pwc-archive/papers-with-abstracts huggingface dataset:
Dynamic Graph Learning based on Graph Laplacian
Date: 2020-02-17 00:00:00
Tasks: Graph Learning, Time Series, Time Series Analysis

The purpose of this paper is to infer a global (collective) model of
time-varying responses of a set of nodes as a dynamic graph, where the
individual time series are respectively observed at each of the nodes. The
motivation of this work lies in the search for a connectome model which
properly captures brain functionality upon observing activities in different
regions of the brain and possibly of individual neurons. We formulate the
problem as a quadratic objective functional of observed node signals over short
time intervals, subjected to the proper regularization reflecting the graph
smoothness and other dynamics involving the underlying graph's Laplacian, as
well as the time evolution smoothness of the underlying graph. The resulting
joint optimization is solved by a continuous relaxation and an introduced novel
gradient-projection scheme. We apply our algorithm to a real-world dataset
comprising recorded activities of individual brain cells. The resulting model
is shown to not only be viable but also efficiently computable.
Artificial-Noise-Aided Secure MIMO Wireless Communications via Intelligent Reflecting Surface
Authors: Sheng Hong, Cunhua Pan, Hong Ren, Kezhi Wang, Arumugam Nallanathan
Date: 2020-02-17 00:00:00

This paper considers a MIMO secure wireless communication system aided by the physical layer security technique of sending artificial noise (AN). To further enhance the system security performance, the advanced intelligent reflecting surface (IRS) is invoked in the AN-aided communication system, where the base station (BS), legitimate information receiver (IR) and eavesdropper (Eve) are equipped with multiple antennas. With the aim for maximizing the secrecy rate (SR), the transmit precoding (TPC) matrix at the BS, covariance matrix of AN and phase shifts at the IRS are jointly optimized subject to constrains of transmit power limit and unit modulus of IRS phase shifts. Then, the secrecy rate maximization (SRM) problem is formulated, which is a non-convex problem with multiple coupled variables. To tackle it, we propose to utilize the block coordinate descent (BCD) algorithm to alternately update the TPC matrix, AN covariance matrix, and phase shifts while keeping SR non-decreasing. Specifically, the optimal TPC matrix and AN covariance matrix are derived by Lagrangian multiplier method, and the optimal phase shifts are obtained by Majorization-Minimization (MM) algorithm. Since all variables can be calculated in closed form, the proposed algorithm is very efficient. We also extend the SRM problem to the more general multiple-IRs scenario and propose a BCD algorithm to solve it. Finally, simulation results validate the effectiveness of system security enhancement via an IRS.
Crisis contagion in the world trade network
Authors: Célestin Coquidé, José Lages, Dima L. Shepelyansky
Date: 2020-02-17 00:00:00

We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an \textit{on-off} phase transition governed by a bankruptcy threshold $\kappa$ related to the trade balance of the countries. For $\kappa>\kappa_c$, the contagion is circumscribed to less than 10\% of the countries, whereas, for $\kappa<\kappa_c$, the crisis is global with about 90\% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.
Pricing Bitcoin Derivatives under Jump-Diffusion Models
Date: 2020-02-17 00:00:00

In recent years cryptocurrency trading has captured the attention of
practitioners and academics. The volume of the exchange with standard
currencies has known a dramatic increasing of late. This paper addresses to the
need of models describing a bitcoin-US dollar exchange dynamic and their use to
evaluate European option having bitcoin as underlying asset.
How Do Expectations Affect Learning About Fundamentals? Some Experimental Evidence
Authors: Kieran Marray, Nikhil Krishna, Jarel Tang
Date: 2020-02-17 00:00:00

We test how individuals with incorrect beliefs about their ability learn about an external parameter (`fundamental') when they cannot separately identify the effects of their ability, actions, and the parameter on their output. Heidhues et al. (2018) argue that learning makes overconfident individuals worse off as their beliefs about the fundamental get less accurate, causing them to take worse actions. In our experiment, subjects take incorrectly-marked tests, and we measure how they learn about the marker's accuracy over time. Overconfident subjects put in less effort, and their beliefs about the marker's accuracy got worse, as they learnt. Beliefs about the proportion of correct answers marked as correct fell by 0.05 over the experiment. We find no effect in underconfident subjects.
5G Simulation-Based Experimentation Framework for Vertical Performance Assessment
Date: 2020-02-17 00:00:00
Tasks: Diversity

5G is being designed as a common platform where multiple vertical
applications will be able to co-exist and grow in a seamless manner. The
diversity of the vertical requirements as well as the particular features of
the 5G network itself, make it a real challenge to be able to assess or predict
applications performance for those verticals. In this paper we motivate the
fact that because of the very nature of verticals and 5G infrastructure,
measurements alone will not be sufficient for application performance
monitoring and prediction. We then propose a comprehensive framework to
integrate those measurements in a simulation setting, presenting the key
features and current roadblocks for an end-to-end wide-spread implementation.
A New Approach in Optimal Control of Step-Down Converters Based on a Switch-State Controller
Date: 2020-02-18 00:00:00

In this paper, an optimal approach based on on-off controller is used to
optimally control a DC-DC step-down converter. It is shown that the
conventional controller techniques of DC-DC converters based on a linearized
averaging model have several drawbacks, including different operating mode,
linearization concerns, and constraint difficulties. A single-mode discretize
state-space model is used, and a new optimal approach policy is implemented to
control a step-down DC-DC converter. The simulation results confirm that the
proposed DC-DC model associated with the optimal controller functions properly
in controlling a DC-DC unfixed switch-mode step-down converter that is facing
load changes, noisy inputs, and start-up procedure.
Bit Error Rate Analysis of M-ARY PSK and M-ARY QAM Over Rician Fading Channel
Date: 2020-02-16 00:00:00
Tasks: Diversity

This paper mainly illustrates the Bit error rate performance of M-ary QAM and
M-ary PSK for different values of SNR over Rician Fading channel. A signal
experiences multipath propagation in the wireless communication system which
causes expeditious signal amplitude fluctuations in time, is defined as fading.
Rician Fading is a small signal fading. Rician fading is a hypothetical model
for radio propagation inconsistency produced by fractional cancellation of a
radio signal by itself and as a result the signal reaches in the receiver by
several different paths. In this case, at least one of the destination paths is
being lengthened or shortened. From this paper , it can be observed that the
value of Bit error rate decreases when signal to noise ratio increases in
decibel for Mary QAM and M-ary PSK such as 256 QAM, 64 PSK etc. Constellation
diagrams of M-QAM and M-PSK have also been showed in this paper using MATLAB
Simulation. The falling of Bit error rate with the increase of diversity order
for a fixed value of SNR has also been included in this paper. Diversity is a
influential receiver system which offers improvement over received signal
strength.
Lightweight hardware implementation of VVC transform block for ASIC decoder
Date: 2020-02-18 00:00:00
Tasks: 4k, Decoder

Versatile Video Coding (VVC) is the next generation video coding standard
expected by the end of 2020. Compared to its predecessor, VVC introduces new
coding tools to make compression more efficient at the expense of higher
computational complexity. This rises a need to design an efficient and
optimised implementation especially for embedded platforms with limited memory
and logic resources. One of the newly introduced tools in VVC is the Multiple
Transform Selection (MTS). This latter involves three Discrete Cosine Transform
(DCT)/Discrete Sine Transform (DST) types with larger and rectangular transform
blocks. In this paper, an efficient hardware implementation of all DCT/DST
transform types and sizes is proposed. The proposed design uses 32 multipliers
in a pipelined architecture which targets an ASIC platform. It consists in a
multi-standard architecture that supports the transform block of recent MPEG
standards including AVC, HEVC and VVC. The architecture is optimized and
removes unnecessary complexities found in other proposed architec-tures by
using regular multipliers instead of multiple constant multi-pliers. The
synthesized results show that the proposed method which sustain a constant
throughput of two pixels/cycle and constant la-tency for all block sizes can
reach an operational frequency of 600 Mhz enabling to decode in real-time 4K
videos at 48 fps.
Model based fractional order controller design for process plants satisfying desired robustness criteria
Date: 2020-02-18 00:00:00

