In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

Objective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction.  Results: DOX and CS-Ag

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

Aims of this research to determine asbestos fibers levels in surrounding air of some crowded sites of Baghdad city were monitored in summer 2020. Collection of samples was conducted by directing air flow to a mixed cellulose ester membrane filter mounted on an open‑faced filter holder using sniffer a low flow sampling pump, samples of air were collected from five studied areas selected in some heavy traffic areas of Baghdad city, (Al-Bayaa and Al-Shurta tunnel, Al-Jadriya, and Al-Meshin commercial complex, control), then analyzed to determine concentrations of asbestos fibers. Counting of asbestos on the filters was carried out through using both scanning electron microscope SEM and an energy dispersive X‑ray system EDS to count

Asphalt pavement properties in Iraq are highly affected by elevated summer air temperatures. One of these properties is stiffness (resilient modulus). To explain the effect of air temperatures on stiffness of asphalt concrete, it is necessary to determine the distribution of temperatures through the pavement asphalt concrete layers. In this study, the distribution of pavement temperatures at three depths (2cm,7cm, 10cm) below the pavement surface is determined by using the temperature data logger instrument. A relationship for determining pavement temperature as related to depth and air temperature has been suggested. To achieve the objective of this thesis, the prepared specimens have been tested for indirect tension in accordance with

Asphalt binder is a thermoplastic material that conducts as an elastic solid at lower service temperatures or throughout fast loading rate. At a high temperature or slow rate of loading, asphalt binder conducts as a different liquid. The classical duplication generates a required to assess the mechanical properties of asphalt concrete at the anticipated service temperature to reduce the stress cracking, which happens at lower temperatures, fatigue, and the plastic deformation at higher temperatures (rutting). In this study, an achievement was made to assess the effect of temperature on the mechanical characteristics of asphalt concrete mixes. A total of 132 asphalt concrete samples were attended utilizing two asphalt cement grades (40-50) a

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin