Drought Assessment Based on Fused Satellite and Station Precipitation Data: An Example from the Chengbi River Basin, China

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought.

A new gamma degradation process with random effect and state-dependent measurement error

In this paper, a new gamma-based degradation process with random effect is proposed that allows to account for the presence of measurement error that depends in stochastic sense on the measured degradation level. This new model extends a perturbed gamma model recently suggested in the literature, by allowing for the presence of a unit to unit variability. As the original one, the extended model is not mathematically tractable. The main features of the proposed model are illustrated. Maximum likelihood estimation of its parameters from perturbed degradation measurements is addressed. The likelihood function is formulated. Hence, a new maximization procedure that combines a particle filter and an expectation-maximization algorithm is suggested that allows to overcome the numerical issues posed by its direct maximization. Moreover, a simple algorithm based on the same particle filter method is also described that allows to compute the cumulative distribution function of the remaining useful life and the conditional probability density function of the hidden degradation level, given the past noisy measurements. Finally, two numerical applications are developed where the model parameters are estimated from two sets of perturbed degradation measurements of carbon-film resistors and fuel cell membranes. In the first example the presence of random effect is statistically significant while in the second example it is not significant. In the applications, the presence of random effect is checked via appropriate statistical procedures. In both the examples, the influence of accounting for the presence of random effect on the estimates of the cumulative distribution function of the remaining useful life of the considered units is also discussed. Obtained results demonstrate the affordability of the proposed approach and the usefulness of the proposed model.

NONPARAMETRIC KERNEL DISTRIBUTION FUNCTION ESTIMATION NEAR ENDPOINTS

In this paper, two kernel cumulative distribution function estimators are introduced and investigated in order to improve the boundary effects, we will restrict our attention to the right boundary. The first estimator uses a self-elimination between modify theoretical Bias term and the classical kernel estimator itself. The basic technique of construction the second estimator is kind of a generalized reflection method involving reflection a transformation of the observed data. The theoretical properties of our estimators turned out that the Bias has been reduced to the second power of the bandwidth, simulation studies and two real data applications were carried out to check these phenomena and are conducted that the proposed estimators are better than the existing boundary correction methods.

AN APPROXIMATE METHOD TO PRESENT THE BUCKLING STRENGTH OF A GRILLAGE IN A PROBABILISTIC FORM

An approximate method for calculation in probabilistic terms of the buckling strength of a grillage under unidirectional in-plane compression is proposed. The geometric properties of longitudinals and transverses and the mechanical properties (yield stress and modulus of elasticity) of the material they are built from are treated as random parameters that may change over ship’s service life. The cumulative distribution function of the grillage’s critical buckling strength is calculated by using an analytical formula for multitude sets of input parameters while all of them having the same level of certainty. The assumption is that the critical buckling strength has the same (or very similar) level of certainty as that of the input parameters. The accuracy of the proposed approximate method is relatively high (the maximal error is around 2%). It is recommended for use when specialized computer programs for application of Monte Carlo simulation method are not available. The method does not require a complicated specialized computer program and can be run on EXCEL computer program.

Model Based or Model Free? Comparing Adaptive Methods for Estimating Thresholds in Neuroscience

The quantification of human perception through the study of psychometric functions Ψ is one of the pillars of experimental psychophysics. In particular, the evaluation of the threshold is at the heart of many neuroscience and cognitive psychology studies, and a wide range of adaptive procedures has been developed to improve its estimation. However, these procedures are often implicitly based on different mathematical assumptions on the psychometric function, and unfortunately, these assumptions cannot always be validated prior to data collection. This raises questions about the accuracy of the estimator produced using the different procedures. In the study we examine in this letter, we compare five adaptive procedures commonly used in psychophysics to estimate the threshold: Dichotomous Optimistic Search (DOS), Staircase, PsiMethod, Gaussian Processes, and QuestPlus. These procedures range from model-based methods, such as the PsiMethod, which relies on strong assumptions regarding the shape of Ψ, to model-free methods, such as DOS, for which assumptions are minimal. The comparisons are performed using simulations of multiple experiments, with psychometric functions of various complexity. The results show that while model-based methods perform well when Ψ is an ideal psychometric function, model-free methods rapidly outshine them when Ψ deviates from this model, as, for instance, when Ψ is a beta cumulative distribution function. Our results highlight the importance of carefully choosing the most appropriate method depending on the context.

Metode Power Control sebagai Manajemen Interferensi pada Komunikasi Device to Device

Teknologi komunikasi yang sedang berkembang saat ini sudah memasuki generasi ke-5 (5G), dengan salah satu solusi yang ditawarkan adalah komunikasi device to device (D2D). Skema yang digunakan pada makalah ini adalah cooperative D2D dengan Mobile User Equipment (MUE) yang berada jauh dari eNodeB (eNB). D2D User Equipment (DUE) berperan sebagai relay yang membantu MUE dalam meningkatkan kualitas layanan. Efek yang ditimbulkan komunikasi D2D adalah interferensi, sehingga untuk mengatasinya dilakukan metode power control. Makalah ini menggunakan tiga simulasi perbandingan, yaitu Tanpa Power Control, skema Power Control 1, dan Power Control 2. Skema yang digunakan pada Power Control 1 adalah skema fixed power control, sedangkan skema Power Control 2 menggunakan adaptive power control. Dengan menggunakan Cumulative Distribution Function (CDF), diperoleh hasil bahwa skema Power Control 1 mampu memperbaiki SINR sebesar 0,124 dB untuk downlink dan 0,0814 dB untuk uplink, sedangkan skema Power Control 2 mampu menaikkan SINR 0,0316 dB untuk downlink dan 0,0627 dB untuk uplink. Berdasarkan hasil akhir terkait SINR, throughput, dan CDF, metode Power Control 1 memiliki hasil yang lebih baik daripada metode Power Control 2.

Statistical Inference for a General Family of Modified Exponentiated Distributions

In this paper, a modified exponentiated family of distributions is introduced. The new model was built from a continuous parent cumulative distribution function and depends on a shape parameter. Its most relevant characteristics have been obtained: the probability density function, quantile function, moments, stochastic ordering, Poisson mixture with our proposal as the mixing distribution, order statistics, tail behavior and estimates of parameters. We highlight the particular model based on the classical exponential distribution, which is an alternative to the exponentiated exponential, gamma and Weibull. A simulation study and a real application are presented. It is shown that the proposed family of distributions is of interest to applied areas, such as economics, reliability and finances.