Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm

Maysam Sachit Khudair

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Publication Date

Wed Jan 15 2003

Journal Name

كلية الترا ث الجامعة

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Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm

Maysam Sachit Khudair

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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

Publication Date

Sat Feb 01 2020

Journal Name

Journal Of Economics And Administrative Sciences

Properties of Kumaraswamy binary Distribution and compare methods of estimating parameters

توزيع كوماراسوامي

مقدرات الإمكان الأعظم

مقدرات العزوم

مقدرات المربعات الصغر المطورة.

Kumaraswamy distribution

Maximum Likelihood Estimator

Moment Estimator

least square develop estimator.

احمد رزاق

اياد حبيب

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The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

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Publication Date

Wed Nov 01 2023

Journal Name

Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )

After Introducing Artificial Intelligence, can Pharmacists Still Find a Job?

Ehab

Samer

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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 Aug 15 2023

Journal Name

Al-academy

The effectiveness of artificial intelligence in contemporary digital graphic design

الفاعلية

الذكاء الاصطناعي

التصميم الكرافيكي الرقمي

Fouad

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In our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial inte

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Publication Date

Mon Jan 01 2024

Journal Name

International Journal Of Mathematics And Computer Science

Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition

Wisal

Shahlaa

Samera

Aseel

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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date

Fri Aug 16 2024

Journal Name

International Journal Of Mathematics And Computer Science

Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition

Palm print

Random Forest

Support Vector Machine

k-NN

SqueezNet

Machine Learning

Wisal Hashim

Shahlaa

Samera Shams

Aseel

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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date

Sat Dec 14 2019

Journal Name

International Journal On Emerging Technologies

Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns

Stone columns

artificial neural network

ultimate bearing capacity

ground improvement

Matlab neural network toolbox

neural technology model.

Nesreen Kurdy

Assad

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ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

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Publication Date

Sat Dec 01 2018

Journal Name

Political Sciences Journal

Soft power employment strategy in foreign affairs (Eygpt after Mubarak Regime : An Analytical study)

أ.م.د.علي حسين

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(January 25, 2011) represented a real opportunity to bring about fundamental changes in Egyptian foreign policy and to start a new phase that would cut off all the negative and problematic aspects of Egyptian politics in the period before the revolution. Through the employment of Egypt's huge balance and the role of historical is a civilization rooted in the roots of thousands of years and Islamic reference represented over more than a thousand years the Islamic medium of religion in the start of vision and tools to achieve the Egyptian national interest, and safeguarding Egyptian national security in its comprehensive sense. The research attempts to answer a central question: Is there a role for Egyptian soft power in the Islamic world

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Publication Date

Fri Jul 01 2016

Journal Name

Journal Of Engineering

An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

multi-robot system

path planning

multi-objective approaches

adaptive multi-objective particle swarm optimization

danger zones.

Nizar Hadi

Jaafer Ahmed

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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date

Sun Apr 30 2023

Journal Name

Iraqi Journal Of Science

An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection

Isra H.

Dhia A.

Bara'a Ali

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Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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