pwc-archive/papers-with-abstracts huggingface dataset:
A Linear Modeling Approach on LTGP Signals and Seismic Activity
Date: 2018-04-10 00:00:00

This study illustrates presents a set of the Long-Term Geoelectric Potential
(LTGP) measurements that are collected for experimental investigation in
Western Greece during a five-year period (1993-1997). During this period, many
major destructive earthquake events occurred that caused human casualties and
extended material damages. The collection and processing of geoelectric
measurements was done by an automated data acquisition system at the
Seismological Laboratory of the University of Patras, Greece. This novel study
considers seismic activity of this area as a typical linear dynamic system and
the dynamic relationship between the magnitude of earthquakes and Long-Term
Geoelectric Potential signals is inferred by the Recursive Least Square
algorithm. The results are encouraging and show that linear dynamic systems,
which are widely used in modern control theory, can describe efficiently the
dynamic behavior of seismic activity and become a useful interpretative tool of
seismic phenomenon.
Better than Rician: Modelling millimetre wave channels as Two-Wave with Diffuse Power
Date: 2018-04-10 00:00:00

This contribution provides experimental evidence for the two-wave with
diffuse power (TWDP) fading model. We have conducted two indoor millimetre wave
measurement campaigns with directive horn antennas at both link ends. One horn
antenna is mounted in a corner of our laboratory, while the other is steerable
and scans azimuth and elevation. Our first measurement campaign is based on
scalar network analysis with 7 GHz of bandwidth. Our second measurement
campaign obtains magnitude and phase information, additionally sampled
directionally at several positions in space. %This second measurement campaign
is limited to 2 GHz bandwidth. We apply Akaike's information criterion to
decide whether Rician fading sufficiently explains the data or the generalized
TWDP fading model is necessary. Our results indicate that the TWDP fading
hypothesis is favoured over Rician fading in situations where the steerable
antenna is pointing towards reflecting objects or is slightly misaligned at
line-of-sight. We demonstrate TWDP fading in several different domains, namely,
frequency, space, and time.
The self-referring DNA and protein: a remark on physical and geometrical aspects
Authors: Tsvi Tlusty
Date: 2018-04-10 00:00:00

All known life forms are based upon a hierarchy of interwoven feedback loops, operating over a cascade of space, time and energy scales. Among the most basic loops are those connecting DNA and proteins. For example, in genetic networks, DNA genes are expressed as proteins, which may bind near the same genes and thereby control their own expression. In this molecular type of self-reference, information is mapped from the DNA sequence to the protein and back to DNA. There is a variety of dynamic DNA-protein self-reference loops, and the purpose of this remark is to discuss certain geometrical and physical aspects related to the back and forth mapping between DNA and proteins. The discussion raises basic questions regarding the nature of DNA and proteins as self-referring matter, which are examined in a simple toy model.
The Quaternion-Based Spatial Coordinate and Orientation Frame Alignment Problems
Date: 2020-02-27 00:00:00

We review the general problem of finding a global rotation that transforms a
given set of points and/or coordinate frames (the "test" data) into the best
possible alignment with a corresponding set (the "reference" data). For 3D
point data, this "orthogonal Procrustes problem" is often phrased in terms of
minimizing a root-mean-square deviation or RMSD corresponding to a Euclidean
distance measure relating the two sets of matched coordinates. We focus on
quaternion eigensystem methods that have been exploited to solve this problem
for at least five decades in several different bodies of scientific literature
where they were discovered independently. While numerical methods for the
eigenvalue solutions dominate much of this literature, it has long been
realized that the quaternion-based RMSD optimization problem can also be solved
using exact algebraic expressions based on the form of the quartic equation
solution published by Cardano in 1545; we focus on these exact solutions to
expose the structure of the entire eigensystem for the traditional 3D spatial
alignment problem. We then explore the structure of the less-studied
orientation data context, investigating how quaternion methods can be extended
to solve the corresponding 3D quaternion orientation frame alignment (QFA)
problem, noting the interesting equivalence of this problem to the
rotation-averaging problem, which also has been the subject of independent
literature threads. We conclude with a brief discussion of the combined 3D
translation-orientation data alignment problem. Appendices are devoted to a
tutorial on quaternion frames, a related quaternion technique for extracting
quaternions from rotation matrices, and a review of quaternion
rotation-averaging methods relevant to the orientation-frame alignment problem.
Supplementary Material covers extensions of quaternion methods to the 4D
problem.
Sensing Hidden Vehicles by Exploiting Multi-Path V2V Transmission
Date: 2018-04-10 00:00:00
Tasks: Autonomous Driving, Position

This paper presents a technology of sensing hidden vehicles by exploiting
multi-path vehicle-to-vehicle (V2V) communication. This overcomes the
limitation of existing RADAR technologies that requires line-of-sight (LoS),
thereby enabling more intelligent manoeuvre in autonomous driving and improving
its safety. The proposed technology relies on transmission of orthogonal
waveforms over different antennas at the target (hidden) vehicle. Even without
LoS, the resultant received signal enables the sensing vehicle to detect the
position, shape, and driving direction of the hidden vehicle by jointly
analyzing the geometry (AoA/AoD/propagation distance) of individual propagation
path. The accuracy of the proposed technique is validated by realistic
simulation including both highway and rural scenarios.
Controlling seizure propagation in large-scale brain networks
Date: 2018-04-10 00:00:00

Information transmission in the human brain is a fundamentally dynamic
network process. In partial epilepsy, this process is perturbed and highly
synchronous seizures originate in a local network, the so-called epileptogenic
zone (EZ), before recruiting other close or distant brain regions. We studied
patient-specific brain network models of 15 drug-resistant epilepsy patients
with implanted stereotactic electroencephalography (SEEG) electrodes. Each
personalized brain model was derived from structural data of magnetic resonance
imaging (MRI) and diffusion tensor weighted imaging (DTI), comprising 88 nodes
equipped with region specific neural mass models capable of demonstrating a
range of epileptiform discharges. Each patients virtual brain was further
personalized through the integration of the clinically hypothesized EZ.
Subsequent simulations and connectivity modulations were performed and
uncovered a finite repertoire of seizure propagation patterns. Across patients,
we found that (i) patient-specific network connectivity is predictive for the
subsequent seizure propagation pattern; (ii)seizure propagation is
characterized by a systematic sequence of brain states; (iii) propagation can
be controlled by an optimal intervention on the connectivity matrix; (iv) the
degree of invasiveness can be significantly reduced via the here proposed
seizure control as compared to traditional resective surgery. To stop seizures,
neurosurgeons typically resect the EZ completely. We showed that stability
analysis of the network dynamics using graph theoretical metrics estimates
reliably the spatiotemporal properties of seizure propagation. This suggests
novel less invasive paradigms of surgical interventions to treat and manage
partial epilepsy.
On the Regimes in Millimeter wave Networks: Noise-limited or Interference-limited?
Date: 2018-04-10 00:00:00
Tasks: Management

Given the overcrowding in the 300 MHz-3 GHz spectrum, millimeter wave
(mmWave) spectrum is a promising candidate for the future generations of
wireless networks. With the unique propagation characteristics at mmWave
frequencies, one of the fundamental questions to address is whether mmWave
networks are noise or interference-limited. The regime in which the network
operates significantly impacts the MAC layer design, resource allocation
procedure and also interference management techniques. In this paper, we first
derive the statistical characteristic of the cumulative interference in
finite-sized mmWave networks considering configuration randomness across
spatial and spectral domains while including the effect of blockages.
Subsequently, using the derived interference model we set up a likelihood ratio
test (LRT) (that is dependent on various network parameters) in order to detect
the regime of the network from an arbitrarily located user standpoint. Unlike
traditional networks, in mmWave networks, different likelihood of experiencing
an interference-limited regime can be observed at different locations.
High-resolution computer meshes of the lower body bones of an adult human female derived from CT images
Authors: Manish Sreenivasa, Daniel Gonzalez-Alvarado
Date: 2018-04-10 00:00:00

Background Computer-based geometrical meshes of bones are important for applications in computational biomechanics as well as clinical software. There is however a lack of freely available detailed bone meshes, especially related to the human female morphology. Methods & Results We provide high resolution bone meshes of the lower body, derived from CT images of a 59 year old female cadaver that were sourced from the Visible Human Data Set, Visible Human Project (NIH, USA). Important bone landmarks and joint rotation axes are identified from the extracted meshes. A script-based framework is developed to provide a graphical user interface that can visualize, resample and modify the meshes to fit different subject scales. Conclusion This open-data resource fills a gap in available data and is provided for free usage in research and other applications. The associated scripts allows users to easily transform the meshes to different laboratory and software setups. This resource may be accessed through the following web link: https://github.com/manishsreenivasa/BMFToolkit This document is the author's version of this article.
Moment Inequalities in the Context of Simulated and Predicted Variables
Date: 2018-04-10 00:00:00

This paper explores the effects of simulated moments on the performance of
inference methods based on moment inequalities. Commonly used confidence sets
for parameters are level sets of criterion functions whose boundary points may
depend on sample moments in an irregular manner. Due to this feature,
simulation errors can affect the performance of inference in non-standard ways.
In particular, a (first-order) bias due to the simulation errors may remain in
the estimated boundary of the confidence set. We demonstrate, through Monte
Carlo experiments, that simulation errors can significantly reduce the coverage
probabilities of confidence sets in small samples. The size distortion is
particularly severe when the number of inequality restrictions is large. These
results highlight the danger of ignoring the sampling variations due to the
simulation errors in moment inequality models. Similar issues arise when using
predicted variables in moment inequalities models. We propose a method for
properly correcting for these variations based on regularizing the intersection
of moments in parameter space, and we show that our proposed method performs
well theoretically and in practice.
Report on the 7th International Workshop on Bibliometric-enhanced Information Retrieval (BIR 2018)
Authors: Mayr Philipp, Frommholz Ingo, Cabanac Guillaume
Date: 2018-04-10 00:00:00
Tasks: Information Retrieval, Retrieval

The Bibliometric-enhanced Information Retrieval (BIR) workshop series has
started at ECIR in 2014 and serves as the annual gathering of IR researchers
who address various information-related tasks on scientific corpora and
bibliometrics. We welcome contributions elaborating on dedicated IR systems, as
well as studies revealing original characteristics on how scientific knowledge
is created, communicated, and used. This report presents all accepted papers at
the 7th BIR workshop at ECIR 2018 in Grenoble, France.
On the Performance of Non-Orthogonal Multiple Access Systems with Imperfect Successive Interference Cancellation
Date: 2018-04-11 00:00:00
Tasks: Diversity

Non-orthogonal multiple access (NOMA) technique has sparked a growing
research interest due to its ability to enhance the overall spectral efficiency
of wireless systems. In this paper, we investigate the pairwise error
probability (PEP) performance of conventional NOMA systems, where an exact
closed form expression for the PEP is derived for different users, to give some
insight about the reliability of the far and near users. Through the derivation
of PEP expressions, we demonstrate that the maximum achievable diversity order
is proportional to the user's order. The obtained error probability expressions
are used to formulate an optimization problem that minimizes the overall bit
error rate (BER) under power and error rate threshold constrains. The derived
analytical results, corroborated by Monte Carlo simulations, are presented to
show the diversity order and error rate performance of each individual user.
Complex pattern formation driven by the interaction of stable fronts in a competition-diffusion system
Date: 2018-10-31 00:00:00

The ecological invasion problem in which a weaker exotic species invades an
ecosystem inhabited by two strongly competing native species is modelled by a
three-species competition-diffusion system. It is known that for a certain
range of parameter values competitor-mediated coexistence occurs and complex
spatio-temporal patterns are observed in two spatial dimensions. In this paper
we uncover the mechanism which generates such patterns. Under some assumptions
on the parameters the three-species competition-diffusion system admits two
planarly stable travelling waves. Their interaction in one spatial dimension
may result in either reflection or merging into a single homoclinic wave,
depending on the strength of the invading species. This transition can be
understood by studying the bifurcation structure of the homoclinic wave. In
particular, a time-periodic homoclinic wave (breathing wave) is born from a
Hopf bifurcation and its unstable branch acts as a separator between the
reflection and merging regimes. The same transition occurs in two spatial
dimensions: the stable regular spiral associated to the homoclinic wave
destabilizes, giving rise first to an oscillating breathing spiral and then
breaking up producing a dynamic pattern characterized by many spiral cores. We
find that these complex patterns are generated by the interaction of two
planarly stable travelling waves, in contrast with many other well known cases
of pattern formation where planar instability plays a central role.
Monte Carlo pathwise sensitivities for barrier options
Date: 2019-04-18 00:00:00

The Monte Carlo pathwise sensitivities approach is well established for
smooth payoff functions. In this work, we present a new Monte Carlo algorithm
that is able to calculate the pathwise sensitivities for discontinuous payoff
functions. Our main tool is to combine the one-step survival idea of Glasserman
and Staum with the stable differentiation approach of Alm, Harrach, Harrach and
Keller. As an application we use the derived results for a two-dimensional
calibration of a CoCo-Bond, which we model with different types of discretely
monitored barrier options.
Experimental similarity assessment for a collection of fragmented artifacts
Authors: Biasotti Silvia, Thompson Elia Moscoso, Spagnuolo Michela
Date: 2018-04-11 00:00:00

In the Visual Heritage domain, search engines are expected to support
archaeologists and curators to address cross-correlation and searching across
multiple collections. Archaeological excavations return artifacts that often
are damaged with parts that are fragmented in more pieces or totally missing.
The notion of similarity among fragments cannot simply base on the geometric
shape but style, material, color, decorations, etc. are all important factors
that concur to this concept. In this work, we discuss to which extent the
existing techniques for 3D similarity matching are able to approach fragment
similarity, what is missing and what is necessary to be further developed.
Non-convex optimization for 3D point source localization using a rotating point spread function
Date: 2018-09-27 00:00:00

We consider the high-resolution imaging problem of 3D point source image
recovery from 2D data using a method based on point spread function (PSF)
engineering. The method involves a new technique, recently proposed by
S.~Prasad, based on the use of a rotating PSF with a single lobe to obtain
depth from defocus. The amount of rotation of the PSF encodes the depth
position of the point source. Applications include high-resolution single
molecule localization microscopy as well as the problem addressed in this paper
on localization of space debris using a space-based telescope. The localization
problem is discretized on a cubical lattice where the coordinates of nonzero
entries represent the 3D locations and the values of these entries the fluxes
of the point sources. Finding the locations and fluxes of the point sources is
a large-scale sparse 3D inverse problem. A new nonconvex regularization method
with a data-fitting term based on Kullback-Leibler (KL) divergence is proposed
for 3D localization for the Poisson noise model. In addition, we propose a new
scheme of estimation of the source fluxes from the KL data-fitting term.
Numerical experiments illustrate the efficiency and stability of the algorithms
that are trained on a random subset of image data before being applied to other
images. Our 3D localization algorithms can be readily applied to other kinds of
depth-encoding PSFs as well.
Incompressible limit of a continuum model of tissue growth with segregation for two cell populations
Date: 2018-04-11 00:00:00

This paper proposes a model for the growth two interacting populations of
cells that do not mix. The dynamics is driven by pressure and cohesion forces
on the one hand and proliferation on the other hand. Following earlier works on
the single population case, we show that the model approximates a free boundary
Hele Shaw type model that we characterise using both analytical and numerical
arguments.
Some elementary mechanisms for critical transitions and hysteresis in simple predator prey models
Date: 2018-04-11 00:00:00

Trait-mediated indirect effects are increasingly acknowledged as important
components in the dynamics of ecological systems. The hamiltonian form of the
LV equations is traditionally modified by adding density dependence to the prey
variable and functional response to the predator variable. Enriching these
non-linear elements with a trait-mediation added to the carrying capacity of
the prey creates the dynamics of critical transitions and hysteretic zones.
Optimal liquidation under stochastic price impact
Date: 2018-04-11 00:00:00

