Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

Autonomous systems are these systems which power themselves from the available ambient energies in addition to their duties. In the next few years, autonomous systems will pervade society and they will find their ways into different applications related to health, security, comfort and entertainment. Piezoelectric harvesters are possible energy converters which can be used to convert the available ambient vibration energy into electrical energy. In this contribution, an energy harvesting cantilever array with magnetic tuning including three piezoelectric bimorphs is investigated theoretically and experimentally. Other than harvester designs proposed before, this array is easy to manufacture and insensitive to manufacturi

High temperature superconductors with a nominal composition HgBa2Ca2Cu3O8+δ
for different values of pressure (0.2,0.3, 0.5, 0.6, 0.9, 1.0 & 1.1)GPa were prepared by
a solid state reaction method. It has been found that the samples were semiconductor
P=0.2GPa.while the behavior of the other samples are superconductor in the rang
(80-300) K. Also the transition temperature Tc=143K is the maximum at P is equal to
0.5GPa. X-ray diffraction showed a tetragonal structure with the decreasing of the
lattice constant c with the increasing of the pressure. Also we found an increasing of
the density with the pressure.

Abstract

The present investigation aimed to formulate a liquid self-microemulsifying drug delivery system (SMEDDS) of tacrolimus to enhance its oral bioavailability by improving its dispersibility and dissolution rate. Four liquid SMEDDS were prepared using maisine CC as oil phase, labrasol ALF as surfactant and transcutol HP as co-surfactant based on the solubility studies of tacrolimus in these components. The phase behavior of the components and the area of microemulsion were evaluated using pseudoternary phase diagrams. The formulations were also assessed for thermodynamic stability, robustness to dilution, self-emulsification time, drug content, globule size and polydispersity index. The prepared SMEDDS formulations exhibi

Littoral and benthic invertebrates from Roundwood Reservoir System were sampled. Oligochaetes and molluscs were the dominant organisms in the littoral and benthic areas Trichopterans and chironomids were the most abundant insect groups. Scuba diving samples reinforced that view. Other groups of macroinvertebrates were poorly represented. Vertical and horizontal hauls of zooplankton revealed that there were twelve species of zooplankton present. Daphnia hyalina Leydig and Bosmina coregoni Baird were the two dominant species.

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

This research aims to choose the appropriate  probability ‎ distribution  ‎‏‎ to the reliability‎        analysis‎ for  an   item through ‎ collected data for operating and stoppage  time of  the case  study.

    Appropriate choice for .probability distribution   is when  the data look to be on or  close the form fitting line for probability plot and test the data  for  goodness of fit .

     Minitab’s 17 software  was used ‎  for this  purpose after  arranging collected data and setting it in the the program‎.

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In this paper, a national grid-connected photovoltaic (PV) system is proposed. It extracts the maximum power point (MPP) using three-incremental-steps perturb and observe (TISP&O) maximum power point tracking (MPPT) method. It improves the classic P&O by using three incremental duty ratio (ΔD) instead of a single one in the conventional P and O MPPT method. Therefore, the system's performance is improved to a higher speed and less power fluctuation around the MPP. The Boost converter controls the MPPT and then is connected to a three-phase voltage source inverter (VSI). This type of inverter needs a high and constant input voltage. A second-order low pass (LC) filter is connected to the output of VSI to reduce t