A simple, accurate and sensitive spectrophotometric method for the determination of Procaine penicillin (PP) is described. The method is based on charge-transfer reaction of PP with metol (N-methyl-p-hydroxy aniline) in the presence of ferric sulphate to form a purple-water soluble complex ,which is stable and has a maximum absorption at 510 nm .A graph of absorbance versus concentration shows that Beer’s low is obeyed over the concentration range of 3-80 µg /ml of PP (i.e.,3-80 ppm) with a molar absorbativity of 4.945 ×103 L.mol-1.cm-1 ,Sandell sensitivity of 0.1190 µg cm-2 ,a relative error of (-1.57)-2.79 % and a standard deviation of less than 0.59 depending on the concentration of PP.The optimum conditions for full co

The knowledge related with lexical items can be realized as including relations of meaning a cross words. Words that share a similarity of meaning are called to be synonymous, and words that share a contrary of meaning are called to be antonymous. Both of them are universal linguistic phenomenon that exist in terms of linguistic system of every language. The present study aims at finding out areas of difficulty that Iraqi EFL learners encounter in the use of synonymy and antonymy, both on the recognition and production levels. Also tries to detect the main reasons behind such difficulties. A diagnostic test of two parts, namely, recognition and production, is designed. The test is built to include two linguistic phenomenon which are: synony

Meloxicam (MLX) is non-steroidal anti -inflammatory, poorly water soluble, highly permeable drug and the rate of its oral absorption is often controlled by the dissolution rate in the gastrointestinal tract. Solid dispersion (SD) is an effective technique for enhancing the solubility and dissolution rate of such drug.

    The present study aims to enhance the solubility and the dissolution rate of MLX by SD technique by solvent evaporation method using sodium alginate (SA), hyaluronic acid (HA), collagen and xyloglucan (XG) as gastro-protective hydrophilic natural polymers.

Twelve formulas were prepared in different drug: polymer ratios and evaluated for their, percentage yield, drug content,  water so

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from