We assume a continuous-time price impact model similar to Almgren-Chriss but
with the added assumption that the price impact parameters are stochastic
processes modeled as correlated scalar Markov diffusions. In this setting, we
develop trading strategies for a trader who desires to liquidate his inventory
but faces price impact as a result of his trading. For a fixed trading horizon,
we perform coefficient expansion on the Hamilton-Jacobi-Bellman equation
associated with the trader's value function. The coefficient expansion yields a
sequence of partial differential equations that we solve to give closed-form
approximations to the value function and optimal liquidation strategy. We
examine some special cases of the optimal liquidation problem and give
financial interpretations of the approximate liquidation strategies in these
cases. Finally, we provide numerical examples to demonstrate the effectiveness
of the approximations.
Big Data Driven Vehicular Networks
Date: 2018-04-11 00:00:00

Vehicular communications networks (VANETs) enable information exchange among
vehicles, other end devices and public networks, which plays a key role in road
safety/infotainment, intelligent transportation system, and self-driving
system. As the vehicular connectivity soars, and new on-road mobile
applications and technologies emerge, VANETs are generating an ever-increasing
amount of data, requiring fast and reliable transmissions through VANETs. On
the other hand, a variety of VANETs related data can be analyzed and utilized
to improve the performance of VANETs. In this article, we first review the
VANETs technologies to efficiently and reliably transmit the big data. Then,
the methods employing big data for studying VANETs characteristics and
improving VANETs performance are discussed. Furthermore, we present a case
study where machine learning schemes are applied to analyze the VANETs
measurement data for efficiently detecting negative communication conditions.
On Using Non-Volatile Memory in Apache Lucene
Authors: Pydipaty Ramdoot, Saha Amit
Date: 2018-04-12 00:00:00
Tasks: Information Retrieval, Retrieval

Apache Lucene is a widely popular information retrieval library used to
provide search functionality in an extremely wide variety of applications.
Naturally, it has to efficiently index and search large number of documents.
With non-volatile memory in DIMM form factor (NVDIMM), software now has access
to durable, byte-addressable memory with write latency within an order of
magnitude of DRAM write latency.
  In this preliminary article, we present the first reported work on the impact
of using NVDIMM on the performance of committing, searching, and near-real time
searching in Apache Lucene. We show modest improvements by using NVM but, our
empirical study suggests that bigger impact requires redesigning Lucene to
access NVM as byte-addressable memory using loads and stores, instead of
accessing NVM via the file system.
Functional geometry of protein-protein interaction networks
Date: 2018-04-12 00:00:00
Tasks: Clustering

Motivation: Protein-protein interactions (PPIs) are usually modelled as
networks. These networks have extensively been studied using graphlets, small
induced subgraphs capturing the local wiring patterns around nodes in networks.
They revealed that proteins involved in similar functions tend to be similarly
wired. However, such simple models can only represent pairwise relationships
and cannot fully capture the higher-order organization of protein interactions,
including protein complexes. Results: To model the multi-sale organization of
these complex biological systems, we utilize simplicial complexes from
computational geometry. The question is how to mine these new representations
of PPI networks to reveal additional biological information. To address this,
we define simplets, a generalization of graphlets to simplicial complexes. By
using simplets, we define a sensitive measure of similarity between simplicial
complex network representations that allows for clustering them according to
their data types better than clustering them by using other state-of-the-art
measures, e.g., spectral distance, or facet distribution distance. We model
human and baker's yeast PPI networks as simplicial complexes that capture PPIs
and protein complexes as simplices. On these models, we show that our newly
introduced simplet-based methods cluster proteins by function better than the
clustering methods that use the standard PPI networks, uncovering the new
underlying functional organization of the cell. We demonstrate the existence of
the functional geometry in the PPI data and the superiority of our
simplet-based methods to effectively mine for new biological information hidden
in the complexity of the higher order organization of PPI networks.