pwc-archive/papers-with-abstracts huggingface dataset:
High-precision terahertz frequency modulated continuous wave imaging method using continuous wavelet transform
Date: 2019-05-28 00:00:00

Inspired by the extensive application of terahertz imaging technologies in
the field of aerospace, we exploit a terahertz frequency modulated continuous
wave imaging method with continuous wavelet transform algorithm to detect a
multilayer heat shield made of special materials. This method uses the
frequency modulation continuous wave system to catch the reflected terahertz
signal and then processing the image data by the continuous wavelet transform
with different basis functions. By calculating the sizes of the defects area in
the final images and then comparing the results with real samples, a novel and
practical high-precision terahertz imaging method are demonstrated. Our method
can be an effective tool for the terahertz nondestructive testing of
composites, drugs and some cultural heritages.
Multi-channel lock-in based differential front-end for broadband Raman spectroscopy
Date: 2019-06-25 00:00:00
Tasks: Sensitivity

In Broadband Stimulated Raman Spectroscopy, the intrinsic limit given by the
laser shot noise is seldom reached due to the electronic noise of the front-end
amplifier and the intensity fluctuations of the laser source. In this paper we
present a low-noise multi-channel acquisition system, with an
integration-oriented design, able to compensate the common-mode fluctuations of
the laser output power with the pseudo-differential structure and reach a
sensitivity better than 10 ppm thanks to the lock-in technique.
On the many-to-one strongly stable fractional matching set
Date: 2020-05-22 00:00:00
Tasks: All

For a many-to-one matching market where firms have strict and
$\boldsymbol{q}$-responsive preferences, we give a characterization of the set
of strongly stable fractional matchings as the union of the convex hull of all
connected sets of stable matchings. Also, we prove that a strongly stable
fractional matching is represented as a convex combination of stable matchings
that are ordered in the common preferences of all firms.
A Novel Relay Selection Strategy of Cooperative Network Impaired by Bursty Impulsive Noise
Date: 2019-05-29 00:00:00

Best relay selection (BRS) is crucial in enhancing the performance of
cooperative networks. In contrast to most previous works, where the guidelines
for BRS are limited to Gaussian noise, in this article, we propose a novel
relay selection protocol for a decode-and-forward cooperative network taking
into account the bursty impulsive noise (IN). The proposed protocol chooses the
N'th best relay considering both the channel gains and the states of the IN of
the source-relay and relay-destination links. For this scheme, to obtain the
state of IN, we propose a state detection algorithm using maximum a posteriori
(MAP) detection. To analyze the performance of the proposed protocol, we first
derive closed-form expressions for the probability density function (PDF) of
the received signal-to-noise ratio assuming all the relays know the state of IN
perfectly (genie-condition). Then, these PDFs are used to derive closed-form
expressions for the bit error rate (BER) and the outage probability. Finally,
we also derive the asymptotic BER and outage expressions to quantify the
diversity benefits. We show that the proposed MAP-based N'th BRS protocol
attains the derived genie-aided analytical results and outperforms the
conventional relay selection protocol, optimized for the Gaussian case, and
which does not take into account the IN memory.
A Novel Dual Modality Sensor With Sensitivities to Permittivity, Conductivity, and Permeability
Date: 2019-05-28 00:00:00

In this paper, an electromagnetic sensor which can operate simultaneously in
capacitive and inductive modalities with sensitivities to permittivity,
conductivity, and permeability is developed, and a novel measurement strategy
is proposed accordingly. The sensor is composed of two planar spiral coils with
a track width of 4 mm, which promotes its capacitive mode. The capacitive
coupling is measured in common mode, while the inductive coupling is measured
in differential mode. In capacitive mode, the sensor is sensitive to changes in
permittivity, i.e., the dielectric material distribution; while in inductive
mode, it is sensitive to magnetically permeable material and electrically
conductive material. Furthermore, it is demonstrated that the sensor can
simultaneously measure dielectric and conductive materials. This novel sensing
element has been designed and implemented. Experimental results verified its
effectiveness in dual modality measurement.
Reducing the Lift-Off Effect on Permeability Measurement for Magnetic Plates From Multifrequency Induction Data
Date: 2019-05-28 00:00:00

Liftoff variation causes errors in eddy current measurement of nonmagnetic
plates as well as magnetic plates. For nonmagnetic plates, previous work has
been carried out to address the issue. In this paper, we follow a similar
strategy, but try to reduce the lift-off effect on another index, zerocrossing
frequency for magnetic plates. This modified index, termed as the compensated
zero-crossing frequency, can be obtained from the measured multifrequency
inductance spectral data using the algorithm we developed in this paper. Since
the zero-crossing frequency can be compensated, the permeability of magnetic
plates can finally be predicted by deriving the relation between the
permeability and zero-crossing frequency from Dodd and Deeds method. We have
derived the method through mathematical manipulation and verified it by both
simulation and experimental data. The permeability error caused by liftoff can
be reduced within 7.5%.
Robust measurement of innovation performances in Europe with a hierarchy of interacting composite indicators
Date: 2019-05-18 00:00:00
Tasks: Benchmarking, Decision Making

For long time the measurement of innovation has been in the forefront of
policy makers' and researchers' agenda worldwide. Therefore, there is an
ongoing debate about which indicators should be used to measure innovation.
Recent approaches have favoured the use of composite innovation indicators.
However, there is no consensus about the appropriate methodology to aggregate
the varying dimensions of innovation into a single summary indicator. One of
the best known examples of composite innovation indicators is the European
Innovation Scoreboard (EIS). It is a relevant tool for benchmarking innovation
in Europe. Still, the EIS lacks a proper scheme for weighting the included
indicators according to their relative importance. In this context, we propose
an appraisal methodology permitting to take into consideration the interaction
of criteria and robustness concerns related to the elicitation of the weights
assigned to the elementary indicators. With this aim, we apply the
hierarchical-SMAA-Choquet integral approach. This integrated multicriteria
decision making (MCDM) method helps the users to rank and benchmark countries'
innovation performance taking into account the importance and interaction of
criteria assigned by themselves, rather than equal weights or weights
exogenously fixed by external experts.
Multi-Numerology Multiplexing and Inter-Numerology Interference Analysis for 5G
Date: 2019-05-29 00:00:00

Fifth generation (5G) radio access technology (RAT) is expected to flexibly
serve multiple services with extremely diverse requirements. One of the steps
taken toward fulfilling this vision of the 5G-RAT is an introduction of the
multi-numerology concept, where multiple frame structures with different
subcarrier spacings coexist in one frequency band. Though efficient in
providing the required flexibility, this approach introduces a new kind of
interference into the system known as inter numerology interference (INI). This
study is geared toward analyzing the INI problem considering a cyclic prefix
orthogonal frequency domain multiplexing (CP-OFDM) system and exposing the
factors contributing to it through mathematical analyses. In-depth discussion
of various critical issues concerning multi-numerology system such as frequency
domain multiplexing and time domain symbol alignment for mixed numerologies is
presented. Based on the findings of the conducted analyses, the paper
highlights some approaches for minimizing INI in the system. The developed
mathematical analysis is finally verified by Monte-Carlo simulations.
Detectability, Duality, and Surplus Extraction
Authors: Giuseppe Lopomo, Luca Rigotti, Chris Shannon
Date: 2019-05-29 00:00:00

We study surplus extraction in the general environment of McAfee and Reny (1992), and provide two alternative proofs of their main theorem. The first is an analogue of the classic argument of Cremer and McLean (1985, 1988), using geometric features of the set of agents' beliefs to construct a menu of contracts extracting the desired surplus. This argument, which requires a finite state space, also leads to a counterexample showing that full extraction is not possible without further significant conditions on agents' beliefs or surplus, even if the designer offers an infinite menu of contracts. The second argument uses duality and applies for an infinite state space, thus yielding the general result of McAfee and Reny (1992). Both arguments suggest methods for studying surplus extraction in settings beyond the standard model, in which the designer or agents might have objectives other than risk neutral expected value maximization.
Error-speed correlations in biopolymer synthesis
Authors: Davide Chiuchiú, Yuhai Tu, Simone Pigolotti
Date: 2019-05-30 00:00:00

Synthesis of biopolymers such as DNA, RNA, and proteins are biophysical processes aided by enzymes. Performance of these enzymes is usually characterized in terms of their average error rate and speed. However, because of thermal fluctuations in these single-molecule processes, both error and speed are inherently stochastic quantities. In this paper, we study fluctuations of error and speed in biopolymer synthesis and show that they are in general correlated. This means that, under equal conditions, polymers that are synthesized faster due to a fluctuation tend to have either better or worse errors than the average. The error-correction mechanism implemented by the enzyme determines which of the two cases holds. For example, discrimination in the forward reaction rates tends to grant smaller errors to polymers with faster synthesis. The opposite occurs for discrimination in monomer rejection rates. Our results provide an experimentally feasible way to identify error-correction mechanisms by measuring the error-speed correlations.
Separating an Outlier from a Change
Authors: Deniz Sargun, C. Emre Koksal
Date: 2019-05-30 00:00:00
Tasks: Change Detection

We study the change detection problem with an unknown post-change distribution. Under this constraint, the unknown change in the distribution of observations may occur in many ways without much structure on the observations, whereas, before the change point, a false alarm (outlier) is highly structured, following a particular sample path. We first characterize these likely events for the deviation and propose a method to test the empirical distribution, relative to the most likely way for it to occur as an outlier. We benchmark our method with finite moving average (FMA) and generalized likelihood ratio tests (GLRT) under 4 different performance criteria including the run time time complexity. Finally, we apply our method on economic market indicators and climate data. Our method successfully captures the regime shifts during times of historical significance for the markets and identifies the current climate change phenomenon to be a highly likely regime shift rather than a random event.
The Income Fluctuation Problem and the Evolution of Wealth
Date: 2020-02-29 00:00:00

We analyze the household savings problem in a general setting where returns
on assets, non-financial income and impatience are all state dependent and
fluctuate over time. All three processes can be serially correlated and
mutually dependent. Rewards can be bounded or unbounded and wealth can be
arbitrarily large. Extending classic results from an earlier literature, we
determine conditions under which (a) solutions exist, are unique and are
globally computable, (b) the resulting wealth dynamics are stationary, ergodic
and geometrically mixing, and (c) the wealth distribution has a Pareto tail. We
show how these results can be used to extend recent studies of the wealth
distribution. Our conditions have natural economic interpretations in terms of
asymptotic growth rates for discounting and return on savings.
Measurement of permeability for ferrous metallic plates using a novel lift-off compensation technique on phase signature
Date: 2019-05-28 00:00:00
Tasks: Prediction

Lift-off of sensor affects the prediction of electromagnetic properties for
both ferrous and non-ferrous steel plates. In this paper, we developed a
strategy to address this issue for ferrous plates. With increased lift-off, the
phase of the measured impedance for steel plates reduces. Meanwhile, the
magnitude of the impedance signal decreases. Based on these facts, a phase
compensation algorithm is developed which corrects the phase change due to
lift-off considering the magnitude of the impedance signal. Further, a new
magnetic permeability prediction technique is presented, which has been
validated by analytical and measured results. With this new technique, the
error in permeability prediction is less than 2% within the range of lift-offs
tested.
An equivalent-effect phenomenon in eddy current non-destructive testing of thin structures
Date: 2019-05-28 00:00:00

The inductance/impedance due to thin metallic structures in non-destructive
testing (NDT) is difficult to evaluate. In particular, in Finite Element Method
(FEM) eddy current simulation, an extremely fine mesh is required to accurately
simulate skin effects especially at high frequencies, and this could cause an
extremely large total mesh for the whole problem, i.e. including, for example,
other surrounding structures and excitation sources like coils. Consequently,
intensive computation requirements are needed. In this paper, an
equivalent-effect phenomenon is found, which has revealed that alternative
structures can produce the same effect on the sensor response, i.e. mutual
impedance/inductance of coupled coils if a relationship (reciprocal
relationship) between the electrical conductivity and the thickness of the
structure is observed. By using this relationship, the mutual
inductance/impedance can be calculated from the equivalent structures with much
fewer mesh elements, which can significantly save the computation time. In eddy
current NDT, coils inductance/impedance is normally used as a critical
parameter for various industrial applications, such as flaw detection, coating
and microstructure sensing. Theoretical derivation, measurements and
simulations have been presented to verify the feasibility of the proposed
phenomenon.
Determination of the magnetic permeability, electrical conductivity, and thickness of ferrite metallic plates using a multi-frequency electromagnetic sensing system
Date: 2019-05-28 00:00:00

In this paper, an inverse method was developed which can, in principle,
reconstruct arbitrary permeability, conductivity, thickness, and lift-off with
a multi-frequency electromagnetic sensor from inductance spectroscopic
measurements. The system fives the error of "Bad character(s) in field
Abstract" for no reason. Please refer to manuscript for the full abstract.
Threshold Regression with Nonparametric Sample Splitting
Authors: Yoonseok Lee, Yulong Wang
Date: 2019-05-30 00:00:00
Tasks: regression

This paper develops a threshold regression model where an unknown relationship between two variables nonparametrically determines the threshold. We allow the observations to be cross-sectionally dependent so that the model can be applied to determine an unknown spatial border for sample splitting over a random field. We derive the uniform rate of convergence and the nonstandard limiting distribution of the nonparametric threshold estimator. We also obtain the root-n consistency and the asymptotic normality of the regression coefficient estimator. Our model has broad empirical relevance as illustrated by estimating the tipping point in social segregation problems as a function of demographic characteristics; and determining metropolitan area boundaries using nighttime light intensity collected from satellite imagery. We find that the new empirical results are substantially different from those in the existing studies.
Simultaneous induction of SSMVEP and SMR Using a Gaiting video stimulus: a novel hybrid brain-computer interface
Date: 2019-05-30 00:00:00
Tasks: Brain Computer Interface, EEG, Electroencephalogram (EEG), Rhythm, SSVEP

We proposed a novel visual stimulus for brain-computer interface. The
stimulus is in the form gaiting sequence of a human. The hypothesis is that
observing such a visual stimulus would simultaneously induce 1) steady-state
motion visual evoked potential (SSMVEP) in the occipital area, similarly to an
SSVEP stimulus; and 2) sensorimotor rhythm (SMR) in the primary sensorimotor
area, because such action observation (AO) could activate the mirror neuron
system. Canonical correlation analysis (CCA) was used to detect SSMVEP from
occipital EEG, and event-related spectral perturbations (ERSP) were used to
identify SMR in the EEG from the sensorimotor area. The results showed that the
proposed visual gaiting stimulus-induced SSMVEP, with classification accuracies
of 88.9 $\pm$ 12.0% in a four-class scenario. More importantly, it induced
clear and sustained event-related desynchronization/synchronization (ERD/ERS)
in the EEG from the sensorimotor area, while no ERD/ERS in the sensorimotor
area could be observed when the other two SSVEP stimuli were used. Further, for
participants with sufficiently clear SSMVEP pattern (classification accuracy >
85%), the ERD index values in mu-beta band induced by the proposed gaiting
stimulus were statistically different from that of the other two types of
stimulus. Therefore, a novel BCI based on the proposed stimulus has potential
in neurorehabilitation applications because it simultaneously has the high
accuracy of an SSMVEP (~90% accuracy in a four-class setup) and the ability to
activate sensorimotor cortex. And such potential will be further explored in
future studies.
Radio Frequency Magnet-free Circulators Based on Spatiotemporal Modulation of Surface Acoustic Wave Filters
Date: 2019-05-30 00:00:00

In this paper, a new generation of magnet-free circulators with high
performance is proposed. Circulators are crucial devices in modern
communication systems due to their ability to enable full-duplexing and double
the spectral efficiency directly in the physical layer of the radio-frequency
(RF) front-end. Traditionally, Lorentz reciprocity is broken by applying
magnetic bias to ferrite materials, therefore conventional circulators are
bulky and expensive. In this paper, this problem is addressed by replacing the
magnetic bias with periodic spatiotemporal modulation. Compared to previous
works, the proposed circulator is constructed using surface acoustic wave (SAW)
filters instead of transmission lines (TL), which reduces the modulation
frequency by at least a factor of 20 and ensures ultra-low power consumption
and high linearity. The miniaturized high quality (Q) factor SAW filters also
lead to a low-loss non-reciprocal band with strong isolation (IX) and broad
bandwidth (BW) on a chip scale, therefore addressing such limitations in
previous magnet-free demonstrations. Furthermore, compared to the conventional
differential circuit configuration, a novel quad configuration is developed,
which doubles the intermodulation-free bandwidth.
Characterization of cell division control strategies through continuous rate models
Authors: Cesar Augusto Nieto-Acuna, Juan Carlos Arias-Castro, Carlos Arturo Sanchez-Isaza, Cesar Augusto Vargas-Garcia, Juan Manuel Pedraza
Date: 2019-05-31 00:00:00

Recent experiments have supported the Adder model for E. coli division control. This model posits that bacteria grow, on average, a fixed size before division. It also predicts decorrelation between the noise in the added size and the size at birth. Here we use new experiments and a theoretical approach based on continuous rate models to explore deviations from the adder strategy, specifically, the division control of E. coli growing with glycerol as carbon source. In this medium, the division strategy is sizer-like, which means that the added size decreases with the size at birth. We found that in a sizer-like strategy the mean added size decreases with the size at birth while the noise in added size increases. We discuss possible molecular mechanisms underlying this strategy, and propose a general model that encompasses the different division strategies.
Improving the resolution of Cryo-EM single particle analysis
Date: 2020-03-11 00:00:00
Tasks: Single Particle Analysis

We presented a new 3D refinement method for Cryo-EM single particle analysis
which can improve the resolution of final electron density map in this paper.
We proposed to enforce both sparsity and smoothness to improve the regularity
of electron density map in the refinement process. To achieve this goal, we
designed a novel type of real space penalty function and incorporated it into
the refinement process. We bridged the backprojection step with local kernel
regression, thus enabling us to embed the 3D model in reproducing kernel
Hilbert space using specific kernels. We also proposed a first order method to
solve the resulting optimization problem and implemented it efficiently with
CUDA. We compared the performance of our new method with respect to the
traditional method on real datasets using a set of widely used metrics for
Cryo-EM model validation. We demonstrated that our method outperforms the
traditional method in terms of those metrics. The implementation of our method
can be found at https://github.com/alncat/cryoem.
Cross-sectional Learning of Extremal Dependence among Financial Assets
Date: 2019-10-27 00:00:00
Proceeding: NeurIPS 2019 12

We propose a novel probabilistic model to facilitate the learning of
multivariate tail dependence of multiple financial assets. Our method allows
one to construct from known random vectors, e.g., standard normal,
sophisticated joint heavy-tailed random vectors featuring not only distinct
marginal tail heaviness, but also flexible tail dependence structure. The
novelty lies in that pairwise tail dependence between any two dimensions is
modeled separately from their correlation, and can vary respectively according
to its own parameter rather than the correlation parameter, which is an
essential advantage over many commonly used methods such as multivariate $t$ or
elliptical distribution. It is also intuitive to interpret, easy to track, and
simple to sample comparing to the copula approach. We show its flexible tail
dependence structure through simulation. Coupled with a GARCH model to
eliminate serial dependence of each individual asset return series, we use this
novel method to model and forecast multivariate conditional distribution of
stock returns, and obtain notable performance improvements in multi-dimensional
coverage tests. Besides, our empirical finding about the asymmetry of tails of
the idiosyncratic component as well as the market component is interesting and
worth to be well studied in the future.