In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection criteria, as- sessing the correct detection of zero coefficients and the false omission of nonzero coef- ficients. A practical application involving financial data from the Baghdad Soft Drinks Company demonstrates their utility in identifying key predictors of stock market value. The results indicate that MAVE-SCAD performs well in high-dimensional and complex scenarios, whereas MAVE-ALASSO is better suited to small samples, producing more parsimonious models. These results highlight the effectiveness of these two methods in addressing key challenges in semiparametric modeling
The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P
... Show MoreIntrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system
... Show MoreIn this paper, new approach based on coupled Laplace transformation with decomposition method is proposed to solve type of partial differential equation. Then it’s used to find the accurate solution for heat equation with initial conditions. Four examples introduced to illustrate the accuracy, efficiency of suggested method. The practical results show the importance of suggested method for solve differential equations with high accuracy and easy implemented.
Materials recycling has a significant economic and environmental impact; as a result, steel, aluminium, plastic, and other recyclable materials have been pushed for use in construction materials. One of these recyclable materials is the crumb rubber, has been considered as a pavement component. The general behaviour of the composite rubber-hot mix asphalt system would be varied from that of the conventional rubber free mix. In this review, desirable characteristics of hot mix asphalt are highlighted first. Also, effect of gradation and the main types of rubber are specified. Afterward, many studies that considered the crumb rubber as a waste product and its associated mixture and modifiers are reviewed. The factors affect the crumb
... Show MoreThis research is devoted to investigating the thermal buckling analysis behaviour of laminated composite plates subjected to uniform and non-uniform temperature fields by applying an analytical model based on a refined plate theory (RPT) with five unknown independent variables. The theory accounts for the parabolic distribution of the transverse shear strains through the plate thickness and satisfies the zero-traction boundary condition on the surface without using shear correction factors; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by using the virtual work principle and solved via Navier-type analytical procedure to obtain critica
... Show MoreAmong the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
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