The Trade War Between the United States and China and Its Impact On the World Economy2017-2019

م.د.علي طارق الزبيدي

doi:10.30907/jj.v0i60.497

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Publication Date

Thu Dec 31 2020

Journal Name

Political Sciences Journal

Issue Number

60

DOI

10.30907/jj.v0i60.497

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The Trade War Between the United States and China and Its Impact On the World Economy2017-2019

Trade war

United States of America

China

م.د.علي طارق الزبيدي

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The trade war, of course, leads to a sharp tension in international relations because the economy is the lifeblood of the states. In the world of trade and economy, countries began to lean towards cooperation. Economic relations after World War II were more liberal, trade barriers were removed and global trade became more flexible and smooth

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Publication Date

Sat May 31 2025

Journal Name

3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges

Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies

With the advent of technology

the fear of losing control has consistently accompanied humanity. While humans have discovered

invented

and created many remarkable things

they have also been haunted by the possibility of their creations turning against them. This fear

often referred to as the Frankenstein Complex

derives its name from Mary Shelley's Frankenstein (􀀔􀀛􀀔􀀛)

in which Dr. Frankenstein's creation ultimately destroys its maker. The Frankenstein Complex embodies the subconscious fear of artificial intelligence (AI) surpassing and potentially dominating humankind. This apprehension has inspired numerous literary works

including Daniel H. Wilson’s novels. The present study examines the widespread fear of AI

which has fueled conspiracy theories in literature. These theories have not only amplified public anxiety but also hindered understanding among those with limited knowledge of AI and robotics. Dr. Wilson

a robotics expert

uses his imagination as a driving force for both his writing and his inventions. The research focuses on incidents leading to the rise of robots

the concept of the New War

how it was fought

and how it concluded. By comparing

contrasting

and analyzing literary elements and devices with prominent conspiracy theories

the study highlights the interplay between fiction and scientific development. The researchers conclude that while many conspiracy theories contain elements of truth

they often inspire scientists to explore them further. Additionally

some conspiracy theories warrant serious consideration. The study recommends acknowledging the Frankenstein Complex while maintaining faith in the potential benefits of artificial intelligence.

Ansam

Mayada

Zahraa

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Publication Date

Tue Jun 30 2020

Journal Name

Iraqi Journal Of Chemical And Petroleum Engineering

Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field

Rate of penetration

artificial neural network

Dynamic elastic properties

Nasiriya Oil Field

Yasser

Fadhil

Yousif

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The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

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Publication Date

Fri Dec 30 2016

Journal Name

Al-kindy College Medical Journal

Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining

DVT risk factors

analysis of DVT risk factors

Data mining and DVT

Muthanna D.R.

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Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti

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Publication Date

Sat Oct 01 2022

Journal Name

The Iraqi Postgraduate Medical Journal

Acceptance of COVID19 Vaccines among Health Care Workers in Al Risafa Directorate of Health in Baghdad

acceptance

COVID-19

Vaccines

health care workers

Al Risafa Directorate of Health

Ghaith Sabri Mohammed

Iman Ahmed Mohammed

Reem Zeki Mohammed

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Publication Date

Sat Aug 06 2022

Journal Name

Ijci. International Journal Of Computers And Information

Techniques for DDoS Attack in SDN: A Comparative Study

Keywords: machine learning

Software-Defined Networking

Network Security

Distributed Denial of Service

Ahmed

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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

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Publication Date

Wed Jul 30 2025

Journal Name

Methodsx

New Modifications of ADM with Applications in Kind of PDEs

Modified algorithmsModified AD methodTwo- step AD methodLaplace AD MethodPDE of parabolic type

Eman Mohmmed

Aqeel Falih

Farah Feasal

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This paper presents seven modified Adomian Decomposition Method (ADM) techniques for efficiently solving initial value problems, especially those involving non-homogeneous and nonlinear differential equations. While the classical ADM is effective for linear homogeneous cases, it has difficulties solving more complex problems. The proposed modifications—from MADM1 to MLADM—include Maclaurin and Taylor expansions, Laplace transforms, and single-step iterations.• These modifications enhance convergence, reduce complexity, and improve accuracy.• Each method offers specific advantages, such as accelerating convergence (MADM2, RADM4), simplifying computation (TSADM5), and achieving higher accuracy (MLADM).• Numerical examples confirm th

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Publication Date

Sun Apr 28 2024

Journal Name

Journal Of Advances In Information Technology

Enhancement of Recommendation Engine Technique for Bug System Fixes

bugs

fusion of intelligent optimization

artificial neural networks

machine and deep learning

Jalal Sadoon Hameed

Mohammed

Furat Nidhal

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This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

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Publication Date

Fri Jul 01 2016

Journal Name

Journal Of Engineering

Optimization of Hole Cleaning In Iraqi Directional Oil Wells

hole cleaning

rate of penetration

equivalent circulating density

directional well

cuttings bed

Ayad A. Al-Haleem

Abdul-Aali

Firas Mohammed

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Efficient cuttings transport and hole cleaning are very important factors for obtaining an effective drilling operation. In an inclined and horizontal drilling, hole cleaning issue is a common and complex problem.

The scope of this research is to study the drilling parameters which affect hole cleaning in Iraqi directional wells through studying and analyzing some drilled wells ( vertical , directional (30 degree) , directional (60 degree) and horizontal ).An excel sheet is prepared to calculate carrying capacity index which represents an indicator for good hole cleaning in different sections. The study indicated through the field investigations, practical experiences and theoretical calculations tha

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Publication Date

Mon Jan 30 2023

Journal Name

Iraqi Journal Of Science

Detection of mexB Multidrug Efflux Gene in Some Local Isolates of Pseudomonas aeruginosa

Pseudomonas aeruginosa

mexB efflux gene

Antibiotic resistance

Inhibition of efflux pump

Curcumin

Najlaa Nabhan Yaseen

Dalia Azher

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According to the prevalence of multidrug resistance bacteria, especially Pseudomonas aeruginosa, in which the essential mechanism of drug resistance is the ability to possess an efflux pump by which extrusion of antimicrobial agents usually occurs, this study aims to detect the presence of mexB multidrug efflux gene in some local isolates of this bacteria that show resistance towards three antibiotics, out of five. Sensitivity test to antibiotics was performed on all isolates by using meropenem (10μg/disc), imipenem (10μg/disc), amikacin (30 μg/disc), ciprofloxacin (5μg/disc) and ceftazidime (30 μg/disc). Conventional PCR results showed the presence of mexB gene (244bp) in four isolates out of ten (40%). In addition,25, 50μg/ml of cur

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Publication Date

Tue Feb 28 2023

Journal Name

Periodicals Of Engineering And Natural Sciences (pen)

Development prediction algorithm of vehicle travel time based traffic data

Prediction Algorithm

Travel Times

Universal Transverse Mercator (UTM)

Polygon of Traffic Data

Muna Hadi

P.

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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

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