pwc-archive/papers-with-abstracts huggingface dataset:
Multi-time Predictions of Wildfire Grid Map using Remote Sensing Local Data
Authors: Hyung-Jin Yoon, Petros Voulgaris
Date: 2022-09-15 00:00:00
Tasks: Management, Time Series, Time Series Analysis

Due to recent climate changes, we have seen more frequent and severe wildfires in the United States. Predicting wildfires is critical for natural disaster prevention and mitigation. Advances in technologies in data processing and communication enabled us to access remote sensing data. With the remote sensing data, valuable spatiotemporal statistical models can be created and used for resource management practices. This paper proposes a distributed learning framework that shares local data collected in ten locations in the western USA throughout the local agents. The local agents aim to predict wildfire grid maps one, two, three, and four weeks in advance while online processing the remote sensing data stream. The proposed model has distinct features that address the characteristic need in prediction evaluations, including dynamic online estimation and time-series modeling. Local fire event triggers are not isolated between locations, and there are confounding factors when local data is analyzed due to incomplete state observations. Compared to existing approaches that do not account for incomplete state observation within wildfire time-series data, on average, we can achieve higher prediction performance.
The fallacy of herd immunity
Authors: Carlos Hernandez-Suarez
Date: 2022-09-19 00:00:00

Here we show that herd immunity is not a measure we can implement, trust, control or depend on, and that waiting for herd immunity to play a role is tantamount to hope for the best. Herd immunity is not some protection, as it has been referred to, but a reduction in the chance of infection that a population can achieve only if more infections occur, which is paradoxical. The discussion on when there will be enough herd immunity for the COVID-19 epidemics to halt, delivers the public and policy makers the wrong message that we can wait for something to happen to relax containment measures. Here we review a non-orthodox construction of an epidemic that unveils what herd immunity really means, that is easy to understand by non-experts.
Efficient Integrated Volatility Estimation in the Presence of Infinite Variation Jumps via Debiased Truncated Realized Variations
Authors: B. Cooper Boniece, José E. Figueroa-López, Yuchen Han
Date: 2022-09-21 00:00:00

Statistical inference for stochastic processes based on high-frequency observations has been an active research area for more than two decades. One of the most well-known and widely studied problems has been the estimation of the quadratic variation of the continuous component of an It\^o semimartingale with jumps. Several rate- and variance-efficient estimators have been proposed in the literature when the jump component is of bounded variation. However, to date, very few methods can deal with jumps of unbounded variation. By developing new high-order expansions of the truncated moments of a locally stable L\'evy process, we propose a new rate- and variance-efficient volatility estimator for a class of It\^o semimartingales whose jumps behave locally like those of a stable L\'evy process with Blumenthal-Getoor index $Y\in (1,8/5)$ (hence, of unbounded variation). The proposed method is based on a two-step debiasing procedure for the truncated realized quadratic variation of the process and can also cover the case $Y<1$. Our Monte Carlo experiments indicate that the method outperforms other efficient alternatives in the literature in the setting covered by our theoretical framework.
A French Connection? Recognition and Entente for the Taliban
Authors: Mandeep Singh Rai Misty Wyatt, Sydney Farrar, Kristina Alabado
Date: 2022-09-21 00:00:00

This paper will explore a way forward for French-Afghan relations post United Nations (U.N.) occupation. The summer of 2021 proved to be very tumultuous as the Taliban lay in waiting for U.N. forces to withdraw in what many would call a hasty, poorly thought-out egress operation. The Taliban effectively retook all major cities, including the capital, Kabul, and found themselves isolated as U.N. states closed embassies and severed diplomatic relations. Now, Afghanistan finds itself without international aid and support and on the verge of an economic crisis. France now has the opportunity to initiate a leadership role in the establishment and recovery of the new Afghan government.
International institutions and power politics in the context of Chinese Belt and Road Initiative
Authors: Mandeep Singh Rai
Date: 2022-09-21 00:00:00
Tasks: Position

The subject of international institutions and power politics continues to occupy a central position in the field of International Relations and to the world politics. It revolves around key questions on how rising states, regional powers and small states leverage international institutions for achieving social, political, economic gains for themselves. Taking into account one of the rising powers China and the role of international institutions in the contemporary international politics, this paper aims to demonstrate, how in pursuit of power politics, various states (Small, Regional and Great powers) utilise international institutions by making them adapt to the new power realities critical to world politics.
Powering Europe with North Sea Offshore Wind: The Impact of Hydrogen Investments on Grid Infrastructure and Power Prices
Authors: Goran Durakovic, Pedro Crespo del Granado, Asgeir Tomasgard
Date: 2022-09-21 00:00:00

