pwc-archive/papers-with-abstracts huggingface dataset:
Intranational Skill-relevance Model of the Immigrant's Self-selection: Further Evidence of the Stylized Fact from the E-9 Employment Permit System (EPS)
Authors: Kwonhyung Lee, Yejin Lim, Sunghyun Cho
Date: 2023-06-14 00:00:00

This study expands upon the foundation of 'Skill-Relevance-Self Selection' model on labor immigration, introduced by our previous study (Lee, Lim, & Cho, 2022). In detail, we seek an empirical confirmation of the model by providing evidence of the attained -- however, yet to be tested -- stylized fact: 'as the discount of intranational skill-relevance by immigration is intensified, the wage differential of international labor immigration is diminished'. Utilizing the hypothesis and data meticulously formulated and selected in consideration of Employment Permit System (EPS) and the typology of host nations, OLS linear regression results reasonably support all hypotheses with statistical significance, thereby inductively substantiating our constructed model. This paper contributes to existing labor immigration economics literature in three following aspects: (1) Acknowledge the previously overlooked factor of 'skill relevance discount' in labor immigration as an independent parameter, separate from the 'Moving cost' of Borjas model (1987; 1991); (2) Demonstrate the down-to-earth economic implications of host nation typology, thereby establishing a taxonomy in existence, rather than an ideal classification; (3) Seek a complementary synthesis of two grand strands of research methodology -- that is, deductive mathematical modeling and inductive statistical testing.
Response toward Public Health Policy Ambiguity and Insurance Decisions
Authors: Qiang Li
Date: 2023-06-14 00:00:00

Adjustments to public health policy are common. This paper investigates the impact of COVID-19 policy ambiguity on specific groups' insurance consumption. The results show that sensitive groups' willingness to pay (WTP) for insurance is 12.2% above the benchmark. Groups that have experienced income disruptions are more likely to suffer this. This paper offers fresh perspectives on the effects of pandemic control shifts.
Scalable-Complexity Steered Response Power Mapping based on Low-Rank and Sparse Interpolation
Authors: Thomas Dietzen, Enzo De Sena, Toon van Waterschoot
Date: 2023-06-14 00:00:00

The steered response power (SRP) is a popular approach to compute a map of the acoustic scene, typically used for acoustic source localization. The SRP map is obtained as the frequency-weighted output power of a beamformer steered towards a grid of candidate locations. Due to the exhaustive search over a fine grid at all frequency bins, conventional frequency domain-based SRP (conv. FD-SRP) results in a high computational complexity. Time domain-based SRP (conv. TD-SRP) implementations reduce computational complexity at the cost of accuracy using the inverse fast Fourier transform (iFFT). In this paper, to enable a more favourable complexity-performance trade-off as compared to conv. FD-SRP and conv. TD-SRP, we consider the problem of constructing a fine SRP map over the entire search space at scalable computational cost. We propose two approaches to this problem. Expressing the conv. FD-SRP map as a matrix transform of frequency-domain GCCs, we decompose the SRP matrix into a sampling matrix and an interpolation matrix. While sampling can be implemented by the iFFT, we propose to use optimal low-rank or sparse approximations of the interpolation matrix for complexity reduction. The proposed approaches, refered to as sampling + low-rank interpolation-based SRP (SLRI-SRP) and sampling + sparse interpolation-based SRP (SSPI-SRP), are evaluated in various localization scenarios with speech as source signals and compared to the state-of-the-art. The results indicate that SSPI-SRP performs better if large array apertures are used, while SLRI-SRP performs better at small array apertures or a large number of microphones. In comparison to conv. FD-SRP, two to three orders of magnitude of complexity reduction can achieved, often times enabling a more favourable complexity-performance trade-off as compared to conv. TD-SRP. A MATLAB implementation is available online.
MCR-Data2vec 2.0: Improving Self-supervised Speech Pre-training via Model-level Consistency Regularization
Authors: Ji Won Yoon, Seok Min Kim, Nam Soo Kim
Date: 2023-06-14 00:00:00
Tasks: Self-Supervised Learning

Self-supervised learning (SSL) has shown significant progress in speech processing tasks. However, despite the intrinsic randomness in the Transformer structure, such as dropout variants and layer-drop, improving the model-level consistency remains under-explored in the speech SSL literature. To address this, we propose a new pre-training method that uses consistency regularization to improve Data2vec 2.0, the recent state-of-the-art (SOTA) SSL model. Specifically, the proposed method involves sampling two different student sub-models within the Data2vec 2.0 framework, enabling two output variants derived from a single input without additional parameters. Subsequently, we regularize the outputs from the student sub-models to be consistent and require them to predict the representation of the teacher model. Our experimental results demonstrate that the proposed approach improves the SSL model's robustness and generalization ability, resulting in SOTA results on the SUPERB benchmark.
Cognitive performance in open-plan office acoustic simulations: Effects of room acoustics and semantics but not spatial separation of sound sources
Authors: Manuj Yadav, Markus Georgi, Larissa Leist, Maria Klatte, Sabine J. Schlittmeier, Janina Fels
Date: 2023-06-13 00:00:00

The irrelevant sound effect (ISE) characterizes short-term memory performance impairment during irrelevant sounds relative to quiet. Irrelevant sound presentation in most laboratory-based ISE studies has been rather limited to represent complex scenarios including open-plan offices (OPOs) and not many studies have considered serial recall of heard information. This paper investigates ISE using an auditory-verbal serial recall task, wherein performance was evaluated for relevant factors in simulating OPO acoustics: the irrelevant sounds including the semanticity of speech, reproduction methods over headphones, and room acoustics. Results (Experiments 1 and 2) show that ISE was exhibited in most conditions with anechoic (irrelevant) nonspeech sounds with/without speech, but the effect was substantially higher with meaningful speech compared to foreign speech, suggesting a semantic effect. Performance differences in conditions with diotic and binaural reproductions were not statistically robust, suggesting limited role of spatial separation of sources. In Experiment 3, statistically robust ISE were exhibited for binaural room acoustic conditions with mid-frequency reverberation times, T30 (s) = 0.4, 0.8, 1.1, suggesting cognitive impairment regardless of sound absorption representative of OPOs. Performance differences in T30 = 0.4 s relative to T30 = 0.8 and 1.1 s conditions were statistically robust. This emphasizes the benefits for cognitive performance with increased sound absorption, reinforcing extant room acoustic design recommendations. Performance differences in T30 = 0.8 s vs. 1.1 s were not statistically robust. Collectively, these results suggest that certain findings from ISE studies with idiosyncratic acoustics may not translate well to complex OPO acoustic environments.
Geometric Wide-Angle Camera Calibration: A Review and Comparative Study
Authors: Jianzhu Huai, Yuan Zhuang, Yuxin Shao, Grzegorz Jozkow, Binliang Wang, Yijia He, Alper Yilmaz
Date: 2023-06-15 00:00:00
Tasks: Camera Calibration, Survey

Wide-angle cameras are widely used in photogrammetry and autonomous systems which rely on the accurate metric measurements derived from images. To find the geometric relationship between incoming rays and image pixels, geometric camera calibration (GCC) has been actively developed. Aiming to provide practical calibration guidelines, this work surveys the existing GCC tools and evaluates the representative ones for wide-angle cameras. The survey covers camera models, calibration targets, and algorithms used in these tools, highlighting their properties and the trends in GCC development. The evaluation compares six target-based GCC tools, namely, BabelCalib, Basalt, Camodocal, Kalibr, the MATLAB calibrator, and the OpenCV-based ROS calibrator, with simulated and real data for wide-angle cameras described by four parametric projection models. These tests reveal the strengths and weaknesses of these camera models, as well as the repeatability of these GCC tools. In view of the survey and evaluation, future research directions of wide-angle GCC are also discussed.
Dealing With Non-Gaussianity of SAR-derived Wet Surface Ratio for Flood Extent Representation Improvement
Authors: Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini, Ehouarn Simon, Raquel Rodriguez Suquet, Santiago Peña Luque
Date: 2023-06-14 00:00:00

Owing to advances in data assimilation, notably Ensemble Kalman Filter (EnKF), flood simulation and forecast capabilities have greatly improved in recent years. The motivation of the research work is to reduce comprehensively the uncertainties in the model parameters, forcing and hydraulic state, and consequently improve the overall flood reanalysis and forecast capability, especially in the floodplain. It aims at assimilating SAR-derived (typically from Sentinel-1 mission) flood extent observations, expressed in terms of wet surface ratio. The non-Gaussianity of the observation errors associated with the SAR flood observations violates a major hypothesis regarding the EnKF and jeopardizes the optimality of the filter analysis. Therefore, a special treatment of such non-Gaussianity with a Gaussian anamorphosis process is thus proposed. This strategy was validated and applied over the Garonne Marmandaise catchment (Southwest of France) represented with the TELEMAC-2D hydrodynamic model, focusing on a major flood event that occurred in December 2019. The assimilation of the SAR-derived wet surface ratio observations, in complement to the in-situ water surface elevations, is illustrated to consequentially improve the flood representation.
Waveforms for sub-THz 6G: Design Guidelines
Authors: Muris Sarajlić, Nuutti Tervo, Aarno Pärssinen, Le Hang Nguyen, Hardy Halbauer, Kilian Roth, Vaidyanathan Kumar, Tommy Svensson, Ahmad Nimr, Stephan Zeitz, Meik Dörpinghaus, Gerhard Fettweis
Date: 2023-06-15 00:00:00

The projected sub-THz (100 - 300 GHz) part of the upcoming 6G standard will require a careful design of the waveform and choice of slot structure. Not only that the design of the physical layer for 6G will be driven by ambitious system performance requirements, but also hardware limitations, specific to sub-THz frequencies, pose a fundamental design constraint for the waveform. In this contribution, general guidelines for the waveform design are given, together with a non-exhaustive list of exemplary waveforms that can be used to meet the design requirements.
Mixed-ADC Based PMCW MIMO Radar Angle-Doppler Imaging
Authors: Xiaolei Shang, Ronghao Lin, Yuanbo Cheng
Date: 2023-06-15 00:00:00
Tasks: Autonomous Driving, parameter estimation

Phase-modulated continuous-wave (PMCW) multiple-input multiple-output (MIMO) radar systems are known to possess excellent mutual interference mitigation capabilities, but require costly and power-hungry high sampling rate and high-precision analog-to-digital converters (ADC's). To reduce cost and power consumption, we consider a mixed-ADC architecture, in which most receive antenna outputs are sampled by one-bit ADC's, and only one or a few outputs by high-precision ADC's. We first derive the Cram{\'e}r-Rao bound (CRB) for the mixed-ADC based PMCW MIMO radar to characterize the best achievable performance of an unbiased target parameter estimator. The CRB analysis demonstrates that the mixed-ADC architecture with a relatively small number of high-precision ADC's and a large number of one-bit ADC's allows us to drastically reduce the hardware cost and power consumption while still maintain a high dynamic range needed for autonomous driving applications. We also introduce a two-step estimator to realize the computationally efficient maximum likelihood (ML) estimation of the target parameters. We formulate the angle-Doppler imaging problem as a sparse parameter estimation problem, and a computationally efficient majorization-minimization (MM) based estimator of sparse parameters, referred to as mLIKES, is devised for accurate angle-Doppler imaging. This is followed by using a relaxation-based approach to cyclically refine the results of mLIKES for accurate off-grid target parameter estimation. Numerical examples are provided to demonstrate the effectiveness of the proposed algorithms for angle-Doppler imaging using mixed-ADC based PMCW MIMO radar.
Code Optimization and Angle-Doppler Imaging for ST-CDM LFMCW MIMO Radar Systems
Authors: Xiaolei Shang, Yuanbo Cheng
Date: 2023-06-15 00:00:00
Tasks: parameter estimation

