New Criterion for Lunar Crescent Visibility

A new criterion for lunar crescent visibility has been established using 737 observations, almost half of them obtained by the Islamic Crescent Observation Project (ICOP). This criterion is based on two variables, viz. the topocentric arc of vision and the topocentric crescent width. The new model is able to predict the visibility of the lunar crescent both for naked eye and optically aided observations. From the database we found a Danjon limit of 6.4 degrees. Vice-President of “Crescents, Calendars and Mawaqeet Committee” of AUASS.     

Investigation of SVM and Level Set Interactive Methods for Road Extraction from Google Earth Images

Currently, methods of extracting spatial information from satellite images are mainly based on visual interpretations and drawing the consequences by human factor, which is both costly and time consuming. A large volume of data collected by satellite sensors, and significant improvement in spatial and spectral resolution of these images require the development of new methods for optimal use of these data in order to produce rapid economic and updating road maps. In this study, a new automatic method is proposed for road extraction by integrating the SVM and Level Set methods. The estimated probability of classification by SVM is used as input in Level Set Method. The average of completeness, correctness, and quality was 84.19, 88.69 and 76.06% respectively indicate high performance of proposed method for road extraction from Google Earth images.     

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and <Emphasis Type="Italic">t</Emphasis>-distributed deviations

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.     

A new empirical equation for predicting the maximum initial amplitude of submarine landslide-generated waves

Landslides - The accurate prediction of landslide tsunami amplitudes has been a challenging task given large uncertainties associated with landslide parameters and often the lack of enough...     

Uncertainty quantification of landslide runout motion considering soil interdependent anisotropy and fabric orientation

Landslides - Natural soils often exhibit an anisotropic fabric pattern as a result of soil deposition, weathering, or filling. This paper aims to investigate the effect of soil interdependent...     

A probabilistic framework to make a decision on the post-earthquake functionality of bridges considering the damage,residual displacement,and aftershock

Bulletin of Earthquake Engineering - Making a decision on the post-earthquake functionality of structures has always been one of the most challenging issues in earthquake engineering. There is an...     

Reliability framework for characterizing heat wave and cold spell events

Natural Hazards - Extreme weather events such as heat waves and cold spells affect people’s lives. This study develops a probabilistic framework to evaluate heat waves and cold spells. As...