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.

In this paper, a sufficient condition for stability of a system of nonlinear multi-fractional order differential equations on a finite time interval with an illustrative example, has been presented to demonstrate our result. Also, an idea to extend our result on such system on an infinite time interval is suggested.

A new laboratory study conducted on stepped spillways in order to investigate their efficiency of dissipating flow energy. All previous study on stepped spillway indicated that the flow energy dissipation decreased as increasing in discharge. Increasing in the step numbers and the spillway slope led to energy dissipation decrease. In this study, an experimental attempt to increase energy dissipation at variable discharges was performed on stepped spillway and that leads to decreasing the cost of initiating the stilling basin or may be ignoring it. Five spillways were constructed from concrete and tested to investigate and compare among them. Three were roughed by gravel with different size for each one, one of them was s

Experimental and numerical studies have been conducted for the effect of injected air bubbles on the heat transfer coefficient through the water flow in a vertical pipe under the influence of uniform heat flux. The investigated parameters were water flow rate of (10, 14 and 18) lit/min, air flow rate of (1.5, 3 and 4) lit/min for subjected heat fluxes of (27264, 36316 and 45398) W/m2. The energy, momentum and continuity equations were solved numerically to describe the motion of flow. Turbulence models k-ε was implemented. The mathematical model is using a CFD code Fluent (Ansys15). The water was used as continuous phase while the air was represented as dispersed. phase. The experimental work includes design, build and instrument a test

Water flow into unsaturated porous media is governed by the Richards’ partial differential equation expressing the mass conservation and Darcy’s laws. The Richards’ equation may be written in three forms,where the dependent variable is pressure head or moisture content, and the constitutive relationships between water content and pressure head allow for conversion of one form into the other. In the present paper, the “moisture-based" form of Richards’ equation is linearized by applying Kirchhoff’s transformation, which
combines the soil water diffusivity and soil water content. Then the similarity method is used to obtain the analytical solution of wetting front position. This exact solution is obtained by means of Lie’s

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization