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 cri

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The fluctuation and expansion ratios have been studied for cylindrical gas-solid fluidized columns by using air as fluidizing medium and Paracetamol as the bed material. The variables were the column diameter (0.0762, 0.15, and 0.18 m), static bed height (0.05, 0.07, and 0.09 m), and air velocity to several times of minimum fluidization velocity. The results showed that both the fluctuation and expansion ratios had a direct relation with air velocity and an inverse one with column diameter and static bed height. A good agreement was between the experimental results and the calculated values by using the correlation equations from the literature.

In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.