Automatic event detection from time series signals has wide applications, such as abnormal event detection in video surveillance and event detection in geophysical data. Traditional detection methods detect events primarily by the use of similarity and correlation in data. Those methods can be inefficient and yield low accuracy. In recent years, because of the significantly increased computatio...

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general a...

This paper reviews selected recent innovations that expand the range of applicability of a number of new and emerging structural steel systems that can provide effective seismic performance. Focus is on recent developments on: (a) Steel Plate Shear Walls having light gauge infill plates; (b) Perforated Steel Plate Shear Walls; (c) Buckling Restrained Braced frames designed to meet Structural Fu...

Seismic sensors collect massive quantities of data that contain a wealth of information about processes within the earth. Seismologists are increasingly adopting data mining and machine learning techniques to identify previously unknown earthquakes in large seismic data sets. Our new earthquake detection method, Fingerprint and Similarity Thresholding (FAST), enables waveform-similarity-based e...

Hilbert–Huang transform (HHT) is a popular method to analyze nonlinear and non-stationary data. It has been widely used in geophysical prospecting. This paper analyzes the mode mixing problems of empirical mode decomposition (EMD) and introduces the noncontact measurement and detection of instantaneous seismic attributes using complementary ensemble empirical mode decomposition (CEEMD). Numeric...

Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

This study presents a plan for seismic monitoring of a region around a potential nuclear power plant. Seismic monitoring is needed to evaluate seismic risk. The International Atomic Energy Agency has set guidelines on seismic hazard evaluation and monitoring of such areas. According to these guidelines, we have made a plan for a local network of seismic stations to collect data for seismic sour...

In recent years, human interference in seismic-station environments has posed challenges to the quality and accuracy of seismic signals, making data processing difficult. To accurately identify caused by personnel ensure reliability seismic-network instrument detection data, it is necessary track detected targets across consecutive frames. Deep neural networks have made significant progress thi...

The damage of buildings and manmade structures, where most of human activities occur, is the major cause of casualties of from earthquakes. In this paper, an improved technique, Earthquake Damage Visualization (EDV) is presented for the rapid detection of earthquake damage using the Synthetic Aperture Radar (SAR) data. The EDV is based on the pre-seismic and co-seismic coherence change method. ...

Many subterranean mammals are reported to generate or respond to seismic vibrations. Potential uses of seismic sensitivity in these animals include intraspecific communication between burrow systems, location of prey, detection of predators and even “seismic echolocation” of distant obstacles. Although the auditory and/or somatosensory systems have been variously implicated, the mechanisms used...