Hydrogen will be a central cross-sectoral energy carrier in the decarbonization of the European energy system. This paper investigates how a large-scale deployment of green hydrogen production affects the investments in transmission and generation towards 2060, analyzes the North Sea area with the main offshore wind projects, and assesses the development of an offshore energy hub. Results indicate that the hydrogen deployment has a tremendous impact on the grid development in Europe and in the North Sea. Findings indicate that total power generation capacity increases around 50%. The offshore energy hub acts mainly as a power transmission asset, leads to a reduction in total generation capacity, and is central to unlock the offshore wind potential in the North Sea. The effect of hydrogen deployment on power prices is multifaceted. In regions where power prices have typically been lower than elsewhere in Europe, it is observed that hydrogen increases the power price considerably. However, as hydrogen flexibility relieves stress in high-demand periods for the grid, power prices decrease in average for some countries. This suggests that while the deployment of green hydrogen will lead to a significant increase in power demand, power prices will not necessarily experience a large increase.
Heterogeneous earning responses to inheritance: new event-study evidence from Norway
Authors: Xiaoguang Ling
Date: 2022-09-21 00:00:00

It has long been assumed that inheritances, particularly large ones, have a negative effect on the labor supply of inheritors. Using Norwegian registry data, I examine the inheritance-induced decline in inheritors' wages and occupational income. In contrast to prior research, my estimates allow the dynamic effect of inheritances on labor supply to vary among inheritor cohorts. The estimation approach adopted and the 25-year long panel data make it possible to trace the dynamics of the effect for at least 20 years, which is twice as long as the study period in previous studies. Since all observations in the sample are inheritors, I avoid the selection problem arising in studies employing non-inheritors as controls. I find that large parental inheritances (more than one million Norwegian kroner) reduce annual wage and occupational income by, at most, 4.3%, which is about half the decrease previously identified. The magnitude of the effect increases with the size of the inheritance. Large inheritances also increase the probability of being self-employed by more than 1%, although entrepreneurship may be dampened by inheritances that are excessively large. The inheritance effect lasts for up to 10 years and is heterogeneous across sexes and age groups. Male heirs are more likely to reduce their labor supply after receiving the transfer. Young heirs are more likely to be self-employed, and their annual occupational income is, therefore, less affected by inheritances in the long run; for the very young inheriting large amounts of wealth from their grandparents, the probability of their attaining a post-secondary education declines by 2%.
The Power of Non-Superpowers
Authors: Tomoo Kikuchi, Shuige Liu
Date: 2022-09-21 00:00:00

We propose a game-theoretic model to investigate how non-superpowers with heterogenous preferences and endowments shape the superpower competition for a sphere of influence. Two superpowers play a Stackelberg game by providing club goods. Their utility depends on non-superpowers who form coalitions to join a club in the presence of externality. The coalition formation, which depends on the characteristics of non-superpowers, influences the behavior of superpowers and thus the size of their clubs. Our data-based simulations of the subgame perfect equilbirum capture how the US-China competition depends on other countries.
Effects of Work-From-Home on University Students and Faculty
Authors: Avni Singh
Date: 2022-09-13 00:00:00

The work-from-home policy affected people of all demographics and professions, including students and faculty at universities. After the onset of the COVID-19 pandemic in 2020, institutions moved their operations online, affecting the motivation levels, communication abilities, and mental health of students and faculty around the world. This paper is based mainly on primary data collected from students from around the world, and professors at universities in Bengaluru, India. It explores the effects of work-from-home as a policy in terms of how it changed learning during the pandemic and how it has permanently altered it in a post-pandemic future. Further, it suggests and evaluates policies on how certain negative effects of the work-from-home policy can be mitigated.
GIST-AiTeR System for the Diarization Task of the 2022 VoxCeleb Speaker Recognition Challenge
Authors: Dongkeon Park, Yechan Yu, Kyeong Wan Park, Ji Won Kim, Hong Kook Kim
Date: 2022-09-21 00:00:00
Tasks: Action Detection, Activity Detection, Clustering, Speaker Recognition, Speech Enhancement

This report describes the submission system of the GIST-AiTeR team at the 2022 VoxCeleb Speaker Recognition Challenge (VoxSRC) Track 4. Our system mainly includes speech enhancement, voice activity detection , multi-scaled speaker embedding, probabilistic linear discriminant analysis-based speaker clustering, and overlapped speech detection models. We first construct four different diarization systems according to different model combinations with the best experimental efforts. Our final submission is an ensemble system of all the four systems and achieves a diarization error rate of 5.12% on the challenge evaluation set, ranked third at the diarization track of the challenge.
Matched Quality Evaluation of Temporally Downsampled Videos with Non-Integer Factors
Authors: Christian Herglotz, Geetha Ramasubbu, André Kaup
Date: 2022-09-21 00:00:00

Recent research has shown that temporal downsampling of high-frame-rate sequences can be exploited to improve the rate-distortion performance in video coding. However, until now, research only targeted downsampling factors of powers of two, which greatly restricts the potential applicability of temporal downsampling. A major reason is that traditional, objective quality metrics such as peak signal-to-noise ratio or more recent approaches, which try to mimic subjective quality, can only be evaluated between two sequences whose frame rate ratio is an integer value. To relieve this problem, we propose a quality evaluation method that allows calculating the distortion between two sequences whose frame rate ratio is fractional. The proposed method can be applied to any full-reference quality metric.
A Comparative Analysis of the Time and Energy Demand of Versatile Video Coding and High Efficiency Video Coding Reference Decoders
Authors: Matthias Kränzler, Christian Herglotz, André Kaup
Date: 2022-09-21 00:00:00
Tasks: Decoder

This paper investigates the decoding energy and decoding time demand of VTM-7.0 in relation to HM-16.20. We present the first detailed comparison of two video codecs in terms of software decoder energy consumption. The evaluation shows that the energy demand of the VTM decoder is increased significantly compared to HM and that the increase depends on the coding configuration. For the coding configuration randomaccess, we find that the decoding energy is increased by over 80% at a decoding time increase of over 70%. Furthermore, results indicate that the energy demand increases by up to 207% when Single Instruction Multiple Data (SIMD) instructions are disabled, which corresponds to the HM implementation style. By measurements, it is revealed that the coding tools MIP, AMVR, TPM, LFNST, and MTS increase the energy efficiency of the decoder. Furthermore, we propose a new coding configuration based on our analysis, which reduces the energy demand of the VTM decoder by over 17% on average.
Extending Video Decoding Energy Models for 360° and HDR Video Formats in HEVC
Authors: Matthias Kränzler, Christian Herglotz, André Kaup
Date: 2022-09-21 00:00:00
Tasks: Decoder

Research has shown that decoder energy models are helpful tools for improving the energy efficiency in video playback applications. For example, an accurate feature-based bit stream model can reduce the energy consumption of the decoding process. However, until now only sequences of the SDR video format were investigated. Therefore, this paper shows that the decoding energy of HEVC-coded bit streams can be estimated precisely for different video formats and coding bit depths. Therefore, we compare a state-of-the-art model from the literature with a proposed model. We show that bit streams of the 360{\deg}, HDR, and fisheye video format can be estimated with a mean estimation error lower than 3.88% if the setups have the same coding bit depth. Furthermore, it is shown that on average, the energy demand for the decoding of bit streams with a bit depth of 10-bit is 55% higher than with 8-bit.
Decoding Energy Modeling For Versatile Video Coding
Authors: Matthias Kränzler, Christian Herglotz, André Kaup
Date: 2022-09-21 00:00:00
Tasks: Decoder

In previous research, it was shown that the software decoding energy demand of High Efficiency Video Coding (HEVC) can be reduced by 15$\%$ by using a decoding-energy-rate-distortion optimization algorithm. To achieve this, the energy demand of the decoder has to be modeled by a bit stream feature-based model with sufficiently high accuracy. Therefore, we propose two bit stream feature-based models for the upcoming Versatile Video Coding (VVC) standard. The newly introduced models are compared with models from literature, which are used for HEVC. An evaluation of the proposed models reveals that the mean estimation error is similar to the results of the literature and yields an estimation error of 1.85% with 10-fold cross-validation.
Advanced Design Space Exploration for Joint Energy and Quality Optimization for VVC
Authors: Matthias Kränzler, Christian Herglotz, André Kaup
Date: 2022-09-21 00:00:00

In recent studies, it could be shown that the energy demand of Versatile Video Coding (VVC) decoders can be twice as high as comparable High Efficiency Video Coding (HEVC) decoders. A significant part of this increase in complexity is attributed to the usage of new coding tools. By using a design space exploration algorithm, it was shown that the energy demand of VVC-coded sequences could be reduced if different coding tool profiles were used for the encoding process. This work extends the algorithm with several optimization strategies, methodological adjustments to optimize perceptual quality, and a new minimization criterion. As a result, we significantly improve the Pareto front, and the rate-distortion and energy efficiency of the state-of-the-art design space exploration. Therefore, we show an energy demand reduction of up to 47% with less than 30% additional bit rate, or a reduction of over 35% with approximately 6% additional bit rate.
Analytic Optimization-Based Microbubble Tracking in Ultrasound Super-Resolution Microscopy
Authors: Md Ashikuzzaman, Brandon Helfield, Hassan Rivaz
Date: 2022-09-21 00:00:00
Tasks: Position, Super-Resolution

Ultrasound localization microscopy (ULM) refers to a promising medical imaging modality that systematically leverages the advantages of contrast-enhanced ultrasound (CEUS) to surpass the diffraction barrier and delineate the microvascular map. Localization and tracking of microbubbles (MBs), two significant steps of ULM, facilitate generating the vascular map and the velocity distribution, respectively. Herein, we propose a novel MB tracking technique considering temporal pairing as a bubble-set registration problem. Iterative registration is performed between the bubble sets in two consecutive time instants by analytically optimizing a cost function that takes position and point-spread function (PSF) similarities as well as physically plausible levels of bubbles' movement into account. Furthermore, we infer MBs' parity in a fuzzy manner instead of binary. The proposed technique performs well in validation experiments with two synthetic and two in vivo datasets provided by the Ultrasound Localisation and TRacking Algorithms for Super Resolution (ULTRA-SR) Challenge.
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution
Authors: Wensi Zhang, Xiaoling Zhang, Xu Zhan, Yuetonghui Xu, Jun Shi, Shunjun Wei
Date: 2022-09-21 00:00:00
Tasks: Image Restoration, Position

Images of near-field SAR contains spatial-variant sidelobes and clutter, subduing the image quality. Current image restoration methods are only suitable for small observation angle, due to their assumption of 2D spatial-invariant degradation operation. This limits its potential for large-scale objects imaging, like the aircraft. To ease this restriction, in this work an image restoration method based on the 2D spatial-variant deconvolution is proposed. First, the image degradation is seen as a complex convolution process with 2D spatial-variant operations. Then, to restore the image, the process of deconvolution is performed by cyclic coordinate descent algorithm. Experiments on simulation and measured data validate the effectiveness and superiority of the proposed method. Compared with current methods, higher precision estimation of the targets' amplitude and position is obtained.
Complicated Background Suppression of ViSAR Image For Moving Target Shadow Detection
Authors: Zhenyu Yang, Xiaoling Zhang, Xu Zhan
Date: 2022-09-21 00:00:00
Tasks: Shadow Detection

The existing Video Synthetic Aperture Radar (ViSAR) moving target shadow detection methods based on deep neural networks mostly generate numerous false alarms and missing detections, because of the foreground-background indistinguishability. To solve this problem, we propose a method to suppress complicated background of ViSAR for moving target detection. In this work, the proposed method is used to suppress background; then, we use several target detection networks to detect the moving target shadows. The experimental result shows that the proposed method can effectively suppress the interference of complicated back-ground information and improve the accuracy of moving target shadow detection in ViSAR. The existing Video Synthetic Aperture Radar (ViSAR) moving target shadow detection methods based on deep neural networks mostly generate numerous false alarms and missing detections, because of the foreground-background indistinguishability. To solve this problem, we propose a method to suppress complicated background of ViSAR for moving target detection. In this work, the proposed method is used to suppress background; then, we use several target detection networks to detect the moving target shadows. The experimental result shows that the proposed method can effectively suppress the interference of complicated back-ground information and improve the accuracy of moving target shadow detection in ViSAR.
Two Dimensional Sparse-Regularization-Based InSAR Imaging with Back-Projection Embedding
Authors: Xu Zhan, Xiaoling Zhang, Shunjun Wei, Jun Shi
Date: 2022-09-21 00:00:00
Tasks: Image Registration, Vocal Bursts Valence Prediction

Interferometric Synthetic Aperture Radar (InSAR) Imaging methods are usually based on algorithms of match-filtering type, without considering the scene's characteristic, which causes limited imaging quality. Besides, post-processing steps are inevitable, like image registration, flat-earth phase removing and phase noise filtering. To solve these problems, we propose a new InSAR imaging method. First, to enhance the imaging quality, we propose a new imaging framework base on 2D sparse regularization, where the characteristic of scene is embedded. Second, to avoid the post processing steps, we establish a new forward observation process, where the back-projection imaging method is embedded. Third, a forward and backward iterative solution method is proposed based on proximal gradient descent algorithm. Experiments on simulated and measured data reveal the effectiveness of the proposed method. Compared with the conventional method, higher quality interferogram can be obtained directly from raw echoes without post-processing. Besides, in the under-sampling situation, it's also applicable.
Efficient Non-Uniform Structured Mesh Generation Algorithm for Computational Electromagnetics
Authors: Apostolos Spanakis-Misirlis
Date: 2022-09-21 00:00:00

Despite the rapidly evolving field of computational electromagnetics, few open-source tools have managed to tackle the problem of automatic mesh generation for properly discretizing the problem of interest into a finite set of elements (cells). While several mesh generation algorithms have been established in the field of computational physics, the vast majority of such tools are targeted solely towards tetrahedral mesh formation, with the intended primary application being the finite element method. In this work, a computationally efficient non-uniform structured (rectilinear) mesh generation algorithm for electromagnetic simulations is presented. We examine the speed, performance and adaptability against previous work, and we evaluate its robustness against a complex geometry case with a commercially-generated grid. The mesh and simulation results produced using the generated grids of the proposed method are found to be in solid agreement.