An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Objectives: The aim of the study was, to assess the nurse's role regarding cardiovascular drug
administration in Erbil city.
Methodology: A descriptive survey was conducted in Hawler teaching and Rizgari teaching Hospitals. The
number of samples is 50 nurses; the period of the study was started from 15th of November 2008 up to
the end of March 2009. A questionnaire was developed by investigators based on extensive review of
available studies and literatures. Data were collected through application of observational check list
consist of two part, part one was demographic sheet and part two about nurse’s responsibility regarding
medication administration which include (before, during, after drug administration). Data

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

According to so many previous studies, lack of sufficient information during prescribing steps may lead to medication errors. Thus, the presence of the clinical pharmacist during routine rounding process in the ward with intervention of patient care plan may reduce the probability of adverse drug events (ADEs).This study evaluate role of the clinical pharmacists, as a member of medical team with the physician, on ADEs and report their interventions in the internal medicine unit. This study was designed to compare between two groups of patients, those receiving care from a rounding team (physician, nurse, and clinical pharmacist) (study or intervention group with 51 patient); and those receiving c

Background: The use of antiepileptic drugs (AEDs) during pregnancy warrants several side effects and also deleterious effects on fetal development, the antiepileptic drugs have potential to affect the fetal development throughout the pregnancy although, the majority of infants born to epileptic pregnant women are normal but more expose to the malformations. Aim: The present study aimed to investigate the effect of carbamazepine drug on the kidney development at day 7 postnatally in the Albino Rat (Rattus rattus) as a mammalian model. Material & Methods: 20 healthy pregnant female rats were divided into two groups, 10 pregnant rats in each group; group one served as control group administrated distal water while group two used as experimenta