Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

Polymorphisms in the genes of G-protein subunit beta 3 (GNB3); rs5443, tryptophan hydroxylase 1 (TPH1); rs211105 and rs4537731, tryptophan hydroxylase 2 (TPH2); rs4570625 and sodium voltage-gated channel alpha subunit 5 (SCN5A); rs1805124, have known to cause the abnormalities in the gastrointestinal tract that are implicated to irritable bowel syndrome (IBS) predisposition. Upfront genetic polymorphism genotyping in IBS-related gene polymorphisms will help to intervene and guide the decision-making in the management of IBS patients. This study aimed to develop a genotyping method to detect the respective polymorphisms using nested allele-specific multiplex polymerase chain reaction (NASM-PCR). A combi

The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

     Recent developments in technology and the area of digital communications have rendered digital images increasingly susceptible to tampering and alteration by persons who are not authorized to do so. This may appear to be acceptable, especially if an image editing process is necessary to delete or add a particular scene that improves the quality the image. But what about images used in authorized governmental transactions? The consequences can be severe; any altered document is considered forged under the law and may cause confusion. Also, any document that cannot be verified as being authentic is regarded as a fake and cannot be used, inflicting harm on people. The suggested work intends to reduce fraud in electronic documents u

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).

          In this paper, the survival function has been estimated for the patients with lung cancer using different parametric estimation methods depending on sample for completing real data which explain the period of survival for patients who were ill with the lung cancer based on the diagnosis of disease or the entire of patients in a hospital for a time 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 estimation of the survival function for the lung cancer by using pre-test singles stage shrinkage estimator method was the best   . <

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr