pwc-archive/papers-with-abstracts huggingface dataset:
Computing Dynamic User Equilibrium on Large-Scale Networks Without Knowing Global Parameters
Authors: Duong Viet Thong, Aviv Gibali, Mathias Staudigl, Phan Tu Vuong
Date: 2020-10-08 00:00:00

Dynamic user equilibrium (DUE) is a Nash-like solution concept describing an equilibrium in dynamic traffic systems over a fixed planning period. DUE is a challenging class of equilibrium problems, connecting network loading models and notions of system equilibrium in one concise mathematical framework. Recently, Friesz and Han introduced an integrated framework for DUE computation on large-scale networks, featuring a basic fixed-point algorithm for the effective computation of DUE. In the same work, they present an open-source MATLAB toolbox which allows researchers to test and validate new numerical solvers. This paper builds on this seminal contribution, and extends it in several important ways. At a conceptual level, we provide new strongly convergent algorithms designed to compute a DUE directly in the infinite-dimensional space of path flows. An important feature of our algorithms is that they give provable convergence guarantees without knowledge of global parameters. In fact, the algorithms we propose are adaptive, in the sense that they do not need a priori knowledge of global parameters of the delay operator, and which are provable convergent even for delay operators which are non-monotone. We implement our numerical schemes on standard test instances, and compare them with the numerical solution strategy employed by Friesz and Han.
Impedance-optical Dual-modal Cell Culture Imaging with Learning-based Information Fusion
Authors: Zhe Liu, Pierre Bagnaninchi, Yunjie Yang
Date: 2021-06-15 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction

While Electrical Impedance Tomography (EIT) has found many biomedicine applications, a better resolution is needed to provide quantitative analysis for tissue engineering and regenerative medicine. This paper proposes an impedance-optical dual-modal imaging framework, which is mainly aimed at high-quality 3D cell culture imaging and can be extended to other tissue engineering applications. The framework comprises three components, i.e., an impedance-optical dual-modal sensor, the guidance image processing algorithm, and a deep learning model named multi-scale feature cross fusion network (MSFCF-Net) for information fusion. The MSFCF-Net has two inputs, i.e., the EIT measurement and a binary mask image generated by the guidance image processing algorithm, whose input is an RGB microscopic image. The network then effectively fuses the information from the two different imaging modalities and generates the final conductivity image. We assess the performance of the proposed dual-modal framework by numerical simulation and MCF-7 cell imaging experiments. The results show that the proposed method could significantly improve image quality, indicating that impedance-optical joint imaging has the potential to reveal the structural and functional information of tissue-level targets simultaneously.
Precise phase retrieval for propagation-based images using discrete mathematics
Authors: J. A. Pollock, K. S. Morgan, L. C. P. Croton, M. K. Croughan, G. Ruben, N. Yagi, H. Sekiguchi, M. J. Kitchen
Date: 2021-06-14 00:00:00
Tasks: Computational Efficiency, Computed Tomography (CT), Retrieval

The ill-posed problem of phase retrieval in optics, using one or more intensity measurements, has a multitude of applications using electromagnetic or matter waves. Many phase retrieval algorithms are computed on pixel arrays using discrete Fourier transforms due to their high computational efficiency. However, the mathematics underpinning these algorithms is typically formulated using continuous mathematics, which can result in a loss in spatial resolution in the reconstructed images. Herein we investigate how phase retrieval algorithms for propagation-based phase-contrast X-ray imaging can be rederived using discrete mathematics and result in more precise retrieval for single- and multi-material objects and for spectral image decomposition. We validate this theory through experimental measurements of spatial resolution using computed tomography (CT) reconstructions of plastic phantoms and biological tissue, using detectors with a range of imaging system point spread functions (PSFs). We demonstrate that if the PSF substantially suppresses high spatial frequencies, the potential improvement from utilising the discrete derivation is limited. However, with detectors characterised by a single pixel PSF (e.g. direct, photon-counting X-ray detectors), a significant improvement in spatial resolution can be obtained, demonstrated here at up to 17%.
Comparisons of Australian Mental Health Distributions
Authors: David Gunawan, William Griffiths, Duangkamon Chotikapanich
Date: 2021-06-15 00:00:00

Bayesian nonparametric estimates of Australian mental health distributions are obtained to assess how the mental health status of the population has changed over time and to compare the mental health status of female/male and indigenous/non-indigenous population subgroups. First- and second-order stochastic dominance are used to compare distributions, with results presented in terms of the posterior probability of dominance and the posterior probability of no dominance. Our results suggest mental health has deteriorated in recent years, that males mental health status is better than that of females, and non-indigenous health status is better than that of the indigenous population.
Young people between education and the labour market during the COVID-19 pandemic in Italy
Authors: Davide Fiaschi, Cristina Tealdi
Date: 2021-06-15 00:00:00

We analyse the distribution and the flows between different types of employment (self-employment, temporary, and permanent), unemployment, education, and other types of inactivity, with particular focus on the duration of the school-to-work transition (STWT). The aim is to assess the impact of the COVID-19 pandemic in Italy on the careers of individuals aged 15-34. We find that the pandemic worsened an already concerning situation of higher unemployment and inactivity rates and significantly longer STWT duration compared to other EU countries, particularly for females and residents in the South of Italy. In the midst of the pandemic, individuals aged 20-29 were less in (permanent and temporary) employment and more in the NLFET (Neither in the Labour Force nor in Education or Training) state, particularly females and non Italian citizens. We also provide evidence of an increased propensity to return to schooling, but most importantly of a substantial prolongation of the STWT duration towards permanent employment, mostly for males and non Italian citizens. Our contribution lies in providing a rigorous estimation and analysis of the impact of COVID-19 on the carriers of young individuals in Italy, which has not yet been explored in the literature.
The Relationship between Foreign Direct Investment and Economic Growth: A Case of Turkey
Authors: Orhan Gokmen
Date: 2021-06-15 00:00:00

This paper examines the relationship between net FDI inflows and real GDP for Turkey from 1970 to 2019. Although conventional economic growth theories and most empirical research suggest that there is a bi-directional positive effect between these macro variables, the results indicate that there is a uni-directional significant short-run positive effect of real GDP on net FDI inflows to Turkey by employing the Vector Error Correction Model, Granger Causality, Impulse Response Functions and Variance Decomposition. Also, there is no long-run effect has been found. The findings recommend Turkish authorities optimally benefit from the potential positive effect of net incoming FDI on the real GDP by allocating it for the productive sectoral establishments while effectively maintaining the country's real economic growth to attract further FDI inflows.
Re-examining the Philosophical Underpinnings of the Melting Pot vs. Multiculturalism in the Current Immigration Debate in the United States
Authors: Daniel Woldeab, Robert Yawson, Irina Woldeab
Date: 2021-06-15 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction, Translation

Immigration to the United States is certainly not a new phenomenon, and it is therefore natural for immigration, culture and identity to be given due attention by the public and policy makers. However, current discussion of immigration, legal and illegal, and the philosophical underpinnings is lost in translation, not necessarily on ideological lines, but on political orientation. In this paper we reexamine the philosophical underpinnings of the melting pot versus multiculturalism as antecedents and precedents of current immigration debate and how the core issues are lost in translation. We take a brief look at immigrants and the economy to situate the current immigration debate. We then discuss the two philosophical approaches to immigration and how the understanding of the philosophical foundations can help streamline the current immigration debate.
Cyclical behavior of evolutionary dynamics in coordination games with changing payoffs
Authors: George Loginov
Date: 2021-06-15 00:00:00

The paper presents a model of two-speed evolution in which the payoffs in the population game (or, alternatively, the individual preferences) slowly adjust to changes in the aggregate behavior of the population. The model investigates how, for a population of myopic agents with homogeneous preferences, changes in the environment caused by current aggregate behavior may affect future payoffs and hence alter future behavior. The interaction between the agents is based on a symmetric two-strategy game with positive externalities and negative feedback from aggregate behavior to payoffs, so that at every point in time the population has an incentive to coordinate, whereas over time the more popular strategy becomes less appealing. Under the best response dynamics and the logit dynamics with small noise levels the joint trajectories of preferences and behavior converge to closed orbits around the unique steady state, whereas for large noise levels the steady state of the logit dynamics becomes a sink. Under the replicator dynamics the unique steady state of the system is repelling and the trajectories are unbounded unstable spirals.
Fragility of Confounded Learning
Authors: Xuanye Wang
Date: 2021-06-14 00:00:00
Tasks: All

We consider an observational learning model with exogenous public payoff shock. We show that confounded learning doesn't arise for almost all private signals and almost all shocks, even if players have sufficiently divergent preferences.
ADEPT: A Dataset for Evaluating Prosody Transfer
Authors: Alexandra Torresquintero, Tian Huey Teh, Christopher G. R. Wallis, Marlene Staib, Devang S Ram Mohan, Vivian Hu, Lorenzo Foglianti, Jiameng Gao, Simon King
Date: 2021-06-15 00:00:00
Tasks: text-to-speech, Text to Speech

Text-to-speech is now able to achieve near-human naturalness and research focus has shifted to increasing expressivity. One popular method is to transfer the prosody from a reference speech sample. There have been considerable advances in using prosody transfer to generate more expressive speech, but the field lacks a clear definition of what successful prosody transfer means and a method for measuring it. We introduce a dataset of prosodically-varied reference natural speech samples for evaluating prosody transfer. The samples include global variations reflecting emotion and interpersonal attitude, and local variations reflecting topical emphasis, propositional attitude, syntactic phrasing and marked tonicity. The corpus only includes prosodic variations that listeners are able to distinguish with reasonable accuracy, and we report these figures as a benchmark against which text-to-speech prosody transfer can be compared. We conclude the paper with a demonstration of our proposed evaluation methodology, using the corpus to evaluate two text-to-speech models that perform prosody transfer.
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech
Authors: Pu Wang, Bagher BabaAli, Hugo Van hamme
Date: 2021-06-15 00:00:00
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition, Spoken Language Understanding

End-to-end (E2E) spoken language understanding (SLU) systems avoid an intermediate textual representation by mapping speech directly into intents with slot values. This approach requires considerable domain-specific training data. In low-resource scenarios this is a major concern, e.g., in the present study dealing with SLU for dysarthric speech. Pretraining part of the SLU model for automatic speech recognition targets helps but no research has shown to which extent SLU on dysarthric speech benefits from knowledge transferred from other dysarthric speech tasks. This paper investigates the efficiency of pre-training strategies for SLU tasks on dysarthric speech. The designed SLU system consists of a TDNN acoustic model for feature encoding and a capsule network for intent and slot decoding. The acoustic model is pre-trained in two stages: initialization with a corpus of normal speech and finetuning on a mixture of dysarthric and normal speech. By introducing the intelligibility score as a metric of the impairment severity, this paper quantitatively analyzes the relation between generalization and pathology severity for dysarthric speech.
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition
Authors: Jicheng Zhang, Yizhou Peng, Pham Van Tung, HaiHua Xu, Hao Huang, Eng Siong Chng
Date: 2021-06-15 00:00:00
Tasks: Multi-Task Learning, speech-recognition, Speech Recognition

In this paper, we propose a single multi-task learning framework to perform End-to-End (E2E) speech recognition (ASR) and accent recognition (AR) simultaneously. The proposed framework is not only more compact but can also yield comparable or even better results than standalone systems. Specifically, we found that the overall performance is predominantly determined by the ASR task, and the E2E-based ASR pretraining is essential to achieve improved performance, particularly for the AR task. Additionally, we conduct several analyses of the proposed method. First, though the objective loss for the AR task is much smaller compared with its counterpart of ASR task, a smaller weighting factor with the AR task in the joint objective function is necessary to yield better results for each task. Second, we found that sharing only a few layers of the encoder yields better AR results than sharing the overall encoder. Experimentally, the proposed method produces WER results close to the best standalone E2E ASR ones, while it achieves 7.7% and 4.2% relative improvement over standalone and single-task-based joint recognition methods on test set for accent recognition respectively.
An adaptive Lagrange multiplier determination method for rate-distortion optimisation in hybrid video codecs
Authors: Fan Zhang, David R. Bull
Date: 2021-06-15 00:00:00
Tasks: Video Compression

This paper describes an adaptive Lagrange multiplier determination method for rate-quality optimisation in video compression. Inspired by the experimental results of a Lagrange multiplier selection test, the presented approach adaptively estimates the optimum Lagrange multiplier for different video content, based on distortion statistics of recently encoded frames. The proposed algorithm has been fully integrated into both the H.264 and HEVC reference codecs, and is used in rate-distortion optimisation for encoding B frames. The results show promising (up to 11% on the sequences tested) overall bitrate savings, for a minimal increase in complexity, on various types of test content based on Bjontegaard delta measurements.
Quality assessment methods for perceptual video compression
Authors: Fan Zhang, David R. Bull
Date: 2021-06-15 00:00:00
Tasks: Video Compression

This paper describes a quality assessment model for perceptual video compression applications (PVM), which stimulates visual masking and distortion-artefact perception using an adaptive combination of noticeable distortions and blurring artefacts. The method shows significant improvement over existing quality metrics based on the VQEG database, and provides compatibility with in-loop rate-quality optimisation for next generation video codecs due to its latency and complexity attributes. Performance comparison are validated against a range of different distortion types.
Physical Layer Security Framework for Optical Non-Terrestrial Networks
Authors: Olfa Ben Yahia, Eylem Erdogan, Gunes Karabulut Kurt, Ibrahim Altunbas, Halim Yanikomeroglu
Date: 2021-06-15 00:00:00

In this work, we propose a new physical layer security framework for optical space networks. More precisely, we consider two practical eavesdropping scenarios: free-space optical (FSO) eavesdropping in the space and FSO eavesdropping in the air. In the former, we assume that a high altitude platform station (HAPS) is trying to capture the confidential information from the low earth orbit (LEO) satellite, whereas in the latter, an unmanned aerial vehicle (UAV) eavesdropper is trying to intercept the confidential information from the HAPS node. To quantify the overall performance of both scenarios, we obtain closed-form secrecy outage probability (SOP) and probability of positive secrecy capacity (PPSC) expressions and validate with Monte Carlo simulations. Furthermore, we provide important design guidelines that can be helpful in the design of secure non-terrestrial networks.
On the Use of HAPS to Increase Secrecy Performance in Satellite Networks
Authors: Olfa Ben Yahia, Eylem Erdogan, Gunes Karabulut Kurt
Date: 2021-06-15 00:00:00

In this paper, we investigate the secrecy performance of radio frequency (RF) eavesdropping for a high altitude platform station (HAPS) aided satellite communication (SatCom) system. More precisely, we propose a new SatCom scheme where a HAPS node is used as an intermediate relay to transmit the satellite's signal to the ground station (GS). In this network, free-space optical (FSO) communication is adopted between HAPS and satellite, whereas RF communication is used between HAPS and GS as the line-of-sight (LoS) communication cannot be established. To quantify the overall secrecy performance of the proposed scheme, closed-form secrecy outage probability (SOP) and the probability of positive secrecy capacity (PPSC) expressions are derived. Moreover, we investigate the effect of pointing error and shadowing severity parameters. Finally, design guidelines that can be useful in the design of practical SatCom networks are presented.
Over-the-Air Equalization with Reconfigurable Intelligent Surfaces
Authors: Emre Arslan, Ibrahim Yildirim, Fatih Kilinc, Ertugrul Basar
Date: 2021-06-15 00:00:00

Reconfigurable intelligent surface (RIS)-empowered communications is on the rise and is a promising technology envisioned to aid in 6G and beyond wireless communication networks. RISs can manipulate impinging waves through their electromagnetic elements enabling some sort of control over the wireless channel. In this paper, the potential of RIS technology is explored to perform a sort of virtual equalization over-the-air for frequency-selective channels whereas, equalization is generally conducted at either the transmitter or receiver in conventional communication systems. Specifically, with the aid of an RIS, the frequency-selective channel from the transmitter to the RIS is transformed to a frequency-flat channel through elimination of inter-symbol interference (ISI) components at the receiver. ISI is eliminated by adjusting the phases of impinging signals particularly to maximize the incoming signal of the strongest tap. First, a general end-to-end system model is provided and a continuous to discrete-time signal model is presented. Subsequently, a probabilistic analysis for the elimination of ISI terms is conducted and reinforced with computer simulations. Furthermore, a theoretical error probability analysis is performed along with computer simulations. It is analyzed and demonstrated that conventional RIS phase alignment methods, can successfully eliminate ISI and the RIS-aided communication channel can be converted from frequency-selective to frequency-flat.
Massive Wireless Energy Transfer with Statistical CSI Beamforming
Authors: Francisco A. Monteiro, Onel L. A. López, Hirley Alves
Date: 2021-06-15 00:00:00
Tasks: Fairness

Wireless energy transfer (WET) is a promising solution to enable massive machine-type communications (mMTC) with low-complexity and low-powered wireless devices. Given the energy restrictions of the devices, instant channel state information at the transmitter (CSIT) is not expected to be available in practical WET-enabled mMTC. However, because it is common that the terminals appear spatially clustered, some degree of spatial correlation between their channels to the base station (BS) is expected to occur. The paper considers a massive antenna array at the BS for WET that only has access to i) the first and second order statistics of the Rician channel component of the multiple-input multiple-output (MIMO) channel and also to ii) the line-of-sight MIMO component. The optimal precoding scheme that maximizes the total energy available to the single-antenna devices is derived considering a continuous alphabet for the precoders, permitting any modulated or deterministic waveform. This may lead to some devices in the clusters being assigned a low fraction of the total available power in the cluster, creating a rather uneven situation among them. Consequently, a fairness criterion is introduced, imposing a minimum amount of power allocated to the terminals. A piece-wise linear harvesting circuit is considered at the terminals, with both saturation and a minimum sensitivity, and a constrained version of the precoder is also proposed by solving a non-linear programming problem. A paramount benefit of the constrained precoder is the encompassment of fairness in the power allocation to the different clusters. Moreover, given the polynomial complexity increase of the proposed unconstrained precoder, and the observed linear gain of the system's available sum-power with an increasing number of antennas at the ULA, the use of massive antenna arrays is desirable.
An Alternative Statistical Characterization of TWDP Fading Model
Authors: A. Maric, P. Njemcevic, E. Kaljic
Date: 2021-06-15 00:00:00

Two-wave with diffuse power (TWDP) is one of the most promising models for description of small-scale fading effects in emerging wireless networks. However, its current statistical characterization has several fundamental issues. Primarily, conventional TWDP parameterization is not in accordance with the model's underlying physical mechanisms. In addition, available TWDP expressions for PDF, CDF, and MGF are given either in integral or approximate forms, or as mathematically untractable closed-form expressions. Consequently, the existing TWDP statistical characterization does not allow accurate evaluation of system performance (such as error and outage probability) in all fading conditions for most modulation and diversity techniques. In this paper, the existing statistical characterization of the TWDP fading model is improved by overcoming some of the noticed issues. In this regard, physically justified TWDP parameterization is proposed and used for further calculations. Additionally, exact infinite-series PDF and CDF are introduced. Based on these expressions, the exact MGF of the SNR is derived in form suitable for mathematical manipulations. The applicability of the proposed MGF for derivation of the exact average symbol error probability (ASEP) is demonstrated with the example of M-ary PSK modulation. Therefore, in this paper, M-ary PSK ASEP is derived as an explicit expression for the first time in the literature. The derived expression is further simplified for large SNR values in order to obtain a closed-form asymptotic ASEP, which is shown to be applicable for SNR > 20 dB. All proposed expressions are verified by Monte Carlo simulation in a variety of TWDP fading conditions.