Frequency-dependent AVO attribute: theory and example

Fluid-saturated rocks generally have seismic velocities that depend upon frequency. Exploring this property may help us discriminate different fluids from seismic data. In this paper, we introduce a scheme to calculate a frequency-dependent AVO attribute in order to estimate seismic dispersion from pre-stack data, and apply it to North Sea data. The scheme essentially combines the two-term approximation of Smith and Gidlow (1987) with the method of spectral decomposition based on the Wigner-Ville distribution, which is used to achieve high resolution. The result suggests the potential of this method for detection of seismic dispersion due to fluid saturation

STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

In this work, we propose a novel Spatial-Temporal Attention (STA) approach to tackle the large-scale person re-identification task in videos. Different from the most existing methods, which simply compute representations of video clips using frame-level aggregation (e.g. average pooling), the proposed STA adopts a more effective way for producing robust clip-level feature representation. Concretely, our STA fully exploits those discriminative parts of one target person in both spatial and temporal dimensions, which results in a 2-D attention score matrix via inter-frame regularization to measure the importances of spatial parts across different frames. Thus, a more robust clip-level feature representation can be generated according to a weighted sum operation guided by the mined 2-D attention score matrix. In this way, the challenging cases for video-based person re-identification such as pose variation and partial occlusion can be well tackled by the STA. We conduct extensive experiments on two large-scale benchmarks, i.e. MARS and DukeMTMC-VideoReID. In particular, the mAP reaches 87.7% on MARS, which significantly outperforms the state-of-the-arts with a large margin of more than 11.6%.Comment: Accepted as a conference paper at AAAI 201

Urban biodiversity conservation planning integrating the analysis of green space structure and functional connection

The process of urbanization and population growth lead to the fragmentation of biological habitat and the loss of biodiversity. It is of great significance to use effective models and indicators to evaluate landscape connectivity and construct green space network for habitat restoration and biodiversity conservation. Taking Fengtai District of Beijing as an example, firstly, the optimal distance threshold of green space construction suitable for biological migration is discussed by using the connectivity index based on graph theory, and the source patches are selected according to the evaluation results of landscape connectivity. Secondly, the resistance surface is constructed by using the minimum cost path model, and the potential connection path of species migration is determined by Linkage Mapper tool. Finally, according to the relative importance of patch and corridor in the quantitative source of current density, the “pinch” area, which is very important to species migration, is identified, and the model recognition results are compared with the empirical observation results of remote sensing satellite map and bird abundance. The results showed that the ecological base of green space in the western part of the study area was good, which provided the main habitat for species, and the patch fragmentation of green space in the central and eastern regions was serious, so it was necessary to increase urban green space as a stepping stone for species migration in pinch areas. The circuit model focusing on species diffusion is introduced in the study, which makes up for the lack of urban green space network construction method at the level of biodiversity conservation, clarifies the present situation of habitat quality and the future development of green space network in Fengtai District of Beijing, and provides scientific reference for the optimization of regional green space pattern and biodiversity conservation planning strategy

Hopf bifurcation and stability analysis of flexible rotor-bearing system

Analytical model of a long bearing was used to study the self-excited vibration of a single disc flexible rotor-bearing system on sliding bearing support. A shooting method was applied to track and acquire periodic solution of flexible rotor system after the Hopf bifurcation. Stability of periodic solution was analyzed on the basis of Floquet theory. Gas film eddying, oscillation and other nonlinear features were considered. High-speed air hybrid bearing test-bed was used to verify gas film oscillation arising from coupling between natural frequency and gas film eddying frequency. The “bounded” nature of chaotic vibration and the process of rubbing caused by instability of air film were observed. Finally, a distinguishing criterion named “practical stability” was provided

Estimating seismic dispersion from prestack data using frequency-dependent AVO analysis

Recent laboratory measurement studies have suggested a growing consensus that fluid saturated rocks can have frequency-dependent properties within the seismic bandwidth. It is appealing to try to use these properties for the discrimination of fluid saturation from seismic data. In this paper, we develop a frequency-dependent AVO (FAVO) attribute to measure magnitude of dispersion from pre-stack data. The scheme essentially extends the Smith and Gidlow (1987)’s two-term AVO approximation to be frequency-dependent, and then linearize the frequency-dependent approximation with Taylor series expansion. The magnitude of dispersion can be estimated with least-square inversion. A high-resolution spectral decomposition method is of vital importance during the implementation of the FAVO attribute calculation. We discuss the resolution of three typical spectral decomposition techniques: the short term Fourier transform (STFT), continuous wavelet transform (CWT) and Wigner-Vill Distribution (WVD) based methods. The smoothed pseudo Wigner-Ville Distribution (SPWVD) method, which uses smooth windows in time and frequency domain to suppress cross-terms, provides higher resolution than that of STFT and CWT. We use SPWVD in the FAVO attribute to calculate the frequency-dependent spectral amplitudes from pre-stack data. We test our attribute on forward models with different time scales and crack densities to understand wave-scatter induced dispersion at the interface between an elastic shale and a dispersive sandstone. The FAVO attribute can determine the maximum magnitude of P-wave dispersion for dispersive partial gas saturation case; higher crack density gives rise to stronger magnitude of P-wave dispersion. Finally, the FAVO attribute was applied to real seismic data from the North Sea. The result suggests the potential of this method for detection of seismic dispersion due to fluid saturation

Visual balance--the tightrope of computer generated layout

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1995.Includes bibliographical references (leaves [55]-60).by Xiaoyang Yang.M.S

Can ChatGPT reduce human financial analysts’ optimistic biases?

This paper examines the potential of ChatGPT, a large language model, as a financial advisor for listed firm performance forecasts. We focus on the constituent stocks of the China Securities Index 300 and compare ChatGPT’s forecasts for major financial performance measures with human analysts’ forecasts and the realised values. Our findings suggest that ChatGPT can correct the optimistic biases of human analysts. This study contributes to the literature by exploring the potential of ChatGPT as a financial advisor and demonstrating its role in reducing human biases in financial decision-making