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Revolutionizing Higher Education by Harnessing the Power of AI and Big Data for Sustainable Education
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The integration of Artificial Intelligence with Big Data Analytics is one of the most groundbreaking developments that could change the face of educational sustainability in higher education.. Using AI and Big Data technologies not only makes the educational process more efficient but also changes the way people learn and thus opens the door for educators and institutions to make decisions based on the data. The document imparts the manner that the use of AI and the digital revolution can remove student requirements, execute the efficiency of the curriculum, and acquire the balance of educational resources through a majority of instances and the latest developments in that field. Furthermore, the paper, along with the issues of morality with the use of technology and the problems of the tech sector, is very clear about the necessity for policies that will ensure equal access for all users of digital resources. In sum, the writer puts forward the idea of AI and Big Data as the main force behind the redesign of a new higher education system that is resilient, flexible, and capable of meeting the demands of a constantly changing world economy and thus, the wider objective of sustainable education would be achievable.

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
China's Soft Power and Diplomacy towards Middle East Region after 2011
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The study deals with China's soft power and diplomacy in the Middle East, and it focuses specifically on the tools and foundations of China's soft diplomacy and how it achieves its goals in the region in addition to its challenges in the region. In this regard, the study also focuses on the Chinese Belt and Road Initiative and its soft foundations and how they serve China’s diplomacy and soft power in the region. The study ends with a set of conclusions, perhaps the most prominent of which is that diplomacy and soft power have become a fundamental pillar of China's foreign policy to achieve its foreign goals and to establish an international system compatible with China's principles. As for the Middle East, China has established a poli

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Publication Date
Wed Oct 01 2025
Journal Name
Results In Engineering
Advances in Piezoelectric Energy Harvesting: Materials, Configurations, and Power Optimisation Strategies
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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Utilizing Load and Loss Factors in Determination of the Technical Power Losses in Distribution System’s Feeders: Case Study
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This study uses load factor and loss factor to determine the power losses of the electrical feeders. An approach is presented to calculate the power losses in the distribution system. The feeder’s technical data and daily operation recorded data are used to calculate and analyze power losses.

This paper presents more realistic method for calculating the power losses based on load and loss factors instead of the traditional methods of calculating the power losses that uses the RMS value of the load current which not consider the load varying with respect to the time. Eight 11kV feeders are taken as a case study for our work to calculate load factor, loss factor and power losses. Four of them (F40, F42, F43 and F

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Publication Date
Tue Oct 01 2013
Journal Name
Proceedings Of The International Astronomical Union
The infrared <i>K</i>-band identification of the DSO/G2 source from VLT and Keck data
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Abstract<p>A fast moving infrared excess source (G2) which is widely interpreted as a core-less gas and dust cloud approaches Sagittarius A* (Sgr A*) on a presumably elliptical orbit. VLT <italic>K<sub>s</sub></italic>-band and Keck <italic>K</italic>′-band data result in clear continuum identifications and proper motions of this ∼19<sup><italic>m</italic></sup> Dusty S-cluster Object (DSO). In 2002-2007 it is confused with the star S63, but free of confusion again since 2007. Its near-infrared (NIR) colors and a comparison to other sources in the field speak in favor of the DSO being an IR excess star with photospheric continuum emission at 2 microns than a</p> ... Show More
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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
A proposed method for cleaning data from outlier values using the robust rfch method in structural equation modeling
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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Governance Mechanisms on the Accounting Disclosure of the Sustainable Development of Iraqi Economic Units
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The research aims to demonstrate the impact of governance mechanisms on the quality of financial reports in the light of the accounting disclosure for sustainable development represented in (accounting disclosure for economic development, accounting disclosure for environmental development, and accounting disclosure for social development) in a sample of banks listed in the Iraq Stock Exchange.

Governance mechanisms were measured by evaluating and analyzing the mechanisms in banks for the research sample consisting of (15) banks, based on the governance guide issued by the Central Bank, as well as the banks’ financial reports for the years 2016 -2018, and the dimensions of accounting disclosure for sust

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Linear Programming Method Based Optimal Power Flow Problem for Iraqi Extra High Voltage Grid (EHV)
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The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

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Publication Date
Wed May 29 2019
Journal Name
Journal Of Planner And Development
Sustainable spatial development strategy for rural villages (An analytical study applied to Rural commune of Al-Hira)
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Villages in most rural areas of the developing world, including Iraq, suffer from a deterioration in the urban structure in its various aspects, both in the lack of internal planning in terms of residential unit design which is not commensurate with the sustainable health life, in addition to the lack of infrastructure and community services networks As well as road networks linking them to neighboring urban centers, which was accompanied by the emergence of other problems, including the desire of the population to migrate to neighboring cities and the deterioration of economic activities due to lack of activation of economic development plans (Rural villages suffer from a lack of interest in urban development within the regional spatial

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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