Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.

KOV = 3.3 * 10^-10

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Diabetes mellitus type 2 (T2DM) is a chronic and progressive condition, which affects people all around the world. The risk of complications increases with age if the disease is not managed properly. Diabetic neuropathy is caused by excessive blood glucose and lipid levels, resulting in nerve damage. Apelin is a peptide hormone that is found in different human organs, including the central nervous system and adipose tissue. The aim of this study is to estimate Apelin levels in diabetes type 2 and Diabetic peripheral Neuropathy (DPN) Iraqi patients and show the extent of peripheral nerve damage. The current study included 120 participants: 40 patients with Diabetes Mellitus, 40 patients with Diabetic peripheral Neuropathy, and 40 healthy

This study examines patterns of exposure of Iraqi university students to selective daily Iraqi newspapers and the motives of this exposure, as well as its associated factors that affect the average exposure. It tries to answer several questions, including those related to the levels of exposure of Iraqi university students to daily Iraqi newspapers and classification of patterns of selective exposure to daily Iraqi newspapers and the most prominent Iraqi daily newspapers that are selectively exposed by Iraqi university students. It also examines the motives of this selective exposure and factors that increase the degree of exposure to the daily Iraqi newspapers, and the most prominent stages in which Iraqi university students find their

Groundwater is an essential source because of its high quality and continuous availability characterize this water resource. Therefore, the study of groundwater has required more attention. The present study aims to assess and manage groundwater quality's suitability for various purposes through the Geographical Information System GIS and the Water Quality Index WQI. The study area is located in the city of Baghdad in central Iraq, with an approximate area of ​​900 , data were collected from the relevant official departments representing the locations of 97 wells of groundwater in the study area for the year 2019, as it included physicochemical parameters such as  pH, EC, TDS, Na, K, Mg, Ca, Cl,  , and &nbs

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and