The aim of present study was to develop solid and liquid  self-microemulsifying drug  delivery system of poorly water soluble drug mebendazole using Aerosil 200 as solid carrier.  Microemulsions are clear, stable, isotropic liquid mixtures of oil, water and surfactant, frequently in combination with a co-surfactant having droplet size range usually in the range of 20-250 nm. Oleic acid, tween 80 and polypropylene glycol were selected as oil, surfactant and co-surfactant respectively and for preparation of stable SMEDDS, micro emulsion region was identified by constructing pseudo ternary phase diagram containing different proportion of surfactant: co-surfactant (1:1, 2:1 and 3:1), oil and water. In brief S/ CoS mix means su

Abstract

The research aims to determine the role of the efficiency of Human Resources Information System in the effectiveness of Employees Performance Appraisal System in the Ministry of Higher Education and Scientific Research / Center for the ministry, it was touching the researchers need the ministry to devise methods that employ outputs Human Resources Information System in the organization surveyed for the development of methods and levels of process evaluate the performance of its employees, in order to identify the extent of the role played by human resources information system in the process of assessing the performance of employees, we raised the question of the President as follows:

Occupies total quality management applications play a key role in the development of institutions of higher education performance and achieve its strategic objectives through the commitment of senior management and their employees to continuous improvement of the quality of performance in the various areas of work, and can be integrated knowledge management processes, which means identifying information of value and how to take advantage. The data were collected using the style of the questionnaire for the purpose of analyzing their results on a sample composed of 83 member of the administrative leadership in colleges as representing the decision-making centers in those colleges . 

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Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

<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

<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

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel