An experiment was conducted in the plastic house of the Botanical Garden in the Department of Biology, College of Education for Pure Sciences (Ibn Al-Haitham), University of Baghdad during one growth season. The experiment included the study of the effect of three concentrations of citric acid (0, 75, 150) mg. L-1 and four concentrations of malic acid (0, 50, 100, 150) mg. L-1 and their interaction in some of the growth and yield parameters of the broad bean plant, plant height, dry weight, number of leaves, total chlorophyll content, the number of flowers and pods and the weight of the pod. The experiment was carried out in full random design (4× 3) and with three duplicates, the results showed a significant effect of citric and malic aci

One of the most important virulence factors in Pseudomonas aeruginosa is biofilm formation, as it works as a barrier for entering antibiotics into the bacterial cell. Different environmental and nutritional conditions were used to optimize biofilm formation using microtitre plate assay by P. aeruginosa. The low nutrient level of the medium represented by tryptic soy broth (TSB) was better in biofilm formation than the high nutrient level of the medium with Luria Broth (LB). The optimized condition for biofilm production at room temperature (25 °C) is better than at host temperature (37 °C). Moreover, the staining with 0.1% crystal violet and reading the biofilm with wavelength 360 are considered essential factors in

ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021

تعد الرماية واحدة من الألعاب التي يقاس مستوى الانجاز فيها بالأرقام إذ ارتفعت الأرقام المسجلة بالنسبة لسلاح المسدس الهوائي حتى وصلت عند بعض الأبطال العالميين إلى الانجاز النهائي ، وقد لجأ المدربون إلى مختلف الطرق التدريبية, وان ضعف الثبات والتركيز هما اللذان يقودان إلى هبوط مستوى الانجاز في الرماية ، ولتحقيق التركيز والثبات المطلوبين أثناء الرمي يجب التدريب على مطاولة حمل السلاح التي تعد من أصعب تدريبات الر

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the