pwc-archive/papers-with-abstracts huggingface dataset:
Industrial Indoor Measurements from 2-6 GHz for the 3GPP-NR and QuaDRiGa Channel Model
Date: 2019-06-28 00:00:00

Providing reliable low latency wireless links for advanced manufacturing and
processing systems is a vision of Industry 4.0. Developing, testing and rating
requires accurate models of the radio propagation channel. The current 3GPP-NR
model as well as the QuaDRiGa model lack the propagation parameters for the
industrial indoor scenario. To close this gap, measurements were conducted at
2.37 GHz and 5.4 GHz at operational Siemens premises in Nuremberg, Germany.
Furthermore, the campaign was planned to allow the test and parameterization of
new features of the QuaDRiGa channel model such as support for device-to-device
(D2D) radio links and spatial consistency. A total of 5.9 km measurement track
was used to extract the statistical model parameters for line of sight (LOS)
and Non-LOS propagation conditions. It was found that the metallic walls and
objects in the halls create a rich scattering environment, where a large number
of multipath components arrive at the receiver from all directions. This leads
to a robust communication link, provided that the transceivers can handle the
interference. The extracted parameters can be used in geometric-stochastic
channel models such as QuaDRiGa to support simulation studies, both on link and
system level.
On the robust existence of piecewise quadratic Lyapunov functions for hybrid models of gene regulatory networks
Date: 2019-06-28 00:00:00

In this work we addressed the problem of stability analysis for an uncertain
piecewise affine model of a genetic regulatory network. In particular we
considered polytopic parameter uncertainties on the proteins production rate
functions, giving conditions for the existence of a piecewise quadratic
Lyapunov function for any possible realization of the system. In the spirit of
other works in literature, the resulting conditions will be given on the
vertices of the parameter polytope, while still taking into consideration the
piecewise nature of the Lyapunov function and the presence, in general, of
sliding modes solutions. An example is shown to prove the validity and
applicability of the theoretical results.
An Image Source Method Framework for Arbitrary Reflecting Boundaries
Date: 2019-06-28 00:00:00
Tasks: Room Impulse Response (RIR)

We propose a theoretical framework for the image source method that
generalizes to arbitrary reflecting boundaries, e.g. boundaries that are curved
or even with certain openings. Furthermore, it can seamlessly incorporate
boundary absorption, source directivity, and nonspecular reflections. This
framework is based on the notion of reflection paths that allows the
introduction of the concepts of validity and visibility of virtual sources.
These definitions facilitate the determination, for a given source and receiver
location, of the distribution of virtual sources that explain the boundary
effects of a wide range of reflecting surfaces. The structure of the set of
virtual sources is then more general than just punctual virtual sources. Due to
this more diverse configuration of image sources, we represent the room impulse
response as an integral involving the temporal excitation signal against a
measure determined by the source and receiver locations, and the original
boundary. The latter smoothly enables, in an analytically tractable manner, the
incorporation of more general boundary shapes as well as directivity of sources
and boundary absorption while, at the same time, maintaining the conceptual
benefits of the image source method.
A multifactorial evaluation framework for gene regulatory network reconstruction
Date: 2019-06-28 00:00:00
Tasks: Experimental Design, Management, Time Series, Time Series Analysis

In the past years, many computational methods have been developed to infer
the structure of gene regulatory networks from time-series data. However, the
applicability and accuracy presumptions of such algorithms remain unclear due
to experimental heterogeneity. This paper assesses the performance of recent
and successful network inference strategies under a novel, multifactorial
evaluation framework in order to highlight pragmatic tradeoffs in experimental
design. The effects of data quantity and systems perturbations are addressed,
thereby formulating guidelines for efficient resource management.
  Realistic data were generated from six widely used benchmark models of
rhythmic and non-rhythmic gene regulatory systems with random perturbations
mimicking the effect of gene knock-out or chemical treatments. Then,
time-series data of increasing lengths were provided to five state-of-the-art
network inference algorithms representing distinctive mathematical paradigms.
The performances of such network reconstruction methodologies are uncovered
under various experimental conditions. We report that the algorithms do not
benefit equally from data increments. Furthermore, for rhythmic systems, it is
more profitable for network inference strategies to be run on long time-series
rather than short time-series with multiple perturbations. By contrast, for the
non-rhythmic systems, increasing the number of perturbation experiments yielded
better results than increasing the sampling frequency. We expect that future
benchmark and algorithm design would integrate such multifactorial
considerations to promote their widespread and conscientious usage.
Compressing Flow Fields with Edge-aware Homogeneous Diffusion Inpainting
Date: 2020-04-29 00:00:00

