pwc-archive/papers-with-abstracts huggingface dataset:
Pricing Formulae of Power Binary and Normal Distribution Standard Options and Applications
Authors: Hyong-Chol O, Dae-Sung Choe
Date: 2019-03-11 00:00:00

In this paper the Buchen's pricing formulae of (higher order) asset and bond binary options are incorporated into the pricing formula of power binary options and a pricing formula of "the normal distribution standard options" with the maturity payoff related to a power function and the density function of normal distribution is derived. And as their applications, pricing formulae of savings plans that provide a choice of indexing and discrete geometric average Asian options are derived and the fact that the price of discrete geometric average Asian option converges to the price of continuous geometric average Asian option when the largest distance between neighboring monitoring times goes to zero is proved.
Affine term structure models : a time-changed approach with perfect fit to market curves
Date: 2020-01-24 00:00:00

We address the so-called calibration problem which consists of fitting in a
tractable way a given model to a specified term structure like, e.g., yield or
default probability curves. Time-homogeneous jump-diffusions like Vasicek or
Cox-Ingersoll-Ross (possibly coupled with compounded Poisson jumps, JCIR), are
tractable processes but have limited flexibility; they fail to replicate actual
market curves. The deterministic shift extension of the latter (Hull-White or
JCIR++) is a simple but yet efficient solution that is widely used by both
academics and practitioners. However, the shift approach is often not
appropriate when positivity is required, which is a common constraint when
dealing with credit spreads or default intensities. In this paper, we tackle
this problem by adopting a time change approach. On the top of providing an
elegant solution to the calibration problem under positivity constraint, our
model features additional interesting properties in terms of implied
volatilities. It is compared to the shift extension on various credit risk
applications such as credit default swap, credit default swaption and credit
valuation adjustment under wrong-way risk. The time change approach is able to
generate much larger volatility and covariance effects under the positivity
constraint. Our model offers an appealing alternative to the shift in such
cases.
Highway traffic data: macroscopic, microscopic and criticality analysis for capturing relevant traffic scenarios and traffic modeling based on the highD data set
Date: 2019-03-11 00:00:00

This work provides a comprehensive analysis on naturalistic driving behavior
for highways based on the highD data set. Two thematic fields are considered.
First, some macroscopic and microscopic traffic statistics are provided. These
include the traffic flow rate and the traffic density, as well as velocity,
acceleration and distance distributions. Additionally, the dependencies to each
other are examined and compared to related work. The second part investigates
the distributions of criticality measures. The Time-To-Collision, Time-Headway
and a third measure, which couples both, are analyzed. These measures are also
combined with other indicators. Scenarios, in which these measures reach a
critical level, are separately discussed. The results are compared to related
work as well. The two main contributions of this work can be stated as follows.
First, the analysis on the criticality measures can be used to find suitable
thresholds for rare traffic scenarios. Second, the statistics provided in this
work can also be utilized for traffic modeling, for example in simulation
environments.
A fractional-order difference Cournot duopoly game with long memory
Date: 2019-03-11 00:00:00

We reconsider the Cournot duopoly problem in light of the theory for long
memory. We introduce the Caputo fractional-order difference calculus to
classical duopoly theory to propose a fractional-order discrete Cournot duopoly
game model, which allows participants to make decisions while making full use
of their historical information. Then we discuss Nash equilibria and local
stability by using linear approximation. Finally, we detect the chaos of the
model by employing a 0-1 test algorithm.
Using satellite image classification and digital terrain modelling to assess forest species distribution on mountain slopes.A case study in Varatec Forest District
Date: 2019-03-11 00:00:00
Tasks: image-classification, Image Classification, Satellite Image Classification

The relation between ecological conditions and geomorphological factors is
considered the basis for species distribution in Romania. In this context, the
location of each species within parts of the mountain slopes is difficult on a
medium to brad scale level. The paper presents methodology to combine
vegetation data, obtained from IKONOS satellite images, and Digital Elevation
Model obtained from digitized topographic maps. The study area is a northern
slope of the Stanisoarei Mountains with a gradient of species from beech mixed
and coniferous stands.
Reactive learning strategies for iterated games
Date: 2019-03-11 00:00:00

In an iterated game between two players, there is much interest in
characterizing the set of feasible payoffs for both players when one player
uses a fixed strategy and the other player is free to switch. Such
characterizations have led to extortionists, equalizers, partners, and rivals.
Most of those studies use memory-one strategies, which specify the
probabilities to take actions depending on the outcome of the previous round.
Here, we consider "reactive learning strategies," which gradually modify their
propensity to take certain actions based on past actions of the opponent. Every
linear reactive learning strategy, $\mathbf{p}^{\ast}$, corresponds to a memory
one-strategy, $\mathbf{p}$, and vice versa. We prove that for evaluating the
region of feasible payoffs against a memory-one strategy,
$\mathcal{C}\left(\mathbf{p}\right)$, we need to check its performance against
at most $11$ other strategies. Thus, $\mathcal{C}\left(\mathbf{p}\right)$ is
the convex hull in $\mathbb{R}^{2}$ of at most $11$ points. Furthermore, if
$\mathbf{p}$ is a memory-one strategy, with feasible payoff region
$\mathcal{C}\left(\mathbf{p}\right)$, and $\mathbf{p}^{\ast}$ is the
corresponding reactive learning strategy, with feasible payoff region
$\mathcal{C}\left(\mathbf{p}^{\ast}\right)$, then
$\mathcal{C}\left(\mathbf{p}^{\ast}\right)$ is a subset of
$\mathcal{C}\left(\mathbf{p}\right)$. Reactive learning strategies are
therefore powerful tools in restricting the outcomes of iterated games.
Individual-Level SNP Diversity and Similarity Profiles
Date: 2019-03-11 00:00:00
Tasks: Diversity

Classic concepts of genetic (gene) diversity (heterozygosity) such as Nei
(1973: PNAS) and Nei and Li (1979: PNAS) nucleotide diversity were defined
within the context of populations. Although variations are often measured in
population context, the basic carriers of variation are individuals. Hence,
measuring variations such as SNP of individual against a reference genome,
which has been ignored currently, is certainly of its own right. Indeed,
similar practice has been a tradition in ecology, where the basic framework of
diversity measure is individual community sample. We propose to use
Renyi-entropy-derived Hill numbers to define SNP (single nucleotide
polymorphism) diversity (including alpha-, beta-, and gamma-diversities) and
similarity profiles. Hill numbers are derived from Renyi entropy, of which
Shannon entropy is a special case and which have found widely applications
including measuring the quantum information entanglement, wealth distribution
in economics and ecological diversity. The newly proposed SNP diversity not
only complements the existing genetic diversity concepts by offering
individual-level metrics, but also offers building blocks for comparative
genetic analysis at higher levels. The profile concept also helps to resolve a
dilemma in measuring diversity: the choice from various diversity indexes,
because diversity profile unifies some of the most commonly used indexes (as
special cases) with different diversity orders (along the rareness-commonness
spectrum of gene mutations). Finally, the profiles can be estimated with
rarefaction approach, which may help to relieve some effect of insufficient
sequencing coverage.
Emergence of Brain Rhythms: Model Interpretation of EEG Data
Date: 2019-03-11 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

Electroencephalography (EEG) monitors ---by either intrusive or noninvasive
electrodes--- time and frequency variations and spectral content of voltage
fluctuations or waves, known as brain rhythms, which in some way uncover
activity during both rest periods and specific events in which the subject is
under stimulus. This is a useful tool to explore brain behavior, as it
complements imaging techniques that have a poorer temporal resolution. We here
approach the understanding of EEG data from first principles by studying a
networked model of excitatory and inhibitory neurons which generates a variety
of comparable waves. In fact, we thus reproduce $\alpha$, $\beta,$ $\gamma$ and
other rhythms as observed by EEG, and identify the details of the respectively
involved complex phenomena, including a precise relationship between an input
and the collective response to it. It ensues the potentiality of our model to
better understand actual mind mechanisms and its possible disorders, and we
also describe kind of stochastic resonance phenomena which locate main
qualitative changes of mental behavior in (e.g.) humans. We also discuss the
plausible use of these findings to design deep learning algorithms to detect
the occurence of phase transitions in the brain and to analyse its
consequences.
Computation of the phase step between two-step fringe patterns based on Gram--Schmidt algorithm
Date: 2019-03-11 00:00:00

We present the evaluation of a closed form formula for the calculation of the
original step between two randomly shifted fringe patterns. Our proposal
extends the Gram--Schmidt orthonormalization algorithm for fringe pattern.
Experimentally, the phase shift is introduced by a electro--mechanical devices
(such as piezoelectric or moving mounts).The estimation of the actual phase
step allows us to improve the phase shifting device calibration. The evaluation
consists of three cases that represent different pre-normalization processes:
First, we evaluate the accuracy of the method in the orthonormalization process
by estimating the test step using synthetic normalized fringe patterns with no
background, constant amplitude and different noise levels. Second, we evaluate
the formula with a variable amplitude function on the fringe patterns but with
no background. Third, we evaluate non-normalized noisy fringe patterns
including the comparison of pre-filtering processes such as the Gabor filter
banks and the isotropic normalization process, in order to emphasize how they
affect in the calculation of the phase step.
Toxin-mediated competition in weakly motile bacteria
Date: 2019-07-18 00:00:00

Many bacterial species produce toxins that inhibit their competitors. We
model this phenomenon by extending classic two-species Lotka-Volterra
competition in one spatial dimension to incorporate toxin production by one
species. Considering solutions comprising two adjacent single-species colonies,
we show how the toxin inhibits the susceptible species near the interface
between the two colonies. Moreover, a sufficiently effective toxin inhibits the
susceptible species to such a degree that an `inhibition zone' is formed
separating the two colonies. In the special case of truly non-motile bacteria,
i.e. with zero bacterial diffusivity, we derive analytical expressions
describing the bacterial distributions and size of the inhibition zone. In the
more general case of weakly motile bacteria, i.e. small bacterial diffusivity,
these two-colony solutions become travelling waves. We employ numerical methods
to show that the wavespeed is dependent upon both interspecific competition and
toxin strength; precisely which colony expands at the expense of the other
depends upon the choice of parameter values. In particular, a sufficiently
effective toxin allows the producer to expand at the expense of the
susceptible, with a wavespeed magnitude that is bounded above as the toxin
strength increases. This asymptotic wavespeed is independent of interspecific
competition and due to the formation of the inhibition zone; when the colonies
are thus separated, there is no longer direct competition between the two
species and the producer can invade effectively unimpeded by its competitor. We
note that the minimum toxin strength required to produce an inhibition zone
increases rapidly with increasing bacterial diffusivity, suggesting that even
moderately motile bacteria must produce very strong toxins if they are to
benefit in this way.
Hyperspectral Calibration of Art: Acquisition and Calibration Workflows
Authors: Ruven Pillay, Jon Y Hardeberg, Sony George
Date: 2019-03-11 00:00:00
Tasks: Change Detection

Hyperspectral imaging has become an increasingly used tool in the analysis of works of art. However, the quality of the acquired data and the processing of that data to produce accurate and reproducible spectral image cubes can be a challenge to many cultural heritage users. The calibration of data that is both spectrally and spatially accurate is an essential step in order to obtain useful and relevant results from hyperspectral imaging. Data that is too noisy or inaccurate will produce sub-optimal results when used for pigment mapping, the detection of hidden features, change detection or for quantitative spectral documentation. To help address this, therefore, we will examine the specific acquisition and calibration workflows necessary for works of art. These workflows includes the key parameters that must be addressed during acquisition and the essential steps and issues at each of the stages required during post-processing in order to fully calibrate hyperspectral data. In addition we will look in detail at the key issues that affect data quality and propose practical solutions that can make significant differences to overall hyperspectral image quality.
Non-Uniform BCSK Modulation in Nutrient-Limited Relay-Assisted Molecular Communication System: Optimization and Performance Evaluation
Date: 2019-05-15 00:00:00

In this paper, a novel non-uniform Binary Concentration Shift Keying (BCSK)
modulation in the course of molecular communication is introduced. We consider
the nutrient limiting as the main reason for avoiding the nanotransmitters to
release huge number of molecules at once. The solution of this problem is in
the utilization of the BCSK modulation. In this scheme, nanotransmitter
releases the information molecules non-uniformly during the time slot. The
3-dimensional diffusion channel with 3-dimensional drift is considered in this
paper. To boost the bit error rate (BER) performance, we consider a
relay-assisted molecular communication via diffusion. Our computations
demonstrate how the pulse shape of BCSK modulation affects the BER, and we also
derive the energy consumption of non-uniform BCSK in the closed-form
expression. We study the parameters that can affect the BER performance, in
particular the distance between the nanotransmitter and the nanoreceiver, the
drift velocity of the medium, and the symbol duration. Furthermore, we propose
an optimization problem that is designed to find the optimal symbol duration
value that maximizes the number of successful received bits. The proposed
algorithm to solve the optimization problem is based on the bisection method.
The analytical results show that non-uniform BCSK modulation outperforms
uniform BCSK modulation in BER performance, when the aggregate energy is fixed.
The COST IRACON Geometry-based Stochastic Channel Model for Vehicle-to-Vehicle Communication in Intersections
Date: 2020-01-14 00:00:00

Vehicle-to-vehicle (V2V) wireless communications can improve traffic safety
at road intersections and enable congestion avoidance. However, detailed
knowledge about the wireless propagation channel is needed for the development
and realistic assessment of V2V communication systems. We present a novel
geometry-based stochastic MIMO channel model with support for frequencies in
the band of 5.2-6.2 GHz. The model is based on extensive high-resolution
measurements at different road intersections in the city of Berlin, Germany. We
extend existing models, by including the effects of various obstructions,
higher order interactions, and by introducing an angular gain function for the
scatterers. Scatterer locations have been identified and mapped to measured
multi-path trajectories using a measurement-based ray tracing method and a
subsequent RANSAC algorithm. The developed model is parameterized, and using
the measured propagation paths that have been mapped to scatterer locations,
model parameters are estimated. The time variant power fading of individual
multi-path components is found to be best modeled by a Gamma process with an
exponential autocorrelation. The path coherence distance is estimated to be in
the range of 0-2 m. The model is also validated against measurement data,
showing that the developed model accurately captures the behavior of the
measured channel gain, Doppler spread, and delay spread. This is also the case
for intersections that have not been used when estimating model parameters.
Narrowband IoT: An Appropriate Solution for Developing Countries
Date: 2019-03-12 00:00:00

Internet of things (IoT) is very much attractive for several sensor based
applications. It provides large coverage of the services with small amount of
resources. Its applications span from the ordinary scenarios such as sensing in
the common digital ecosystem to the far more complicated processes of modern
manufacturing, agriculture, security provisioning, location tracking and health
care. Several types of IoTs have been proposed for the recent applications.
Narrowband IoT (NBIoT) is one of the economical versions of the IoTs. It is a
low power wide area network technology and thus suitable for resource limited
scenarios. In the developing countries, the resources are scarce and economical
solutions are always preferable. Therefore, NBIoT is an attractive solution for
the developing countries. In this article, we present its features and
functions which make it suitable for developing countries. We also provide
several sector based analysis which are suitable for the NBIoT deployment.
Success of Alignment-Free Oligonucleotide (k-mer) Analysis Confirms Relative Importance of Genomes not Genes in Speciation and Phylogeny
Date: 2019-04-25 00:00:00

The utility of DNA sequence substrings (k-mers) in alignment-free
phylogenetic classification, including that of bacteria and viruses, is
increasingly recognized. However, its biological basis eludes many twenty-first
century practitioners. A path from the nineteenth century recognition of the
informational basis of heredity to the modern era can be discerned. Crick's DNA
"unpairing postulate" predicted that recombinational pairing of homologous DNAs
during meiosis would be mediated by short k-mers in the loops of stem-loop
structures extruded from classical duplex helices. The complementary "kissing"
duplex loops - like tRNA anticodon-codon k-mer duplexes - would seed a more
extensive pairing that would then extend until limited by lack of homology or
other factors. Indeed, this became the principle behind alignment-based methods
that assessed similarity by degree of DNA-DNA reassociation in vitro. These are
now seen as less sensitive than alignment-free methods that are closely
consistent, both theoretically and mechanistically, with chromosomal
anti-recombination models for the initiation of divergence into new species.
The analytical power of k-mer differences supports the theses that evolutionary
advance sometimes serves the needs of nucleic acids (genomes) rather than
proteins (genes), and that such differences have often played a role in early
speciation events.
Risks and Benefits of Using a Commercially Available Ventricular Assist Device for Failing Fontan Cavopulmonary Support: A Modeling Investigation
Date: 2019-04-18 00:00:00
Tasks: Circulatory Failure

Fontan patients often develop circulatory failure and are in desperate need
of a therapeutic solution. A blood pump surgically placed in the cavopulmonary
pathway can substitute the function of the absent sub-pulmonary ventricle by
generating a mild pressure boost. However, there is currently no commercially
available device designed for the cavopulmonary application; and the risks and
benefits of implanting a ventricular assist device (VAD) originally designed
for the left ventricular application on the right circulation of failing Fontan
patients is not yet clear. Moreover, further research is needed to compare the
hemodynamics between the two clinically-considered surgical configurations
(Full Support and IVC Support) for cavopulmonary assist, with Full and IVC
Support corresponding to the entire venous return or only the inferior venous
return, respectively, being routed through the VAD. In this study, we used a
numerical model of the failing Fontan physiology to evaluate the Fontan
hemodynamic response to a left VAD during the IVC and Full supports. We
observed that during the Full support the VAD improved the cardiac output while
maintaining blood pressures within safe ranges, and lowered the IVC pressure to
<15mmHg; however, we found a potential risk of lung damage at higher pump
speeds due to the excessive pulmonary pressure elevation. IVC support the other
hand, did not benefit the hemodynamics of the example failing Fontan patients,
resulting in the superior vena cava pressure increasing to an unsafe level of
>20 mmHg. The findings in this study may be helpful to surgeons for recognizing
the risks of a cavopulmonary VAD and developing coherent clinical strategies
for the implementation of cavopulmonary support.
A Deep Learning Based Resource Allocation Scheme in Vehicular Communication Systems
Date: 2019-03-10 00:00:00
Tasks: CPU, regression

In vehicular communications, intracell interference and the stringent latency
requirement are challenging issues. In this paper, a joint spectrum reuse and
power allocation problem is formulated for hybrid vehicle-to-vehicle (V2V) and
vehicle-to-infrastructure (V2I) communications. Recognizing the high capacity
and low-latency requirements for V2I and V2V links, respectively, we aim to
maximize the weighted sum of the capacities and latency requirement. By
decomposing the original problem into a classification subproblem and a
regression sub-problem, a convolutional neural network (CNN) based approach is
developed to obtain real-time decisions on spectrum reuse and power allocation.
Numerical results further demonstrate that the proposed CNN can achieve similar
performance as the Exhaustive method, while needs only 3.62% of its CPU
runtime.
Mapping Target Location from Doppler Data
Date: 2019-03-12 00:00:00

In this paper, we present an algorithm for determining a curve on the earth's
terrain on which a stationary emitter must lie according to a single Doppler
shift measured on an unmanned aerial vehicle (UAV) or a low earth orbit
satellite (LEOS). The mobile vehicle measures the Doppler shift and uses it to
build equations for a particular right circular cone according to the Doppler
shift and the vehicle's velocity, then determines a curve consisting of points
which represents the intersections of the cone with an ellipsoid that
approximately describes the earth's surface. The intersection points of the
cone with the ellipsoid are mapped into a digital terrain data set, namely
Digital Terrain Elevation Data (DTED), to generate the intersection points on
the earth's terrain. The work includes consideration of the possibility that
the rotation of the earth could affect the Doppler shift, and of the errors
resulting from the non-constant refractive index of the atmosphere and from
lack of precise knowledge of the transmitter frequency.