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

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

A new derivatives of Schiff bases connected with 5H-thiazolo[3,4-b][1,3,4]thiadiazole ring 5a-c were prepared via many reactions starting by treating 1,4-phenylene diamine 1 with chloroacetylchloride to prepared compound 2, then reaction with p-hydroxybenzaldehyde to synthesize compound 3 then, this was reacted with thioglycolic acid and thiosemicarazide to giveN,N-(1.4-phenylene)bis(2-(4-(2-amino-5Hthiazolo[4,3-b][1,3,4]thiadiazol-5-yl)phenoxy)acetamide) 4. Compound 4 was treated with different aromatic aldehydes to give a new derivatives of Schiff bases containing 5H-thiazolo[3,4-b][1,3,4]thiadiazole ring 5a-c. The synthesized compounds were characterized using FTIR spectrophotometer and 1H NMR spectroscopy and the biological activity of

The mass attenuation coefficient for beta particles through pure Polyvinyl chloride (PVC) and flax fibers- reinforced PVC composite were investigated as a function of the absorber thickness and the absorber to source distance. The beta particles mass attenuation coefficients were obtained using a NaI(Tl) energy selective scintillation counter with 90Sr/ 90Y beta source having an energy range from (0.546-2.275) MeV. Pure PVC polymer samples were prepared by compacting the PVC powder in a mould at high pressure (10bar) and temperature about 140°C for 30 minutes. A hot press system was used for this process. The experimentally obtained values of mass attenuation coefficients for 90Sr and 90Y were found to be 7.72 cm2.g-1and 0.842 cm2.g-1 r

The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depen

          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

Since the time it emerged, stylistics, as a field of knowledge which ‎combines both linguistics and literature, acquired a special status in the ‎linguistic arena. Its significance in complementing the meaning ‎delivered by linguistic means has been proven and acknowledged ‎through numerous stylistic analytic attempts of different literary works ‎and in different languages. The question put forward in this paper is ‎whether or not the stylistic analysis can work as effectively on translated ‎texts as it does on the original ones without having the results reached ‎by the analysis distorting the meaning of the original text. An attempt to ‎investigate this question is made herein by conducting a lexical stylistic ‎analysi

A new class of higher derivatives  for harmonic univalent functions defined by a generalized fractional integral operator inside an open unit disk E is the aim of this paper.