In spite of the fact that efficient compression methods for dense
two-dimensional flow fields would be very useful for modern video codecs,
hardly any research has been performed in this area so far. Our paper addresses
this problem by proposing the first lossy diffusion-based codec for this
purpose. It keeps only a few flow vectors on a coarse grid. Additionally stored
edge locations ensure the accurate representation of discontinuities. In the
decoding step, the missing information is recovered by homogeneous diffusion
inpainting that incorporates the stored edges as reflecting boundary
conditions. In spite of the simple nature of this codec, our experiments show
that it achieves remarkable quality for compression ratios up to 800 : 1.
Near-Optimal Dynamic Asset Allocation in Financial Markets with Trading Constraints
Authors: Thijs Kamma, Antoon Pelsser
Date: 2019-06-28 00:00:00

We develop a dual-control method for approximating investment strategies in incomplete environments that emerge from the presence of trading constraints. Convex duality enables the approximate technology to generate lower and upper bounds on the optimal value function. The mechanism rests on closed-form expressions pertaining to the portfolio composition, from which we are able to derive the near-optimal asset allocation explicitly. In a real financial market, we illustrate the accuracy of our approximate method on a dual CRRA utility function that characterises the preferences of a finite-horizon investor. Negligible duality gaps and insignificant annual welfare losses substantiate accuracy of the technique.
Novel Suboptimal approaches for Hyperparameter Tuning of Deep Neural Network [under the shelf of Optical Communication]
Date: 2019-06-26 00:00:00

Hyperparameter tuning is the main challenge of machine learning (ML)
algorithms. Grid search is a popular method in hyperparameter tuning of simple
ML algorithms; however, high computational complexity in complex ML algorithms
such as Deep Neural Networks (DNN) is the main barrier towards its practical
implementation. In this paper, two novel suboptimal grid search methods are
presented, which search the grid marginally and alternating. In order to
examine these methods, hyperparameter tuning is applied on two different DNN
based Optical Communication (OC) systems (Fiber OC, and Free Space Optical
(FSO) communication). The hyperparameter tuning of ML algorithms, despite its
importance is ignored in ML for OC investigations. In addition, this is the
first consideration of both FSO and Fiber OC systems in an ML for OC
investigation. Results indicate that despite greatly reducing computation load,
favorable performance could be achieved by the proposed methods. In addition,
it is shown that the alternating search method has better performance than
marginal grid search method. In sum, the proposed structures are
cost-effective, and appropriate for real-time applications.
3D Channel Modeling and Characterization for Hypersurface Empowered Indoor Environment at 60 GHz Millimeter-Wave Band
Date: 2019-06-28 00:00:00

This paper proposes a three-dimensional (3D) communication channel model for
an indoor environment considering the effect of the Hypersurface. The
Hypersurface is a software controlled intelligent metasurface, which can be
used to manipulate electromagnetic waves, as for example for non-specular
reflection and full absorption. Thus it can control the impinging rays from a
transmitter towards a receiver location in both LOS and NLOS paths, e.g. to
combat distance and improve wireless connectivity. We focus on the 60 GHz
mmWave frequency band due to its increasing significance in 5G/6G networks and
evaluate the effect of Hypersurface in an indoor environment in terms of
attenuation coefficients related to the Hypersurface reflection and absorption
functionalities, using CST simulation, a 3D electromagnetic simulator of high
frequency components. To highlight the benefits of Hypersurface coated walls
versus plain walls, we use the derived Hypersurface 3D channel model and a
custom 3D ray-tracing simulator for plain walls considering a typical indoor
scenario for different Tx-Rx location and separation distances.
The Branching-Course MPC Algorithm for Maritime Collision Avoidance
Date: 2019-06-28 00:00:00
Tasks: Collision Avoidance

