pwc-archive/papers-with-abstracts huggingface dataset:
Physical Multi-Layer Phantoms for Intra-Body Communications
Date: 2018-06-11 00:00:00

This paper presents approaches to creating tissue mimicking materials that
can be used as phantoms for evaluating the performance of Body Area Networks
(BAN). The main goal of the paper is to describe a methodology to create a
repeatable experimental BAN platform that can be customized depending on the
BAN scenario under test. Comparisons between different material compositions
and percentages are shown, along with the resulting electrical properties of
each mixture over the frequency range of interest for intra-body
communications; 100 KHz to 100 MHz. Test results on a composite multi-layer
sample are presented confirming the efficacy of the proposed methodology. To
date, this is the first paper that provides guidance on how to decide on
concentration levels of ingredients, depending on the exact frequency range of
operation, and the desired matched electrical characteristics (conductivity vs.
permittivity), to create multi-layer phantoms for intra-body communication
applications.
A Growth Model with Unemployment
Date: 2018-06-11 00:00:00
Tasks: model

A standard growth model is modified in a straightforward way to incorporate
what Keynes (1936) suggests in the "essence" of his general theory. The
theoretical essence is the idea that exogenous changes in investment cause
changes in employment and unemployment. We implement this idea by assuming the
path for capital growth rate is exogenous in the growth model. The result is a
growth model that can explain both long term trends and fluctuations around the
trend. The modified growth model was tested using the U.S. economic data from
1947 to 2014. The hypothesized inverse relationship between the capital growth
and changes in unemployment was confirmed, and the structurally estimated model
fits fluctuations in unemployment reasonably well.
The Role of Agricultural Sector Productivity in Economic Growth: The Case of Iran's Economic Development Plan
Date: 2018-06-11 00:00:00
Tasks: Management, Time Series, Time Series Analysis

This study provides the theoretical framework and empirical model for
productivity growth evaluations in agricultural sector as one of the most
important sectors in Iran's economic development plan. We use the Solow
residual model to measure the productivity growth share in the value-added
growth of the agricultural sector. Our time series data includes value-added
per worker, employment, and capital in this sector. The results show that the
average total factor productivity growth rate in the agricultural sector is
-0.72% during 1991-2010. Also, during this period, the share of total factor
productivity growth in the value-added growth is -19.6%, while it has been
forecasted to be 33.8% in the fourth development plan. Considering the
effective role of capital in the agricultural low productivity, we suggest
applying productivity management plans (especially in regards of capital
productivity) to achieve future growth goals.
Indexed Dynamic Programming to boost Edit Distance and LCSS Computation
Authors: Barbay Jérémy, Olivares Andrés
Date: 2018-06-12 00:00:00

There are efficient dynamic programming solutions to the computation of the
Edit Distance from $S\in[1..\sigma]^n$ to $T\in[1..\sigma]^m$, for many natural
subsets of edit operations, typically in time within $O(nm)$ in the worst-case
over strings of respective lengths $n$ and $m$ (which is likely to be optimal),
and in time within $O(n{+}m)$ in some special cases (e.g. disjoint alphabets).
We describe how indexing the strings (in linear time), and using such an index
to refine the recurrence formulas underlying the dynamic programs, yield faster
algorithms in a variety of models, on a continuum of classes of instances of
intermediate difficulty between the worst and the best case, thus refining the
analysis beyond the worst case analysis. As a side result, we describe similar
properties for the computation of the Longest Common Sub Sequence $LCSS(S,T)$
between $S$ and $T$, since it is a particular case of Edit Distance, and we
discuss the application of similar algorithmic and analysis techniques for
other dynamic programming solutions. More formally, we propose a parameterized
analysis of the computational complexity of the Edit Distance for various set
of operators and of the Longest Common Sub Sequence in function of the area of
the dynamic program matrix relevant to the computation.
Asymmetric response to PMI announcements in China's stock returns
Date: 2018-06-12 00:00:00

Considered an important macroeconomic indicator, the Purchasing Managers'
Index (PMI) on Manufacturing generally assumes that PMI announcements will
produce an impact on stock markets. International experience suggests that
stock markets react to negative PMI news. In this research, we empirically
investigate the stock market reaction towards PMI in China. The asymmetric
effects of PMI announcements on the stock market are observed: no market
reaction is generated towards negative PMI announcements, while a positive
reaction is generally generated for positive PMI news. We further find that the
positive reaction towards the positive PMI news occurs 1 day before the
announcement and lasts for nearly 3 days, and the positive reaction is observed
in the context of expanding economic conditions. By contrast, the negative
reaction towards negative PMI news is prevalent during downward economic
conditions for stocks with low market value, low institutional shareholding
ratios or high price earnings. Our study implies that China's stock market
favors risk to a certain extent given the vast number of individual investors
in the country, and there may exist information leakage in the market.
State and Network Structures of Stock Markets around the Global Financial Crisis
Date: 2018-06-12 00:00:00

We consider the effects of the 2008 global financial crisis on the global
stock market before, during, and after the crisis. We generate complex networks
from a cross-correlation matrix such as the threshold network (TN) and the
minimal spanning tree (MST). In the threshold network, we assign a threshold
value by using the mean and standard deviation of cross-correlation
coefficients. When the threshold is equal to the mean of these coefficients, we
observe a giant cluster composed of three economic zones in all three periods.
We find that during the crisis, the countries in the Asian zone were weakly
connected and those in the American zone were tightly linked to the countries
in the European zone. At a large threshold, the three economic zones were
fragmented. The European countries connected tightly, but the Asian countries
bound weakly. The MST constructed from the distance matrix. In the MST, France
remained a hub node in all three periods. The size of the MST shrank slightly
during the crisis. We observe a scaling relation between the network distance
of nodes from the central hub (France) and the geometrical distance. We observe
the topological change of the financial network structure during the global
financial crisis. The TN and MST are complementary roles to understand the
connecting structure of financial complex networks. The TN reveals to observe
the clustering effects and robustness of the cluster during the financial
crisis. The MST shows the central hub and connecting node among the economic
zones.
Ranking Robustness Under Adversarial Document Manipulations
Authors: Goren Gregory, Kurland Oren, Tennenholtz Moshe, Raiber Fiana
Date: 2018-06-13 00:00:00
Tasks: Learning-To-Rank, Retrieval

For many queries in the Web retrieval setting there is an on-going ranking
competition: authors manipulate their documents so as to promote them in
rankings. Such competitions can have unwarranted effects not only in terms of
retrieval effectiveness, but also in terms of ranking robustness. A case in
point, rankings can (rapidly) change due to small indiscernible perturbations
of documents. While there has been a recent growing interest in analyzing the
robustness of classifiers to adversarial manipulations, there has not yet been
a study of the robustness of relevance-ranking functions. We address this
challenge by formally analyzing different definitions and aspects of the
robustness of learning-to-rank-based ranking functions. For example, we
formally show that increased regularization of linear ranking functions
increases ranking robustness. This finding leads us to conjecture that
decreased variance of any ranking function results in increased robustness. We
propose several measures for quantifying ranking robustness and use them to
analyze ranking competitions between documents' authors. The empirical findings
support our formal analysis and conjecture for both RankSVM and LambdaMART.
Foreign Exchange Markets with Last Look
Date: 2018-06-12 00:00:00

We examine the Foreign Exchange (FX) spot price spreads with and without Last
Look on the transaction. We assume that brokers are risk-neutral and they quote
spreads so that losses to latency arbitrageurs (LAs) are recovered from other
traders in the FX market. These losses are reduced if the broker can reject,
ex-post, loss-making trades by enforcing the Last Look option which is a
feature of some trading venues in FX markets. For a given rejection threshold
the risk-neutral broker quotes a spread to the market so that her expected
profits are zero. When there is only one venue, we find that the Last Look
option reduces quoted spreads. If there are two venues we show that the market
reaches an equilibrium where traders have no incentive to migrate. The
equilibrium can be reached with both venues coexisting, or with only one venue
surviving. Moreover, when one venue enforces Last Look and the other one does
not, counterintuitively, it may be the case that the Last Look venue quotes
larger spreads.
Characteristic Analysis of 1024-Point Quantized Radix-2 FFT/IFFT Processor
Date: 2018-06-10 00:00:00

The precise analysis and accurate measurement of harmonic provides a reliable
scientific industrial application. However, the high-performance DSP processor
is the important method of electrical harmonic analysis. Hence, in this
research work, the effort was taken to design a novel high-resolution single
1024-point fast Fourier transform (FFT) and inverse fast Fourier transform
(IFFT) processors for improvement of the harmonic measurement techniques.
Meanwhile, the project is started with design and simulation to demonstrate the
benefit that is achieved by the proposed 1024-point FFT/IFFT processor. The
pipelined structure is incorporated in order to enhance the system efficiency.
As such, a pipelined architecture was proposed to statically scale the
resolution of the processor to suite adequate trade-off constraints. The
proposed FFT makes use of programmable fixed-point/floating-point to realize
higher precision FFT.
Novel Architecture of Pipeline Radix 2 power of 2 SDF FFT Based on Digit-Slicing Technique
Date: 2018-06-10 00:00:00

The prevalent need for very high-speed digital signals processing in wireless
communications has driven the communications system to high-performance levels.
The objective of this paper is to propose a novel structure for efficient
implementation for the Fast Fourier Transform (FFT) processor to meet the
requirement for high-speed wireless communication system standards. Based on
the algorithm, architecture analysis, the design of pipeline Radix 2power of 2
SDF FFT processor based on digit-slicing Multiplier-Less is proposed.
Furthermore, this paper proposed an optimal constant multiplication arithmetic
design to multiply a fixed point input selectively by one of the several
present twiddle factor constants. The proposed architecture was simulated using
MATLAB software and the Field Programmable Gate Array (FPGA) Virtex 4 was
targeted to synthesis the proposed architecture. The design was tested in real
hardware of TLA5201 logic analyzer and the ISE synthesis report results the
high speed of 669.277 MHz with the total equivalent gate count of 14,854.
Meanwhile, It can be found as significant improvement over Radix 22 DIF SDF FFT
processor and can be concluded that the proposed pipeline Radix 22 DIF SDF FFT
processor based on digit-slicing multiplier-less is an enable in solving
problems that affect the most high-speed wireless communication systems
capability in FFT and possesses huge potentials for future related works and
research areas.
Planar Dipole Antenna Design At 1800MHz Band Using Different Feeding Methods For GSM Application
Date: 2018-06-10 00:00:00

This research work focuses on the design and simulation of a planar dipole
antenna for 1800MHZ Band for Global System Mobile GSM application using
Computer Software Technology CST studio software. The antenna is structured on
a fire resistance FR4 substrate with a relative constant of 4.3 S/m. Two types
of feeding configuration are designed to feed the antenna in order to match 50
ohm transmission lines which are via-hole integrated balun and quarter
wavelength open stub. The via-hole is capable to provide maximum return loss of
25dB, bandwidth of 18.4 percent and the voltage standing wave ratio (VSWR) of
1.116 V at optimum dimension of length 59mm and width 4mm, the bandwidth is
improved 25 percent to 30 percent by extending the width of the antenna 8 mm to
10 mm followed by deterioration of return loss value to 15dB. While the open
stub at length of 67 mm, the width of 6 mm and height 1.6mm will provide max
return loss of 47.88dB and bandwidth of 17 percent with VSWR 1.008 less than 2.
The way that the antenna substrate has influenced the performance of the
antenna. The lower relative constant will result in the higher return lows,
narrower bandwidth and better radiation pattern in trade-off the resonant
length Via-hole and then the quarter wave open stub are most convenient for
practical implementation.
Computation Rate Maximization in UAV-Enabled Wireless Powered Mobile-Edge Computing Systems
Date: 2018-07-17 00:00:00
Tasks: Edge-computing

Mobile edge computing (MEC) and wireless power transfer (WPT) are two
promising techniques to enhance the computation capability and to prolong the
operational time of low-power wireless devices that are ubiquitous in Internet
of Things. However, the computation performance and the harvested energy are
significantly impacted by the severe propagation loss. In order to address this
issue, an unmanned aerial vehicle (UAV)-enabled MEC wireless powered system is
studied in this paper. The computation rate maximization problems in a
UAV-enabled MEC wireless powered system are investigated under both partial and
binary computation offloading modes, subject to the energy harvesting causal
constraint and the UAV's speed constraint. These problems are non-convex and
challenging to solve. A two-stage algorithm and a three-stage alternative
algorithm are respectively proposed for solving the formulated problems. The
closed-form expressions for the optimal central processing unit frequencies,
user offloading time, and user transmit power are derived. The optimal
selection scheme on whether users choose to locally compute or offload
computation tasks is proposed for the binary computation offloading mode.
Simulation results show that our proposed resource allocation schemes
outperforms other benchmark schemes. The results also demonstrate that the
proposed schemes converge fast and have low computational complexity.
Efficient Tracking of Sparse Signals via an Earth Mover's Distance Dynamics Regularizer
Authors: Nicholas P. Bertrand, Adam S. Charles, John Lee, Pavel B. Dunn, Christopher J. Rozell
Date: 2018-06-12 00:00:00

Tracking algorithms such as the Kalman filter aim to improve inference performance by leveraging the temporal dynamics in streaming observations. However, the tracking regularizers are often based on the $\ell_p$-norm which cannot account for important geometrical relationships between neighboring signal elements. We propose a practical approach to using the earth mover's distance (EMD) via the earth mover's distance dynamic filtering (EMD-DF) algorithm for causally tracking time-varying sparse signals when there is a natural geometry to the coefficient space that should be respected (e.g., meaningful ordering). Specifically, this paper presents a new Beckmann formulation that dramatically reduces computational complexity, as well as an evaluation of the performance and complexity of the proposed approach in imaging and frequency tracking applications with real and simulated neurophysiology data.
Electronic schematic for bio-plausible dopamine neuromodulation of eSTDP and iSTDP
Date: 2018-05-28 00:00:00

In this technical report we present novel results of the dopamine
bio-plausible neuromodulation excitatory (eSTDP) and inhibitory (iSTDP)
learning. We present the principal schematic for the neuromodulation of D1 and
D2 receptors of dopamine, wiring schematic for both cases as well as the
simulatory experiments results done in LTSpice.
Application of FPGA Acceleration in ADC Performance Calibration
Date: 2018-06-10 00:00:00
Tasks: CPU

In recent years, high speed and high resolution analog-to-digital converter
(ADC) is widely employed in many physical experiments, especially in high
precision time and charge measurement. The rapid increasing amount of digitized
data demands faster computing. FPGA acceleration has an attracting prospect in
data process for its stream process and parallel process feature. In this
paper, an ADC performance calibration application based on FPGA acceleration is
described. FPGA reads the ADC digitized data stream from PC memory, processes
and then writes processed result back to the PC memory. PCIE bus is applied to
increase the data transfer speed, and floating point algorithm is applied to
improve the accuracy. The test result shows that FPGA acceleration can reduce
the processing time of the ADC performance calibration compared with
traditional method of C-based CPU processing. This frame of PCIE-based FPGA
acceleration method can be applied in analysis and simulation in the future
physical experiment for large ADC array, such as CCD camera and waveform
digitization readout electronics calibration.
A mathematical formalism for natural selection with arbitrary spatial and genetic structure
Date: 2018-11-14 00:00:00

We define a general class of models representing natural selection between
two alleles. The population size and spatial structure are arbitrary, but
fixed. Genetics can be haploid, diploid, or otherwise; reproduction can be
asexual or sexual. Biological events (e.g.~births, deaths, mating, dispersal)
depend in arbitrary fashion on the current population state. Our formalism is
based on the idea of genetic sites. Each genetic site resides at a particular
locus and houses a single allele. Each individual contains a number of sites
equal to its ploidy (one for haploids, two for diploids, etc.). Selection
occurs via replacement events, in which alleles in some sites are replaced by
copies of others. Replacement events depend stochastically on the population
state, leading to a Markov chain representation of natural selection. Within
this formalism, we define reproductive value, fitness, neutral drift, and
fixation probability, and prove relationships among them. We identify four
criteria for evaluating which allele is selected and show that these become
equivalent in the limit of low mutation. We then formalize the method of weak
selection. The power of our formalism is illustrated with applications to
evolutionary games on graphs and to selection in a haplodiploid population.
Null Space Based Preemptive Scheduling For Joint URLLC and eMBB Traffic in 5G Networks
Date: 2018-06-10 00:00:00
Tasks: Decoder, Scheduling

In this paper, we propose a null-space-based preemptive scheduling framework
for cross-objective optimization to always guarantee robust URLLC performance,
while extracting the maximum possible eMBB capacity. The proposed scheduler
perpetually grants incoming URLLC traffic a higher priority for instant
scheduling. In case that radio resources are not immediately schedulable,
proposed scheduler forcibly enforces an artificial spatial user separation, for
the URLLC traffic to get instantly scheduled over shared resources with ongoing
eMBB transmissions. A pre-defined reference spatial subspace is constructed for
which scheduler instantly picks the active eMBB user whose precoder is the
closest possible. Then, it projects the eMBB precoder on-the-go onto the
reference subspace, in order for its paired URLLC user to orient its decoder
matrix into one possible null space of the reference subspace. Hence, a robust
decoding ability is always preserved at the URLLC user, while cross-maximizing
the ergodic capacity. Compared to the state-of-the-art proposals from industry
and academia, proposed scheduler shows extreme URLLC latency robustness with
significantly improved overall spectral efficiency. Analytical analysis and
extensive system level simulations are presented to support paper conclusions.
Information Retrieval in African Languages
Authors: Suleman Hussein
Date: 2018-06-12 00:00:00
Tasks: Information Retrieval, Position, Retrieval

Developing Information Retrieval (IR) tools and techniques in African
languages suffers from the dual problems of a lack of algorithms and very small
test data collections. This affects the creation of practical IR systems and
limits the ability to apply IR to address human and socio-economic problems,
which is an urgent need in poor countries. This position paper presents an
overview of recent and current work conducted at the University of Cape Town in
this area. While many problems have been investigated at an early stage,
limited dataset sizes for local African languages still persists as a
significant limitation and stumbling block.
Key challenges facing data-driven multicellular systems biology
Date: 2019-09-27 00:00:00

Increasingly sophisticated experiments, coupled with large-scale
computational models, have the potential to systematically test biological
hypotheses to drive our understanding of multicellular systems. In this short
review, we explore key challenges that must be overcome to achieve robust,
repeatable data-driven multicellular systems biology. If these challenges can
be solved, we can grow beyond the current state of isolated tools and datasets
to a community-driven ecosystem of interoperable data, software utilities, and
computational modeling platforms. Progress is within our grasp, but it will
take community (and financial) commitment.
Blue-blocking spectacles lenses for retinal damage protection and circadian rhythm: evaluation parameters
Authors: Regina Comparetto, Alessandro Farini
Date: 2018-06-11 00:00:00
Tasks: Blocking, Rhythm

There is evidence for the effect of blue light on circadian cycle and ocular pathologies. Moreover, the introduction of LED lamps has increased the presence of blue light. In the last two years, many different blue blocking ophthalmic lenses have been introduced. Due to the different effect of blue light on ocular media and circadian rhythm, we have defined two indices that describe the level of protection of the lenses towards the retina and the circadian cycle under different lighting as for example daylight and tablet. These indexes can help in individuating the right lens for ocular protection.