Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

Pseudomonas aeruginosa is the most common opportunistic pathogen causing morbidity and mortality in hospitalized patients due to its multiple resistance mechanisms. Therefore, as a therapeutic option becomes restricted, the search for a new agent is a preference. So P. aeruginosa is an extremely versatile Gram-negative bacterium capable of thriving in a broad spectrum of environments, and this performs main problems to workers in the field of health. One hundred and fifty samples were collected from different sources from Baghdad hospitals, divided into two main groups: clinical (100) specimens and (50) samples as an environmental, collected from October 2019 to the March 2020. All of these samples were cultured by specific and differential

Corrosion inhibiting admixtures are unique among other methods to protect reinforced concrete from corrosion damage. In this study, the effect of furfural on the fresh and hardened properties of concrete mixes of 35 and 45 MPa compressive strengths as well as the corrosion inhibition of furfural was evaluated. Furfural was added at different dosages (1, 2 and 3% by weight of cement) with and without superplasticizer (HRWR). Different electrochemical measurements were performed (Half-cell potential, Tafel plot and linear polarization resistance). Electrochemical measurements confirmed that furfural dramatically reduces the rate of corrosion; the inhibition efficiencies were 62.7 and 63.8 % due to 3% furfural addition to 35 and 45MPa-concr

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

Background: The Apgar score is calculated based on the five features: heart rate, reflexes, color, muscle tone, and respiratory effort. Each element is scored from 0 to 2, with a total probable score of 10 at 1 minute and 5 minute. Aim: To study the influence of gestational diabetes mellitus (GDM) and diabetes mellitus on APGAR score in neonate. Materials and methods: The samples were studied from Department of Obstetrics and Gynaecology in Al-Imamain Al-Kadhimiyain (AS) Medical city, Baghdad Teaching Hospital and Al-Karkh Maternity Hospital in the period between 1 December 2016 and 1 may 2017, after obtaining the approval from Iraqi Ministry of Health. A total of 102 neonates were included in this study which includes 34 neonates of mother

The development of new building materials, able of absorbing more energy is an active research area. Engineering Cementitious Composite (ECC) is a class of super-elastic fiberreinforced cement composites characterized by high ductility and tight crack width control. The use of bendable concrete produced from Portland Limestone Cement (PLC) may lead to an interest in new concrete mixes. Impact results of bendable concrete reinforced with steel mesh and polymer fibers will provide data for the use of this concrete in areas subject to impact loading. The experimental part consisted of compressive strength and impact resistance tests along with a result comparison with unreinforced concrete. Concrete samples, with dimensions of 100×

Abstract

Stainless steel (AISI 304) has good electrical and thermal conductivities, good corrosion resistance at ambient temperature, apart from these it is cheap and abundantly available; but has good mechanical properties such as hardness. To improve the  hardness and corrosion resistance of stainless steel its surface can be modified by developing nanocomposite coatings applied on its surface. The main objective of this paper is to study effect of electroco-deposition method on microhardness and corrosion resistance of stainless steel, and to analyze effect of nanoparticles (Al₂O₃, ZrO₂ , and SiC)  on properties of composite coatings. I