A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

The quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

We present a reliable algorithm for solving, homogeneous or inhomogeneous, nonlinear ordinary delay differential equations with initial conditions. The form of the solution is calculated as a series with easily computable components. Four examples are considered for the numerical illustrations of this method. The results reveal that the semi analytic iterative method (SAIM) is very effective, simple and very close to the exact solution demonstrate reliability and efficiency of this method for such problems.

Polyacetal was synthesized from the reaction of PVA with para-methyoxy benzaldehyde. Polymer metal complexwas prepared by reaction with Cu, polymer blend with Chitosan was prepared through the technique of solution casting method.All prepared compounds have been characterized through FT-IR, DSC, SEM as well as the Biological activity. The FT-IR results indicated the formation of polyacetal. The DSC results indicated the thermal stability regarding prepared polymer, polymermetal complex and Chitosan polymer blends. Antibacterial potential related to synthesized polyacetal, its metal complex andChitosan blend against four types of bacteria namely, Staphylococcus aureas, Psedomonas aeruginosa, Bacillus subtilis, Escherichia coli was examined a

The following dilution 5×10-1, 10-1, 10?2 , 10-3 gm/L for the indigenous isolate of Bacillus thuringiensis bacteria and the commercially isalate were used for experiments against the different stages of fig moth of E.cautella which exposed by filter paper method. The results showed that mortality of larval stages was increased with the increasing concentration of the biocide, in addition to increase in the mortality of the larval stages reached to the highest percentage in the third days of treatment of the larval stage in comparison with the first and second days of exposure. The results also showed that the sensitivity of larval stages was increased in first and second instars while reduced in the last instars .The high percentage