This article presents a new algorithm for short-term maritime collision
avoidance (COLAV) named the branching-course MPC (BC-MPC) algorithm. The
algorithm is designed to be robust with respect to noise on obstacle estimates,
which is a significant source of disturbance when using exteroceptive sensors
such as e.g. radars for obstacle detection and tracking. Exteroceptive sensors
do not require vessel-to-vessel communication, which enables COLAV toward
vessels not equipped with e.g. automatic identification system (AIS)
transponders, in addition to increasing the robustness with respect to faulty
information which may be provided by other vessels. The BC-MPC algorithm is
compliant with rules 8 and 17 of the International Regulations for Preventing
Collisions at Sea (COLREGs), and favors maneuvers following rules 13-15. This
results in a COLREGs-aware algorithm which can ignore rules 13-15 when
necessary. The algorithm is experimentally validated in several full-scale
experiments in the Trondheimsfjord in 2017 using a radar-based system for
obstacle detection and tracking. The COLAV experiments show good performance in
compliance with the desired algorithm behavior.
A Note on Shift Retrieval Problems
Authors: Cristian Rusu
Date: 2019-06-28 00:00:00
Tasks: Retrieval

In this note, we discuss the shift retrieval problems, both classical and compressed, and provide connections between them using circulant matrices. We review the properties of circulant matrices necessary for our calculations and then show how shifts can be recovered from a single measurement.
Smart Charging Benefits in Autonomous Mobility on Demand Systems
Date: 2019-09-17 00:00:00

In this paper, we study the potential benefits from smart charging for a
fleet of electric vehicles (EVs) providing autonomous mobility-on-demand (AMoD)
services. We first consider a profit-maximizing platform operator who makes
decisions for routing, charging, rebalancing, and pricing for rides based on a
network flow model. Clearly, each of these decisions directly influence the
fleet's smart charging potential; however, it is not possible to directly
characterize the effects of various system parameters on smart charging under a
classical network flow model. As such, we propose a modeling variation that
allows us to decouple the charging and routing problems faced by the operator.
This variation allows us to provide closed-form mathematical expressions
relating the charging costs to the maximum battery capacity of the vehicles as
well as the fleet operational costs. We show that investing in larger battery
capacities and operating more vehicles for rebalancing reduces the charging
costs, while increasing the fleet operational costs. Hence, we study the
trade-off the operator faces, analyze the minimum cost fleet charging strategy,
and provide numerical results illustrating the smart charging benefits to the
operator.
Katugampola Generalized Conformal Derivative Approach to Inada Conditions and Solow-Swan Economic Growth Model
Date: 2019-06-29 00:00:00

This article shows a new focus of mathematic analysis for the Solow-Swan
economic growth model, using the generalized conformal derivative Katugampola
(KGCD). For this, under the same Solow-Swan model assumptions, the Inada
conditions are extended, which, for the new model shown here, depending on the
order of the KGCD. This order plays an important role in the speed of
convergence of the closed solutions obtained with this derivative for capital
(k) and for per-capita production (y) in the cases without migration and with
negative migration. Our approach to the model with the KGCD adds a new
parameter to the Solow-Swan model, the order of the KGCD and not a new state
variable. In addition, we propose several possible economic interpretations for
that parameter.
P-hacking in clinical trials and how incentives shape the distribution of results across phases
Date: 2020-03-19 00:00:00

Clinical research should conform to high standards of ethical and scientific
integrity, given that human lives are at stake. However, economic incentives
can generate conflicts of interest for investigators, who may be inclined to
withhold unfavorable results or even tamper with data in order to achieve
desired outcomes. To shed light on the integrity of clinical trial results,
this paper systematically analyzes the distribution of p-values of primary
outcomes for phase II and phase III drug trials reported to the
ClinicalTrials.gov registry. First, we detect no bunching of results just above
the classical 5% threshold for statistical significance. Second, a density
discontinuity test reveals an upward jump at the 5% threshold for phase III
results by small industry sponsors. Third, we document a larger fraction of
significant results in phase III compared to phase II. Linking trials across
phases, we find that early favorable results increase the likelihood of
continuing into the next phase. Once we take into account this selective
continuation, we can explain almost completely the excess of significant
results in phase III for trials conducted by large industry sponsors. For small
industry sponsors, instead, part of the excess remains unexplained.
Distributed Design of Robust Kalman Filters over Corrupted Channels
Authors: Xingkang He, Karl Henrik Johansson, Haitao Fang
Date: 2019-06-29 00:00:00

We study distributed filtering for a class of uncertain systems over corrupted communication channels. We propose a distributed robust Kalman filter with stochastic gains, through which upper bounds of the conditional mean square estimation errors are calculated online. We present a robust collective observability condition, under which the mean square error of the distributed filter is proved to be uniformly upper bounded if the network is strongly connected. For better performance, we modify the filer by introducing a switching fusion scheme based on a sliding window. It provides a smaller upper bound of the conditional mean square error. Numerical simulations are provided to validate the theoretical results and show that the filter scales to large networks.
Hybrid Collision Avoidance for ASVs Compliant with COLREGs Rules 8 and 13-17
Date: 2019-07-14 00:00:00
Tasks: Collision Avoidance, Model Predictive Control

This paper presents a three-layered hybrid collision avoidance (COLAV) system
for autonomous surface vehicles, compliant with rules 8 and 13-17 of the
International Regulations for Preventing Collisions at Sea (COLREGs). The COLAV
system consists of a high-level planner producing an energy-optimized
trajectory, a model predictive control based mid-level COLAV algorithm
considering moving obstacles and the COLREGs, and the branching-course model
predictive control algorithm for short-term COLAV handling emergency situations
in accordance with the COLREGs. Previously developed algorithms by the authors
are used for the high-level planner and short-term COLAV, while we in this
paper further develop the mid-level algorithm to make it comply with COLREGs
rules 13-17. This includes developing a state machine for classifying obstacle
vessels using a combination of the geometrical situation, the distance and time
to the closest point of approach (CPA) and a new CPA-like measure. The
performance of the hybrid COLAV system is tested through numerical simulations
for three scenarios representing a range of different challenges, including
multi-obstacle situations with multiple simultaneously active COLREGs rules,
and also obstacles ignoring the COLREGs. The COLAV system avoids collision in
all the scenarios, and follows the energy-optimized trajectory when the
obstacles do not interfere with it.
Detailed study of a moving average trading rule
Date: 2019-06-29 00:00:00

We present a detailed study of the performance of a trading rule that uses
moving average of past returns to predict future returns on stock indexes. Our
main goal is to link performance and the stochastic process of the traded
asset. Our study reports short, medium and long term effects by looking at the
Sharpe ratio (SR). We calculate the Sharpe ratio of our trading rule as a
function of the probability distribution function of the underlying traded
asset and compare it with data. We show that if the performance is mainly due
to presence of autocorrelation in the returns of the traded assets, the SR as a
function of the portfolio formation period (look-back) is very different from
performance due to the drift (average return). The SR shows that for look-back
periods of a few months the investor is more likely to tap into
autocorrelation. However, for look-back larger than few months, the drift of
the asset becomes progressively more important. Finally, our empirical work
reports a new long-term effect, namely oscillation of the SR and propose a
non-stationary model to account for such oscillations.
Relaxing the Exclusion Restriction in Shift-Share Instrumental Variable Estimation
Authors: Nicolas Apfel
Date: 2019-06-29 00:00:00

