This research explores the themes of identity and alienation in Tsitsi Dangarembga's famous novel, Nervous Conditions, through Kimberlé Crenshaw's intersectionality theory. The story takes place in postcolonial Zimbabwe and delivers a fascinating illustration of the intersecting domains of gender, race, class, and colonial legacies that shape the characters' experiences of identity and alienation. Benefitting from Crenshaw's intersectional paradigm, this article explores the multidimensional interface of societal categorizations and power relations in the novel, revealing the complex dynamics of individuals as they negotiate their identities in a postcolonial context. Through a thorough examination of Tambudzai's journey and the problems o
... Show MoreIn this work, an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.
In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.
This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreRecently, many materials have shown that they can be used as alternatives to chemicals materials in order to be used to improve the properties of drilling fluids. Some of these materials are banana peels and corn cobs which both are considered environmentally- friendly materials. The results of the X-ray diffraction examination have proved that the main components of these materials are cellulose and hemicellulose, which contribute greatly to the increasing of the effectiveness of these two materials. Due to their distinct composition, these two materials have improved the rheological properties (plastic viscosity and yield point) and reduced the filtration of the drilling fluids to a large extent. The addition rates used for each o
... Show MoreA Destructive Parenthood : The Problematic Motherhood in Selected Poems by Salvia Plath
The CuInSe2 (CIS) nanocrystals are synthesized by arrested precipitation from molecular precursors are added to a hot solvent with organic cap- ping ligands to control nanocrystal formation and growth. CIS thin films deposited onto glass substrate by spray - coating, then selenized in Ar- atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as -deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illumination. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CIS have the chalcopyrite structure as the major phase with a preferred orientation along (112) direction and the atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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