pwc-archive/papers-with-abstracts huggingface dataset:
A Hybrid Recommendation Method Based on Feature for Offline Book Personalization
Authors: Li Xixi, Xing Jiahao, Wang Haihui, Zheng Lingfang, Jia Suling, Wang Qiang
Date: 2018-04-26 00:00:00
Tasks: Collaborative Filtering

Recommendation system has been widely used in different areas. Collaborative
filtering focuses on rating, ignoring the features of items itself. In order to
effectively evaluate customers preferences on books, taking into consideration
of the characteristics of offline book retail, we use LDA model to calculate
customers preference on book topics and use word2vec to calculate customers
preference on book types. When forecasting rating on books, we take two factors
into consideration: similarity of customers and correlation between customers
and books. The experiment shows that our hybrid recommendation method based on
features performances better than single recommendation method in offline book
retail data.
Identifying Effects of Multivalued Treatments
Date: 2018-04-30 00:00:00

Multivalued treatment models have typically been studied under restrictive
assumptions: ordered choice, and more recently unordered monotonicity. We show
how treatment effects can be identified in a more general class of models that
allows for multidimensional unobserved heterogeneity. Our results rely on two
main assumptions: treatment assignment must be a measurable function of
threshold-crossing rules, and enough continuous instruments must be available.
We illustrate our approach for several classes of models.
Machine Learning for Predictive On-Demand Deployment of UAVs for Wireless Communications
Date: 2018-04-30 00:00:00
Tasks: BIG-bench Machine Learning, Fairness

In this paper, a novel machine learning (ML) framework is proposed for
enabling a predictive, efficient deployment of unmanned aerial vehicles (UAVs),
acting as aerial base stations (BSs), to provide on-demand wireless service to
cellular users. In order to have a comprehensive analysis of cellular traffic,
an ML framework based on a Gaussian mixture model (GMM) and a weighted
expectation maximization (WEM) algorithm is introduced to predict the potential
network congestion. Then, the optimal deployment of UAVs is studied to minimize
the transmit power needed to satisfy the communication demand of users in the
downlink, while also minimizing the power needed for UAV mobility, based on the
predicted cellular traffic. To this end, first, the optimal partition of
service areas of each UAV is derived, based on a fairness principle. Next, the
optimal location of each UAV that minimizes the total power consumption is
derived. Simulation results show that the proposed ML approach can reduce the
required downlink transmit power and improve the power efficiency by over 20%,
compared with an optimal deployment of UAVs with no ML prediction.
Measuring uncertainty during respiratory rate estimation using pressure-sensitive mats
Date: 2018-04-30 00:00:00
Tasks: Respiratory Rate Estimation

We develop and evaluate a respiratory rate estimation algorithm that utilizes
data from pressure-sensitive mat (PSM) technology for continuous patient
monitoring in neonatal intensive care units (NICU). An analysis of the random
effect of drift and systematic effect of creep in the PSM data is presented,
showing that these are essentially dependent on the applied load and contact
surface. Uncertainty measurements are pivotal when estimating physiologic
parameters. The standard uncertainty in the PSM data is here represented by the
percent drift. Next, we evaluate the applicability of PSM technology to
estimate RR in neonatal patient simulator trials under five mixed effects
including internally and externally induced motion, mattress type, grunting,
laying position, and different breathing rates. We analyze the limits of
agreement on the mixed effects model to derive the uncertainty in the estimated
RR obtained through two estimation techniques. In comparison with the gold
standard RR values, we achieved a mean bias of 0.56 breaths per minute (bpm)
with an error bounded by a 95% confidence interval of [-2.26, 3.37] bpm. These
results meet the clinical accuracy requirements of RR within +/-5 bpm.
Comparing time and frequency domain estimation of neonatal respiratory rate using pressure-sensitive mats
Date: 2018-04-30 00:00:00

Pressure-sensitive mats (PSM) have proved to be useful in the estimation of
respiratory rates (RR) in adult patients. However, PSM technology has not been
extensively applied to derive physiologic parameters in infant and neonatal
patients. This research evaluates the applicability of the capacitive XSensor
PSM technology to estimate a range of RR in neonatal patient simulator trials
conducted under several experimental conditions. PSM data are analyzed in both
the time and frequency domain and comparative results are presented. For the
frequency-domain approach, in addition to estimating RR, a measure of
confidence is also derived from the relative height of peaks in the
periodogram. The study demonstrates that frequency domain analysis of
mean-shifted PSM data achieves the best possible RR estimation, with zero
percent error, as compared to the lowest achievable RMS error of 1.57 percent
in the time domain. The frequency domain approach outperforms the time domain
analysis whether examining raw data or those preprocessed by normalizing,
detrending and median filtering.
Implementation of Artifact Detection in Critical Care: A Methodological Review
Date: 2018-04-30 00:00:00
Tasks: Artifact Detection, Event Detection

Artifact Detection (AD) techniques minimize the impact of artifacts on
physiologic data acquired in Critical Care Units (CCU) by assessing quality of
data prior to Clinical Event Detection (CED) and Parameter Derivation (PD).
This methodological review introduces unique taxonomies to synthesize over 80
AD algorithms based on these six themes: (1) CCU; (2) Physiologic Data Source;
(3) Harvested data; (4) Data Analysis; (5) Clinical Evaluation; and (6)
Clinical Implementation. Review results show that most published algorithms:
(a) are designed for one specific type of CCU; (b) are validated on data
harvested only from one Original Equipment Manufacturer (OEM) monitor; (c)
generate Signal Quality Indicators (SQI) that are not yet formalised for useful
integration in clinical workflows; (d) operate either in standalone mode or
coupled with CED or PD applications; (e) are rarely evaluated in real-time; and
(f) are not implemented in clinical practice. In conclusion, it is recommended
that AD algorithms conform to generic input and output interfaces with commonly
defined data: (1) type; (2) frequency; (3) length; and (4) SQIs. This shall
promote (a) reusability of algorithms across different CCU domains; (b)
evaluation on different OEM monitor data; (c) fair comparison through
formalised SQIs; (d) meaningful integration with other AD, CED and PD
algorithms; and (e) real-time implementation in clinical workflows.
FPGA Acceleration of Short Read Alignment
Date: 2018-04-30 00:00:00

Aligning millions of short DNA or RNA reads, of 75 to 250 base pairs each, to
a reference genome is a significant computation problem in bioinformatics. We
present a flexible and fast FPGA-based short read alignment tool. Our aligner
makes use of the processing power of FPGAs in conjunction with the greater host
memory bandwidth and flexibility of software to improve performance and achieve
a high level of configurability. This flexible design supports a variety of
reference genome sizes without the performance degradation suffered by other
software and FPGA-based aligners. It is also better able to support the
features of new alignment algorithms, which frequently crop up in the rapidly
evolving field of bioinformatics. We demonstrate these advantages in a case
study where we align RNA-Seq data from a hypothesized mouse / human xenograft.
In this case study, our aligner provides a speedup of 5.6x over BWA-SW with
energy savings of 21%, while also reducing incorrect short read classification
by 29%. To demonstrate the flexibility of our system we show that the speedup
can be substantially improved while retaining most of the accuracy gains over
BWA-SW. The speedup can be increased to 71.3x, while still enjoying a 28%
incorrect classification improvement and 52% improvement in unaligned reads.
Fixation probabilities for the Moran process in evolutionary games with two strategies: graph shapes and large population asymptotics
Date: 2018-04-30 00:00:00
Tasks: Math

This paper is based on the complete classification of evolutionary scenarios
for the Moran process with two strategies given by Taylor et al. (B. Math.
Biol. 66(6): 1621--1644, 2004). Their classification is based on whether each
strategy is a Nash equilibrium and whether the fixation probability for a
single individual of each strategy is larger or smaller than its value for
neutral evolution. We improve on this analysis by showing that each
evolutionary scenario is characterized by a definite graph shape for the
fixation probability function. A second class of results deals with the
behavior of the fixation probability when the population size tends to
infinity. We develop asymptotic formulae that approximate the fixation
probability in this limit and conclude that some of the evolutionary scenarios
cannot exist when the population size is large.
Hardware Implementation of A Non-RLL Soft-decoding Beacon-based Visible Light Communication Receiver
Date: 2018-05-30 00:00:00
Tasks: Indoor Localization

Visible light communication (VLC)-based beacon systems, which usually
transmit identification (ID) information in small-size data frames are applied
widely in indoor localization applications. There is one fact that flicker of
LED light should be avoid in any VLC systems. Current flicker mitigation
solutions based on run-length limited (RLL) codes suffer from reduced code
rates, or are limited to hard-decoding forward error correction (FEC) decoders.
Recently, soft-decoding techniques of RLL-codes are proposed to support
soft-decoding FEC algorithms, but they contain potentials of high-complexity
and time-consuming computations. Fortunately, non-RLL direct current
(DC)-balance solutions can overcome the drawbacks of RLL-based algorithms,
however, they meet some difficulties in system latency or inferior
error-correction performances. Recently, non-RLL flicker mitigation solution
based on Polar code has proved to be an optimal approach due to its natural
equal probabilities of short runs of 1's and 0's with high error-correction
performance. However, we found that this solution can only maintain the DC
balance only when the data frame length is sufficiently long. Accordingly,
short beacon-based data frames might still be a big challenge for flicker
mitigation in such non-RLL cases. In this paper, we introduce a flicker
mitigation solution designed for VLC-based beacon systems that combines a
simple pre-scrambler with a Polar encoder which has a codeword smaller than the
previous work 8 times. We also propose a hardware architecture for the proposed
compact non-RLL VLC receiver for the first time. Also, a 3-bit soft-decision
filter is introduce to enable soft-decoding of Polar decoder to improve the
performance of the receiver.
A code-free optical undersampling technique for broadband microwave spectrum measurement
Date: 2019-07-31 00:00:00

A novel broadband microwave (MW) spectrum measurement (BMSM) scheme based on
code-free optical undersampling and homodyne detection is proposed. The fully
analog generation of optical pulses with a far-less-than-Nyquist rate is only
through modulating cascaded electrooptical modulators by a single RF tone
instead of any high-speed coding sequence modulation. Homodyne detection will
reduce the analysis bandwidth of BMSM and enhance the detection performance of
weak signal. A multi-band signal with 20 GHz spectral range and SNR = 61 dB is
used to investigate the BMSM performance of this scheme, and the results show
good performance for BMSM. The potentials for further optimization in practice
are also discussed.
Impact of Vehicle-to-Vehicle Communication Reliability on Safety Applications: An Experimental Study
Date: 2018-04-29 00:00:00

Vehicle-to-Vehicle (V2V) communication using Dedicated Short Range
Communications (DSRC) technology provides promising benefits for drastically
reducing vehicle collisions. A decentralized approach combined with DSRC allow
vehicles in a highly mobile and complex network to send and receive safety
messages with high reliability and low latency. Notably, there are many factors
that may cause the system to become unreliable due to communication failures.
While the reliability of V2V communication has been a subject of study by
researchers, there is still open questions regarding how the placement of DSRC
devices (inside or outside the host vehicle), the vehicle's interior elements
or the differences in altitude can affect the V2V communications. This paper
aims to provide experimental testing data and analysis to quantify the impact
of relative vehicle speeds, differences in altitudes between two vehicles, and
vehicle's interior obstacles (which can vary depending on the placement of DSRC
device and when communicating with front vs. rear vehicles) on the reliability
of V2V communications.
Novel Hard Link-Switching Scheme using Pre-Scanning for Indoor VLC Networks
Date: 2018-04-21 00:00:00
Tasks: Position

VLC is attracting a lot of attention as an emerging potential technology for
deployment in next generation indoor wireless networks. Use of efficient link
switching scheme among VLC access points is critical in indoor environment to
provide seamless connectivity to mobile users. This paper presents a novel
position prediction link switching scheme for indoor visible light
communication systems. The method exploits the fact that indoor scenario (light
fixtures/furniture) mostly remains unchanged, therefore, this information can
be stored at the coordinator end. Thus, the user is not required to search for
the best transmitter when RSS is reduced to a threshold value as in
conventional methods which cause substantial delay in switching process.
Simulation results show that the proposed scheme for indoor VLC System achieves
the dual purpose of adequate illumination and mobility to user in considered
indoor scenario.
Agents' beliefs and economic regimes polarization in interacting markets
Date: 2018-04-20 00:00:00

In the present paper a model of a market consisting of real and financial
interacting sectors is studied. Agents populating the stock market are assumed
to be not able to observe the true underlying fundamental, and their beliefs
are biased by either optimism or pessimism. Depending on the relevance they
give to beliefs, they select the best performing strategy in an evolutionary
perspective. The real side of the economy is described within a
multiplier-accelerator framework with a nonlinear, bounded investment function.
We show that strongly polarized beliefs in an evolutionary framework can
introduce multiplicity of steady states, which, consisting in enhanced or
depressed levels of income, reflect and reproduce the optimistic or pessimistic
nature of the agents' beliefs. The polarization of these steady states, which
coexist with an unbiased steady state, positively depends on that of the
beliefs and on their relevance. Moreover, with a mixture of analytical and
numerical tools, we show that such static characterization is inherited also at
the dynamical level, with possibly complex attractors that are characterized by
endogenously fluctuating pessimistic and optimistic levels of national income
and price. This framework, when stochastic perturbations are included, is able
to account for stylized facts commonly observed in real financial markets, such
as fat tails and excess volatility in the returns distributions, as well as
bubbles and crashes for stock prices.
Aide et Croissance dans les pays de l'Union Economique et Mon{\'e}taire Ouest Africaine (UEMOA) : retour sur une relation controvers{\'e}e
Date: 2018-04-13 00:00:00

The main purpose of this paper is to analyze threshold effects of official
development assistance (ODA) on economic growth in WAEMU zone countries. To
achieve this, the study is based on OECD and WDI data covering the period
1980-2015 and used Hansen's Panel Threshold Regression (PTR) model to
"bootstrap" aid threshold above which its effectiveness is effective. The
evidence strongly supports the view that the relationship between aid and
economic growth is non-linear with a unique threshold which is 12.74% GDP.
Above this value, the marginal effect of aid is 0.69 points, "all things being
equal to otherwise". One of the main contribution of this paper is to show that
WAEMU countries need investments that could be covered by the foreign aid. This
later one should be considered just as a complementary resource. Thus, WEAMU
countries should continue to strengthen their efforts in internal resource
mobilization in order to fulfil this need.
Epidemiological data challenges: planning for a more robust future through data standards
Authors: Fairchild Geoffrey, Tasseff Byron, Khalsa Hari, Generous Nicholas, Daughton Ashlynn R., Velappan Nileena, Priedhorsky Reid, Deshpande Alina
Date: 2018-11-24 00:00:00
Tasks: Decision Making

Accessible epidemiological data are of great value for emergency preparedness
and response, understanding disease progression through a population, and
building statistical and mechanistic disease models that enable forecasting.
The status quo, however, renders acquiring and using such data difficult in
practice. In many cases, a primary way of obtaining epidemiological data is
through the internet, but the methods by which the data are presented to the
public often differ drastically among institutions. As a result, there is a
strong need for better data sharing practices. This paper identifies, in detail
and with examples, the three key challenges one encounters when attempting to
acquire and use epidemiological data: 1) interfaces, 2) data formatting, and 3)
reporting. These challenges are used to provide suggestions and guidance for
improvement as these systems evolve in the future. If these suggested data and
interface recommendations were adhered to, epidemiological and public health
analysis, modeling, and informatics work would be significantly streamlined,
which can in turn yield better public health decision-making capabilities.
Seemless Utilization of Heterogeneous XSede Resources to Accelerate Processing of a High Value Functional Neuroimaging Dataset
Date: 2018-05-17 00:00:00

We describe the technical effort used to process a voluminous high value
human neuroimaging dataset on the Open Science Grid with opportunistic use of
idle HPC resources to boost computing capacity more than 5-fold. With minimal
software development effort and no discernable competitive interference with
other HPC users, this effort delivered 15,000,000 core hours over 7 months.
Approximate Analytical Solution of a Cancer Immunotherapy Model by the Application of Differential Transform and Adomian Decomposition Methods
Date: 2018-04-21 00:00:00

Immunotherapy plays a major role in tumour treatment, in comparison with
other methods of dealing with cancer. The Kirschner-Panetta (KP) model of
cancer immunotherapy describes the interaction between tumour cells, effector
cells and interleukin-2 which are clinically utilized as medical treatment. The
model selects a rich concept of immune-tumour dynamics. In this paper,
approximate analytical solutions to KP model are represented by using the
differential transform and Adomian decomposition. The complicated nonlinearity
of the KP system causes the application of these two methods to require more
involved calculations. The approximate analytical solutions to the model are
compared with the results obtained by numerical fourth order Runge-Kutta
method.
Identification of Key Proteins Involved in Axon Guidance Related Disorders: A Systems Biology Approach
Authors: Ishtiaque Ahammad
Date: 2018-04-17 00:00:00

Axon guidance is a crucial process for growth of the central and peripheral nervous systems. In this study, 3 axon guidance related disorders, namely- Duane Retraction Syndrome (DRS) , Horizontal Gaze Palsy with Progressive Scoliosis (HGPPS) and Congenital fibrosis of the extraocular muscles type 3 (CFEOM3) were studied using various Systems Biology tools to identify the genes and proteins involved with them to get a better idea about the underlying molecular mechanisms including the regulatory mechanisms. Based on the analyses carried out, 7 significant modules have been identified from the PPI network. Five pathways/processes have been found to be significantly associated with DRS, HGPPS and CFEOM3 associated genes. From the PPI network, 3 have been identified as hub proteins- DRD2, UBC and CUL3.
When a `rat race' implies an intergenerational wealth trap
Date: 2018-04-30 00:00:00

Two critical questions about intergenerational outcomes are: one, whether
significant barriers or traps exist between different social or economic
strata; and two, the extent to which intergenerational outcomes do (or can be
used to) affect individual investment and consumption decisions. We develop a
model to explicitly relate these two questions, and prove the first such `rat
race' theorem, showing that a fundamental relationship exists between high
levels of individual investment and the existence of a wealth trap, which traps
otherwise identical agents at a lower level of wealth. Our simple model of
intergenerational wealth dynamics involves agents which balance current
consumption with investment in a single descendant. Investments then determine
descendant wealth via a potentially nonlinear and discontinuous competitiveness
function about which we do not make concavity assumptions. From this model we
demonstrate how to infer such a competitiveness function from investments,
along with geometric criteria to determine individual decisions. Additionally
we investigate the stability of a wealth distribution, both to local
perturbations and to the introduction of new agents with no wealth.
Evaluation of 5G New Radio Non-orthogonal Multiple Access Methods for Military Applications
Date: 2019-05-20 00:00:00

Non-orthogonal multiple access (NOMA) is an enabling technique to support
massive connectivity and utilize the radio resources more efficiently. A number
of novel NOMA schemes have been proposed for 5G New Radio (NR) standards. In
this study, we evaluate various 5G NOMA methods for different military
communications scenarios. First, we provide the description of basic principles
in each evaluated scheme, then we investigate and compare their performances
under different system parameters such as spectral efficiency, overload factor
and antenna numbers in various channel models. Finally, we provide the
discussions and insights on the suitability of the evaluated schemes for the
considered military scenarios based on simulations.