Many economic studies use shift-share instruments to estimate causal effects. Often, all shares need to fulfil an exclusion restriction, making the identifying assumption strict. This paper proposes to use methods that relax the exclusion restriction by selecting invalid shares. I apply the methods in two empirical examples: the effect of immigration on wages and of Chinese import exposure on employment. In the first application, the coefficient becomes lower and often changes sign, but this is reconcilable with arguments made in the literature. In the second application, the findings are mostly robust to the use of the new methods.
Coexistence of fast and slow gamma oscillations in one population of inhibitory spiking neurons
Date: 2019-06-29 00:00:00
Tasks: Hippocampus, Rhythm

Oscillations are a hallmark of neural population activity in various brain
regions with a spectrum covering a wide range of frequencies. Within this
spectrum gamma oscillations have received particular attention due to their
ubiquitous nature and to their correlation with higher brain functions.
Recently, it has been reported that gamma oscillations in the hippocampus of
behaving rodents are segregated in two distinct frequency bands: slow and fast.
These two gamma rhythms correspond to dfferent states of the network, but their
origin has been not yet clarified. Here, we show theoretically and numerically
that a single inhibitory population can give rise to coexisting slow and fast
gamma rhythms corresponding to collective oscillations of a balanced spiking
network. The slow and fast gamma rhythms are generated via two different
mechanisms: the fast one being driven by the coordinated tonic neural firing
and the slow one by endogenous fluctuations due to irregular neural activity.
We show that almost instantaneous stimulations can switch the collective gamma
oscillations from slow to fast and vice versa. Furthermore, to make a closer
contact with the experimental observations, we consider the modulation of the
gamma rhythms induced by a slower (theta) rhythm driving the network dynamics.
In this context, depending on the strength of the forcing, we observe
phase-amplitude and phase-phase coupling between the fast and slow gamma
oscillations and the theta forcing. Phase-phase coupling reveals different
theta-phases preferences for the two coexisting gamma rhythms.
A Data-Validated Host-Parasite Model for Infectious Disease Outbreaks
Date: 2019-08-29 00:00:00

The use of model experimental systems and mathematical models is important to
further understanding of infectious disease dynamics and strategize disease
mitigation. Gyrodactylids are helminth ectoparasites of teleost fish which have
many dynamical characteristics of microparasites but offer the advantage that
they can be quantified and tracked over time, allowing further insight into
within-host and epidemic dynamics. In this paper, we design a model to describe
host-parasite dynamics of the well-studied guppy-Gyrodactylus turnbulli system,
using experimental data to estimate parameters and validate it. We estimate the
basic reproduction number (R_0), for this system. Sensitivity analysis reveals
that parasite growth rate, and the rate at which the guppy mounts an immune
response have the greatest impact on outbreak peak and timing both for initial
outbreaks and on longer time scales. These findings highlight guppy population
resistance and parasite virulence as key factors in disease control, and future
work should focus on incorporating heterogeneity in host resistance into
disease models and extrapolating to other host-parasite systems.
Tracking VIX with VIX Futures: Portfolio Construction and Performance
Authors: Tim Leung, Brian Ward
Date: 2019-06-29 00:00:00

We study a series of static and dynamic portfolios of VIX futures and their effectiveness to track the VIX index. We derive each portfolio using optimization methods, and evaluate its tracking performance from both empirical and theoretical perspectives. Among our results, we show that static portfolios of different VIX futures fail to track VIX closely. VIX futures simply do not react quickly enough to movements in the spot VIX. In a discrete-time model, we design and implement a dynamic trading strategy that adjusts daily to optimally track VIX. The model is calibrated to historical data and a simulation study is performed to understand the properties exhibited by the strategy. In addition, comparing to the volatility ETN, VXX, we find that our dynamic strategy has a superior tracking performance.