Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia

Precipitation is a key input variable for hydrological and climate studies. Rain gauges can provide reliable precipitation measurements at a point of observations. However, the uncertainty of rain measurements increases when a rain gauge network is sparse. Satellite-based precipitation estimations SPEs appear to be an alternative source of measurements for regions with limited rain gauges. However, the systematic bias from satellite precipitation estimation should be estimated and adjusted. In this study, a method of removing the bias from the precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping of gauge and satellite measurements over several climate zones as well as inverse-weighted distance for the interpolation of gauge measurements. Seven years (2010–2016) of daily precipitation estimation from PERSIANN-CCS was used to test and adjust the bias of estimation over Saudi Arabia. The first 6 years (2010–2015) are used for calibration, while 1 year (2016) is used for validation. The results show that the mean yearly bias is reduced by 90%, and the yearly root mean square error is reduced by 68% during the validation year. The experimental results confirm that the proposed method can effectively adjust the bias of satellite-based precipitation estimations

How do microorganisms reach the stratosphere?

A number of studies have demonstrated that bacteria and fungi are present in the stratosphere. Since the tropopause is generally regarded as a barrier to the upward movement of particles it is difficult to see how such microorganisms can reach heights above 17 km. Volcanoes provide an obvious means by which this could be achieved, but these occur infrequently and any microorganisms entering the stratosphere from this source will rapidly fall out of the stratosphere. Here, we suggest mechanisms by which microorganisms might reach the stratosphere on a more regular basis; such mechanisms are, however, likely only to explain how micrometre to submicrometre particles could be elevated into the stratosphere. Intriguingly, clumps of bacteria of size in excess of 10 μm have been found in stratospheric samples. It is difficult to understand how such clumps could be ejected from the Earth to this height, suggesting that such bacterial masses may be incoming to Earth. We suggest that the stratospheric microflora is made up of two components: (a) a mixed population of bacteria and fungi derived from Earth, which can occasionally be cultured; and (b) a population made up of clumps of, viable but non-culturable, bacteria which are too large to have originated from Earth; these, we suggest, have arrived in the stratosphere from space. Finally, we speculate on the possibility that the transfer of bacteria from the Earth to the highly mutagenic stratosphere may have played a role in bacterial evolution

Coupled plasmon - phonon excitations in extrinsic monolayer graphene

The existence of an acoustic plasmon in extrinsic (doped or gated) monolayer graphene was found recently in an {\it ab initio} calculation with the frozen lattice [M. Pisarra {\it et al.}, arXiv:1306.6273, 2013]. By the {\em fully dynamic} density-functional perturbation theory approach, we demonstrate a strong coupling of the acoustic plasmonic mode to lattice vibrations. Thereby, the acoustic plasmon in graphene does not exist as an isolated excitation, but it is rather bound into a combined plasmon-phonon mode. We show that the coupling provides a mechanism for the {\em bidirectional} energy exchange between the electronic and the ionic subsystems with fundamentally, as well as practically, important implications for the lattice cooling and heating by electrons in graphene.Comment: 5 pages, 4 figure

E-commerce development risk evaluation using MCDM techniques

© Springer International Publishing Switzerland 2016. Electronic commerce (EC) development takes place in a complex and dynamic environment that includes high levels of risk and uncertainty. This paper proposes a new method for assessing the risks associated with EC development using multi-criteria decision-making techniques A model based on the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to assist EC project managers and decision makers in formalizing the types of thinking that are required in assessing the current risk environment of their EC development in a more systematic manner than previously. The solution includes the use of AHP for analyzing the problem structure and determining the weights of risk factors. The TOPSIS technique helps to obtain a final ranking among projects, and the results of an evaluation show the usefulness performance of the method

Backbending phenomena in light nuclei at A~60 mass region

Recent studies of the backbending phenomenon in medium light weight nuclei near A~60 expanded greatly our interest about how the single particle orbits are nonlinearly affected by the collective motion. As a consequence we have applied a modi…ed version of the exponential model with the inclusion of paring correlation to describe the energy spectra of the ground state bands and/or the backbending phenomenon in mass region at A~60. A firm conclusion is obtained concerning the successful validity of the proposed modified model in describing the backbending phenomenon in this region. Comparison with different theoretical descriptions is discussed.Comment: 4 pages, 1 figure

KACST Arabic Text Classification Project: Overview and Preliminary Results

Electronically formatted Arabic free-texts can be found in abundance these days on the World Wide Web, often linked to commercial enterprises and/or government organizations. Vast tracts of knowledge and relations lie hidden within these texts, knowledge that can be exploited once the correct intelligent tools have been identified and applied. For example, text mining may help with text classification and categorization. Text classification aims to automatically assign text to a predefined category based on identifiable linguistic features. Such a process has different useful applications including, but not restricted to, E-Mail spam detection, web pages content filtering, and automatic message routing. In this paper an overview of King Abdulaziz City for Science and Technology (KACST) Arabic Text Classification Project will be illustrated along with some preliminary results. This project will contribute to the better understanding and elaboration of Arabic text classification techniques

An adaptive moving mesh method for two-dimensional thin film flow equations with surface tension

In this paper, we extend our previous work [A. Alharbi and S. Naire, An adaptive moving mesh method for thin film flow equations with surface tension, J. Computational and Applied Mathematics, 319 (2017), pp. 365-384.] on a one-dimensional r-adaptive moving mesh technique based on a mesh density function and moving mesh partial differential equations (MMPDEs) to two dimensions. As a test problem, we consider the gravitydriven thin film flow down an inclined and pre-wetted plane including surface tension and a moving contact line. This technique accurately captures and resolves the moving contact line and associated fingering instability. Moreover, the computational effort is hugely reduced in comparison to a fixed uniform mesh