This paper contributes to the design of a fractional order (FO) internal
model controller (IMC) for a first order plus time delay (FOPTD) process model
to satisfy a given set of desired robustness specifications in terms of gain
margin (Am) and phase margin (Pm). The highlight of the design is the choice of
a fractional order (FO) filter in the IMC structure which has two parameters
(lambda and beta) to tune as compared to only one tuning parameter (lambda) for
traditionally used integer order (IO) filter. These parameters are evaluated
for the controller, so that Am and Pm can be chosen independently. A new
methodology is proposed to find a complete solution for controller parameters,
the methodology also gives the system gain cross-over frequency (wg) and phase
cross-over frequency (wp). Moreover, the solution is found without any
approximation of the delay term appearing in the controller.
Heart Rate Variability as an Indicator of Thermal Comfort State
Authors: Kizito Nkurikiyeyezu, Yuta Suzuki, Yoshito Tobe, Guillaume Lopez, Kiyoshi Itao
Date: 2020-02-18 00:00:00
Tasks: Heart Rate Variability

Thermal comfort is a personal assessment of one's satisfaction with the surroundings. Yet, most thermal comfort delivery mechanisms preclude physiological and psychological precursors to thermal comfort. Accordingly, many people feel either cold or hot in an environment that is supposedly thermally comfortable to most people. To address this issue, this paper proposes to use people's heart rate variability (HRV) as an alternative indicator of thermal comfort. Since HRV is linked to homeostasis, we hypothesize that it could be used to predict people's thermal comfort status. To test our hypothesis, we analyzed statistical, spectral, and nonlinear HRV indices of 17 human subjects doing light office work in a cold, a neutral, and a hot environment. The resulting HRV indices were used as inputs to machine learning classification algorithms. We observed that HRV is distinctively altered depending on the thermal environment and that it is possible to steadfastly predict each subject's thermal environment (cold, neutral, and hot) with up to a 93.7% prediction accuracy. The result of this study implies that it could be possible to design automatic real-Time thermal comfort controllers based on people's HRV.
The Market Price of Risk for Delivery Periods: Pricing Swaps and Options in Electricity Markets
Authors: Annika Kemper, Maren D. Schmeck, Anna Kh. Balci
Date: 2020-02-18 00:00:00

In electricity markets, futures contracts typically function as a swap since they deliver the underlying over a period of time. In this paper, we introduce a market price for the delivery periods of electricity swaps, thereby opening an arbitrage-free pricing framework for derivatives based on these contracts. Furthermore, we use a weighted geometric averaging of an artificial geometric futures price over the corresponding delivery period. Without any need for approximations, this averaging results in geometric swap price dynamics. Our framework allows for including typical features as the Samuelson effect, seasonalities, and stochastic volatility. In particular, we investigate the pricing procedures for electricity swaps and options in line with Arismendi et al. (2016), Schneider and Tavin (2018), and Fanelli and Schmeck (2019). A numerical study highlights the differences between these models depending on the delivery period.
Dataset after seven years simulating hybrid energy systems with Homer Legacy
Date: 2020-02-13 00:00:00

Homer Legacy software is a well-known software for simulation of small hybrid
systems that can be used for both design and research. This dataset is a set of
files generated by Homer Legacy bringing the simulation results of hybrid
energy systems over the last seven years, as a consequence of the research work
led by Dr. Alexandre Beluco, Federal University of Rio Grande do Sul, in
southern Brazil. The data correspond to thirty papers published in the last
seven years. Two of them describe hydro PV hybrid systems with photovoltaic
panels operating on the water surface of reservoirs. One of these twelve papers
suggests the model-ing of hydropower plants with reservoirs and the other the
modeling of pumped hydro stor-age, and a third still uses these models in a
place that could receive both the two types of hy-droelectric power plant. The
other simulated hybrid systems include wind turbines, diesel generators,
batteries, among other components. This data article describes the files that
inte-grate this dataset and the papers that have been published presenting the
hybrid systems under study and discussing the results. The files that make up
this dataset are available on Mendeley Data repository at
dx.doi.org/10.17632/ybxsttf2by.2.
An Energy-Efficient Accelerator Architecture with Serial Accumulation Dataflow for Deep CNNs
Date: 2020-02-15 00:00:00

Convolutional Neural Networks (CNNs) have shown outstanding accuracy for many
vision tasks during recent years. When deploying CNNs on portable devices and
embedded systems, however, the large number of parameters and computations
result in long processing time and low battery life. An important factor in
designing CNN hardware accelerators is to efficiently map the convolution
computation onto hardware resources. In addition, to save battery life and
reduce energy consumption, it is essential to reduce the number of DRAM
accesses since DRAM consumes orders of magnitude more energy compared to other
operations in hardware. In this paper, we propose an energy-efficient
architecture which maximally utilizes its computational units for convolution
operations while requiring a low number of DRAM accesses. The implementation
results show that the proposed architecture performs one image recognition task
using the VGGNet model with a latency of 393 ms and only 251.5 MB of DRAM
accesses.
Synaptic clock as a neural substrate of consciousness
Authors: Bartosz Jura
Date: 2020-02-18 00:00:00

In this theoretical work the temporal aspect of consciousness is analyzed. We start from the notion that while conscious experience seems to change constantly, yet for any of its contents to be consciously perceived they must last for some non-zero duration of time, which appears to constitute certain conflict. We posit that, in terms of phenomenological analysis of consciousness, the temporal aspect, and this apparent conflict in particular, might be the most basic property, likely inherent to any conceivable form of consciousness. It is then outlined how taking this perspective offers a concrete way of relating the properties of consciousness directly to the neural plasticity mechanisms of learning and memory, and specifying how exactly subjective experience might be related to processes of information integration. In particular, we propose synaptic clock to constitute a content-specific neural substrate of consciousness, explaining how it would correspond to this temporal aspect. Then, we propose a viewpoint, in which moments of subjective time have different durations, depending on the type of information processed, proportional to the time units of corresponding synaptic clocks, and being in principle different for different brain regions and nervous systems in different animal species. Relation and possible contributions of this viewpoint to the extensional model of time consciousness are discussed. Finally, we consider the two alternative views on the structure of consciousness, namely a static and a dynamic one, and argue in favor of the latter, proposing that consciousness can be best understood if change is considered its only dimension.
Classifying sleep states using persistent homology and Markov chain: a Pilot Study
Date: 2020-02-17 00:00:00
Tasks: Topological Data Analysis

Obstructive sleep Apnea (OSA) is a form of sleep disordered breathing
characterized by frequent episodes of upper airway collapse during sleep.
Pediatric OSA occurs in 1-5% of children and can related to other serious
health conditions such as high blood pressure, behavioral issues, or altered
growth. OSA is often diagnosed by studying the patient's sleep cycle, the
pattern with which they progress through various sleep states such as
wakefulness, rapid eye-movement, and non-rapid eye-movement. The sleep state
data is obtained using an overnight polysomnography test that the patient
undergoes at a hospital or sleep clinic, where a technician manually labels
each 30 second time interval, also called an "epoch", with the current sleep
state. This process is laborious and prone to human error. We seek an automatic
method of classifying the sleep state, as well as a method to analyze the sleep
cycles. This article is a pilot study in sleep state classification using two
approaches: first, we'll use methods from the field of topological data
analysis to classify the sleep state and second, we'll model sleep states as a
Markov chain and visually analyze the sleep patterns. In the future, we will
continue to build on this work to improve our methods.
Analyzing Grant-Free Access for URLLC Service
Authors: Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis
Date: 2020-02-18 00:00:00

5G New Radio (NR) is expected to support new ultra-reliable low-latency communication (URLLC) service targeting at supporting the small packets transmissions with very stringent latency and reliability requirements. Current Long Term Evolution (LTE) system has been designed based on grantbased (GB) (i.e., dynamic grant) random access, which can hardly support the URLLC requirements. Grant-free (GF) (i.e., configured grant) access is proposed as a feasible and promising technology to meet such requirements, especially for uplink transmissions, which effectively saves the time of requesting/waiting for a grant. While some basic GF access features have been proposed and standardized in NR Release-15, there is still much space to improve. Being proposed as 3GPP study items, three GF access schemes with Hybrid Automatic Repeat reQuest (HARQ) retransmissions including Reactive, K-repetition, and Proactive, are analyzed in this paper. Specifically, we present a spatiotemporal analytical framework for the contention-based GF access analysis. Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances. We propose a tractable approach to derive and analyze the latent access failure probability of the typical UE under three GF HARQ schemes. Our results show that under shorter latency constraints, the Proactive scheme provides the lowest latent access failure probability, whereas, under longer latency constraints, the K-repetition scheme achieves the lowest latent access failure probability, which depends on K. If K is overestimated, the Proactive scheme provides lower latent access failure probability than the K-repetition scheme.
The interconnectedness of the economic content in the speeches of the US Presidents
Date: 2020-02-18 00:00:00

The speeches stated by influential politicians can have a decisive impact on
the future of a country. In particular, the economic content of such speeches
affects the economy of countries and their financial markets. For this reason,
we examine a novel dataset containing the economic content of 951 speeches
stated by 45 US Presidents from George Washington (April 1789) to Donald Trump
(February 2017). In doing so, we use an economic glossary carried out by means
of text mining techniques. The goal of our study is to examine the structure of
significant interconnections within a network obtained from the economic
content of presidential speeches. In such a network, nodes are represented by
talks and links by values of cosine similarity, the latter computed using the
occurrences of the economic terms in the speeches. The resulting network
displays a peculiar structure made up of a core (i.e. a set of highly central
and densely connected nodes) and a periphery (i.e. a set of non-central and
sparsely connected nodes). The presence of different economic dictionaries
employed by the Presidents characterize the core-periphery structure. The
Presidents' talks belonging to the network's core share the usage of generic
(non-technical) economic locutions like "interest" or "trade". While the use of
more technical and less frequent terms characterizes the periphery (e.g.
"yield" ). Furthermore, the speeches close in time share a common economic
dictionary. These results together with the economics glossary usages during
the US periods of boom and crisis provide unique insights on the economic
content relationships among Presidents' speeches.
Joint Data and Active User Detection for Grant-free FTN-NOMA in Dynamic Networks
Date: 2020-02-19 00:00:00

Both faster than Nyquist (FTN) signaling and non-orthogonal multiple access
(NOMA) are promising next generation wireless communications techniques as a
benefit of their capability of improving the system's spectral efficiency. This
paper considers an uplink system that combines the advantages of FTN and NOMA.
Consequently, an improved spectral efficiency is achieved by deliberately
introducing both inter-symbol interference (ISI) and inter-user interference
(IUI). More specifically, we propose a grant-free transmission scheme to reduce
the signaling overhead and transmission latency of the considered NOMA system.
To distinguish the active and inactive users, we develop a novel message
passing receiver that jointly estimates the channel state, detects the user
activity, and performs decoding. We conclude by quantifying the significant
spectral efficiency gain achieved by our amalgamated FTN-NOMA scheme compared
to the orthogonal transmission system, which is up to 87.5%.