In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct Estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound Estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

This study aimed to estimate the genetic parameters of body weight traits in Markhoz goats, using B-spline random regression models. The data used in this study included 19549 records collected during 29 years (1992-2021) in Markhoz goat Breeding Research Station, located in Sanandaj, Iran. The model used to analyze data included fixed effects (year of birth, sex, type of birth and age of dam) and random effects including direct additive genetic, maternal additive genetic, permanent environmental and maternal permanent environmental assuming homogeneous and heterogeneous residual variance during the time. Akaike (BIC) and Bayesian (BIC) information criteria were used to compare the models and bspq.4.4.4.4 was selected as the best model. The direct heritability values for birth, 3-month, 6-month, 9-month and 12-month weights were estimated to be 0.14, 0.16, 0.08, 0.28 and 0.26, respectively. Genetic correlation between body weights at birth and 3-month, birth and 6-month, birth and 9-month, birth and 12-month, 3-month and 6-month, 3-month and 9-month, 3-month and 12-month, 6-months and 9-month and 9-month and 12-month were 0.22, 0.38, 0.21, 0.56, -0.26, 0.30, 0.62, 0.86 and 0.77, respectively. The highest phenotypic correlation was between the weight of 9-month and 12-month (0.82) and the lowest correlation was between birth weight and 3-month and 6-month (0.12). The results showed that the 9-month weight is a good criterion for selection in Markhoz goats.

Background and Aim: At present, there are various methods for performing diagnostic tests. Due to the fact that saliva is easily available compared to other body fluids, it can be collected from patients in a noninvasive way and there is no risk of cross-infection because of it, so its use has become more common. Also, the analysis of substances in saliva can be a reflection of a person's oral and systemic conditions. Despite its advantages as a diagnostic fluid, the lack of sufficient information about the methods of collecting and storing samples prevents the repeated use of saliva. In this article, it has been tried to collect the most standard methods of saliva collection, required conditions and supplies, and how to maintain, and provide them to users. Material and Methods: In this review article, data were collected by searching articles which were published between year 2000 and 2020 in domestic and foreign journals, using databases such as: PubMed, PubMed Central, Medline, EBSCO, Google Scholar and Embase with keywords: Saliva, Dry Mouth, Xerostomia, Salivary Determination and Saliva Estimation. Among the relevant authorities, the articles that were cited many times and were more up-to-date, were selected. Conclusion: It seems like using saliva in modern diagnostic tests, makes the diagnosis of many diseases easier, faster and more accurate. The standard methods of saliva collection in this article can be used as a guide for laboratory-clinical researchs by researchers.

Introduction The two-parameter Burr type XII (Burr(, ,, )) distribution has been proposed as a lifetime model and a model in accelerated life test data representing times to breakdown of an insulating fluid. A classical method for estimating the parameter of interest is based on sample information, for example, calculating the maximum likelihood estimator (MLE). A Bayesian approach to a statistical problem requires defining a prior distribution over the parameter space and loss function. Many Bayesians believe that just one prior can be elicited. In practice, the prior knowledge is vague, and any produced prior distribution is only an approximation to the true one. Various solutions to this problem, such as robust Bayesian Estimation, have been proposed. Another method is E-Bayesian Estimation, introduced by Han (١, ٩, ٩, ٧, ), obtained by the expectation of a Bayes estimate of the unknown parameter over the hyperparameters. Material and Methods Suppose that n devices are placed on test simultaneously, and the test will finish immediately after r components have failed. r is fixed, and the length of the experiment is a random variable. This is a type-II censoring type, and data consisting of the r smallest lifetimes are x = (x1, : : :, xr). In some Estimation problems, using an unbounded loss function may be inappropriate. For example, in estimating the mean life of the components of an aircraft, the amount of loss for estimating the parameter by an estimator is essentially bounded. We consider the Burr type XII model and obtain the Bayesian and E-Bayesian Estimation of ,using censored data under a reflected gamma loss function. The uniqueness of this study comes from the fact that, thus far, no attempt has been made to use the E-Bayesian method for Estimation in the Burr type XII model under the reflected gamma loss function. The method of E-Bayesian Estimation is based on the expectation of Bayesian Estimation over the hyperparameters of the prior distribution. The properties of EBayesian Estimations and asymptotic relations are computed. A simulation study is conducted for comparison of the performances of proposed estimators. Results and Discussion A simulation study is performed to compare the proposed estimators. The samples are generated from the Burr(1,0: 1) distribution for selected values of n, and censored samples are obtained using some selected values of r. The Bayesian and E-Bayesian Estimations are computed for selected values of c,u and v. The estimated bias and risks are calculated for repeated 10000 times. It is observed from the simulation study that the performances of E-Bayesian estimates improve by increasing n (and r). Moreover, the estimator ^ , EB3 has the most minor estimated bias and risk and therefore, it is proposed for Estimation of , .

In non-coherent Direction Of Arrival (DOA) Estimation, the goal is to determine DOA based only on the magnitude of the received sensor array signal. The advantage of the non-coherent DOA Estimation is its robustness against phase errors; despite phase errors present in both sensors and phase shifters, direction of arrival can be estimated. In this paper, DOA is estimated using a frequency Estimation technique which can be simply implemented by discrete Fast Fourier Transform (FFT) methods. In addition, for removing the ambiguity and solving the nonlinear equations, a reference target with high power emission is used. Simulation results, in both linear and plane array cases show the efficiency and robustness of the proposed algorithm against phase errors.

In this paper optimization of frequency offset Estimation technique based on channel Estimation, which is desirable for frequency selective channels and hasfast convergence speed, for using in HF channel is addressed. Because of time variations coherence time in HF channel is short, which leads to a severe degradation in the performance of above technique in this channel. An optimization of said technique is proposed in which after removing coarse frequency offset Estimation and knowing residual frequency offset range, incorrect Estimations can be removed and others can be averaged to give final correct estimate. Simulation is conducted underchannel parameters with respect to MIL-STD-188-110B. the results show that proposed optimization result in improved performance of frequency offset Estimation technique based on channel Estimation.

Time-Delay-Estimation (TDE) has been a topic of interest in many applications in the past few decades. The emphasis of this work is on the application of model-based Estimation (MBE) for TDE of ultrasonic signals used in ultrasonic thickness gaging. Ultrasonic thickness gaging is based on precise measurement of the time difference between successive echoes which reflect back from the back wall of the test piece. The received echoes are modeled by Gaussian pulses and the desired system response is estimated using Gauss-Newton and Space Alternating Generalized Expectation Maximization (SAGE) algorithms. In addition to the model-based Estimation approach, five other TDE techniques including peak-to-peak measurement, cross-correlation, cross-correlation with interpolation, phase-slope, and cross-correlation with Wiener filtering are also considered and compared with the SAGE. The main advantage of the SAGE algorithm, in addition to its higher accuracy, is its ability to deconvolve the overlapping echoes.