pwc-archive/papers-with-abstracts huggingface dataset:
Safety Control with Preview Automaton
Date: 2020-01-17 00:00:00
Tasks: Autonomous Driving

This paper considers the problem of safety controller synthesis for systems
equipped with sensor modalities that can provide preview information. We
consider switched systems where switching mode is an external signal for which
preview information is available. In particular, it is assumed that the sensors
can notify the controller about an upcoming mode switch before the switch
occurs. We propose preview automaton, a mathematical construct that captures
both the preview information and the possible constraints on switching signals.
Then, we study safety control synthesis problem with preview information. An
algorithm that computes the maximal invariant set in a given mode-dependent
safe set is developed. These ideas are demonstrated on two case studies from
autonomous driving domain.
Mathematical Analysis of Dynamic Risk Default in Microfinance
Date: 2019-07-10 00:00:00
Tasks: Management

In this work we will develop a new approach to solve the non repayment
problem in microfinance due to the problem of asymmetric information. This
approach is based on modeling and simulation of ordinary differential systems
where time remains a primordial component, they thus enable microfinance
institutions to manage their risk portfolios by a prediction of numbers of
solvent and insolvent borrowers ever a period, in order to define or redefine
its development strategy, investment and management in an area, where the
population is often poor and in need a mechanism of financial inclusion.
Digital image quantification of rice sheath blight: Optimized segmentation and automatic classification
Authors: Da-Young Lee, Dong-Yeop Na, Yong Seok Heo, Guo-Liang Wang
Date: 2019-07-10 00:00:00
Tasks: General Classification

Rapid and accurate phenotypic screening of rice germplasms is crucial in screening for sources of rice sheath blight resistance. However, visual and/or caliper-based estimations of coalescing, necrotic, ShB disease lesions are time-consuming, labor-intensive and exposed to human rater subjectivity. Here, we propose the use of RGB images and image processing techniques to quantify ShB disease progression in terms of lesion height and diseased area. To be specific, we developed a pixel color- and coordinate-based K-Means Clustering (PCC-KMC) algorithm utilizing Mahalanobis metric aimed at accurate segmentation of symptomatic and non-symptomatic regions within rice stem images. The performance of PCC-KMC was evaluated using Lin's concordance correlation coefficient by comparing its results to visual measurements of ShB lesion height and to lesion/diseased area measured using ImageJ. Low bias and high precision were observed for absolute lesion height (bias=0.93, precision=0.94) and absolute symptomatic area (bias=0.98, precision=0.97) studies. Moreover, we introduced a convolutional neural network (CNN) for the automatic annotation on clusters, termed PCC-KMC-CNN. Our CNN was trained based on 85%:15% of composition for training and testing dataset from total 168 ShB-infected stem sample images, recording 92% accuracy and 0.21 loss. PCC-KMC-CNN also showed high accuracy and precision for the absolute lesion height (bias=0.86, precision=0.90) and absolute diseased area (bias=0.99, precision=0.97) studies. These results demonstrate that the present methodology has great potential and promise to substitute the traditional visual-based ShB disease severity assessment.
Message passing-based link configuration in short range millimeter wave systems
Date: 2019-07-11 00:00:00
Tasks: compressed sensing

Millimeter wave (mmWave) communication in typical wearable and data center
settings is short range. As the distance between the transmitter and the
receiver in short range scenarios can be comparable to the length of the
antenna arrays, the common far field approximation for the channel may not be
applicable. As a result, dictionaries that result in a sparse channel
representation in the far field setting may not be appropriate for short
distances. In this paper, we develop a novel framework to exploit the structure
in short range mmWave channels. The proposed method splits the channel into
several subchannels for which the far field approximation can be applied. Then,
the structure within and across different subchannels is leveraged using
message passing. We show how information about the antenna array geometry can
be used to design message passing factors that incorporate structure across
successive subchannels. Simulation results indicate that our framework can be
used to achieve better beam alignment with fewer channel measurements when
compared to standard compressed sensing-based techniques that do not exploit
structure across subchannels.
On the probability of strain invasion in endemic settings: accounting for individual heterogeneity and control in multi-strain dynamics
Date: 2019-07-11 00:00:00
Tasks: Unity

The rise of antimicrobial drug resistance is an imminent threat to global
health that has warranted, and duly received, considerable attention within the
medical, microbiological and modelling communities. Outbreaks of drug-resistant
pathogens are ignited by the emergence and transmission of mutant variants
descended from wild-type strains circulating in the community. In this work we
investigate the stochastic dynamics of the emergence of a novel disease strain,
introduced into a population in which it must compete with an existing endemic
strain. In analogy with past work on single-strain epidemic outbreaks, we apply
a branching process approximation to calculate the probability that the new
strain becomes established. As expected, a critical determinant of the survival
prospects of any invading strain is the magnitude of its reproduction number
relative to that of the background endemic strain. Whilst in most circumstances
this ratio must exceed unity in order for invasion to be viable, we show that
differential control scenarios can lead to less-fit novel strains invading
populations hosting a fitter endemic one. This analysis and the accompanying
findings will inform our understanding of the mechanisms that have led to past
instances of successful strain invasion, and provide valuable lessons for
thwarting future drug-resistant strain incursions.
A community perspective on the concept of marine holobionts: state-of-the-art, challenges, and future directions
Date: 2019-07-11 00:00:00

Host-microbe interactions play crucial roles in marine ecosystems, but we
still have very little understanding of the mechanisms that govern these
relationships, the evolutionary processes that shape them, and their ecological
consequences. The holobiont concept is a renewed paradigm in biology that can
help describe and understand these complex systems. It posits that a host and
its associated microbiota, living together in a long-lasting relationship, form
the holobiont, and have to be studied together, as a coherent biological and
functional unit, in order to understand the biology, ecology and evolution of
the organisms. Here we discuss critical concepts and opportunities in marine
holobiont research and identify key challenges in the field. We highlight the
potential economic, sociological, and environmental impacts of the holobiont
concept in marine biological, evolutionary, and environmental sciences with
comparisons to terrestrial science whenever appropriate. A deeper understanding
of such complex systems, however, will require further technological and
conceptual advances. The most significant challenge will be to bridge
functional research on simple and tractable model systems and global
approaches. This will require scientists to work together as an (inter)active
community in order to address, for instance, ecological and evolutionary
questions and the roles of holobionts in biogeochemical cycles.
Terahertz Band: The Last Piece of RF Spectrum Puzzle for Communication Systems
Date: 2019-07-11 00:00:00

Ultra-high bandwidth, negligible latency and seamless communication for
devices and applications are envisioned as major milestones that will
revolutionize the way by which societies create, distribute and consume
information. The remarkable expansion of wireless data traffic that we are
witnessing recently has advocated the investigation of suitable regimes in the
radio spectrum to satisfy users' escalating requirements and allow the
development and exploitation of both massive capacity and massive connectivity
of heterogeneous infrastructures. To this end, the Terahertz (THz) frequency
band (0.1-10 THz) has received noticeable attention in the research community
as an ideal choice for scenarios involving high-speed transmission.
Particularly, with the evolution of technologies and devices, advancements in
THz communication is bridging the gap between the millimeter wave (mmW) and
optical frequency ranges. Moreover, the IEEE 802.15 suite of standards has been
issued to shape regulatory frameworks that will enable innovation and provide a
complete solution that crosses between wired and wireless boundaries at 100
Gbps. Nonetheless, despite the expediting progress witnessed in THz wireless
research, the THz band is still considered one of the least probed frequency
bands. As such, in this work, we present an up-to-date review paper to analyze
the fundamental elements and mechanisms associated with the THz system
architecture.
Approximate Message Passing for Indoor THz Channel Estimation
Date: 2019-07-11 00:00:00
Tasks: compressed sensing

Compressed sensing (CS) deals with the problem of reconstructing a sparse
vector from an under-determined set of observations. Approximate message
passing (AMP) is a technique used in CS based on iterative thresholding and
inspired by belief propagation in graphical models. Due to the high
transmission rate and a high molecular absorption, spreading loss and
reflection loss, the discrete-time channel impulse response (CIR) of a typical
indoor THz channel is very long and exhibits an approximately sparse
characteristic. In this paper, we develop AMP based channel estimation
algorithms for indoor THz communications. The performance of these algorithms
is compared to the state of the art. We apply AMP with soft- and
hard-thresholding. Unlike the common applications in which AMP with
hard-thresholding diverges, the properties of the THz channel favor this
approach. It is shown that THz channel estimation via hard-thresholding AMP
outperforms all previously proposed methods and approaches the oracle based
performance closely.
Distribution of outbreak sizes for SIR disease in finite populations
Date: 2019-07-11 00:00:00

We consider the spread of a Susceptible-Infected-Recovered (SIR) disease
through finite populations and derive an expression for the final size
distribution. Our derivation allows arbitrary distributions of the number of
transmissions caused by an infected individual. We show how this calculation
can be used to infer parameters of the infectious disease through observations
in multiple small populations. The inference suffers from some identifiability
difficulties, and it requires many observations to distinguish between
parameter combinations that correspond to the same reproductive number.
Combining Social Force Model with Model Predictive Control for Vehicle's Longitudinal Speed Regulation in Pedestrian-Dense Scenarios
Date: 2019-07-11 00:00:00
Tasks: model, Model Predictive Control

In pedestrian-dense traffic scenarios, an autonomous vehicle may have to
safely drive through a crowd of pedestrians while the vehicle tries to keep the
desired speed as much as possible. This requires a model that can predict the
motion of crowd pedestrians and a method for the vehicle to predictively adjust
its speed. In this study, the model-based predictive control (MPC) was combined
with a social-force based vehicle-crowd interaction (VCI) model to regulate the
longitudinal speed of the autonomous vehicle. The predictive feature of the VCI
model can be precisely utilized by the MPC. A criterion for simultaneously
guaranteeing pedestrian safety and keeping the desired speed was designed, and
consequently, the MPC was formulated as a standard quadratic programming (QP)
problem, which can be easily solved by standard QP toolbox. The proposed
approach was compared with the traditional proportional-integral-derivative
(PID) control approach for regulating longitudinal speed. Scenarios of
different pedestrian density were evaluated in simulation. The results
demonstrated the merits of the proposed method to address this type of problem.
It also shows the potential of extending the method to address more complex
vehicle-pedestrian interaction situations.
Fixation properties of rock-paper-scissors games in fluctuating populations
Date: 2020-02-24 00:00:00

Rock-paper-scissors games metaphorically model cyclic dominance in ecology
and microbiology. In a static environment, these models are characterized by
fixation probabilities obeying two different "laws" in large and small
well-mixed populations. Here, we investigate the evolution of these
three-species models subject to a randomly switching carrying capacity modeling
the endless change between states of resources scarcity and abundance. Focusing
mainly on the zero-sum rock-paper-scissors game, equivalent to the cyclic
Lotka-Volterra model, we study how the ${\it coupling}$ of demographic and
environmental noise influences the fixation properties. More specifically, we
investigate which species is the most likely to prevail in a population of
fluctuating size and how the outcome depends on the environmental variability.
We show that demographic noise coupled with environmental randomness "levels
the field" of cyclic competition by balancing the effect of selection. In
particular, we show that fast switching effectively reduces the selection
intensity proportionally to the variance of the carrying capacity. We determine
the conditions under which new fixation scenarios arise, where the most likely
species to prevail changes with the rate of switching and the variance of the
carrying capacity. Random switching has a limited effect on the mean fixation
time that scales linearly with the average population size. Hence,
environmental randomness makes the cyclic competition more egalitarian, but
does not prolong the species coexistence. We also show how the fixation
probabilities of close-to-zero-sum rock-paper-scissors games can be obtained
from those of the zero-sum model by rescaling the selection intensity.
Distributions of Historic Market Data -- Relaxation and Correlations
Date: 2020-02-24 00:00:00
Tasks: Form

We investigate relaxation and correlations in a class of mean-reverting
models for stochastic variances. We derive closed-form expressions for the
correlation functions and leverage for a general form of the stochastic term.
We also discuss correlation functions and leverage for three specific models --
multiplicative, Heston (Cox-Ingersoll-Ross) and combined multiplicative-Heston
-- whose steady-state probability density functions are Gamma, Inverse Gamma
and Beta Prime respectively, the latter two exhibiting "fat" tails. For the
Heston model, we apply the eigenvalue analysis of the Fokker-Planck equation to
derive the correlation function -- in agreement with the general analysis --
and to identify a series of time scales, which are observable in relaxation of
cumulants on approach to the steady state. We test our findings on a very large
set of historic financial markets data.
Cortical Surface Parcellation using Spherical Convolutional Neural Networks
Date: 2019-07-11 00:00:00
Tasks: MORPH

We present cortical surface parcellation using spherical deep convolutional
neural networks. Traditional multi-atlas cortical surface parcellation requires
inter-subject surface registration using geometric features with high
processing time on a single subject (2-3 hours). Moreover, even optimal surface
registration does not necessarily produce optimal cortical parcellation as
parcel boundaries are not fully matched to the geometric features. In this
context, a choice of training features is important for accurate cortical
parcellation. To utilize the networks efficiently, we propose cortical
parcellation-specific input data from an irregular and complicated structure of
cortical surfaces. To this end, we align ground-truth cortical parcel
boundaries and use their resulting deformation fields to generate new pairs of
deformed geometric features and parcellation maps. To extend the capability of
the networks, we then smoothly morph cortical geometric features and
parcellation maps using the intermediate deformation fields. We validate our
method on 427 adult brains for 49 labels. The experimental results show that
our method out-performs traditional multi-atlas and naive spherical U-Net
approaches, while achieving full cortical parcellation in less than a minute.
Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions
Date: 2019-07-12 00:00:00

Economic theory is a mathematically rich field in which there are
opportunities for the formal analysis of singularities and catastrophes. This
article looks at the historical context of singularities through the work of
two eminent Frenchmen around the late 1960s and 1970s. Ren\'e Thom (1923-2002)
was an acclaimed mathematician having received the Fields Medal in 1958,
whereas G\'erard Debreu (1921-2004) would receive the Nobel Prize in economics
in 1983. Both were highly influential within their fields and given the
fundamental nature of their work, the potential for cross-fertilisation would
seem to be quite promising. This was not to be the case: Debreu knew of Thom's
work and cited it in the analysis of his own work, but despite this and other
applied mathematicians taking catastrophe theory to economics, the theory never
achieved a lasting following and relatively few results were published. This
article reviews Debreu's analysis of the so called ${\it regular}$ and ${\it
crtitical}$ economies in order to draw some insights into the economic
perspective of singularities before moving to how singularities arise naturally
in the Nash equilibria of game theory. Finally a modern treatment of stochastic
game theory is covered through recent work on the quantal response equilibrium.
In this view the Nash equilibrium is to the quantal response equilibrium what
deterministic catastrophe theory is to stochastic catastrophe theory, with some
caveats regarding when this analogy breaks down discussed at the end.
Pareto Optimal Demand Response Based on Energy Costs and Load Factor in Smart Grid
Date: 2019-07-12 00:00:00
Tasks: Multiobjective Optimization

Demand response for residential users is essential to the realization of
modern smart grids. This paper proposes a multiobjective approach to designing
a demand response program that considers the energy costs of residential users
and the load factor of the underlying grid. A multiobjective optimization
problem (MOP) is formulated and Pareto optimality is adopted. Stochastic search
methods of generating feasible values for decision variables are proposed.
Theoretical analysis is performed to show that the proposed methods can
effectively generate and preserve feasible points during the solution process,
which comparable methods can hardly achieve. A multiobjective evolutionary
algorithm is developed to solve the MOP, producing a Pareto optimal demand
response (PODR) program. Simulations reveal that the proposed method
outperforms the comparable methods in terms of energy costs while producing a
satisfying load factor. The proposed PODR program is able to systematically
balance the needs of the grid and residential users.
Single-cell micro- and nano-photonic technologies
Authors: Filippo Pisano, Marco Pisanello, Massimo De Vittorio, Ferruccio Pisanello
Date: 2019-07-12 00:00:00

Since the advent of optogenetics, technology development has focused on new methods to optically interact with single nervous cells. This gave rise to the field of photonic neural interfaces, intended as the set of technologies that can modify light radiation in either a linear or non-linear fashion to control and/or monitor cellular functions. These include the use of plasmonic effects, up-conversion, electron transfer and integrated light steering, with some of them already implemented in vivo. This article will review available approaches in this framework, with a particular emphasis on methods operating at the single-unit level or having the potential to reach single-cell resolution.
Energy Aware Wireless System based Software Defined Radio
Date: 2019-07-12 00:00:00

Development of green telecommunication systems is already being considered
highly attractive by standard bodies and recently is attracting research
attention. While most of the research focuses on modeling and simulation, in
this work we implement a lab setup to test an energy aware wireless system
based on software defined radio and solar energy power system. In addition, we
proposed an energy aware adaptive modulation algorithm that considers the state
of charge of the solar energy batteries before setting up the modulation order.
Moreover, the algorithm adapts to user preferences between the connectivity
mode and the quality mode.
Smart Cities: The Hopes and Hypes
Date: 2019-07-12 00:00:00

Smart cities are being planned for several advanced applications and services
for the inhabitants. Smart cities initiative promise many new services which
are not possible in the traditional city frameworks. In the smart city
framework, the basic aim is to provide all the essential services through
sensor based systems which does not need much human intervention. This system
is designed to operate on its own in a self-organizing manner. Therefore, the
hopes are really big from the smart cities to enhance the quality of lives and
the economy. However, some of the promises in the smart cities are very much
over hyped. In this article, we analyse the realities of the smart cities and
their practical significances based on the technological aspects of these
projects. We also address the false promises that are around which are just the
hypes. We clarify these hypes with appropriate logical explanations.
Associate submersions and qualitative properties of nonlinear circuits with implicit characteristics
Date: 2019-07-12 00:00:00

We introduce in this paper an equivalence notion for submersions $U \to \R$,
$U$ open in $\R^2$, which makes it possible to identify a smooth planar curve
with a unique class of submersions. This idea, which extends to the nonlinear
setting the construction of a dual projective space, provides a systematic way
to handle global implicit descriptions of smooth planar curves. We then apply
this framework to model nonlinear electrical devices as {\em classes of
equivalent functions}. In this setting, linearization naturally accommodates
incremental resistances (and other analogous notions) in homogeneous terms.
This approach, combined with a projectively-weighted version of the matrix-tree
theorem, makes it possible to formulate and address in great generality several
problems in nonlinear circuit theory. In particular, we tackle unique
solvability problems in resistive circuits, and discuss a general expression
for the characteristic polynomial of dynamic circuits at equilibria. Previously
known results, which were derived in the literature under unnecessarily
restrictive working assumptions, are simply obtained here by using
dehomogenization. Our results are shown to apply also to circuits with
memristors. We finally present a detailed, graph-theoretic study of certain
stationary bifurcations in nonlinear circuits using the formalism here
introduced.