We consider code optimization and angle-Doppler imaging for slow-time code division multiplexing (ST-CDM) linear frequency-modulated continuous-wave (LFMCW) multiple-input multiple-output (MIMO) radar systems. We optimize the slow-time code via the minimization of a Cram{\'e}r-Rao Bound (CRB)-based metric to enhance the parameter estimation performance. Then, a computationally efficient RELAX-based algorithm is presented to obtain the maximum likelihood (ML) estimates of the target angle-Doppler parameters. Numerical examples show that the proposed approaches can be used to improve the performance of parameter estimation and angle-Doppler imaging of ST-CDM LFMCW MIMO radar systems.
Two-Way Semantic Transmission of Images without Feedback
Authors: Kaiwen Yu, Qi He, Gang Wu
Date: 2023-06-15 00:00:00
Tasks: Generative Adversarial Network, Semantic Communication

As a competitive technology for 6G, semantic communications can significantly improve transmission efficiency. However, many existing semantic communication systems require information feedback during the training coding process, resulting in a significant communication overhead. In this article, we consider a two-way semantic communication (TW-SC) system, where information feedback can be omitted by exploiting the weight reciprocity in the transceiver. Particularly, the channel simulator and semantic transceiver are implemented on both TW-SC nodes and the channel distribution is modeled by a conditional generative adversarial network. Simulation results demonstrate that the proposed TW-SC system performs closing to the state-of-the-art one-way semantic communication systems but requiring no feedback between the transceiver in the training process.
RIDNet Assisted cGAN Based Channel Estimation for One-Bit ADC mmWave MIMO Systems
Authors: Erhan Karakoca, Hasan Nayir, Ali Görçin, Khalid Qaraqe
Date: 2023-06-15 00:00:00
Tasks: Denoising, Generative Adversarial Network

The estimation of millimeter wave (mmWave) massive multiple input multiple output (MIMO) channels becomes compelling when one-bit analog to digital converters (ADCs) are utilized. Furthermore, as the number of antenna increases, pilot overhead scales up to provide consistent channel estimation, eventually degrading spectral efficiency. This study presents a channel estimation approach that combines a conditional generative adversarial network (cGAN) with a novel blind denoising network with a sparse feature attention mechanism. Performance analysis and simulations show that using a cGAN fused with a feature attention-based denoising neural network significantly enhances the channel estimation performance while requiring less pilot transmission.
Robust time-of-arrival localization via ADMM
Authors: Wenxin Xiong, Christian Schindelhauer, Hing Cheung So
Date: 2023-06-15 00:00:00

This article considers the problem of source localization (SL) using possibly unreliable time-of-arrival (TOA) based range measurements. Adopting the strategy of statistical robustification, we formulate TOA SL as minimization of a versatile loss that possesses resistance against the occurrence of outliers. We then present an alternating direction method of multipliers (ADMM) to tackle the nonconvex optimization problem in a computationally attractive iterative manner. Moreover, we prove that the solution obtained by the proposed ADMM will correspond to a Karush-Kuhn-Tucker point of the formulation when the algorithm converges, and discuss reasonable assumptions about the robust loss function under which the approach can be theoretically guaranteed to be convergent. Numerical investigations demonstrate the superiority of our method over many existing TOA SL schemes in terms of positioning accuracy and computational simplicity. In particular, the proposed ADMM achieves estimation results with mean square error performance closer to the Cram\'{e}r-Rao lower bound than its competitors in our simulations of impulsive noise environments.
Theory of Periodic Sequence: Bridging Time-Domain and Frequency-Domain for Computational Electromagnetics
Authors: Ben You, Ke wu
Date: 2023-06-14 00:00:00

Time-periodic form or expression is a ubiquitous natural and man-made phenomenon observable in all the scientific and engineering disciplines. In this article, we propose a theory of periodic sequence (TPS), which can be formulated as a foundational theory for computational sciences and engineering, to transform arbitrary time-periodic electromagnetic (EM) problems into a computational space with mapped discrete events, which is characterized in neither frequency domain nor time domain. Within the TPS framework, periodic-sequential Maxwell's curl equations are decomposed and decoupled to independent and paralleled instances via designated mappings. The fundamental solutions and mapped responses of EM periodic sequences are elucidated, and corroborated by RF/microwave measurements. The nature of outstanding computational parallelism and the unique frequency-independent property make TPS a promising methodology for computational electromagnetics such as analysis of high-speed signal integrity and broadband RF transmission.
On the Generalization and Advancement of Half-Sine-Based Pulse Shaping Filters for Constant Envelope OQPSK Modulation
Authors: Pengcheng Mu, Yan Liu, Zihao Guo, Xiaoyan Hu, Kai-Kit Wong
Date: 2023-06-14 00:00:00

The offset quadrature phase-shift keying (OQPSK) modulation is a key factor for the technique of ZigBee, which has been adopted in IEEE 802.15.4 for wireless communications of Internet of Things (IoT) and Internet of Vehicles (IoV), etc. In this paper, we propose the general conditions of pulse shaping filters (PSFs) with constant envelope (CE) property for OQPSK modulation, which can be easily leveraged to design the PSFs with CE property. Based on these conditions, we further design an advanced PSF called $\alpha$-half-sine PSF. It is verified that the newly designed $\alpha$-half-sine PSF can not only keep the CE property for OQPSK but also achieve better performance than the traditional PSFs in certain scenarios. Moreover, the $\alpha$-half-sine PSF can be simply adjusted to achieve a flexible performance tradeoff between the transition roll-off speed and out-of-band leakage.
Measurement-Based Modeling of Short Range Terahertz Channels and Their Capacity Analysis
Authors: Erhan Karakoca, Hasan Nayir, Güneş Karabulut Kurt, Ali Görçin
Date: 2023-06-14 00:00:00

In this work, extensive propagation characteristics of short range 240 to 300 GHz terahertz (THz) channels are mapped based on a measurement campaign conducted utilizing a novel, task specific measurement system. The measurement system allows collecting measurements from different distances and orientations in a very fine grained resolution, which is a particular issue in achieving realistic THz channel estimation. After the accurate measurement results are obtained, they are investigated in terms of channel impulse and channel frequency response. Furthermore, the fading channel amplitude histograms are modeled with the Gamma mixture model (GMM). The expectation-maximization (EM) algorithm is utilized to determine the corresponding mixture parameters. Also, to demonstrate the flexibility of the GMM, the Dirichlet process Gamma mixture model (DPGMM) is utilized in cases where the EM algorithm fails to represent histograms. Moreover, the suitability of the GMM is evaluated utilizing Kolmogorov Smirnov tests. Results verify that the GMMs can simulate the fading channel of micro-scale THz wireless communication in a realistic way, providing important implications regarding the achievable capacity in these channels. Finally, the average channel capacity of each link is evaluated using the probability density function of GMMs to gain deeper insight into the potential of micro-scale THz communications.
Measurement-based Channel Characterization for A2A and A2G Wireless Drone Communication Systems
Authors: Ubeydullah Erdemir, Batuhan Kaplan, İbrahim Hökelek, Ali Görçin, Hakan Ali Çırpan
Date: 2023-06-14 00:00:00

This paper presents field measurement-based channel characterization for air--to--ground (A2G) and air--to--air (A2A) wireless communication systems using two drones equipped with lightweight software-defined radios. A correlation-based channel sounder is employed such that the transmitting drone broadcasts the sounding waveform with a pseudo-noise sequence and the receiving drone captures the sounding waveform together with the location information for the post-processing analysis. The path loss results demonstrate that the measurement and flat-earth two-ray results have similar trends for A2G while the measurement and free space path loss are similar to each other for A2A. The time delays between the direct path and multipath components are widely spread for A2A while the multipath components are mostly concentrated around the direct path for A2G generating a more challenging communication environment. We observe that the reflections from several buildings having metal roofs and claddings on the measurement site cause sudden peaks in the root-mean-square delay spread. The results indicate that the A2A channel has better characteristics than the A2G under similar mobility conditions.