bank is
represented by its assets and its liabilities.The capital reserves of a bank
are the difference between assets and liabilities of the bank. A bank is
solvent when its capital reserves are greater or equal to zero otherwise the
bank is failed.The banking system dynamics is defined by an initial value
problem for a system of stochastic differential equations whose independent
variable is time and whose dependent variables are the assets and the
liabilities of the banks.The banking system model presented generalizes those
discussed in [4],[3] and describes a homogeneous population of banks. The main
features of the model are a cooperation mechanism among banks and the
possibility of the (direct) intervention of the monetary authority in the
banking system dynamics. We call systemic risk or systemic event in a bounded
time interval the fact that in that time interval at least a given fraction of
the banks fails. The probability of systemic risk in a bounded time interval is
evaluated using statistical simulation. The systemic risk governance pursues
the goal of keeping the probability of systemic risk in a bounded time interval
between two given thresholds.The monetary authority is responsible for the
systemic risk governance.The governance consists in the choice of the assets
and of the liabilities of a kind of "ideal bank" as functions of time and in
the choice of the rules that regulate the cooperation mechanism among
banks.These rules are obtained solving an optimal control problem for the
pseudo mean field approximation of the banking system model. The governance
induces the banks of the system to behave like the "ideal bank". Shocks acting
on the assets or on the liabilities of the banks are simulated.