Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The present work investigates the effect of; superficial air velocities of: 1, 3, and 6 cm/s for two types of perforated distributor on hydrodynamic characteristic in a gas-liquid dispersion column of; air-water, and airaqueous-n-propanol solution. Bubble distribution, gas holdup, and power consumption are parameters take in consideration. Experimental work was carried out in perspex column of 8.5 cm inside diameter and 1.5 m height. Two types of bubble generator (perforated plate) were fixed at the bottom of the column; plate A (99 holes of 0.5 mm diameter and free area of 0.34%), plate B (20 holes of 1.5 mm diameter and free area of 0.62%). Photographic technique was used to measure the bubble parameters. The experimental results were

In this research PbS thin film have been prepared by chemical bath deposition technique (CBD).The PbS film with thickness of (1-1.5)μm was thermally treated at temperature of 100°C for 4 hours. Some Structural characteristics was studied by using X-ray diffraction (XRD)and optical microscope photograph some of chemical gas sensing measurements were carried out ,it shown that the sensitivity of (CO2) gas depend on the grain Size and deposition substrate. The grain size of PbS film deposited on on glass closed to 21.4 nm while 37.97nm for Si substrate. The result of current-voltage characterization shwon the sensitivity of prepared film deposited on Si better than film on glass.

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

The population has been trying to use clean energy instead of combustion. The choice was to use liquefied petroleum gas (LPG) for domestic use, especially for cooking due to its advantages as a light gas, a lower cost, and clean energy. Residential complexes are supplied with liquefied petroleum gas for each housing unit, transported by pipes from LPG tanks to the equipment. This research aims to simulate the design and performance design of the LPG system in the building that is applied to a residential complex in Baghdad taken as a study case with eight buildings. The building has 11 floors, and each floor has four apartments. The design in this study has been done in two parts, part one is the design of an LPG system for one building, an

The synthesis of new substituted cobalt Phthalocyanine (CoPc) was carried out using starting materials Naphthalene-1,4,5, tetracarbonic acid dianhydride (NDI) employing dry process method. Metal oxides (MO) alloy of (60%Ni₃O₄ 40%-Co₃O₄ ) have been functionalized with multiwall carbon nanotubes (F-MWCNTs) to produce (F-MWCNTs/MO) nanocomposite (E2) and mixed with  CoPc to yield (F-MWCNT/CoPc/MO) (E3). These composites were investigated using different analytical and spectrophotometric methods such as ¹H-NMR (0-18 ppm), FTIR spectroscopy in the range of (400-4000cm-1), powder X-rays diffraction (PXRD, 2θ ^o = 10-80), Raman spectroscopy (0-4000 cm^-1), and UV-Visib

Background: In type 2 diabetes mellitus there is a progressive loss of beta cell function. One new
approach yielding promising results is the use of the orally active dipeptidyl peptidase-4 (DPP-4)
inhibitors for type 2 diabetes mellitus.
Objective: This study aims at comparing the possible occurrence of macrovascular & microvascular
complications in Iraqis patients with type 2 diabetes mellitus using two combinations of drugs
metformin + glibenclamide and metformin + sitagliptin.
Methodology: Sixty eight T2DM patients and 34 normal healthy individuals as control group were
enrolled in this study and categorized in to two treatment groups. The group 1 (34 patients ) received
metformin 500 mg three times daily

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati