Automated measurement of quasar redshift with a Gaussian process

ABSTRACT We develop an automated technique to measure quasar redshifts in the Baryon Oscillation Spectroscopic Survey of the Sloan Digital Sky Survey (SDSS). Our technique is an extension of an earlier Gaussian process method for detecting damped Lyman α absorbers (DLAs) in quasar spectra with known redshifts. We apply this technique to a subsample of SDSS DR12 with BAL quasars removed and redshift larger than 2.15. We show that we are broadly competitive to existing quasar redshift estimators, disagreeing with the PCA redshift by more than 0.5 in only $0.38{{\ \rm per\ cent}}$ of spectra. Our method produces a probabilistic density function for the quasar redshift, allowing quasar redshift uncertainty to be propagated to downstream users. We apply this method to detecting DLAs, accounting in a Bayesian fashion for redshift uncertainty. Compared to our earlier method with a known quasar redshift, we have a moderate decrease in our ability to detect DLAs, predominantly in the noisiest spectra. The area under curve drops from 0.96 to 0.91. Our code is publicly available.

Spatio-Temporal Change Detection Using Granger Sequence Pattern

This paper proposed a method to detect changes in causal relations over a multi-dimensional sequence of events. Cluster Sequence Mining algorithm was modified to extract causal relations in the form of g-patterns: a pair of clusters of events that have their occurrence time determined by Granger causality. This paper also proposed the pattern time signature, a probabilistic density function of the cluster sequence occurring at any given time. Synthetic data were used for validation. The result shows that the proposed algorithm can correctly identify the changes in causal relations even under noisy data.

A P- and S-Wave Picking Technique Based on the Probabilistic Density Function of Seismic-Waveform Amplitude

ABSTRACT Picking of P and S waves is a fundamental process in seismology, and various kinds of picking techniques have been developed. Seismic waveforms change dramatically depending on the magnitude, the mechanism of the earthquake, and the positional relationship between the hypocenter and the seismic station. The availability of various picking techniques is supposed to be helpful for appropriately dealing with a variety of seismic records. Hence, in addition to the revision of conventional techniques, the development of new picking techniques is worthwhile. In the present study, we developed a new stochastic technique to detect P and S waves based on the statistical amplitude distribution in the seismic record amplitude. In the proposed method, the probabilistic density function (PDF) of the amplitude is calculated for each segment of seismic records, and the similarity between the PDF of the amplitude and that of the Rayleigh or Gaussian distribution is evaluated by divergence. Because Rayleigh and Gaussian distributions are typically found in amplitude distributions of highly random waves, such as coda waves, the divergence indicates the randomness of the seismic records. P and S waves are found by tracing the temporal change of the divergence. We tested the proposed method using local seismic records for a series of seismic events that occurred before and after the 2016 Kumamoto earthquake. The mean absolute errors for picking P and S waves are 2.72×10−2 and 7.38×10−2 s, respectively. The proposed method is a simple and new statistical picking method that enables automatic detection of P- and S-wave arrivals.

Residual Life Predication of Reinforced Concrete Elements Based on Time-Varying Reliability

Scientific prediction the residual life of existing reinforced concrete elements is an important basis for assessment the structures. The resistance probabilistic density function of reinforced concrete elements was proposed by analyzing the random processes of resistance attenuation of concrete and steel bars. Since the factors of concrete durability damaged and materials deterioration , considered practical conditions of service structures and durability failure criteria of concrete members, a method of calculation the residual life was given, which is verified reasonable through the engineering case.

Formulation of the membership function and determination of the input of fuzzy loads in the structural fuzzy analyzing problem

The fuzzy analyzing process consists of different steps. In this paper, the author considers only the method for formulation of the membership function of fuzzy loads acting on the structure. Based on the membership function of fuzzy loads, the combinations of deterministic of the regression analyzing process will be determined. The membership function of fuzzy loads is selected by the triangular membership function. It is in conformity with the concept on selection of loads in the design standards. The combination of inputs for the analyzing process will be determined, based on the number of present times of the value of input parameters (including the deterministic parameters, fuzzy parameters and the random ones) in the schema of analysis. The number of present times of input parameters is either proportional to value of the corresponding membership function or to the value of the probabilistic density function. A method for determining the appropriate combination of deterministic inputs so that each input parameter will present only one time in each combination is proposed. To illustrate the proposed method, an example on the determination of input combinations of tornado's velocity in Vietnam is presented.