pwc-archive/papers-with-abstracts huggingface dataset:
Quantifying the trade-off between income stability and the number of members in a pooled annuity fund
Authors: Thomas Bernhardt, Catherine Donnelly
Date: 2020-10-30 00:00:00

The number of people who receive a stable income for life from a closed pooled annuity fund is studied. Income stability is defined as keeping the income within a specified tolerance of the initial income in a fixed proportion of future scenarios. The focus is on quantifying the effect of the number of members, which drives the level of idiosyncratic longevity risk in the fund, on the income stability. To do this, investment returns are held constant and systematic longevity risk is omitted. An analytical expression that closely approximates the number of fund members who receive a stable income is derived and is seen to be independent of the mortality model. An application of the result is to calculate the length of time for which the pooled annuity fund can provide the desired level of income stability
Mixed-Integer Optimization for Bio-Inspired Robust Power Network Design
Authors: Hao Huang, Varuneswara Panyam, Mohammad Rasoul Narimani, Astrid Layton, Katherine R. Davis
Date: 2020-10-30 00:00:00

Power systems are susceptible to natural threats including hurricanes and floods. Modern power grids are also increasingly threatened by cyber attacks. Existing approaches that help improve power system security and resilience may not be sufficient; this is evidenced by the continued challenge to supply energy to all customers during severe events. This paper presents an approach to address this challenge through bio-inspired power system network design to improve system reliability and resilience against disturbances. Inspired by naturally robust ecosystems, this paper considers the optimal ecological robustness that recognizes a unique balance between pathway efficiency and redundancy to ensure the survivability against disruptive events for given networks. This paper presents an approach that maximizes ecological robustness in transmission network design by formulating a mixed-integer nonlinear programming optimization problem with power system constraints. The results show the increase of the optimized power system's robustness and the improved reliability with less violations under N-x contingencies.
Considerations in the Automatic Development of Electric Grid Restoration Plans
Authors: Wonhyeok Jang, Hao Huang, Katherine R. Davis, Thomas J. Overbye
Date: 2020-10-30 00:00:00

Power system restoration is a highly complex task that must be performed in a timely manner following a blackout. It is crucial to have the capability of developing a reliable restoration plan that can be adjusted quickly to different system conditions. This paper introduces a framework of an automated process that creates a restoration plan for a given power system. The required input includes the original system data under normal operating conditions and the status of the resources in the system that can be used for restoration. With a set of criteria to select as an option, the presented process can produce a restoration sequence in terms of which generator, load, branches, and breakers to close until a stopping criterion is met. The algorithm of the restoration process is described, and its application to a synthetic 200-bus case provides a restoration sequence from blackstart generating units to critical loads first and then to the rest of the system without violating any limits for frequency, voltage and branch loading.
Adversarial defense for deep speaker recognition using hybrid adversarial training
Date: 2020-10-30 00:00:00
Tasks: Adversarial Defense, Speaker Recognition

Deep neural network based speaker recognition systems can easily be deceived
by an adversary using minuscule imperceptible perturbations to the input speech
samples. These adversarial attacks pose serious security threats to the speaker
recognition systems that use speech biometric. To address this concern, in this
work, we propose a new defense mechanism based on a hybrid adversarial training
(HAT) setup. In contrast to existing works on countermeasures against
adversarial attacks in deep speaker recognition that only use class-boundary
information by supervised cross-entropy (CE) loss, we propose to exploit
additional information from supervised and unsupervised cues to craft diverse
and stronger perturbations for adversarial training. Specifically, we employ
multi-task objectives using CE, feature-scattering (FS), and margin losses to
create adversarial perturbations and include them for adversarial training to
enhance the robustness of the model. We conduct speaker recognition experiments
on the Librispeech dataset, and compare the performance with state-of-the-art
projected gradient descent (PGD)-based adversarial training which employs only
CE objective. The proposed HAT improves adversarial accuracy by absolute 3.29%
and 3.18% for PGD and Carlini-Wagner (CW) attacks respectively, while retaining
high accuracy on benign examples.
Millimeter-wave Multi-mode Circular Antenna Array for Uni-cast Multi-cast and OAM Communication
Authors: Stylianos D. Assimonis, M. Ali Babar Abbasi, Vincent Fusco
Date: 2020-10-27 00:00:00

This paper investigates multi-mode and orbital angular momentum (OAM) mode data transmission techniques by a using a circular antenna array, operating at 28 GHz. The classical mode excitation of the latter is modified such that in the horizontal plane the antenna array operates as multimode transmitter (i.e., it provides broad- , uni- and/or multi-cast transmission), while in the vertical direction OAM transmission occurs: this dual-functionality by a single antenna-array at 28 GHz is presented for the first time. Specifically, it can transmit/receive in either broad-, uni-, multi-cast mode in the horizontal plane and also, it is capable of generating up to 15 spatially orthogonal OAM modes in the vertical direction. The proposed circular array is designed using twelve, low-complexity, multi-layer microstrip patch antennas with high radiation efficiency. It was tested through full electromagnetic analysis in terms of impedance matching, mutual coupling and radiation pattern. It was, also, fabricated and measured: good agreement between simulated and measurement results was observed. The proposed antenna array is perfect candidate for high spectral efficiency data transmission for 5G and beyond wireless applications.
Discrimination in the Venture Capital Industry: Evidence from Field Experiments
Authors: Ye Zhang
Date: 2020-10-30 00:00:00

This paper examines discrimination by early-stage investors based on startup founders' gender and race using two complementary field experiments with real U.S. venture capitalists. Results show the following. (i) Discrimination varies depending on the context. Investors implicitly discriminate against female and Asian founders when evaluating attractive startups, but they favor female and Asian founders when evaluating struggling startups. This helps to reconcile the contradictory results in the extant literature and confirms the theoretical predictions of "discrimination reversion" and "pro-cyclical discrimination" phenomena. (ii) Among multiple coexisting sources of discrimination identified, statistical discrimination and implicit discrimination are important reasons for investors' "anti-minority" behaviors. A consistent estimator is developed to measure the polarization of investors' discrimination behaviors and their separate driving forces. (iii) Homophily exists when investors provide anonymous encouragement to startups in a non-investment setting. (iv) There was temporary, stronger discrimination against Asian founders during the COVID-19 outbreak.
Interference Reduction in Virtual Cell Optimization
Authors: Michal Yemini, Elza Erkip, Andrea J. Goldsmith
Date: 2020-10-30 00:00:00

Virtual cell optimization clusters cells into neighborhoods and performs optimized resource allocation over each neighborhood. In prior works we proposed resource allocation schemes to mitigate the interference caused by transmissions in the same virtual cell. This work aims at mitigating both the interference caused by the transmissions of users in the same virtual cell and the interference between transmissions in different virtual cells. We propose a resource allocation technique that reduces the number of users that cannot achieve their constant guaranteed bit rate, i.e., the "unsatisfied users", in an uplink virtual cell system with cooperative decoding. The proposed scheme requires only the knowledge of the number of users each base station serves and relies on creating the interference graph between base stations at the edges of virtual cells. Allocation of frequency bands to users is based on the number of users each base station would serve in a non cooperative setup. We evaluate the performance of our scheme for a mmWave system. Our numerical results show that our scheme decreases the number of users in the system whose rate falls below the guaranteed rate, set to $128$kbps, $256$kbps or $512$kbps, when compared with our previously proposed optimization methods.
Stochastic quorum percolation and noise focusing in neuronal networks
Date: 2020-10-30 00:00:00

Recent experiments have shown that the spontaneous activity of young
dissociated neuronal cultures can be described as a process of highly
inhomogeneous nucleation and front propagation due to the localization of noise
activity, i.e., noise focusing. However, the basic understanding of the
mechanisms of noise build-up leading to the nucleation remain an open
fundamental problem. Here we present a minimal dynamical model called
stochastic quorum percolation that can account for the observed phenomena,
while providing a robust theoretical framework. The model reproduces the first
and second order phase--transitions of bursting dynamics and neuronal
avalanches respectively, and captures the profound effect metric correlations
in the network topology can have on the dynamics. The application of our
results to other systems such as in the propagation of infectious diseases and
of rumors is discussed.
Fixed-State Log-MAP Detection for Intensity-Modulation and Direct-Detection Optical Systems over Dispersion-Uncompensated Links
Date: 2020-10-30 00:00:00

In this paper, an optimized detection based on log-maximum a posteriori estimation with the fixed number of surviving states (fixed-state Log-MAP) is proposed to cooperate with equalizers to deal with the spectral distortions caused by limited bandwidth and chromatic dispersion for intensity-modulation and direct-detection (IM/DD) optical systems. The equalizers compensates the spectral distortions and optimized detection decodes the useful bits from the noise. For accurately extracting the bits from more serious noise, the optimized detection with larger memory length is required. However, the classical optimized detection such as maximum likelihood-sequence estimation (MLSE) requires exponential-growing computational complexity and storage with the increasing memory length. The fixed-state Log-MAP detection can decrease the computational complexity and storage from the exponential order to linear order. Therefore, the fixed-state Log-MAP detection can compensate more distortions compared to MLSE under the same hardware condition. We experimentally verify the fixed-state Log-MAP detection in a C-band 64 Gbit/s IM/DD on-off keying optical system over a 100 km dispersion-uncompensated link. Under the same hardware condition, the fixed-state Log-MAP detection has a 2 dB improvement of receiver sensitivity compared to MLSE. In conclusion, the fixed-state Log-MAP detection shows the potential for practical IM/DD optical systems.
Beamforming for measurements under disturbed propagation conditions using numerically calculated Green's functions
Date: 2020-10-30 00:00:00
Tasks: Sound Source Localization

Beamforming methods for sound source localization are usually based on
free-field Green's functions to model the sound propagation between source and
microphone. This assumption is known to be incorrect for many industrial
applications and the beamforming results can suffer from this inconsistency
regarding both, accuracy of source power estimation, and accuracy of source
localisation. The aim of this paper is to investigate whether the use of
numerically calculated Green's functions can improve the results of beamforming
measurements.
  The current test cases of numerical and experimental investigations consists
of sources placed in a short rectangular duct. The measurement is performed
outside the duct in a semi-anechoic chamber. A typical example for this kind of
installation is a fan with a heat exchanger.
  The Green's functions for this test case are calculated numerically using the
boundary element method. These tailored Green's functions are used to calculate
the corresponding beamforming steering vectors. The weighting of the Green's
functions in the steering vectors has a decisive influence on the beamforming
results. A generalization of the common steering vector formulations is given
based on two scalars. It is shown that arbitrary differentiable Green's
functions can be used to find the correct source position or source power level
by using the appropriate steering vector formulations.
  Beamforming measurements are performed using a loudspeaker as a reference
source at different positions in the heat exchanger duct. The measurements are
evaluated in the frequency domain and by means of different validation criteria
it can be shown that the results with the numerical calculated Green's function
are improved compared to free field beamforming especially at low frequencies.
The Human Cell Atlas & Equity: Lessons Learned
Authors: Partha P. Majumder, Musa M. Mhlanga, Alex K. Shalek
Date: 2020-10-30 00:00:00

The Human Cell Atlas has been undergoing a massive effort to support global scientific equity. The co-leaders of its Equity Working Group share some lessons learned in the process.
Evolutionary graph theory derived from eco-evolutionary dynamics
Authors: Karan Pattni, Christopher E. Overton, Kieran J. Sharkey
Date: 2020-10-30 00:00:00

A biologically motivated individual-based framework for evolution in network-structured populations is developed that can accommodate eco-evolutionary dynamics. This framework is used to construct a network birth and death model. The evolutionary graph theory model, which considers evolutionary dynamics only, is derived as a special case, highlighting additional assumptions that diverge from real biological processes. This is achieved by introducing a negative ecological feedback loop that suppresses ecological dynamics by forcing births and deaths to be coupled. We also investigate how fitness, a measure of reproductive success used in evolutionary graph theory, is related to the life-history of individuals in terms of their birth and death rates. In simple networks, these ecologically motivated dynamics are used to provide new insight into the spread of adaptive mutations, both with and without clonal interference. For example, the star network, which is known to be an amplifier of selection in evolutionary graph theory, can inhibit the spread of adaptive mutations when individuals can die naturally.
Assessment of mobility deficit and treatment efficacy in adhesive capsulitis by measurement of kinematic parameters using IMU sensors
Authors: Miloš Ajčević, Manuela Deodato, Luigi Murena, Aleksandar Miladinović, Susanna Mezzarobba, Agostino Accardo
Date: 2020-10-30 00:00:00
Tasks: Rhythm

There is a growing research interest towards the use of wireless IMU sensors to assess disability, monitor progress and provide feedback to patients on range of motion and movement performance during upper body rehabilitation. The quality of movement in patients with adhesive capsulitis and relative treatment efficacy has not yet been studied using inertial and magnetic sensors. The aim of this study was to investigate the possibility to quantitatively evaluate capsulate-related deficit versus healthy controls and to assess treatment efficacy by measurement of shoulder kinematic parameters with ISEO protocol using inertial and magnetic measurement system technology. We enrolled 6 patients with adhesive capsulitis (AC) who underwent the experimental assessment by using a set of wireless IMU sensors at the baseline (T0) and after the 15 one-hour individual sessions of physiotherapy (T1). The range of motion in elevation, abduction and the scapulohumeral rhythm kinematic parameters were extracted from measurements performed in enrolled AC patients and in 7 healthy controls. The results of this preliminary study showed that proposed approach based on measurement of shoulder kinematic parameters with ISEO protocol using IMU wireless sensors can be useful in mobility deficit assessment of patients with adhesive capsulitis, as well as for monitoring of treatment efficacy and its further personalization.
Range-Doppler Information and Doppler Scattering Information in Multipulse Radar
Authors: Chao Shi, Dazhuan Xu, Ying Zhou, Weilin Tu
Date: 2020-10-30 00:00:00

In this paper, the general radar measurement probfilems of determining range, Doppler frequency and scatteringproperties parameters are investigated from the viewpoint of Shannons information theory. We adopt the mutual information to evaluate the accuracy of the classification and estimation. The range-Doppler information is examined under the condition that the target is of radial velocity. Its asymptotic upper bound and the corresponding entropy error (EE) are further formulated theoretically. Additionally, the Doppler scattering information induced by targets random motion characteristics is discussed. From the derivation, it is concluded that the Doppler scattering information depends on the eigenvalues of the target scattering correlation matrix. Especially in the case where the pulse interval is larger than targets coherence time, we can find that the formula of the Doppler scattering information is similar to Shannons channel capacity equation, indicating the inherent consistency between the communication theory and radar field. Numerical simulations of these information contents are presented to confirm our theoretical observations. The relationship between the information content and signal-to-noise ratio (SNR) reflects the changes in information acquisition efficiency of a radar system, providing guidance for system designers.
Adaptive Feedforward Control For Reset Feedback Control Systems -- Application in Precision Motion Control
Date: 2020-10-30 00:00:00

This paper presents a novel adaptive feedforward controller design for reset
control systems. The combination of feedforward and reset feedback control
promises high performance as the feedforward guarantees reference tracking,
while the non-linear feedback element rejects disturbances. To overcome
inevitable model mismatches, the feedforward controller adapts to increase
precision in reference tracking. Where linear existing adaptive feedforward
controllers do not guarantee convergence in the presence of reset, this work
presents a novel adaptive law based on converging and diverging regions of
adaptation to achieve good tracking. Experimental results demonstrate the
claimed advantage of the novel method.
Biological Information
Authors: Jürgen Jost
Date: 2020-10-30 00:00:00

In computer science, we can theoretically neatly separate transmission and processing of information, hardware and software, and programs and their inputs. This is much more intricate in biology, Nevertheless, I argue that Shannon's concept of information is useful in biology, although its application is not as straightforward as many people think. In fact, the recently developed theory of information decomposition can shed much light on the complementarity between coding and regulatory, or internal and environmental information. The key challenge that we formulate in this contribution is to understand how genetic information and external factors combine to create an organism, and conversely, how the genome has learned in the course of evolution how to harness the environment, and analogously, how coding, regulation and spatial organization interact in cellular processes.
Joint Transceiver Design Based on Dictionary Learning Algorithm for SCMA
Authors: Shanshan Zhang, Wen Chen, Shaoyuan Chen
Date: 2020-10-30 00:00:00
Tasks: Dictionary Learning, Scheduling

With the explosively increasing demands on the network capacity, throughput and number of connected wireless devices, massive connectivity is an urgent problem for the next generation wireless communications. In this paper, we propose a grant-free access protocol for massive connectivity that utilizes a large number of antennas in a base station (BS) and is expected to be widely deployed in cellular networks. The scheme consists of a sparse structure in sparse code multiple access (SCMA) and receiver processing based on dictionary learning (DL). A large number of devices can transmit data without any scheduling process. Unlike existing schemes, whose signal schedulings require a lot of overhead, the scheduling overhead required by the proposed scheme is negligible, which is attractive for resource utilization and transmission power efficiency. The numerical results show that the proposed scheme has promising performance in massive connectivity scenario of cellular networks.
Resolving Kirchhoff's laws for state-estimator design of Li-ion battery packs connected in parallel
Date: 2020-10-30 00:00:00

A state-space model for Li-ion battery packs with parallel connected cells is
introduced. The key feature of this model is an explicit solution to
Kirchhoff's laws for parallel connected packs, which expresses the branch
currents directly in terms of the model's states, applied current and cell
resistances. This avoids the need to solve these equations numerically. To
illustrate the potential of the proposed model for pack-level control and
estimation, a state-estimator is introduced for the nonlinear parallel pack
model. By exploiting the system structure seen in the solution to Kirchhoff's
laws, algebraic conditions for the observer gains are obtained that guarantee
convergence of the estimator's error. Error convergence is demonstrated through
an argument based upon Aizerman's conjecture. It is hoped that the insight
brought by this model formulation will allow the wealth of results developed
for series connected packs to be applied to those with parallel connections.
Single Channel MMWave FMCW Radar for 2D Target Localization
Authors: Shahrokh Hamidi, Safieddin Safavi-Naeini
Date: 2020-10-30 00:00:00

In this paper, we present a 2D target localization method using two low cost and compact Mellimeter Wave Frequency Modulated Continuous Wave (MMW-FMCW) radars. To create a 2D map we exploit the bilateration method followed by a multi-target tracking block to remove the ghost targets. Finally, we present experimental results based on the data gathered from two FMCW radars operating at $\rm 79 \;GHz$.
Distributionally Robust Newsvendor with Moment Constraints
Authors: Derek Singh, Shuzhong Zhang
Date: 2020-10-30 00:00:00

This paper expands the work on distributionally robust newsvendor to incorporate moment constraints. The use of Wasserstein distance as the ambiguity measure is preserved. The infinite dimensional primal problem is formulated; problem of moments duality is invoked to derive the simpler finite dimensional dual problem. An important research question is: How does distributional ambiguity affect the optimal order quantity and the corresponding profits/costs? To investigate this, some theory is developed and a case study in auto sales is performed. We conclude with some comments on directions for further research.