A laboratory study of directional spectra with maximum likelihood method─I Developing wind wave

From measurements by a circular array consisting of 18 wave gauges in a large wave tank, directional spectra of wind-generated waves in deep water are systematically determined by using maximum likehood method.The investigations reveal that the angular spreading of the wave energy is consistent with cos2s(θ/2) proposed by Longuet-Higgins et al. (1963, Ocean Wad Spectra,11~136), if the bimodal distributions of wave energy are not taken into account. Bimodality occurring on higher frequency than peak frequency is too rare to affect our whole results. Surprisingly, a much broader directional spreading than that of the field, which is interpreted by the strongly nonlinear energy transfer because of the very young waves in laboratory, is found. The parameter s depends on frequency in the same way as observed by Mitsuyasu et al. (1975, Journal of Physical Oceanography, 5, 750~760)and Hasselmann et al. (1980, Journal of physical Oceanography, 10, 1264~1280) in the field, and the relationship between the four nondimensional parameters sm, fo, b1 and b2, determining the directional width, and (corresponding to the inverse of wave age) are given respectively. The observed distributions are found to agree well with the suggestion of Donelan et al. (1985, Philosophical Transaction of Royal Society of London, A315, 509~562) when applied to field waves.

A laboratory study of directional spectrawith maximum likelihood mehod─ⅡDecaying swell

From measurements by a circular array consisting of 18 wave gauges in a large wave tank, directional spectra of swell in deep water are systematically investigated with maximum likelihood method. It is shown that the directional spreading of swell, qualitatively similar to that of developing wind wave which is narrowest in the region of Peak frequency and bxoadens with increasing or decreasing frequency, can be effectively described by cos2s(θ/2) introduced by Longuet-Higgins et al. (1963,Ocean Wave Spectra, 111~136). It is intriguing that bimodal distribution found in our experiments appers at the forward face instead of the rear face of a frequency spectrum in the cases of nonlinearity being very weak. Parameterized by nonlinearity, formulations which can be applied to swell as well as wind wave are proposed. It is concluded that nonlinear interaction plays a central role in controlling the development of directional angular spreading even for the swell.

Maximum likelihood spectrum estimation method and its application in seismo－magnet－icrelation

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ON THE TESTING FOR ALPHA-STABLE DISTRIBUTIONS OF ETHERNET NETWORK TRAFFIC

The modeling of network traffic is important for the design and application of networks, but little is known as to the characteristics of distribution of packets in network traffic. In this letter the distribution of packets in network traffic is explored.

Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors

Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.

A Maximum Likelihood Method for Estimating Probabilistic Strain Amplitude-Fatigue Life Curves

The fatigue lives of materials and structures at different strain levels show het- eroscedasticity. In addition when the number of test specimens is insufficient, the fatigue strength coefficient and fatigue ductility coefficient of the fitting parameters in the total strain life equa- tion may not have definite physical significance. In this work, a maximum likelihood method for estimating probabilistic strain amplitude fatigue life curves is presented based on the fatigue lives at different strain levels. The proposed method is based on the general basic assumption that the logarithm of fatigue life at an arbitrary strain level is normally distributed. The rela- tionship among the parameters of total strain life equation, monotonic ultimate tensile stress and percentage reduction of area is adopted. The presented approach is finally illustrated by two applications. It is shown that probabilistic strain amplitude-fatigue life curves can be eas- ily estimated based on the maximum likelihood method. The results show that fatigue lives at different strain levels have heteroscedasticity and the values of fatigue strength coefficient and fatigue ductility coefficient obtained by the proposed method are close to those of the true tensile fracture stress and true tensile fracture strain.

A Comparative Study of Supervised Classification Methods for Investigating Landslide Evolution in the Mianyuan River Basin,China

The Ms8.0 Wenchuan earthquake of 2008 dramatically changed the terrain surface and caused long-term increases in the scale and frequency of landslides and debris flows.The changing trend of landslides in the earthquake-affected area over the decade since the earthquake remains largely unknown.In this study,we were able to address this issue using supervised classification methods and multitemporal remote sensing images to study landslide evolution in the worst-affected area(Mianyuan River Basin)over a period of ten years.Satellite images were processed using the maximum likelihood method and random forest algorithm to automatically map landslide occurrence from 2007 to 2018.The principal findings are as follows:(1)when compared with visual image analysis,the random forest algorithm had a good average accuracy rate of 87%for landslide identification;(2)postevent landslide occurrence has generally decreased with time,but heavy monsoonal seasons have caused temporary spikes in activity;and(3)the postearthquake landslide activity in the Mianyuan River Basin can be divided into a strong activity period(2008 to 2011),medium activity period(2012 to 2016),and weak activity period(post 2017).Landslide activity remains above the prequake level,with damaging events being rare but continuing to occur.Long-term remote sensing and on-site monitoring are required to understand the evolution of landslide activity after strong earthquakes.

AN ALGORITHM FOR MAXIMUM LIKELIHOOD ESTIMATES TO SEMI-PARAMETRIC REGRESSION MODEL WITH INTERVAL CENSORED DATA

In this paper we study the practical procedure for getting the maximumlikelihood estimates in a semi-parametric regression model with interval censored data.On the basis of the on previous theoretical results, we give the detailed algorithms when there are one or two covariates in the model.

Determining capacity of multimodal multi-commodities freight transportation network from critical link volumes

The commodity transportation capacity between all origin-destination （ OD ） pairs over the multimodal multi-commodities freight transportation network （MMFTN） is determined. A multi-ob- jectives mathematical model is formulated for determining the OD capacity over the MMFTN accord- ing to a transporting capacity matrix that increased from the reference matrixes. The corresponding incremental factor for estimating the capacity matrix is obtained via the maximal likelihood estima- tion method that samples data of differences between the estimated commodity volumes and carrying capacities of the critical links. The proposed formulations are tested by an experimental highway and railroad freight transportation network in an existing literature. The relevant results of OD capacities are displayed and applicability of the algorithm is certified.

Effects of magnitude accuracy and complete－ness data on seismic hazard parameters

This paper is aimed to solve the question that present seismic catalogs are incomplete. The authors improve the maximum likelihood method to estimate seismic hazard parameters, considering different accuracy and completeness. As an example, we calculated the seismic hazard parameters of Fen Wei Seismic Belt and South Shaanxi Region. And based on it, we use single parameter sensitivity analysis method and multi parameter sensitivity analysis method to analyse and discuss the sensitivity of parameters and the uncertainty of result.

Power Hamza Distribution with Application to Lifetime Data

In this paper, a three-parameter lifetime distribution named power Hamza distribution (PH) is proposed. The PH distribution is a useful generalization of the Hamza distribution which accommodates heavy-tailed, upside-down bathtub and J-shaped hazard rates making it more flexible than the Hamza distribution for modelling various kinds of lifetime data. A comprehensive account of the properties of this distribution is presented. The maximum likelihood estimators of the unknown model parameters are discussed. Finally, a real-life data is analyzed for illustrative purpose proving that the PH outperforms the Hamza distribution and several other lifetime distributions.

Iwueze’s Distribution and Its Application

Increased usage of single parameter life-time distributions for reference in development of other life-time distributions and data modeling has attracted the interest of researchers. Because performance ratings differ from one distribution to another and there are increased need for distributions that delivers improved fits, new distributions with a better performance rating capable of providing improved fits have evolved in the Literature. One of such distribution is the Iwueze’s distribution. Iwueze’s distribution is proposed as a new distribution with Gamma and Exponential baseline distributions. Iwueze’s distribution theoretical density, distribution functions and statistical features such as its moments, factors of variation, skewness, kurtorsis, reliability functions, stochastic ordering, absolute deviations from average, absolute deviations from mid-point, Bonferroni and Lorenz curves, Bonferroni and Gini indexes, entropy and the stress and strength reliability have been developed. Iwueze’s distribution curve is not bell-shaped, but rather skewed positively and leptokurtic. The risk measurement function is a monotone non-decreasing function, while the average residual measurement life-time function is a monotone non-increasing function. The parameter of the Iwueze’s distribution was estimated using the likelihood estimation approach. When used for a real-life data modeling, the new proposed Iwueze’s distribution delivers improved and superior fits better than the Akshya, Shambhu, Devya, Amarendra, Aradhana, Sujatha, Akash, Rama, Shanker, Suja, Lindley, Ishita, Prakaamy, Pranav, Exponential, Ram Awadh and Odoma distributions. Iwueze’s distribution is definitely tractable and offers a better distribution than a number of well-known distributions for modeling life-time data, with greater superiority of fit performance ratings.

Link Prediction in Brain Networks Based on a Hierarchical Random Graph Model

Link prediction attempts to estimate the likelihood of the existence of links between nodes based on available brain network information, such as node attributes and observed links. In response to the problem of the poor efficiency of general link prediction methods applied to brain networks, this paper proposes a hierarchical random graph model based on maximum likelihood estimation. This algorithm uses brain network data to create a hierarchical random graph model. Then, it samples the space of all possible dendrograms using a Markov-chain Monte Carlo algorithm. Finally, it calculates the average connection probability. It also employs an evaluation index. Comparing link prediction in a brain network with link prediction in three different networks （Treponemapallidum metabolic network, terrorist networks, and grassland species food webs） using the hierarchical random graph model, experimental results show that the algorithm applied to the brain network has the highest prediction accuracy in terms of AUC scores. With the increase of network scale, AUC scores of the brain network reach 0.8 before gradually leveling off. In addition, the results show AUC scores of various algorithms computed in networks of eight different scales in 28 normal people. They show that the HRG algorithm is far better than random prediction and the ACT global index, and slightly inferior to local indexes CN and LP. Although the HRG algorithm does not produce the best results, its forecast effect is obvious, and shows good time complexity.

Adaptive Evolution of cry Genes in Bacillus thuringiensis:Implications for Their Specificity Determination

The cry gene family, produced during the late exponential phase of growth in Bacillus thuringiensis, is a large, still-growing family of homologous genes, in which each gene encodes a protein with strong specific activity against only one or a few insect species. Extensive studies are mostly focusing on the structural and functional relationships of Cry proteins, and have revealed several residues or domains that are important for the target recognition and receptor attachment. In this study, we have employed a maximum likelihood method to detect evidence of adaptive evolution in Cry proteins, and have identified 24 positively selected residues, which are all located in Domain Ⅱ or Ⅲ. Combined with known data from mutagenesis studies, the majority of these residues, at the molecular level, contribute much to the insect specificity determination. We postulate that the potential pressures driving the diversification of Cry proteins may be in an attempt to adapt for the ＂arm race＂ between δ-endotoxins and the targeted insects, or to enlarge their target spectra, hence result in the functional divergence. The sites identified to be under positive selection would provide targets for further structural and functional analyses on Cry proteins.

ESTIMATION OF DIRECTIONAL SPECTRUM AND REFLECTED COEFFICIENT OF INCIDENT AND REFLECTED WAVE IN PHASE-LOCKED WAVE FIELD

This paper analyses and compares the property of the Modified Bayesian Directional spectrum analysis Method （MBDM） and the Modified Maximum Lkelihood Method （MMLM） that can he used to estimate directional spectrum and reflected coefficient of phase-locked wave field overlapped by multi directional irregular incident and reflected waves. The numerical test verifies the results under different wave conditions, different measurement systems, and different reflection features. The computation speed and stability of the two methods is also compared. The analysis addresses that the MBDM is better than the MMLM for directional spectrum estimating, while the MMLM is better than the MBDM for reflected coefficient estimation and calculating speed and stability.