pwc-archive/papers-with-abstracts huggingface dataset:
Assessing Visual Quality of Omnidirectional Videos
Date: 2019-07-14 00:00:00
Tasks: Visual Question Answering (VQA)

In contrast with traditional video, omnidirectional video enables spherical
viewing direction with support for head-mounted displays, providing an
interactive and immersive experience. Unfortunately, to the best of our
knowledge, there are few visual quality assessment (VQA) methods, either
subjective or objective, for omnidirectional video coding. This paper proposes
both subjective and objective methods for assessing quality loss in encoding
omnidirectional video. Specifically, we first present a new database, which
includes the viewing direction data from several subjects watching
omnidirectional video sequences. Then, from our database, we find a high
consistency in viewing directions across different subjects. The viewing
directions are normally distributed in the center of the front regions, but
they sometimes fall into other regions, related to video content. Given this
finding, we present a subjective VQA method for measuring difference mean
opinion score (DMOS) of the whole and regional omnidirectional video, in terms
of overall DMOS (O-DMOS) and vectorized DMOS (V-DMOS), respectively. Moreover,
we propose two objective VQA methods for encoded omnidirectional video, in
light of human perception characteristics of omnidirectional video. One method
weighs the distortion of pixels with regard to their distances to the center of
front regions, which considers human preference in a panorama. The other method
predicts viewing directions according to video content, and then the predicted
viewing directions are leveraged to allocate weights to the distortion of each
pixel in our objective VQA method. Finally, our experimental results verify
that both the subjective and objective methods proposed in this paper advance
state-of-the-art VQA for omnidirectional video.
Modeling of the Labour Force Redistribution in Investment Projects with Account of their Delay
Date: 2017-09-19 00:00:00

The mathematical model of the labour force redistribution in investment
projects is presented in the article. The redistribution mode of funds, labour
force in particular, according to the equal risk approach applied to the loss
of some assets due to delay in all the investment projects is provided in the
model. The sample of the developed model for three investment projects with the
specified labour force volumes and their defined unit costs at the particular
moment is given.
SIMO channel performance evaluation on indoor environment at 2.4 GHz
Date: 2017-07-12 00:00:00

This work presents an experimental study of Single Input Multiple Output
(SIMO) channel performance in indoor radio propagation environment. Indoor
channel measurements at 2.4 GHz ISM frequency band have been performed using a
versatile channel sounder testbed platform. A single transmitting antenna, four
receiving antennas with two proposed geometries and a four-branch receiver
circuitry were used in order to achieve channel sounder measurements exploiting
baseband signal processing techniques. Deep investigation on SIMO wireless
channel performance was realized through three types of metrics which are
signal strength, gain coefficient and capacity. Performance results indicate
SIMO channel capacity enhancement and illustrate differences between the two
proposed geometries.
Kinetic theory and Brazilian income distribution
Date: 2017-09-19 00:00:00
Tasks: Time Series, Time Series Analysis

We investigate the Brazilian personal income distribution using data from
National Household Sample Survey (PNAD), an annual research available by the
Brazilian Institute of Geography and Statistics (IBGE). It provides general
characteristics of the country's population. Using PNAD data background we also
confirm the effectiveness of a semi-empirical model that reconciles Pareto
power-law for high-income people and Boltzmann- Gibbs distribution for the rest
of population. We use three measures of income inequality: the Pareto index,
the average income and the crossover income. In order to cope with many
dimensions of the income inequality, we calculate these three indices and also
the Gini coefficient for the general population as well as for two kinds of
population dichotomies: black / indigenous / mixed race versus white / yellow;
and men versus women. We also followed the time series of these indices for the
period 2001-2014. The results suggest a decreasing of Brazilian income
inequality over the selected period. Another important result is that
historically-disadvantaged subgroups (Women and black / indigenous / mixed
race),that are the majority of the population, have a more equalitarian income
distribution. These groups have also a smaller monthly income than the others
and this social structure remained virtually unchanged in the period of time.
Numerical analysis for a unified 2 factor model of structural and reduced form types for corporate bonds with fixed discrete coupon
Date: 2018-08-27 00:00:00
Tasks: Form

Conditions of Stability for explicit finite difference scheme and some
results of numerical analysis for a unified 2 factor model of structural and
reduced form types for corporate bonds with fixed discrete coupon are provided.
It seems to be difficult to get solution formula for PDE model which
generalizes Agliardi's structural model [1] for discrete coupon bonds into a
unified 2 factor model of structural and reduced form types and we study a
numerical analysis for it by explicit finite difference scheme. These equations
are parabolic equations with 3 variables and they include mixed derivatives, so
the explicit finite difference scheme is not stable in general. We find
conditions for the explicit finite difference scheme to be stable, in the case
that it is stable, numerically compute the price of the bond and analyze its
credit spread and duration.
An Introduction to Rule-based Modeling of Immune Receptor Signaling
Date: 2017-09-19 00:00:00

Cells process external and internal signals through chemical interactions.
Cells that constitute the immune system (e.g., antigen presenting cell, T-cell,
B-cell, mast cell) can have different functions (e.g., adaptive memory,
inflammatory response) depending on the type and number of receptor molecules
on the cell surface and the specific intracellular signaling pathways activated
by those receptors. Explicitly modeling and simulating kinetic interactions
between molecules allows us to pose questions about the dynamics of a signaling
network under various conditions. However, the application of chemical kinetics
to biochemical signaling systems has been limited by the complexity of the
systems under consideration. Rule-based modeling (BioNetGen, Kappa, Simmune,
PySB) is an approach to address this complexity. In this chapter, by
application to the Fc$\varepsilon$RI receptor system, we will explore the
origins of complexity in macromolecular interactions, show how rule-based
modeling can be used to address complexity, and demonstrate how to build a
model in the BioNetGen framework. Open source BioNetGen software and
documentation are available at http://bionetgen.org.
A shared latent space matrix factorisation method for recommending new trial evidence for systematic review updates
Authors: Surian Didi, Dunn Adam G., Orenstein Liat, Bashir Rabia, Coiera Enrico, Bourgeois Florence T.
Date: 2018-02-27 00:00:00
Tasks: Holdout Set

Clinical trial registries can be used to monitor the production of trial
evidence and signal when systematic reviews become out of date. However, this
use has been limited to date due to the extensive manual review required to
search for and screen relevant trial registrations. Our aim was to evaluate a
new method that could partially automate the identification of trial
registrations that may be relevant for systematic review updates. We identified
179 systematic reviews of drug interventions for type 2 diabetes, which
included 537 clinical trials that had registrations in ClinicalTrials.gov. We
tested a matrix factorisation approach that uses a shared latent space to learn
how to rank relevant trial registrations for each systematic review, comparing
the performance to document similarity to rank relevant trial registrations.
The two approaches were tested on a holdout set of the newest trials from the
set of type 2 diabetes systematic reviews and an unseen set of 141 clinical
trial registrations from 17 updated systematic reviews published in the
Cochrane Database of Systematic Reviews. The matrix factorisation approach
outperformed the document similarity approach with a median rank of 59 and
recall@100 of 60.9%, compared to a median rank of 138 and recall@100 of 42.8%
in the document similarity baseline. In the second set of systematic reviews
and their updates, the highest performing approach used document similarity and
gave a median rank of 67 (recall@100 of 62.9%). The proposed method was useful
for ranking trial registrations to reduce the manual workload associated with
finding relevant trials for systematic review updates. The results suggest that
the approach could be used as part of a semi-automated pipeline for monitoring
potentially new evidence for inclusion in a review update.
Market Dynamics. On A Muse Of Cash Flow And Liquidity Deficit
Date: 2019-03-28 00:00:00

A first attempt at obtaining market--directional information from a
non--stationary solution of the dynamic equation "future price tends to the
value that maximizes the number of shares traded per unit time" [1] is
presented. We demonstrate that the concept of price impact is poorly applicable
to market dynamics. Instead, we consider the execution flow $I=dV/dt$ operator
with the "impact from the future" term providing information about
not--yet--executed trades. The "impact from the future" on $I$ can be directly
estimated from the already--executed trades, the directional information on
price is then obtained from the experimentally observed fact that the $I$ and
$p$ operators have the same eigenfunctions (the exact result in the dynamic
impact approximation $p=p(I)$). The condition for "no information about the
future" is found and directional prediction quality is discussed. This work
makes a substantial contribution toward solving the ultimate market dynamics
problem: find evidence of existence (or proof of non--existence) of an
automated trading machine which consistently makes positive P\&L on a free
market as an autonomous agent (aka the existence of the market dynamics
equation). The software with a reference implementation of the theory is
provided.
Modeling and Analysis of Power Line Communications for Application in Smart Grid
Date: 2017-09-19 00:00:00

Smart grid is an energy infrastructure that increases energy efficiency by
using communication infrastructure, smart meters, smart appliances, automated
control and networking, and more. This paper focuses on the Power Line
Communication (PLC) aspect and technologies used in the smart grid. There are
various challenges and advancements in the smart grid; this research discusses
how PLC can improve smart grid performance. In order to provide applicable
results, practical PLC system parameters and other required data was obtained
from Florida Power and Light (FPL). Modeling of the PLC system with different
types of digital modulations was conducted using MATLAB/Simulink software and
Python. The benefits and design tradeoffs of Amplitude Shift Keying (ASK),
Frequency Shift Keying (FSK), and Phase Shift Keying (PSK) are discussed. The
modulation schemes are compared on the basis of their applicability to a
practical PLC network by comparing the results of the simulations
Image Acquisition System Using On Sensor Compressed Sampling Technique
Date: 2018-01-11 00:00:00
Tasks: compressed sensing, Decoder

Advances in CMOS technology have made high resolution image sensors possible.
These image sensor pose significant challenges in terms of the amount of raw
data generated, energy efficiency and frame rate. This paper presents a new
design methodology for an imaging system and a simplified novel image sensor
pixel design to be used in such system so that Compressed Sensing (CS)
technique can be implemented easily at the sensor level. This results in
significant energy savings as it not only cuts the raw data rate but also
reduces transistor count per pixel, decreases pixel size, increases fill
factor, simplifies ADC, JPEG encoder and JPEG decoder design and decreases
wiring as well as address decoder size by half. Thus CS has the potential to
increase the resolution of image sensors for a given technology and die size
while significantly decreasing the power consumption and design complexity. We
show that it has potential to reduce power consumption by about 23%-65%.
Protection of hamsters from mortality by reducing fecal moxifloxacin concentration with DAV131A in a model of moxifloxacin-induced Clostridium difficile colitis
Date: 2017-09-21 00:00:00

BackgroundLowering the gut exposure to antibiotics during treatments can
prevent microbiota disruption. We evaluated the effect of an activated
charcoal-based adsorbent, DAV131A, on fecal free moxifloxacin concentration and
mortality in a hamster model of moxifloxacin-induced C. difficile
infection.Methods215 hamsters receiving moxifloxacin subcutaneously (D1-D5)
were orally infected at D3 with C. difficile spores. They received various
doses (0-1800mg/kg/day) and schedules (BID, TID) of DAV131A (D1-D8).
Moxifloxacin concentration and C. difficile counts were determined at D3, and
mortality at D12. We compared mortality, moxifloxacin concentration and C.
difficile counts according to DAV131A regimens, and modelled the link between
DAV131A regimen, moxifloxacin concentration and mortality. ResultsAll hamsters
that received no DAV131A died, but none of those that received 1800mg/kg/day. A
significant dose-dependent relationship between DAV131A dose and (i) mortality
rates, (ii) moxifloxacin concentration and (iii) C. difficile counts was
evidenced. Mathematical modeling suggested that (i) lowering moxifloxacin
concentration at D3, which was 58$\mu$g/g (95%CI=50-66) without DAV131A, to
17$\mu$g/g (14-21) would reduce mortality by 90% and (ii) this would be
achieved with a daily DAV131A dose of 703mg/kg (596-809).ConclusionsIn this
model of C. difficile infection, DAV131A reduced mortality in a dose-dependent
manner by decreasing fecal free moxifloxacin concentration.
Interconnection Strategies for Self-Calibration of Large Scale Antenna Arrays
Date: 2018-11-14 00:00:00

In time-division duplexing (TDD) systems, massive multiple-input
multiple-output (MIMO) relies on the channel reciprocity to obtain the downlink
(DL) channel state information (CSI) with the uplink (UL) CSI. In practice, the
mismatches in the radio frequency (RF) analog circuits among different antennas
at the base station (BS) break the end-to-end UL and DL channel reciprocity.
Antenna calibration is necessary to avoid the severe performance degradation
with massive MIMO. Many calibration schemes are available to compensate the RF
gain mismatches and restore the channel reciprocity in TDD massive MIMO
systems. In this paper, we focus on the internal self-calibration scheme where
different BS antennas are interconnected via hardware transmission lines.
First, we study the resulting calibration performance for an arbitrary
interconnection strategy. Next, we obtain closed-form Cramer-Rao lower bound
(CRLB) expressions for each interconnection strategy at the BS with only (M-1)
transmission lines and M denotes the total number of BS antennas. Basing on the
derived results, we further prove that the star interconnection strategy is
optimal for internal self-calibration due to its lowest CRLB. In addition, we
also put forward efficient recursive algorithms to derive the corresponding
maximum-likelihood (ML) estimates of all the calibration coefficients.
Numerical simulation results are also included to corroborate our theoretical
analyses and results.
SimiNet: a Novel Method for Quantifying Brain Network Similarity
Date: 2017-09-21 00:00:00
Tasks: Graph Similarity, Object Categorization

Quantifying the similarity between two networks is critical in many
applications. A number of algorithms have been proposed to compute graph
similarity, mainly based on the properties of nodes and edges. Interestingly,
most of these algorithms ignore the physical location of the nodes, which is a
key factor in the context of brain networks involving spatially defined
functional areas. In this paper, we present a novel algorithm called "SimiNet"
for measuring similarity between two graphs whose nodes are defined a priori
within a 3D coordinate system. SimiNet provides a quantified index (ranging
from 0 to 1) that accounts for node, edge and spatiality features. Complex
graphs were simulated to evaluate the performance of SimiNet that is compared
with eight state-of-art methods. Results show that SimiNet is able to detect
weak spatial variations in compared graphs in addition to computing similarity
using both nodes and edges. SimiNet was also applied to real brain networks
obtained during a visual recognition task. The algorithm shows high performance
to detect spatial variation of brain networks obtained during a naming task of
two categories of visual stimuli: animals and tools. A perspective to this work
is a better understanding of object categorization in the human brain.
Blood-based metabolic signatures in Alzheimer's disease
Date: 2017-09-21 00:00:00

Introduction: Identification of blood-based metabolic changes might provide
early and easy-to-obtain biomarkers.
  Methods: We included 127 AD patients and 121 controls with
CSF-biomarker-confirmed diagnosis (cut-off tau/A$\beta_{42}$: 0.52). Mass
spectrometry platforms determined the concentrations of 53 amine, 22 organic
acid, 120 lipid, and 40 oxidative stress compounds. Multiple signatures were
assessed: differential expression (nested linear models), classification
(logistic regression), and regulatory (network extraction).
  Results: Twenty-six metabolites were differentially expressed. Metabolites
improved the classification performance of clinical variables from 74% to 79%.
Network models identified 5 hubs of metabolic dysregulation: Tyrosine,
glycylglycine, glutamine, lysophosphatic acid C18:2 and platelet activating
factor C16:0. The metabolite network for APOE $\epsilon$4 negative AD patients
was less cohesive compared to the network for APOE $\epsilon$4 positive AD
patients.
  Discussion: Multiple signatures point to various promising peripheral markers
for further validation. The network differences in AD patients according to
APOE genotype may reflect different pathways to AD.
Facebook drives behavior of passive households in stock markets
Date: 2018-05-22 00:00:00
Tasks: Decision Making

Recent studies using data on social media and stock markets have mainly
focused on predicting stock returns. Instead of predicting stock price
movements, we examine the relation between Facebook data and investors'
decision making in stock markets with a unique data on investors' transactions
on Nokia. We find that the decisions to buy versus sell are associated with
Facebook data especially for passive households and also for nonprofit
organizations. At the same time, it seems that more sophisticated
investors---financial and insurance institutions---are behaving independently
from Facebook activities.
Changing Burial Practices Explain Temporal Trends in the 2014 Ebola Outbreak
Date: 2017-09-20 00:00:00

Background: The 2014 Ebola outbreak in West Africa was the largest on record,
resulting in over 25,000 total infections and 15,000 total deaths. Mathematical
modeling can be used to investigate the mechanisms driving transmission during
this outbreak -- in particular, burial practices appear to have been major
source of infections. Methodology/Principal Findings: We developed a
multi-stage model of Ebola virus transmission linked to a game-theoretic model
of population burial practice selection. We fit our model to cumulative
incidence and mortality data from Guinea, Liberia, and Sierra Leone from
January 2014 to March, 2016. The inclusion of behavior change substantially
improved best fit estimates and final size prediction compared to a reduced
model with fixed burials. Best fit trajectories suggest that the majority of
sanitary burial adoption occurred between July, 2014 and October, 2014.
However, these simulations also indicated that continued sanitary burial
practices waned following the resolution of the outbreak.
Conclusions/Significance: Surveillance data from the 2014 outbreak appears to
have a signal of changes in the dominant burial practices in all three
countries. Increased adoption of sanitary burials likely attenuated
transmission, but these changes occurred too late to prevent the explosive
growth of the outbreak during its early phase. For future outbreaks, explicitly
modeling behavior change and collecting data on transmission-related behaviors
may improve intervention planning and outbreak response.
Having your cake and eating it too: Scripted workflows for image manipulation
Date: 2017-08-29 00:00:00
Tasks: Image Manipulation

The reproducibility issue in science has come under increased scrutiny. One
consistent suggestion lies in the use of scripted methods or workflows for data
analysis. Image analysis is one area in science in which little can be done in
scripted methods. The SWIIM Project (Scripted Workflows to Improve Image
Manipulation) is designed to generate workflows from popular image manipulation
tools. In the project, 2 approaches are being taken to construct workflows in
the image analysis area. First, the open-source tool GIMP is being enhanced to
produce an active log (which can be run on a stand-alone basis to perform the
same manipulation). Second, the R system Shiny tool is being used to construct
a graphical user interface (GUI) which works with EBImage code to modify
images, and to produce an active log which can perform the same operations.
This process has been successful to date, but is not complete. The basic method
for each component is discussed, and example code is shown.
Arbitrage and Geometry
Date: 2017-09-21 00:00:00
Tasks: LEMMA

This article introduces the notion of arbitrage for a situation involving a
collection of investments and a payoff matrix describing the return to an
investor of each investment under each of a set of possible scenarios. We
explain the Arbitrage Theorem, discuss its geometric meaning, and show its
equivalence to Farkas' Lemma. We then ask a seemingly innocent question: given
a random payoff matrix, what is the probability of an arbitrage opportunity?
This question leads to some interesting geometry involving hyperplane
arrangements and related topics.