pwc-archive/papers-with-abstracts huggingface dataset:
Empirical forward price distribution from Bitcoin option prices
Date: 2019-01-15 00:00:00

Report presents analysis of empirical distribution of future returns of
bitcoin (BTC) from BTUSD inverse option prices. Logistic pdf is chosen as
underlying distribution to fit option prices. The result is satisfactory and
suggests that these prices can be described with just three or even one
parameter. Fitted Logistic pdf matches forward price movements upto a scaling
factor. Nevertheless, this observation stands alone and does not allow
stochastic description of underlying prices with logistic pdf in similar
fashion as it is done within Black-Scholes modelling framework. Put-call parity
relationship is derived connecting prices of vanilla inverse options and
futures.
Hopf-bifurcation analysis of pneumococcal pneumonia with time delays
Date: 2019-01-15 00:00:00
Tasks: Unity

In this paper, a mathematical model of pneumococcal pneumonia with time
delays is proposed. The stability theory of delay differential equations is
used to analyze the model. The results show that the disease-free equilibrium
is asymptotically stable if the control reproduction ratio R0 is less than
unity and unstable otherwise. The stability of equilibria with delays shows
that the endemic equilibrium is locally stable without delays and stable if the
delays are under conditions. The existence of Hopf-bifurcation is investigated
and transversality conditions proved. The model results suggest that as the
respective delays exceed some critical value past the endemic equilibrium, the
system loses stability through the process of local birth or death of
oscillations. Further, a decrease or an increase in the delays leads to
asymptotic stability or instability of the endemic equilibrium respectively.
The analytical results, are supported by numerical simulations.
  Keywords: Time delay, Pneumococcal pneumonia, Vaccination, Stability,
Hopf-bifurcation
Inference on Functionals under First Order Degeneracy
Date: 2019-01-15 00:00:00

This paper presents a unified second order asymptotic framework for
conducting inference on parameters of the form $\phi(\theta_0)$, where
$\theta_0$ is unknown but can be estimated by $\hat\theta_n$, and $\phi$ is a
known map that admits null first order derivative at $\theta_0$. For a large
number of examples in the literature, the second order Delta method reveals a
nondegenerate weak limit for the plug-in estimator $\phi(\hat\theta_n)$. We
show, however, that the `standard' bootstrap is consistent if and only if the
second order derivative $\phi_{\theta_0}''=0$ under regularity conditions,
i.e., the standard bootstrap is inconsistent if $\phi_{\theta_0}''\neq 0$, and
provides degenerate limits unhelpful for inference otherwise. We thus identify
a source of bootstrap failures distinct from that in Fang and Santos (2018)
because the problem (of consistently bootstrapping a \textit{nondegenerate}
limit) persists even if $\phi$ is differentiable. We show that the correction
procedure in Babu (1984) can be extended to our general setup. Alternatively, a
modified bootstrap is proposed when the map is \textit{in addition} second
order nondifferentiable. Both are shown to provide local size control under
some conditions. As an illustration, we develop a test of common conditional
heteroskedastic (CH) features, a setting with both degeneracy and
nondifferentiability -- the latter is because the Jacobian matrix is degenerate
at zero and we allow the existence of multiple common CH features.
Conversational Intent Understanding for Passengers in Autonomous Vehicles
Authors: Okur Eda, Kumar Shachi H, Sahay Saurav, Esme Asli Arslan, Nachman Lama
Date: 2018-12-14 00:00:00
Tasks: Autonomous Vehicles, Intent Recognition

Understanding passenger intents and extracting relevant slots are important
building blocks towards developing a contextual dialogue system responsible for
handling certain vehicle-passenger interactions in autonomous vehicles (AV).
When the passengers give instructions to AMIE (Automated-vehicle Multimodal
In-cabin Experience), the agent should parse such commands properly and trigger
the appropriate functionality of the AV system. In our AMIE scenarios, we
describe usages and support various natural commands for interacting with the
vehicle. We collected a multimodal in-cabin data-set with multi-turn dialogues
between the passengers and AMIE using a Wizard-of-Oz scheme. We explored
various recent Recurrent Neural Networks (RNN) based techniques and built our
own hierarchical models to recognize passenger intents along with relevant
slots associated with the action to be performed in AV scenarios. Our
experimental results achieved F1-score of 0.91 on utterance-level intent
recognition and 0.96 on slot extraction models.
Robust Power Allocation in Covert Communication: Imperfect CDI
Date: 2019-01-15 00:00:00

The study of the fundamental limits of covert communications, where a
transmitter Alice wants to send information to a desired recipient Bob without
detection of that transmission by an attentive and capable warden Willie, has
emerged recently as a topic of great research interest. Critical to these
analyses is a characterization of the detection problem that is presented to
Willie. Previous work has assumed that the channel distribution information
(CDI) is known to Alice, hence facilitating her characterization of Willie's
capabilities to detect the signal. However, in practice, Willie tends to be
passive and the environment heterogeneous, implying a lack of signaling
interchange between the transmitter and Willie makes it difficult if not
impossible for Alice to estimate the CDI exactly and provide covertness
guarantees. In this paper, we address this issue by developing covert
communication schemes for various assumptions on Alice's imperfect knowledge of
the CDI: 1) when the transmitter knows the channel distribution is within some
distance of a nominal channel distribution; 2) when only the mean and variance
of the channel distribution are available at Alice; 3) when Alice knows the
channel distribution is complex Gaussian but the variance is unknown. In each
case, we formulate new optimization problems to find the power allocations that
maximize covert rate subject to a covertness requirement under uncertain CDI.
Moreover, since Willie faces similar challenges as Alice in estimating the CDI,
we investigate two possible assumptions on the knowledge of the CDI at Willie:
1) CDI is known at Willie, 2) CDI is unknown at Willie. Numerical results are
presented to compare the proposed schemes from various aspects, in particular
the accuracy and efficiency of the proposed solutions for attaining desirable
covert system performance.
PROOF OF VALUE ALIENATION (PoVA) - a concept of a cryptocurrency issuance protocol
Date: 2019-01-15 00:00:00

In this paper, we will describe a concept of a cryptocurrency issuance
protocol which supports digital currencies in a Proof-of-Work (< PoW >) like
manner. However, the methods assume alternative utilization of assets used for
cryptocurrency creation (rather than purchasing electricity necessary for <
mining >).
Design and Analysis of Microfluidic Cell Counter using Spice Simulation
Authors: Sheikh Muhammad Asher Iqbal, Nauman Zaffar Butt
Date: 2019-01-15 00:00:00

Microfluidic cytometers based on coulter principle have recently shown a great potential for point of care biosensors for medical diagnostics. In this study, the design of coulter based microfluidic cytometer is investigated by using electrical circuit simulations. We explore the effects of physical dimensions of the microelectrodes, the measurement volume, size/morphology of the targeted cells, electrical properties of the reagents in the measurement volume, and, the impedance of external readout circuit, on the sensitivity of the sensor. We show that the effect of microelectrode's surface area and the dielectric properties of the suspension medium should be carefully considered when characterizing the output response of the sensor. In particular, the area of microelectrodes can have significant effect on cells electrical opacity( the ratio of the cell impedance at high to low frequency) which is commonly used to distinguish between sub-population of the target cells( e.g. lymphocytes vs monocytes when counting white blood cells).Moreover, we highlight that the opacity response vs frequency can significantly vary depending upon whether the absolute cell impedance or the differential output impedance is used in the calculation. These insights can provide valuable guidelines for the design and characterization of coulter based microfluidic sensors.
The stochastic extinction and stability conditions for a class of malaria epidemic models
Date: 2019-01-14 00:00:00

The stochastic extinction and stability in the mean of a family of SEIRS
malaria models with a general nonlinear incidence rate is presented. The
dynamics is driven by independent white noise processes from the disease
transmission and natural death rates. The basic reproduction number
$R^{*}_{0}$, the expected survival probability of the plasmodium
$E(e^{-(\mu_{v}T_{1}+\mu T_{2})})$, and other threshold values are calculated.
A sample Lyapunov exponential analysis for the system is utilized to obtain
extinction results. Moreover, the rate of extinction of malaria is estimated,
and innovative local Martingale and Lyapunov functional techniques are applied
to establish the strong persistence, and asymptotic stability in the mean of
the malaria-free steady population. %The extinction of malaria depends on
$R^{*}_{0}$, and $E(e^{-(\mu_{v}T_{1}+\mu T_{2})})$. Moreover, for either
$R^{*}_{0}<1$, or $E(e^{-(\mu_{v}T_{1}+\mu T_{2})})<\frac{1}{R^{*}_{0}}$,
whenever $R^{*}_{0}\geq 1$, respectively, extinction of malaria occurs.
Furthermore, the robustness of these threshold conditions to the intensity of
noise from the disease transmission rate is exhibited. Numerical simulation
results are presented.
Predicting Growth Rate from Gene Expression
Date: 2019-01-15 00:00:00

Growth rate is one of the most important and most complex phenotypic
characteristics of unicellular microorganisms, which determines the genetic
mutations that dominate at the population level, and ultimately whether the
population will survive. Translating changes at the genetic level to their
growth rate consequences remains a subject of intense interest, since such a
mapping could rationally direct experiments to optimize antibiotic efficacy or
bioreactor productivity. In this paper, we directly map transcriptional
profiles to growth rates by gathering published gene-expression data from
Escherichia coli and Saccharomyces cerevisiae with corresponding growth-rate
measurements. Using a machine-learning technique called k-nearest-neighbors
regression, we build a model which predicts growth rate from gene expression.
By exploiting the correlated nature of gene expression and sparsifying the
model, we capture 81% of the variance in growth rate of the E. coli dataset
while reducing the number of features from over 4,000 to nine. In S.
cerevisiae, we account for 89% of the variance in growth rate while reducing
from over 5,500 dimensions to 18. Such a model provides a basis for selecting
successful strategies from among the combinatorial number of experimental
possibilities when attempting to optimize complex phenotypic traits like growth
rate.
A study of the persistence and extinction of malaria in a family of epidemic models
Date: 2019-01-14 00:00:00

This paper investigates the deterministic extinction and permanence of a
family of SEIRS malaria models with multiple random delays, and with a general
nonlinear incidence rate. The conditions for the extinction and permanence of
the disease are presented. For the persistence of disease, improved analytical
techniques are employed to obtain eventual lower bounds for the states of the
system, while extinction results are obtained via analyzing the Lyapunov
exponent. The basic reproduction number $R^{*}_{0}$ is calculated, and for
$R^{*}_{0}<1$, extinction of disease occurs, while for $R^{*}_{0}\geq 1$, the
disease persists. But if $R^{*}_{0}\geq 1$, and the expected survival
probability of the plasmodium $E(e^{-(\mu_{v}T_{1}+\mu
T_{2})})<\frac{1}{R^{*}_{0}}$, then extinction occurs. Results are interpreted,
and numerical simulation examples are presented to (a) compare and evaluate the
impacts of the intensity of the incidence rate, and the intensity of response
to malaria control, on the persistence of malaria in the human population, and
(2) to justify the asymptotic stability of the disease-free equilibrium.
An Agent-Based Model to Explain the Emergence of Stylised Facts in Log Returns
Date: 2019-01-15 00:00:00
Tasks: Clustering

This paper outlines an agent-based model of a simple financial market in
which a single asset is available for trade by three different types of
traders. The model was first introduced in the PhD thesis of one of the
authors, see reference [1]. The simulated log returns are examined for the
presence of the stylised facts of financial data. The features of
leptokurtosis, volatility clustering and aggregational Gaussianity are
especially highlighted and studied in detail. The following ingredients are
found to be essential for the production of these stylised facts: the memory of
noise traders who make random trade decisions; the inclusion of technical
traders that trade in line with trends in the price and the inclusion of
fundamental traders who know the "fundamental value" of the stock and trade
accordingly. When these three basic types of traders are included log returns
are produced with a leptokurtic distribution and volatility clustering as well
as some further statistical features of empirical data. This enhances and
broadens our understanding of the fundamental processes involved in the
production of empirical data by the market.
A novel 3D display based on micro-volumetric scanning and real time reconstruction of holograms principle
Authors: Wang Guangjun
Date: 2018-12-16 00:00:00

The present study proposes a novel 3D display contains a micro-volumetric
scanning system (MVS) and a real time reconstruction hologram system (RTRH).
An Inattention Model for Traveler Behavior with e-Coupons
Date: 2018-12-28 00:00:00

In this study, we consider traveler coupon redemption behavior from the
perspective of an urban mobility service. Assuming traveler behavior is in
accordance with the principle of utility maximization, we first formulate a
baseline dynamical model for traveler's expected future trip sequence under the
framework of Markov decision processes and from which we derive approximations
of the optimal coupon redemption policy. However, we find that this baseline
model cannot explain perfectly observed coupon redemption behavior of traveler
for a car-sharing service. To resolve this deviation from utility-maximizing
behavior, we suggest a hypothesis that travelers may not be aware of all
coupons available to them. Based on this hypothesis, we formulate an
inattention model on unawareness, which is complementary to the existing models
of inattention, and incorporate it into the baseline model. Estimation results
show that the proposed model better explains the coupon redemption dataset than
the baseline model. We also conduct a simulation experiment to quantify the
negative impact of unawareness on coupons' promotional effects. These results
can be used by mobility service operators to design effective coupon
distribution schemes in practice.
Partial Relay Selection For Hybrid RF/FSO Systems with Hardware Impairments
Date: 2019-01-16 00:00:00

In this paper, we investigate the performance analysis of dual hop relaying
system consisting of asymmetric Radio Frequency (RF)/Free Optical Space (FSO)
links. The RF channels follow a Rayleigh distribution and the optical links are
subject to Gamma-Gamma fading. We also introduce impairments to our model and
we suggest Partial Relay Selection (PRS) protocol with Amplify-and-Forward (AF)
fixed gain relaying. The benefits of employing optical communication with RF,
is to increase the system transfer rate and thus improving the system
bandwidth. Many previous research attempts assuming ideal hardware (source,
relays, etc.) without impairments. In fact, this assumption is still valid for
low-rate systems. However, these hardware impairments can no longer be
neglected for high-rate systems in order to get consistent results. Novel
analytical expressions of outage probability and ergodic capacity of our model
are derived taking into account ideal and non-ideal hardware cases.
Furthermore, we study the dependence of the outage probability and the system
capacity considering, the effect of the correlation between the outdated CSI
(Channel State Information) and the current source-relay link, the number of
relays, the rank of the selected relay and the average optical Signal to Noise
Ratio (SNR) over weak and strong atmospheric turbulence. We also demonstrate
that for a non-ideal case, the end-to-end Signal to Noise plus Distortion Ratio
(SNDR) has a certain ceiling for high SNR range. However, the SNDR grows
infinitely for the ideal case and the ceiling caused by impairments no longer
exists. Finally, numerical and simulation results are presented.
Instantaneous Arbitrage and the CAPM
Authors: Lars Tyge Nielsen
Date: 2019-01-16 00:00:00
Tasks: Relation

This paper studies the concept of instantaneous arbitrage in continuous time and its relation to the instantaneous CAPM. Absence of instantaneous arbitrage is equivalent to the existence of a trading strategy which satisfies the CAPM beta pricing relation in place of the market. Thus the difference between the arbitrage argument and the CAPM argument in Black and Scholes (1973) is this: the arbitrage argument assumes that there exists some portfolio satisfying the capm equation, whereas the CAPM argument assumes, in addition, that this portfolio is the market portfolio.
Real-time separation of non-stationary sound fields on spheres
Date: 2019-01-16 00:00:00

The sound field separation methods can separate the target field from the
interfering noises, facilitating the study of the acoustic characteristics of
the target source, which is placed in a noisy environment. However, most of the
existing sound field separation methods are derived in the frequency-domain,
thus are best suited for separating stationary sound fields. In this paper, a
time-domain sound field separation method is developed that can separate the
non-stationary sound field generated by the target source over a sphere in
real-time. A spherical array sets up a boundary between the target source and
the interfering sources, such that the outgoing field on the array is only
generated by the target source. The proposed method decomposes the pressure and
the radial particle velocity measured by the array into spherical harmonics
coefficients, and recoveries the target outgoing field based on the time-domain
relationship between the decomposition coefficients and the theoretically
derived spatial filter responses. Simulations show the proposed method can
separate non-stationary sound fields both in free field and room environments,
and over a longer duration with small errors. The proposed method could serve
as a foundation for developing future time-domain spatial sound field
manipulation algorithms.
It's Only Words And Words Are All I Have
Authors: Barman Manash Pratim, Dahekar Kavish, Anshuman Abhinav, Awekar Amit
Date: 2019-01-16 00:00:00
Tasks: All, Binary Classification, General Classification, Multi-class Classification

The central idea of this paper is to demonstrate the strength of lyrics for
music mining and natural language processing (NLP) tasks using the distributed
representation paradigm. For music mining, we address two prediction tasks for
songs: genre and popularity. Existing works for both these problems have two
major bottlenecks. First, they represent lyrics using handcrafted features that
require intricate knowledge of language and music. Second, they consider lyrics
as a weak indicator of genre and popularity. We overcome both the bottlenecks
by representing lyrics using distributed representation. In our work, genre
identification is a multi-class classification task whereas popularity
prediction is a binary classification task. We achieve an F1 score of around
0.6 for both the tasks using only lyrics. Distributed representation of words
is now heavily used for various NLP algorithms. We show that lyrics can be used
to improve the quality of this representation.
Edge-masked CT image reconstruction from limited data
Date: 2019-01-16 00:00:00
Tasks: Image Reconstruction

This paper presents an iterative inversion algorithm for computed tomography
image reconstruction that performs well in terms of accuracy and speed using
limited data. The computational method combines an image domain technique and
statistical reconstruction by using an initial filtered back projection
reconstruction to create a binary edge mask, which is then used in an
l2-regularized reconstruction. Both theoretical and empirical results are
offered to support the algorithm. While in this paper a simple forward model is
used and physical edges are used as the sparse feature, the proposed method is
flexible and can accommodate any forward model and sparsifying transform.
Design of APRS Modem Using IC TCM3105 and ATMega2560 Microcontroller
Date: 2019-01-10 00:00:00

APRS technology is still exists and still developing among amateur radio.
However, in Indonesia there are still not many people who use and utilize APRS.
The high price of APRS modem and difficulties of getting APRS modems is one of
the factors affecting the public interest in APRS. In Indonesia, no one has
developed APRS modem, so that our paper will be discuss about design and
develop of APRS modem using cheap and easy components FSK modem IC TCM3105 and
ATmega2560 as microcontroller. The implementation of APRS standard protocol on
modem that has been made use C programming language on Arduino IDE and the
schematic design and printed circuit board layout use Proteus 8. IC TCM3105
selection is based on the specification of eligible components of APRS device
able to set the baud rate of 1200 bps with FSK modulation technique. The
ATmega2560 microcontroller is chosen as the information signal encoding
processor and calculate the CRC-16-X25 FCS (Frame Check Sequence) for the
information packet according to the standard AX.25 UI Frame APRS protocol.
AX.25 UI Frame APRS protocol consists of flag, destination address, source
address, digipeater address, control field, protocol ID, information field and
FCS. The result of this paper is APRS modem device that has been made can send
the APRS information packet very well. This is proved by APRS packet that has
been sent can be received and repeated by ground station of Pusteksat LAPAN
also connected on APRS international network in aprs.fi. In addition, the
information that has been sent from APRS modem can be decoded correctly by APRS
software decoder such as Soundmodem, AFSK1200, dan AX.25-SCS.
Design of generalized fractional order gradient descent method
Date: 2020-02-16 00:00:00

This paper focuses on the convergence problem of the emerging fractional
order gradient descent method, and proposes three solutions to overcome the
problem. In fact, the general fractional gradient method cannot converge to the
real extreme point of the target function, which critically hampers the
application of this method. Because of the long memory characteristics of
fractional derivative, fixed memory principle is a prior choice. Apart from the
truncation of memory length, two new methods are developed to reach the
convergence. The one is the truncation of the infinite series, and the other is
the modification of the constant fractional order. Finally, six illustrative
examples are performed to illustrate the effectiveness and practicability of
proposed methods.