pwc-archive/papers-with-abstracts huggingface dataset:
Modelling stochastic resonance in humans: the influence of lapse rate
Date: 2017-11-14 00:00:00

Adding noise to a sensory signal generally decreases human performance.
However noise can improve performance too, due to a process called stochastic
resonance (SR). This paradoxical effect may be exploited in psychophysical
experiments, to provide additional insights into how the sensory system deals
with noise. Here, I develop a model for stochastic resonance to study the
influence of noise on human perception, in which the biological parameter of
`lapse rate' was included. I show that the inclusion of lapse rate allows for
the occurrence of stochastic resonance in terms of the performance metric d'.
At the same time, I show that high levels of lapse rate cause stochastic
resonance to disappear. It is also shown that noise generated in the brain
(i.e., internal noise) may obscure any effect of stochastic resonance in
experimental settings. I further relate the model to a standard equivalent
noise model, the linear amplifier model, and show that the lapse rate can
function to scale the threshold versus noise (TvN) curve, similar to the
efficiency parameter in equivalent noise (EN) models. Therefore, lapse rate
provides a psychophysical explanation for reduced efficiency in EN paradigms.
Furthermore, I note that ignoring lapse rate may lead to an overestimation of
internal noise in equivalent noise paradigms. Overall, describing stochastic
resonance in terms of signal detection theory, with the inclusion of lapse
rate, may provide valuable new insights into how human performance depends on
internal and external noise.
A memory mechanism based on two dimensional code of neurosome pattern
Date: 2017-11-14 00:00:00
Tasks: Vocal Bursts Valence Prediction

We have recognized that 2D codes, i.e., a group of strongly connected
neurosomes that can be simultaneously excited, are the basic data carriers for
memory in a brain. An echoing mechanism between two neighboring layers of
neurosomes is assumed to establish temporary memory, and repeating processes
enhance the formation of long-term memory. Creation and degradation of memory
information are statistically. The maximum capacity of memory storage in a
human brain is estimated to be one billion of 2D codes. By triggering one or
more neurosomes in a neurosome-based 2D code, the whole strongly connected
neurosome network is capable of exciting simultaneously and projecting its
excitation onto an analysis layer of neurons in cortex, thus retrieving the
stored memory data. The capability of comparing two 2D codes in the analysis
layer is one of the major brain functions.
Robust massive MIMO Equilization for mmWave systems with low resolution ADCs
Date: 2017-11-14 00:00:00

Leveraging the available millimeter wave spectrum will be important for 5G.
In this work, we investigate the performance of digital beamforming with low
resolution ADCs based on link level simulations including channel estimation,
MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR
type 1 OFDM reference signals. The comparison shows sequential DCD outperforms
MMSE-based MIMO equalization both in terms of detection performance and
complexity. We also show that the DCD based algorithm is more robust to channel
estimation errors. In contrast to the common believe we also show that the
complexity of MMSE equalization for a massive MIMO system is not dominated by
the matrix inversion but by the computation of the Gram matrix.
Evolutionary dynamics and competition stabilize three-species predator-prey communities
Date: 2017-11-14 00:00:00

We perform individual-based Monte Carlo simulations in a community consisting
of two predator species competing for a single prey species, with the purpose
of studying biodiversity stabilization in this simple model system. Predators
are characterized with predation efficiency and death rates, to which Darwinian
evolutionary adaptation is introduced. Competition for limited prey abundance
drives the populations' optimization with respect to predation efficiency and
death rates. We study the influence of various ecological elements on the final
state, finding that both indirect competition and evolutionary adaptation are
insufficient to yield a stable ecosystem. However, stable three-species
coexistence is observed when direct interaction between the two predator
species is implemented.
Considering Durations and Replays to Improve Music Recommender Systems
Authors: Hanna Pierre
Date: 2017-11-14 00:00:00
Tasks: Music Recommendation, Recommendation Systems

The consumption of music has its specificities in comparison with other
media, especially in relation to listening durations and replays. Music
recommendation can take these properties into account in order to predict the
behaviours of the users. Their impact is investigated in this paper. A large
database was thus created using logs collected on a streaming platform, notably
collecting the listening times. The proposed study shows that a high proportion
of the listening events implies a skip action, which may indicate that the user
did not appreciate the track listened. Implicit like and dislike can be deduced
from this information of durations and replays and can be taken into account
for music recommendation and for the evaluation of music recommendation
engines. A quantitative study as usually found in the literature confirms that
neighborhood-based systems considering binary data give the best results in
terms of MAP@k. However, a more qualitative evaluation of the recommended
tracks shows that many tracks recommended, usually evaluated in a positive way,
lead to skips or thus are actually not appreciated. We propose the
consideration of implicit like/dislike as recommendation engine inputs.
Evaluations show that neighbourhood-based engines remain the most precise, but
filtering inputs according to durations and/or replays have a significant
positive impact on the objective of the recommendation engine. The
recommendation process can thus be improved by taking account of listening
durations and replays. We also study the possibility of post-filtering a list
of recommended tracks so as to limit the number of tracks that will be
unpleasantly listened (skip and implicit dislike) and to increase the
proportion of tracks appreciated (implicit like). Several simple algorithms
show that this post-filtering operation leads to an improvement of the quality
of the music recommendations.
Bank Panics and Fire Sales, Insolvency and Illiquidity
Date: 2017-11-14 00:00:00

Banking system crises are complex events that in a short span of time can
inflict extensive damage to banks themselves and to the external economy. The
crisis literature has so far identified a number of distinct effects or
channels that can propagate distress contagiously both directly within the
banking network itself and indirectly, between the network and the external
economy. These contagious effects, and the potential events that trigger these
effects, can explain most aspects of past crises, and are thought to be likely
to dominate future financial crises. Since the current international financial
regulatory regime based on the Basel III Accord does a good job of ensuring
that banks are resilient to such contagion effects taken one at a time,
systemic risk theorists increasingly understand that future crises are likely
to be dominated by the spillovers between distinct contagion channels. The
present paper aims to provide a model for systemic risk that is comprehensive
enough to include the important contagion channels identified in the
literature. In such a model one can hope to understand the dangerous spillover
effects that are expected to dominate future crises. To rein in the number and
complexity of the modelling assumptions, two requirements are imposed, neither
of which is yet well-known or established in the main stream of systemic risk
research. The first, called stock-flow consistency, demands that the financial
system follows a rigorous set of rules based on accounting principles. The
second requirement, called Asset-Liability symmetry, implies that every
proposed contagion channel has a dual channel obtained by interchanging assets
and liabilities, and that these dual channel pairs have a symmetric
mathematical representation.
A new version of the CABLE land surface model, incorporating land-use change, woody vegetation demography and a novel optimisation-based approach to plant coordination of photosynthesis
Date: 2017-11-14 00:00:00

CABLE is a land surface model (LSM) that can be applied stand-alone, as well
as providing for land surface-atmosphere exchange within the Australian
Community Climate and Earth System Simulator (ACCESS). We describe critical new
developments that extend the applicability of CABLE for regional and global
carbon-climate simulations, accounting for vegetation response to biophysical
and anthropogenic forcings. A land-use and land-cover change module, driven by
gross land-use transitions and wood harvest area was implemented, tailored to
the needs of the Coupled Model Intercomparison Project-6 (CMIP6). Novel aspects
include the treatment of secondary woody vegetation, which benefits from a
tight coupling between the land-use module and the Population Orders Physiology
(POP) module for woody demography and disturbance-mediated landscape
heterogeneity. Land-use transitions and harvest associated with secondary
forest tiles modify the annually-resolved patch age distribution within
secondary-vegetated tiles, in turn affecting biomass accumulation and turnover
rates and hence the magnitude of the secondary forest sink. Additionally, we
implemented a novel approach to constrain modelled GPP consistent with the
Co-ordination Hypothesis, predicted by evolutionary theory, which suggests that
electron transport and Rubisco-limited rates adjust seasonally and across
biomes to be co-limiting. We show that the default prior assumption - common to
CABLE and other LSMs - of a fixed ratio of electron transport to carboxylation
capacity is at odds with this hypothesis, and implement an alternative
algorithm for dynamic optimisation of this ratio, such that co-ordination is
achieved as an outcome of fitness maximisation. Results have significant
implications the magnitude of the simulated CO2 fertilisation effect on
photosynthesis in comparison to alternative estimates and observational
proxies.
Linear system security -- detection and correction of adversarial attacks in the noise-free case
Date: 2017-11-15 00:00:00
Tasks: Adversarial Attack

We address the problem of attack detection and attack correction for
multi-output discrete-time linear time-invariant systems under sensor attack.
More specifically, we focus on the situation where adversarial attack signals
are added to some of the system's output signals. A 'security index' is defined
to characterize the vulnerability of a system against such sensor attacks.
Methods to compute the security index are presented as are algorithms to detect
and correct for sensor attacks. The results are illustrated by examples
involving multiple sensors.
Altered structural connectivity of the left visual thalamus in developmental dyslexia
Date: 2017-11-16 00:00:00
Tasks: Diffusion  MRI

Developmental dyslexia is characterized by persistent reading and spelling
deficits. Partly due to technical challenges with investigating subcortical
sensory structures, current research on dyslexia in humans by-and-large focuses
on the cerebral cortex. These studies found that dyslexia is typically
associated with functional and structural alterations of a distributed
left-hemispheric cerebral cortex network. However, findings from animal models
and post-mortem studies in humans suggest that developmental dyslexia might
also be associated with structural alterations in subcortical sensory pathways.
Whether these alterations also exist in developmental dyslexia in-vivo and how
they relate to dyslexia symptoms is currently unknown. Here we used ultra-high
resolution structural magnetic resonance imaging (MRI), diffusion MRI and
probabilistic tractography to investigate the structural connections of the
visual sensory pathway in dyslexia in-vivo. We discovered that individuals with
developmental dyslexia have reduced structural connections in the direct
pathway between the left visual thalamus (LGN) and left middle temporal area
V5/MT, but not between the left LGN and left primary visual cortex (V1). In
addition, left V5/MT-LGN connectivity strength correlated with rapid naming
abilities - a key deficit in dyslexia [14]. These findings provide the first
evidence of specific structural alterations in the connections between the
sensory thalamus and cortex in developmental dyslexia. The results challenge
current standard models and provide novel evidence for the importance of
cortico-thalamic interactions in explaining dyslexia.
The phenomenon of growing surface interference explains the rosette pattern of jaguar
Date: 2017-11-15 00:00:00

One possible mechanism to explain how animals got their coat patterns was
proposed by Alan Turing. He assumed that two kinds of morphogens diffuse on a
surface and interact with each other, generating a reaction-diffusion
mechanism. We developed a new framework for pattern generation incorporating a
non-diffusing transcription factor in the system. The diffusion factors (one
inhibitor and one activator) acting on cell surface receptors modulate the
activity of a transcription factor. The difference in the local concentration
of diffusion factors is translated into the degree of activation of
transcription factors. The speed of this process determines then pattern
formation velocity, i.e. the elapsed time from an initial noisy situation to a
final developed pattern. If the pattern formation velocity slows down compared
to the growth of the surface, the phenomenon of "growing surface interference"
occurs. We find that this phenomenon might explain the rosette pattern observed
on different types of felids and the pale stripes found between the regular
black stripes of zebras. We also investigate the dynamics between pattern
formation velocity and growth and to what extent a pattern may freeze on
growing domains.
Pitch and timbre discrimination at wave-to-spike transition in the cochlea
Date: 2017-11-15 00:00:00

A new definition of musical pitch is proposed. A Finite-Difference Time
Domain (FDTM) model of the cochlea is used to calculate spike trains caused by
tone complexes and by a recorded classical guitar tone. All harmonic tone
complexes, musical notes, show a narrow-band Interspike Interval (ISI) pattern
at the respective fundamental frequency of the tone complex. Still this
fundamental frequency is not only present at the bark band holding the
respective best frequency of this fundamental frequency, but rather at all bark
bands driven by the tone complex partials. This is caused by drop-outs in the
basically regular, periodic spike train in the respective bands. These
drop-outs are caused by the energy distribution in the wave form, where time
spans of low energy are not able to drive spikes. The presence of the
fundamental periodicity in all bark bands can be interpreted as pitch. Contrary
to pitch, timbre is represented as a wide distribution of different ISIs over
bark bands. The definition of pitch is shown to also works with residue
pitches. The spike drop-outs in times of low energy of the wave form also cause
undertones, integer multiple subdivisions in periodicity, but in no case
overtones can appear. This might explain the musical minor scale, which was
proposed to be caused by undertones already in 1880 by Hugo Riemann, still
until now without knowledge about any physical realization of such undertones.
Customer Selection Model with Grouping and Hierarchical Ranking Analysis
Date: 2017-10-10 00:00:00

The purpose of this study was to build a customer selection model based on 20
dimensions, including customer codes, total contribution, assets, deposit,
profit, profit rate, trading volume, trading amount, turnover rate, order
amount, withdraw amount, withdraw rate, process fee, process fee submitted,
process fee retained, net process fee retained, interest revenue, interest
return, exchange house return I and exchange house return II to group and rank
customers. The traditional way to group customers in securities or futures
companies is simply based on their assets. However, grouping customers with
respect to only one dimension cannot give us a full picture about customers'
attributions. It is hard to group customers' with similar attributions or
values into one group if we just consider assets as the only grouping
criterion. Nowadays, securities or futures companies usually group customers
based on managers' experience with lack of quantitative analysis, which is not
effective. Therefore, we use kmeans unsupervised learning methods to group
customers with respect to significant dimensions so as to cluster customers
with similar attributions together. Grouping is our first step. It is the
horizontal analysis in customer study. The next step is customer ranking. It is
the longitudinal analysis. It ranks customers by assigning each customer with a
certain score given by our weighted customer value calculation formula.
Therefore, by grouping and ranking customers, we can differentiate our
customers and rank them based on values instead of blindly reaching everyone.
A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process
Date: 2018-07-11 00:00:00
Tasks: Bayesian Inference, Time Series, Time Series Analysis

Scalability is one of the major issues for real-world Vehicle-to-Vehicle
network realization. To tackle this challenge, a stochastic hybrid modeling
framework based on a non-parametric Bayesian inference method, i.e.,
hierarchical Dirichlet process (HDP), is investigated in this paper. This
framework is able to jointly model driver/vehicle behavior through forecasting
the vehicle dynamical time-series. This modeling framework could be merged with
the notion of model-based information networking, which is recently proposed in
the vehicular literature, to overcome the scalability challenges in dense
vehicular networks via broadcasting the behavioral models instead of raw
information dissemination. This modeling approach has been applied on several
scenarios from the realistic Safety Pilot Model Deployment (SPMD) driving data
set and the results show a higher performance of this model in comparison with
the zero-hold method as the baseline.
Identifying the community structure of the international food-trade multi network
Date: 2017-11-15 00:00:00

Achieving international food security requires improved understanding of how
international trade networks connect countries around the world through the
import-export flows of food commodities. The properties of food trade networks
are still poorly documented, especially from a multi-network perspective. In
particular, nothing is known about the community structure of food networks,
which is key to understanding how major disruptions or 'shocks' would impact
the global food system. Here we find that the individual layers of this network
have densely connected trading groups, a consistent characteristic over the
period 2001 to 2011. We also fit econometric models to identify social,
economic and geographic factors explaining the probability that any two
countries are co-present in the same community. Our estimates indicate that the
probability of country pairs belonging to the same food trade community depends
more on geopolitical and economic factors -- such as geographical proximity and
trade agreements co-membership -- than on country economic size and/or income.
This is in sharp contrast with what we know about bilateral-trade determinants
and suggests that food country communities behave in ways that can be very
different from their non-food counterparts.
Crowd Counting Through Walls Using WiFi
Date: 2017-11-15 00:00:00
Tasks: Crowd Counting

Counting the number of people inside a building, from outside and without
entering the building, is crucial for many applications. In this paper, we are
interested in counting the total number of people walking inside a building (or
in general behind walls), using readily-deployable WiFi transceivers that are
installed outside the building, and only based on WiFi RSSI measurements. The
key observation of the paper is that the inter-event times, corresponding to
the dip events of the received signal, are fairly robust to the attenuation
through walls (for instance as compared to the exact dip values). We then
propose a methodology that can extract the total number of people from the
inter-event times. More specifically, we first show how to characterize the
wireless received power measurements as a superposition of renewal-type
processes. By borrowing theories from the renewal-process literature, we then
show how the probability mass function of the inter-event times carries vital
information on the number of people. We validate our framework with 44
experiments in five different areas on our campus (3 classrooms, a conference
room, and a hallway), using only one WiFi transmitter and receiver installed
outside of the building, and for up to and including 20 people. Our experiments
further include areas with different wall materials, such as concrete, plaster,
and wood, to validate the robustness of the proposed approach. Overall, our
results show that our approach can estimate the total number of people behind
the walls with a high accuracy while minimizing the need for prior
calibrations.
Per-sample immunoglobulin germline inference from B cell receptor deep sequencing data
Date: 2018-04-28 00:00:00

The collection of immunoglobulin genes in an individual's germline, which
gives rise to B cell receptors via recombination, is known to vary
significantly across individuals. In humans, for example, each individual has
only a fraction of the several hundred known V alleles. Furthermore, the
currently-accepted set of known V alleles is both incomplete (particularly for
non-European samples), and contains a significant number of spurious alleles.
The resulting uncertainty as to which immunoglobulin alleles are present in any
given sample results in inaccurate B cell receptor sequence annotations, and in
particular inaccurate inferred naive ancestors. In this paper we first show
that the currently widespread practice of aligning each sequence to its closest
match in the full set of IMGT alleles results in a very large number of
spurious alleles that are not in the sample's true set of germline V alleles.
We then describe a new method for inferring each individual's germline gene set
from deep sequencing data, and show that it improves upon existing methods by
making a detailed comparison on a variety of simulated and real data samples.
This new method has been integrated into the partis annotation and clonal
family inference package, available at https://github.com/psathyrella/partis,
and is run by default without affecting overall run time.