Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

         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 p

         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 work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

Radiotherapy is medical use of ionizing radiation, and commonly applied to the cancerous tumor because of its ability to control cell growth. The amount of radiation used in photon radiation therapy called dose (measured in grey unit), which depend on the type and stage of cancer being treated. In our work, we studied the dose distribution given to the tumor at different depths (zero-20 cm) treated with different field size (4×4- 23×23 cm). Results show that the deeper treated area has less dose rate at the same beam quality and quantity. Also it has been noted increasing in the field increasing in the depth dose at the same depth even if the radiation energy is constant. Increasing in radiation dose attributed to the scattere

Numerical simulations are carried out to evaluate the coherence concept’s effect on the performance regarding the optical system, when observing and imaging the planet’s surface. In numerous optical approaches, the coherence qualities of light sources play an important role. This paper provides an overview about the mathematical formulation of temporal and spatial coherence and incoherence properties of light sources. The circular aperture was used to describe the optical system like a telescope. The simulation results show that diffraction-limited for incoherent imaging system certainly improves the image. Yet, the quality of the image is degraded by the light source's highly spatial and temporal coherence properties, resulting in a

An experimental and theoretical study has been done to investigate the thermal performance of different types of air solar collectors, In this work air solar collector with a dimensions of (120 cm x90 cm x12 cm) , was tested under climate condition of  Baghdad city with a (43° tilt angel)  by using  the absorber plate (1.45 mm thickness, 115 cm height x 84 cm width), which was manufactured from iron painted with a black matt.

The experimental test deals with five types of absorber:-

 Conventional smooth flat plate absorber , Finned absorber , Corrugated absorber plate, Iron wire mesh on absorber And matrix of porous media  on absorber .

The hourly and average efficiency of the collectors