pwc-archive/papers-with-abstracts huggingface dataset:
The Emergence of Innovation Complexity at Different Geographical and Technological Scales
Date: 2019-09-12 00:00:00

We define a novel quantitative strategy inspired by the ecological notion of
nestedness to single out the scale at which innovation complexity emerges from
the aggregation of specialized building blocks. Our analysis not only suggests
that the innovation space can be interpreted as a natural system in which
advantageous capabilities are selected by evolutionary pressure, but also that
the emerging structure of capabilities is not independent of the scale of
observation at which they are observed. Expanding on this insight allows us to
understand whether the capabilities characterizing the innovation space at a
given scale are compatible with a complex evolutionary dynamics or, rather, a
set of essentially independent activities allowing to reduce the system at that
scale to a set of disjoint non interacting sub-systems. This yields a measure
of the innovation complexity of the system, i.e. of the degree of
interdependence between the sets of capabilities underlying the system's
building blocks.
Proceedings of the International Workshop on Reconfigurable and Communication-centric Cyber-Physical Systems (ReCoCyPS 2019)
Date: 2019-06-28 00:00:00

This volume represents the proceedings of the International Workshop on
Reconfigurable and Communication-centric Cyber-Physical Systems (ReCoCyPS
2019), co-located with the 14th International Symposium on Reconfigurable
Communication-centric Systems-on-Chip (ReCoSoC 2019) on July 2-3 2019, York,
United Kingdom.
  The workshop is organised by the EU-funded SAFIRE project consortium.
A Consistent LM Type Specification Test for Semiparametric Panel Data Models
Date: 2019-09-12 00:00:00
Tasks: Vocal Bursts Type Prediction

This paper develops a consistent series-based specification test for
semiparametric panel data models with fixed effects. The test statistic
resembles the Lagrange Multiplier (LM) test statistic in parametric models and
is based on a quadratic form in the restricted model residuals. The use of
series methods facilitates both estimation of the null model and computation of
the test statistic. The asymptotic distribution of the test statistic is
standard normal, so that appropriate critical values can easily be computed.
The projection property of series estimators allows me to develop a degrees of
freedom correction. This correction makes it possible to account for the
estimation variance and obtain refined asymptotic results. It also
substantially improves the finite sample performance of the test.
Lead-Lag-Shaped Interactive Force Estimation by Equivalent Output Injection of Sliding-Mode
Date: 2019-09-12 00:00:00

Estimation of interactive forces, which are mostly unavailable for direct
measurement on the interface between a system and its environment, is an
essential task in various motion control applications. This paper proposes an
interactive force estimation method, based on the well-known equivalent output
injection of the second-order sliding mode. The equivalent output injection is
used to obtain a frequency-unshaped quantity that appears as a matched external
disturbance and encompasses the interactive forces. Afterwards, a universal
lead-lag shaper, depending on dynamics of the motion control system coupled
with its environment, is used to extract an interactive force quantity. Once
identified, the lead-lag shaper can be applied to the given system structure.
An experimental case study, using a valvecontrolled hydraulic cylinder
counteracted by the dynamic load, is demonstrated with an accurate estimation
of the interactive force, that in comparison to the reference measurement.
Pricing Reliability Options under different electricity prices' regimes
Authors: Luisa Andreis, Maria Flora, Fulvio Fontini, Tiziano Vargiolu
Date: 2019-09-12 00:00:00

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first derived by means of closed-form pricing formulae, which are obtained under several assumptions about the dynamics of electricity prices and strike prices. Then, the value of the Reliability Option is simulated under a real-market calibration, using data of the Italian power market. We finally perform sensitivity analyses to highlight the impact of the level and volatility of both power and strike price, of the mean reversion speeds and of the correlation coefficient on the Reliability Options' value.
Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback
Date: 2020-06-29 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

Simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) is an
emerging neuromodulation approach, that enables simultaneous volitional
regulation of both hemodynamic (BOLD fMRI) and electrophysiological (EEG) brain
activities. Here we report the first application of rtfMRI-EEG-nf for emotion
self-regulation training in patients with major depressive disorder (MDD). In
this proof-of-concept study, MDD patients in the experimental group (n=16) used
rtfMRI-EEG-nf during a happy emotion induction task to simultaneously
upregulate two fMRI and two EEG activity measures relevant to MDD. The target
measures included BOLD activities of the left amygdala (LA) and left rostral
anterior cingulate cortex (rACC), and frontal EEG asymmetries in the alpha band
(FAA, [7.5-12.5] Hz) and high-beta band (FBA, [21-30] Hz). MDD patients in the
control group (n=8) were provided with sham feedback signals. An advanced
procedure for improved real-time EEG-fMRI artifact correction was implemented.
The experimental group participants demonstrated significant upregulation of
the LA BOLD activity, FAA, and FBA during the rtfMRI-EEG-nf task, as well as
significant enhancement in fMRI connectivity between the LA and left rACC.
Average individual FAA changes during the rtfMRI-EEG-nf task positively
correlated with depression and anhedonia severities, and negatively correlated
with after-vs-before changes in depressed mood ratings. Temporal correlations
between the FAA and FBA time courses and the LA BOLD activity were
significantly enhanced during the rtfMRI-EEG-nf task. The experimental group
participants reported significant mood improvements after the training. Our
results suggest that the rtfMRI-EEG-nf may have potential for treatment of MDD.
Unitary Shift Operators on a Graph
Date: 2019-09-17 00:00:00

A unitary shift operator (GSO) for signals on a graph is introduced, which
exhibits the desired property of energy preservation over both backward and
forward graph shifts. For rigour, the graph differential operator is also
derived in an analytical form. The commutativity relation of the shift operator
with the Fourier transform is next explored in conjunction with the proposed
GSO to introduce a graph discrete Fourier transform (GDFT) which, unlike
existing approaches, ensures the orthogonality of GDFT bases and admits a
natural frequency-domain interpretation. The proposed GDFT is shown to allow
for a coherent definition of the graph discrete Hilbert transform (GDHT) and
the graph analytic signal. The advantages of the proposed GSO are demonstrated
through illustrative examples.
Qualitative behavior and robustness of dendritic trafficking
Authors: Saeed Aljaberi, Timothy O'Leary, Fulvio Forni
Date: 2019-09-12 00:00:00

The paper studies homeostatic ion channel trafficking in neurons. We derive a nonlinear closed-loop model that captures active transport with degradation, channel insertion, average membrane potential activity, and integral control. We study the model via dominance theory and differential dissipativity to show when steady regulation gives way to pathological oscillations. We provide quantitative results on the robustness of the closed loop behavior to static and dynamic uncertainties, which allows us to understand how cell growth interacts with ion channel regulation.
Ecological communities from random generalised Lotka-Volterra dynamics with non-linear feedback
Date: 2020-03-25 00:00:00
Tasks: Diversity

We investigate the outcome of generalised Lotka-Volterra dynamics of
ecological communities with random interaction coefficients and non-linear
feedback. We show in simulations that the saturation of non-linear feedback
stabilises the dynamics. This is confirmed in an analytical
generating-functional approach to generalised Lotka-Volterra equations with
piecewise linear saturating response. For such systems we are able to derive
self-consistent relations governing the stable fixed-point phase, and to carry
out a linear stability analysis to predict the onset of unstable behaviour. We
investigate in detail the combined effects of the mean, variance and
co-variance of the random interaction coefficients, and the saturation value of
the non-linear response. We find that stability and diversity increases with
the introduction of non-linear feedback, where decreasing the saturation value
has a similar effect to decreasing the co-variance. We also find co-operation
to no longer have a detrimental effect on stability with non-linear feedback,
and the order parameters mean abundance and diversity to be less dependent on
the symmetry of interactions with stronger saturation.
Long range battery-less PV-powered RFID tag sensors
Date: 2019-09-12 00:00:00
Tasks: TAG

Communication range in passive Radio-Frequency Identification (RFID)
front-end devices is a critical barrier in the real-world implementation of
this low-cost technology. Purely passive RFID tags power up by harvesting the
limited RF energy transmitted by the interrogator, and communicate by
backscattering the incident signal. This mode of communication keeps
manufacturing costs below a few cents per tag, but the limited power available
at the tag undermines long-range deployment. In this paper, we present an
approach to use Photovoltaics (PV) to augment the available energy at the tag
to improve read range and sensing capabilities. We provide this extra-energy to
the RFID integrated circuit (IC) using minimum additional electronics yet
enabling persistent sensor-data acquisition. Current and emerging thin-film PV
technologies have significant potential for being very low-cost, hence
eliminating the barrier for implementation and making of PV-RFID wireless
sensors. We reduce the long-range PV-RFID idea to practice by creating
functional prototypes of i) a wireless building environment sensor to monitor
temperature, and ii) an embedded tracker to find lost golf balls. The read
range of PV-RFID is enhanced 8 times compared to conventional passive devices.
In addition, the PV-RFID tags persistently transmit large volumes of sensor
data (>0.14 million measurements per day) without using batteries. For
communication range and energy persistence, we observe good agreement between
calculated estimates and experimental results. We have also identified avenues
for future research to develop low-cost PV-RFID devices for wireless sensing in
the midst of the other competitive wireless technologies such as Bluetooth,
Zigbee, Long Range (LoRa) backscatter etc.
Enhancement of seismic imaging: An innovative deep learning approach
Date: 2019-09-13 00:00:00
Tasks: Deep Learning, Seismic Imaging

Enhancing the frequency bandwidth of the seismic data is always the pursuance
at the geophysical community. High resolution of seismic data provides the key
resource to extract detailed stratigraphic knowledge. Here, a novel approach,
based on deep learning model, is introduced by extracting reflections from well
log data to broaden spectrum bandwidth of seismic data through boosting low and
high frequencies. The corresponding improvement is observed from the
enhancement of resolution of seismic data as well as elimination of sidelobe
artifacts from seismic wavelets. During the training stage of deep learning
model, geo-spatial information by taking consideration of multiple wells
simultaneously is fully guaranteed, which assures that laterally and vertically
geological information are constrained by and accurate away from the well
controls during the inversion procedure. Extensive experiments prove that the
enhanced seismic data is consistent with well log information, and honors rock
property relationships defined from the wells at given locations. Uncertainty
analysis could also be quantitatively assessed to determine the possibilities
of a range of seismic responses by leveraging the outputs from the proposed
approach.
Deep Learning for Cooperative Radio Signal Classification
Date: 2019-09-13 00:00:00
Tasks: Classification, Deep Learning

Radio signal classification has a very wide range of applications in
cognitive radio networks and electromagnetic spectrum monitoring. In this
article, we consider scenarios where multiple nodes in the network participate
in cooperative classification. We propose cooperative radio signal
classification methods based on deep learning for decision fusion, signal
fusion and feature fusion, respectively. We analyze the performance of these
methods through simulation experiments. We conclude the article with a
discussion of research challenges and open problems.
Generalized Duality for Model-Free Superhedging given Marginals
Authors: Arash Fahim, Yu-Jui Huang, Saeed Khalili
Date: 2019-09-13 00:00:00
Tasks: model

In a discrete-time financial market, a generalized duality is established for model-free superhedging, given marginal distributions of the underlying asset. Contrary to prior studies, we do not require contingent claims to be upper semicontinuous, allowing for upper semi-analytic ones. The generalized duality stipulates an extended version of risk-neutral pricing. To compute the model-free superhedging price, one needs to find the supremum of expected values of a contingent claim, evaluated not directly under martingale (risk-neutral) measures, but along sequences of measures that converge, in an appropriate sense, to martingale ones. To derive the main result, we first establish a portfolio-constrained duality for upper semi-analytic contingent claims, relying on Choquet's capacitability theorem. As we gradually fade out the portfolio constraint, the generalized duality emerges through delicate probabilistic estimations.
Frequency-weighted H2-Pseudo-optimal Model Order Reduction
Date: 2020-11-19 00:00:00
Tasks: model

The frequency-weighted model order reduction techniques are used to find a
lower-order approximation of the high-order system that exhibits high-fidelity
within the frequency region emphasized by the frequency weights. In this paper,
we investigate the frequency-weighted H2-pseudo-optimal model order reduction
problem wherein a subset of the optimality conditions for the local optimum is
attempted to be satisfied. We propose two iteration-free algorithms, for the
single-sided frequency-weighted case of H2-model reduction, where a subset of
the optimality conditions is ensured by the reduced system. In addition, the
reduced systems retain the stability property of the original system. We also
present an iterative algorithm for the double-sided frequency-weighted case,
which constructs a reduced-order model that tends to satisfy a subset of the
first-order optimality conditions for the local optimum. The proposed algorithm
is computationally efficient as compared to the existing algorithms. We
validate the theory developed in this paper on three numerical examples.
Efficient Multi-Year Security Constrained AC Transmission Network Expansion Planning
Date: 2019-09-13 00:00:00

Solution of multi-year, dynamic AC Transmission network expansion planning
(TNEP) problem is gradually taking center stage of planning research owing to
its potential accuracy. However, computational burden for a security
constrained AC TNEP is huge compared to that with DC TNEP. For a dynamic,
security constrained AC TNEP problem, the computational burden becomes so very
excessive that solution for even moderately sized systems becomes almost
impossible. Hence, this paper presents an efficient, four-stage solution
methodology for multi-year, network N-1 contingency and voltage stability
constrained, dynamic ACTNEP problems. Several intelligent logical strategies
are developed and applied to reduce the computational burden of optimization
algorithms. The proposed methodology is applied to Garver 6, IEEE 24 and 118
bus systems to demonstrate its efficiency and ability to solve TNEP for varying
system sizes.
A Swash Mass Unmanned Aerial Vehicle: Design, Modeling and Control
Date: 2019-09-13 00:00:00

In this paper, a new unmanned aerial vehicle (UAV) structure, referred to as
swash mass UAV, is presented. It consists of a double blade coaxial shaft rotor
and four swash masses that allow changing the orientation and maneuvering the
UAV. The dynamical system model is derived from the Newton\textquotesingle s
law framework. The rotational behavior of the UAV is discussed as a function of
the design parameters. Given the uniqueness and the form of the obtained
non-linear dynamical system model, a back-stepping control mechanism is
proposed. It is obtained following the Lyapunov's control approach in each
iteration step. Numerical results show that the swashed mass UAV can be
maneuvered with the proposed control algorithm so that linear and aggressive
trajectories can be accurately tracked.
Modulation of the cardiomyocyte contraction inside a hydrostatic pressure bioreactor: $\textit{in vitro}$ verification of the Frank-Starling law
Authors: Lorenzo Fassina, Giovanni Magenes, Roberto Gimmelli, Fabio Naro
Date: 2019-09-12 00:00:00

We have studied beating mouse cardiac syncytia $\textit{in vitro}$ in order to assess the inotropic, ergotropic, and chronotropic effects of both increasing and decreasing hydrostatic pressures. In particular, we have performed an image processing analysis to evaluate the kinematics and the dynamics of those pressure-loaded beating syncytia starting from the video registration of their contraction movement. By this analysis, we have verified the Frank-Starling law of the heart in $\textit{in vitro}$ beating cardiac syncytia and we have obtained their geometrical-functional classification.
FPGA based Implementation of Frequency and Phase Matching Technique for Grid Tied Applications
Date: 2019-09-13 00:00:00

A grid tied inverter converts DC voltage into AC voltage, while synchronizing
it with the supply line phase and frequency. This paper presents an efficient,
robust, and easy-to-implement grid tie mechanism. First, the grid tie mechanism
was simulated in software using LabVIEW and Multisim. Then, the whole system
was practically implemented on hardware. A prototype hardware was developed to
produce AC voltage from solar panels. Phase and frequency of the generated
voltage were synchronized with those of a reference sinusoidal signal. The
synchronization mechanism was digitally implemented on an FPGA, which also
controlled the whole system. We achieved real time frequency matching with an
improved Zero Crossing Detection (ZCD) technique. Phase matching was also
achieved in real time using a modified Phase Locked Loop (PLL) algorithm, which
retains stability while being simpler than the general PLL algorithm.
Experiments demonstrated that the proposed grid tied system reliably
synchronized the phase and frequency of the voltage generated by the
implemented hardware with those of the reference grid voltage.
On the Existence of Flight Equilibria in Longitudinal Dynamics
Date: 2019-09-12 00:00:00

Any control law for aircraft asymptotic stabilization requires the existence
of an equilibrium condition, also called trim flight condition. At a constant
velocity flight, for instance, there must exist an aircraft orientation such
that aerodynamic forces oppose the plane's thrust plus weight, and the torque
balance equals zero. A closer look at the equations characterizing the trim
conditions point out that the existence of aircraft equilibrium configurations
cannot be in general claimed beforehand. By considering aircraft longitudinal
linear dynamics, this paper shows that the existence of flight trim conditions
is a consequence of the vehicle shape or aerodynamics. These results are
obtained independently from the aircraft flight envelope, and do not require
any explicit expression of the aerodynamics acting on the vehicle.
Optimal investment and contingent claim valuation with exponential disutility under proportional transaction costs
Authors: Alet Roux, Zhikang Xu
Date: 2019-09-13 00:00:00

We consider indifference pricing of contingent claims consisting of payment flows in a discrete time model with proportional transaction costs and under exponential disutility. This setting covers utility maximisation as a special case. A dual representation is obtained for the associated disutility minimisation problem, together with a dynamic procedure for solving it. This leads to efficient and convergent numerical procedures for indifference pricing, optimal trading strategies and shadow prices that apply to a wide range of payoffs, a large range of time steps and all magnitudes of transaction costs.
Compositional Synthesis of Decentralized Robust Set-Invariance Controllers for Large-scale Linear Systems
Date: 2019-09-17 00:00:00

Ensuring constraint satisfaction in large-scale systems with hard constraints
is vital in many safety critical systems. The challenge is to design
controllers that are efficiently synthesized offline, easily implementable
online, and provide formal correctness guarantees. In this paper, we provide a
method to compute correct-by-construction controllers for a network of coupled
linear systems with additive bounded disturbances such that i) the design of
the controllers is fully compositional - we use an optimization-based approach
that iteratively computes subsystem-level assume-guarantee contracts in the
form of robust control invariant sets; and ii) the controllers are
decentralized hence online implementation requires only the local state
information. We present illustrative examples, including a case study on a
system with 1000 dimensions.
Distributed Focus and Digital Zoom
Date: 2019-09-13 00:00:00

We explore integrated microcamera focus systems for array cameras. We propose
a new model for system camera integration relying on fast action focus
mechanisms with >10mm aperture. Rather than reducing resolution or expanding
aperture size, such systems can be used in arrays to enable digital zoom. We
show that a common mechanism supports camera modules with focal lengths ranging
from 25 to 60 mm. Designs for each focal length include a fixed objective lens
group and an adjustable back focus group. Increasing the focal power of the
front focal group enables the travel range of available microcamera modules to
accommodate long focal length systems. We present design examples both discrete
and multiscale array camera systems.