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Contrapuntal Voices of Empire: A Postcolonial Analysis of Colonial and Indigenous Narratives in Tayeb Salih's Season of Migration to the North
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This paper offers a postcolonial analysis of Sudanese author Tayeb Salih's novel Season of Migration to the North (1966), emphasizing the interplay between indigenous and colonial narratives. The analysis centers on the protagonist, Mustafa Sa'eed, who embodies its essence. The character of Mustafa Saeed represents the intricate interplay between colonial and indigenous elements. This research employs Edward Said's postcolonial concept, Contrapuntal Reading (1993), which underscores the interconnection of the histories of colonizers and the colonized through the portrayal of Mustafa Saeed's character, focusing on the mechanisms of colonial power, such as cultural hegemony, identity manipulation, and the resistance of the colonized. This study delineates two objectives: examining the dynamic power of the colonized, as exemplified by Mustafa Sa’eed's character, and investigating Mustafa Sa’eed's interactions with British women, reflecting the historical injustices endured by Sudan during the British colonial era. The way Tayeb Salih juxtaposes Western imperial ideals with Sudanese cultural tales facilitates a critique of imperialism. This method facilitates a comprehensive understanding of the interconnected history of colonialism and persistent conflicts within postcolonial identities, rendering the novel a significant examination of the psychological and cultural ramifications of colonial subjugation. The study concluded that Mustafa Sa’eed grapples with the sentiments of colonization, especially when moving to England for his education. Despite possessing dynamic strength, he is ensnared between the two spheres that hinder reconciliation. Sa’eed had a sense of dislocation between the two universes, which is evident in his interactions with European women.

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Gentiopicroside ameliorates lipopolysaccharide-induced acute kidney injury by inhibiting TLR4/NF-κB signaling in mice model
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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Wed Aug 20 2025
Journal Name
International Journal Of Advanced Research In Computer Science
IMPROVE DATA ENCRYPTION BY USING DIFFIE-HELLMAN AND DNA ALGORITHMS, AUTHENTICATED BY HMAC-HASH256
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: The need for means of transmitting data in a confidential and secure manner has become one of the most important subjects in the world of communications. Therefore, the search began for what would achieve not only the confidentiality of information sent through means of communication, but also high speed of transmission and minimal energy consumption, Thus, the encryption technology using DNA was developed which fulfills all these requirements [1]. The system proposes to achieve high protection of data sent over the Internet by applying the following objectives: 1. The message is encrypted using one of the DNA methods with a key generated by the Diffie-Hellman Ephemeral algorithm, part of this key is secret and this makes the pro

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Publication Date
Sat Nov 07 2020
Journal Name
Journal Of Advanced Research In Fluid Mechanics And Thermal Sciences
Fully Automated Measurement Setup for Photovoltaic Panel Performance Evaluation and Testing under LabVIEW Platform
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Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was

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Publication Date
Wed Jan 24 2018
Journal Name
The Journal Of Physical Chemistry C
Novel Approach for Fabricating Transparent and Conducting SWCNTs/ITO Thin Films for Optoelectronic Applications
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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Physics: Conference Series
Photodetector based on Rutile and Anatase TiO<sub>2</sub> nanostructures/n-Si Heterojunction
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Photodetector based on Rutile and Anatase TiO2 nanostructures/n-Si Heterojunction

Publication Date
Thu Nov 01 2018
Journal Name
Curtin University
Gas hydrates investigation: flow assurance for gas production and effects on hydrate-bearing sediments
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This thesis was aimed to study gas hydrates in terms of their equilibrium conditions in bulk and their effects on sedimentary rocks. The hydrate equilibrium measurements for different gas mixtures containing CH4, CO2 and N2 were determined experimentally using the PVT sapphire cell equipment. We imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via μCT. Moreover, the effect of hydrate formation on the P-wave velocities of sandstone was investigated experimentally.

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Study on Flow Characteristics and Heat Transfer Behavior Around Different Geometrical Corrugated Extended Surfaces
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Abstract

The current study presents numerical investigation of the fluid (air) flow characteristics and convection heat transfer around different corrugated surfaces geometry in the low Reynolds number region (Re<1000). The geometries are included wavy, triangle, and rectangular. The effect of different geometry parameters such as aspect ratio and number of cycles per unit length on flow field characteristics and heat transfer was estimated and compared with each other. The computerized fluid dynamics package (ANSYS 14) is used to simulate the flow field and heat transfer, solve the governing equations, and extract the results. It is found that the turbulence intensity for rectangular extended surface was larg

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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