One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Water absorbent polymers (WAP) are new component in producing building materials. They provide internal curing which reduces autogenous cracking, eliminates autogenous shrinkage, mortar strength increased, enhance early age strength to withstand strain, improve the durability, introduce higher early age compressive strength, have higher performance and reduce the effect of insufficient external curing. This research used different percent of polymer balls to choose the percent that provides good development in compressive strength with time for both water and air curing. The water absorption polymer balls in this research have the ability to absorb water and after usage in concrete they spill out the water (internal curing) and shri

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

Seventy of Klebsiella pneumoniae isolates had been collected from some Hospitals in Baghdad city from October to December 2017. The 70 isolates were taken from diverse clinical specimens. All K. pneumoniae isolates were identified based on API 20 E and Vitek2 compact system. Antibiotics sensitivity test was carried out toward 10 antibiotics using discs diffusion method. The level of antibiotics resistance was 81.42% for Ceftriaxone, whereas the low level of antibiotics resistance was 37.14% for Piperacillin. K. pneumoniae isolates were typed genotypically by using two different methods of amplification, multiplex-PCR and enterobacterial repetitive intergenic consensus (ERIC)-PCR typing methods. Results showed that out of 70 isolates, there

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie