The present study combines UV-Vis spectrophotometry and dispersive liquid-liquid microextraction (DLLME) for the preconcentration and determination of trace level clidinium bromide (Clid) in pharmaceutical preparation and real samples. The method is based on ion-pair formation between Clid and bromocresol green in aqueous solution using citrate buffer (pH = 3). The colored product was first extracted using a mixture of 800 µL acetonitrile and 300 µL chloroform solvents. Then, a spectrophotometric measurement of sediment phase was performed at λ = 420 nm. The important parameters affecting the efficiency of DLLME were optimized. Under the optimum conditions, the calibration graphs of standard -1 (Std.), drug, urine and serum were ranged

Some new cyclic imides are prepared by the reaction of ampicillin drug with different cyclic anhydrides as a first step to form amic acids for ampicillin drug. The second step includes the reaction of prepared amic acids with acetic anhydride and anhydrous sodium acetate with heating in THF as a solvent to give cyclic imide compounds. These compounds are identified by melting points, FT-IR, 1H-NMR, and biological activity

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve