In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller

In this work, laboratory experiments were carried out to verify direct contact membrane distillation system’s performance in highly saline water desalination. The study included the investigation of various operating conditions, like feed flow rate, temperature and concentration of NaCl solution and their impact on the permeation flux were discussed. 16 cm² of a flat sheet membrane module with commercial poly-tetra-fluoroethylene (PTFE) membrane, which has 0.22 μm pore size, 96 µm thickness and 78% average porosity, was used. A high salt rejection factor was obtained greater than 99.9%, and the permeation flux up to 17.27 kg/m².h was achieved at 65°C for hot feed side and 20°C for cold side stream.

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

 In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best

In this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.

A particular solution of the two and three dimensional unsteady state thermal or mass diffusion equation is obtained by introducing a combination of variables of the form,
η = (x+y) / √ct , and η = (x+y+z) / √ct, for two and three dimensional equations
respectively. And the corresponding solutions are,
θ (t,x,y) = θ₀ erfc (x+y)/√8ct and θ( t,x,y,z) =θ₀ erfc (x+y+z/√12ct)

In this work, porous silicon (PS) are fabricated using electrochemical etching (ECE) process for p-type crystalline silicon (c-Si) wafers of (100) orientation. The structural, morphological and electrical properties of PS synthesized at etching current density of (10, 20, 30) mA/cm2 at constant etching time 10 min are studied. From X-ray diffraction (XRD) measurement, the value of FWHM is in general decreases with increasing current density for p-type porous silicon (p-PS). Atomic force microscope (AFM) showed that for p-PS the average pore diameter decreases at 20 mA. Porous silicon which formed on silicon will be a junction so I-V characteristics have been studied in the dark to calculate ideality factor (n), and saturation current (Is

This researd exhibit's a method to  determine the change in Gibbs function,(enthai py,entropy.     and     specific     heat     capacity)      tor monovariant   heterogeneous   equilibria   .The  thermodynamical quan.tities were obtained jndirectly with m the measurment  of temperature dependent on eql,lilibrium system.