pwc-archive/papers-with-abstracts huggingface dataset:
Updating Beamformers to Respond to Changes in Users
Date: 2018-03-11 00:00:00

We consider a multi-user multiple-input single-output downlink system that
provides each user with a prespecified level of quality-of-service. The base
station (BS) designs the beamformers so that each user receives a certain
signal-to-interference-and-noise ratio (SINR). In contrast to most of the
available literature in the beamforming field, we focus on the required
modifications when the system changes. We specifically study three cases: (i)
user entering the system, (ii) user leaving the system, and (iii) a change in
the SINR target. We do so in order to avoid designing the entire system from
scratch for every change in the requirements. In each of the three cases, we
describe the modifications required to the beamforming directions and the power
loading. We consider maximum ratio transmission (MRT), zero-forcing (ZF) and
the optimal beamformers. The proposed modifications provide performance that is
either exact or very close to that obtained when we redesign the entire system,
while having much lower computational cost.
Multi-Reference Video Coding Using Stillness Detection
Date: 2018-03-11 00:00:00

Encoders of AOM/AV1 codec consider an input video sequence as succession of
frames grouped in Golden-Frame (GF) groups. The coding structure of a GF group
is fixed with a given GF group size. In the current AOM/AV1 encoder, video
frames are coded using a hierarchical, multilayer coding structure within one
GF group. It has been observed that the use of multilayer coding structure may
result in worse coding performance if the GF group presents consistent
stillness across its frames. This paper proposes a new approach that adaptively
designs the Golden-Frame (GF) group coding structure through the use of
stillness detection. Our new approach hence develops an automatic stillness
detection scheme using three metrics extracted from each GF group. It then
differentiates those GF groups of stillness from other non- still GF groups and
uses different GF coding structures accordingly. Experimental result
demonstrates a consistent coding gain using the new approach.
Multisensor Data Fusion for Water Quality Monitoring using Wireless Sensor Networks
Date: 2018-03-12 00:00:00

In this paper, the application of hierarchical wireless sensor networks in
water quality monitoring is investigated. Adopting a hierarchical structure,
the set of sensors is divided into multiple clusters where the value of the
sensing parameter is almost constant in each cluster. The members of each
cluster transmit their sensing information to the local fusion center (LFC) of
their corresponding cluster, where using some fusion rule, the received
information is combined, and then possibly sent to a higher-level central
fusion center (CFC). A two-phase processing scheme is also envisioned, in which
the first phase is dedicated to detection in the LFC, and the second phase is
dedicated to estimation in both the LFC and the CFC. The focus of the present
paper is on the problem of decision fusion at the LFC: we propose hard- and
soft-decision maximum a posteriori (MAP) algorithms, which exhibit flexibility
in minimizing the total cost imposed by incorrect detections in the first
phase. The proposed algorithms are simulated and compared with conventional
fusion techniques. It is shown that the proposed techniques result in lower
cost. Furthermore, when the number of sensors or the amount of contamination
increases, the performance gap between the proposed algorithms and the existing
methods also widens.
Performance Analysis of Decision Directed Maximum Likelihood MIMO Channel Tracking Algorithm
Date: 2018-03-12 00:00:00

In this paper, the performance of decision directed (DD) maximum likelihood
(ML) channel tracking algorithm is analyzed. The ML channel tracking algorithm
presents efficient performance especially in the decision directed mode of the
operation. In this paper, after introducing the method for analysis of DD
algorithms, the performance of ML Multiple-Input Multiple-Output (MIMO) channel
tracking algorithm in the DD mode of operation is analyzed. In this method
channel tracking error is evaluated for given decision error rate. Then, the
decision error rate is approximated for given channel tracking error. By
solving these two derived equations jointly, both the decision error rate and
the channel tracking error are computed. The presented analysis is compared
with simulation results for different channel ranks, Doppler frequency shifts,
and SNRs, and it is shown that the analysis is a good match for simulation
results especially in high rank MIMO channels and high Doppler shifts.
A Novel Detection Algorithm Efficient for Turbo coded CDMA Signals in Detect and Forward Cooperative Channels
Date: 2018-03-12 00:00:00
Tasks: Diversity

In this paper, a new detection algorithm is proposed for turbo coded Code
Division Multiple Access (CDMA) signals in detect and forward cooperative
channels. Use of user cooperation makes much improvement in the performance of
CDMA systems. Due to the special structure of CDMA systems, cooperative schemes
increase the sum and cutoff capacities of CDMA based wireless systems and
improve the quality of user-partner link which enhances the overall performance
of the system. In this paper, a new combining scheme is proposed that makes the
receiver more robust against the decision errors in the partner link. This
structure is simulated for punctured 1/2 rate 4 states turbo code in a channel
with first-order Markov time variation and different Rice factor variances.
Through various simulations, it is shown when the channel estimates are
available in the partner and receiver, the cooperation between users provides
much diversity gain especially while using the new proposed combining
algorithm.
Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs
Date: 2018-03-12 00:00:00

This paper deals with problem of blind identification of a graph filter and
its sparse input signal, thus broadening the scope of classical blind
deconvolution of temporal and spatial signals to irregular graph domains. While
the observations are bilinear functions of the unknowns, a mild requirement on
invertibility of the filter enables an efficient convex formulation, without
relying on matrix lifting that can hinder applicability to large graphs. On top
of scaling, it is argued that (non-cyclic) permutation ambiguities may arise
with some particular graphs. Deterministic sufficient conditions under which
the proposed convex relaxation can exactly recover the unknowns are stated,
along with those guaranteeing identifiability under the Bernoulli-Gaussian
model for the inputs. Numerical tests with synthetic and real-world networks
illustrate the merits of the proposed algorithm, as well as the benefits of
leveraging multiple signals to aid the (blind) localization of sources of
diffusion.
Temporal processing and context dependency in C. elegans mechanosensation
Date: 2018-03-20 00:00:00

A quantitative understanding of how sensory signals are transformed into
motor outputs places useful constraints on brain function and helps reveal the
brain's underlying computations. We investigate how the nematode C. elegans
responds to time-varying mechanosensory signals using a high-throughput
optogenetic assay and automated behavior quantification. In the prevailing
picture of the touch circuit, the animal's behavior is determined by which
neurons are stimulated and by the stimulus amplitude. In contrast, we find that
the behavioral response is tuned to temporal properties of mechanosensory
signals, like its integral and derivative, that extend over many seconds.
Mechanosensory signals, even in the same neurons, can be tailored to elicit
different behavioral responses. Moreover, we find that the animal's response
also depends on its behavioral context. Most dramatically, the animal ignores
all tested mechanosensory stimuli during turns. Finally, we present a
linear-nonlinear model that predicts the animal's behavioral response to
stimulus.
Estimating Shape of Target Object Moving on Unknown Trajectory by Using Location-Unknown Distance Sensors: Theoretical Framework
Date: 2018-03-19 00:00:00

By using directional distance sensors that have unknown locations, this paper
proposes a method of estimating the shape of a location-unknown target object
$T$ moving with unknown speed on an unknown straight line trajectory.
Regardless of many unknown factors, the proposed method can estimate the shape
by using each sensor's continuous report of the measured distance to $T$
without using side information or additional mechanisms such as locations of
anchor sensors and angle-of-arrival measurements. By using the sensor reports,
the proposed method estimates (i) the moving speed of $T$, (ii) the length and
direction of an edge of $T$, and (iii) the order of consecutive edges. As a
result, we can obtain the shape of $T$.
Mean Field Games with Partial Information for Algorithmic Trading
Date: 2019-03-31 00:00:00
Tasks: Algorithmic Trading

Financial markets are often driven by latent factors which traders cannot
observe. Here, we address an algorithmic trading problem with collections of
heterogeneous agents who aim to perform optimal execution or statistical
arbitrage, where all agents filter the latent states of the world, and their
trading actions have permanent and temporary price impact. This leads to a
large stochastic game with heterogeneous agents. We solve the stochastic game
by investigating its mean-field game (MFG) limit, with sub-populations of
heterogeneous agents, and, using a convex analysis approach, we show that the
solution is characterized by a vector-valued forward-backward stochastic
differential equation (FBSDE). We demonstrate that the FBSDE admits a unique
solution, obtain it in closed-form, and characterize the optimal behaviour of
the agents in the MFG equilibrium. Moreover, we prove the MFG equilibrium
provides an $\epsilon$-Nash equilibrium for the finite player game. We conclude
by illustrating the behaviour of agents using the optimal MFG strategy through
simulated examples.
Saliency Inspired Quality Assessment of Stereoscopic 3D Video
Date: 2018-03-12 00:00:00

To study the visual attentional behavior of Human Visual System (HVS) on 3D
content, eye tracking experiments are performed and Visual Attention Models
(VAMs) are designed. One of the main applications of these VAMs is in quality
assessment of 3D video. The usage of 2D VAMs in designing 2D quality metrics is
already well explored. This paper investigates the added value of incorporating
3D VAMs into Full-Reference (FR) and No-Reference (NR) quality assessment
metrics for stereoscopic 3D video. To this end, state-of-the-art 3D VAMs are
integrated to quality assessment pipeline of various existing FR and NR
stereoscopic video quality metrics. Performance evaluations using a large scale
database of stereoscopic videos with various types of distortions demonstrated
that using saliency maps generally improves the performance of the quality
assessment task for stereoscopic video. However, depending on the type of
distortion, utilized metric, and VAM, the amount of improvement will change.
5G Control Channel Design for Ultra-Reliable Low-Latency Communications
Date: 2018-03-12 00:00:00

The fifth generation (5G) of wireless systems holds the promise of supporting
a wide range of services with different communication requirements.
Ultra-reliable low-latency communications (URLLC) is a generic service that
enables mission-critical applications, such as industrial automation, augmented
reality, and vehicular communications. URLLC has stringent requirements for
reliability and latency of delivering both data and control information. In
order to meet these requirements, the Third Generation Partnership Project
(3GPP) has been introducing new features to the upcoming releases of the
cellular system standards, namely releases 15 and beyond. This article reviews
some of these features and introduces new enhancements for designing the
control channels to efficiently support the URLLC. In particular, a flexible
slot structure is presented as a solution to detect a failure in delivering the
control information at an early stage, thereby allowing timely retransmission
of the control information. Finally, some remaining challenges and envisioned
research directions are discussed for shaping the 5G new radio (NR) as a
unified wireless access technology for supporting different services.
A Modular Design for Geo-Distributed Querying
Authors: Vasilas Dimitrios  LIP6, DELYS, Shapiro Marc  DELYS, LIP6, King Bradley
Date: 2018-03-12 00:00:00

Most distributed storage systems provide limited abilities for querying data
by attributes other than their primary keys. Supporting efficient search on
secondary attributes is challenging as applications pose varying requirements
to query processing systems, and no single system design can be suitable for
all needs. In this paper, we show how to overcome these challenges in order to
extend distributed data stores to support queries on secondary attributes. We
propose a modular architecture that is flexible and allows query processing
systems to make trade-offs according to different use case requirements. We
describe adap-tive mechanisms that make use of this flexibility to enable query
processing systems to dynamically adjust to query and write operation
workloads.
Imaging linear and circular polarization features in leaves with complete Mueller matrix polarimetry
Date: 2018-03-12 00:00:00

Spectropolarimetry of intact plant leaves allows to probe the molecular
architecture of vegetation photosynthesis in a non-invasive and non-destructive
way and, as such, can offer a wealth of physiological information. In addition
to the molecular signals due to the photosynthetic machinery, the cell
structure and its arrangement within a leaf can create and modify polarization
signals. Using Mueller matrix polarimetry with rotating retarder modulation, we
have visualized spatial variations in polarization in transmission around the
chlorophyll a absorbance band from 650 nm to 710 nm. We show linear and
circular polarization measurements of maple leaves and cultivated maize leaves
and discuss the corresponding Mueller matrices and the Mueller matrix
decompositions, which show distinct features in diattenuation, polarizance,
retardance and depolarization. Importantly, while normal leaf tissue shows a
typical split signal with both a negative and a positive peak in the induced
fractional circular polarization and circular dichroism, the signals close to
the veins only display a negative band. The results are similar to the negative
band as reported earlier for single macrodomains. We discuss the possible role
of the chloroplast orientation around the veins as a cause of this phenomenon.
Systematic artefacts are ruled out as three independent measurements by
different instruments gave similar results. These results provide better
insight into circular polarization measurements on whole leaves and options for
vegetation remote sensing using circular polarization.
Interactions mediated by a public good transiently increase cooperativity in growing Pseudomonas putida metapopulations
Date: 2018-03-12 00:00:00

Bacterial communities have rich social lives. A well-established interaction
involves the exchange of a public good in Pseudomonas populations, where the
iron-scavenging compound pyoverdine, synthesized by some cells, is shared with
the rest. Pyoverdine thus mediates interactions between producers and
non-producers and can constitute a public good. This interaction is often used
to test game theoretical predictions on the "social dilemma" of producers. Such
an approach, however, underestimates the impact of specific properties of the
public good, for example consequences of its accumulation in the environment.
Here, we experimentally quantify costs and benefits of pyoverdine production in
a specific environment, and build a model of population dynamics that
explicitly accounts for the changing significance of accumulating pyoverdine as
chemical mediator of social interactions. The model predicts that, in an
ensemble of growing populations (metapopulation) with different initial
producer fractions (and consequently pyoverdine contents), the global producer
fraction initially increases. Because the benefit of pyoverdine declines at
saturating concentrations, the increase need only be transient. Confirmed by
experiments on metapopulations, our results show how a changing benefit of a
public good can shape social interactions in a bacterial population.
Systems, environments, and soliton rate equations (II): Toward realistic modeling
Date: 2018-03-12 00:00:00

In order to solve a system of nonlinear rate equations one can try to use
some soliton methods. The procedure involves three steps: (1) Find a `Lax
representation' where all the kinetic variables are combined into a single
matrix $\rho$, all the kinetic constants are encoded in a matrix $H$; (2) find
a Darboux-Backund dressing transformation for the Lax representation $i\dot
\rho=[H,f(\rho)]$, where $f$ models a time-dependent environment; (3) find a
class of seed solutions $\rho=\rho[0]$ that lead, via a nontrivial chain of
dressings $\rho[0]\to \rho[1]\to \rho[2]\to\dots$ to new solutions, difficult
to find by other methods. The latter step is not a trivial one since a
non-soliton method has to be employed to find an appropriate initial $\rho[0]$.
Procedures that lead to a correct $\rho[0]$ have been discussed in the
literature only for a limited class of $H$ and $f$. Here, we develop a
formalism that works for practically any $H$, and any explicitly time-dependent
$f$. As a result, we are able to find exact solutions to a system of equations
describing an arbitrary number of species interacting through (auto)catalytic
feedbacks, with general time dependent parameters characterizing the
nonlinearity. Explicit examples involve up to 42 interacting species.
System Identification of a Multi-timescale Adaptive Threshold Neuronal Model
Date: 2018-02-23 00:00:00
Tasks: parameter estimation

In this paper, the parameter estimation problem for a multi-timescale
adaptive threshold (MAT) neuronal model is investigated. By manipulating the
system dynamics, which comprise of a non-resetting leaky integrator coupled
with an adaptive threshold, the threshold voltage can be obtained as a
realizable model that is linear in the unknown parameters. This linearly
parametrized realizable model is then utilized inside a prediction error based
framework to identify the threshold parameters with the purpose of predicting
single neuron precise firing times. The iterative linear least squares
estimation scheme is evaluated using both synthetic data obtained from an exact
model as well as experimental data obtained from in vitro rat somatosensory
cortical neurons. Results show the ability of this approach to fit the MAT
model to different types of fluctuating reference data. The performance of the
proposed approach is seen to be superior when comparing with existing
identification approaches used by the neuronal community.
Geodabs: Trajectory Indexing Meets Fingerprinting at Scale
Authors: Chapuis Bertil, Garbinato Benoit
Date: 2018-03-12 00:00:00
Tasks: Copy Detection, Information Retrieval, Retrieval

Finding trajectories and discovering motifs that are similar in large
datasets is a central problem for a wide range of applications. Solutions
addressing this problem usually rely on spatial indexing and on the computation
of a similarity measure in polynomial time. Although effective in the context
of sparse trajectory datasets, this approach is too expensive in the context of
dense datasets, where many trajectories potentially match with a given query.
In this paper, we apply fingerprinting, a copy-detection mechanism used in the
context of textual data, to trajectories. To this end, we fingerprint
trajectories with geodabs, a construction based on geohash aimed at trajectory
fingerprinting. We demonstrate that by relying on the properties of a space
filling curve geodabs can be used to build sharded inverted indexes. We show
how normalization affects precision and recall, two key measures in information
retrieval. We then demonstrate that the probabilistic nature of fingerprinting
has a marginal effect on the quality of the results. Finally, we evaluate our
method in terms of performances and show that, in contrast with existing
methods, it is not affected by the density of the trajectory dataset and that
it can be efficiently distributed.
Information of Epileptic Mechanism and its Systemic Change-points in a Zebrafish's Brain-wide Calcium Imaging Video Data
Date: 2018-02-14 00:00:00

The epileptic mechanism is postulated as that an animal's neurons gradually
diminish their inhibition function coupled with enhanced excitation when an
epileptic event is approaching. Calcium imaging technique is designed to
directly record brain-wide neurons activity in order to discover the underlying
epileptic mechanism. In this paper, using one brain-wide calcium imaging video
of Zebrafish, we compute dynamic pattern information of the epileptic
mechanism, and devise three graphical displays to show the visible functional
aspect of epileptic mechanism over five inter-ictal periods. The foundation of
our data-driven computations for such dynamic patterns relies on one universal
phenomenon discovered across 696 informative pixels. This universality is that
each pixel's progressive 5-percentile process oscillates in an irregular
fashion at first, but, after the middle point of inter-ictal period, the
oscillation is replaced by a steady increasing trend. Such dynamic patterns are
collectively transformed into a visible systemic change-point as an early
warning signal (EWS) of an incoming epileptic event. We conclude through the
graphic displays that pattern information extracted from the calcium imaging
video realistically reveals the Zebrafish's authentic epileptic mechanism.
Analysis of Heterogeneous Cardiac Pacemaker Tissue Models and Traveling Wave Dynamics
Date: 2018-09-12 00:00:00
Tasks: Rhythm

The sinoatrial-node (SAN) is a complex heterogeneous tissue that generates a
stable rhythm in healthy hearts, yet a general mechanistic explanation for when
and how this tissue remains stable is lacking. Although computational and
theoretical analyses could elucidate these phenomena, such methods have rarely
been used in realistic (large-dimensional) gap-junction coupled heterogeneous
pacemaker tissue models. In this study, we adapt a recent model of pacemaker
cells (Severi et al. 2012), incorporating biophysical representations of ion
channel and intracellular calcium dynamics, to capture physiological features
of a heterogeneous population of pacemaker cells, in particular "center" and
"peripheral" cells with distinct intrinsic frequencies and action potential
morphology. Large-scale simulations of the SAN tissue, represented by a
heterogeneous tissue structure of pacemaker cells, exhibit a rich repertoire of
behaviors, including complete synchrony, traveling waves of activity
originating from periphery to center, and transient traveling waves originating
from the center. We use phase reduction methods that do not require fully
simulating the large-scale model to capture these observations. Moreover, the
phase reduced models accurately predict key properties of the tissue electrical
dynamics, including wave frequencies when synchronization occurs, and wave
propagation direction in a variety of tissue models. With the reduced phase
models, we analyze the relationship between cell distributions and coupling
strengths and the resulting transient dynamics. Further, the reduced phase
model predicts parameter regimes of irregular electrical dynamics. Thus, we
demonstrate that phase reduced oscillator models applied to realistic pacemaker
tissue is a useful tool for investigating the spatial-temporal dynamics of
cardiac pacemaker activity.