Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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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.
Publication Date
Fri Feb 01 2019
Journal Name
Journal Of The College Of Education For Women
The Intelligence of the Child in Relation to some Variables
The Intelligence of the Child in Relation to some Variables
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
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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(3)
Publication Date
Tue Dec 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Hybrid compensation of polarization-multiplexed QPSK optical format for high bit rate networks
<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi
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(3)
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
NARMA-L2Model
MLP neural Network
Modified Elman Neural Network
Back Propagation Algorithm
Particle Swarm Optimization
Nonlinear CSTR System.
This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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(2)
Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Accurate Four-Step Hybrid Block Method for Solving Higher-Order Initial Value Problems
Accuracy
Block Method
Convergence
Higher-Order
Initial Value Problems (IVPs)
Ordinary Differential Equations
AMS Group: 65L05
65L06
65L10
This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.
(1)
Publication Date
Mon May 21 2007
Journal Name
Journal Of Planner And Development
Towards a decentralized planning policy in Iraq
decentralized planning
Iraq is changing from the centralized system of governance to the decentralized system, which assumes devolution of more authorities to the local governments of Iraqi provinces and cities. This puts a responsibility on the academics to produce more research work on the best framework for this change, to ensure the best results. The main objective of this research is to suggest a policy for the decentralized transformation in domain of Urban and Regional Planning in Iraq. A suggested program for the transformation is involved in the paper as well, with analysis for the new relationships between different levels of planning authorities depending on democracy. In addition, a description for planning process flows from bottom to top.
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Mobility Models over UDP Traffic Pattern for MANET Using NS-2
MANET
Mobility Models
Traffic Pattern
Bonn Motion
Performance evaluation
The current study presents the simulative study and evaluation of MANET mobility models over UDP traffic pattern to determine the effects of this traffic pattern on mobility models in MANET which is implemented in NS-2.35 according to various performance metri (Throughput, AED (Average End-2-end Delay), drop packets, NRL (Normalize Routing Load) and PDF (Packet Delivery Fraction)) with various parameters such as different velocities, different environment areas, different number of nodes, different traffic rates, different traffic sources, different pause times and different simulation times . A routing protocol.…was exploited AODV(Adhoc On demand Distance Vector) and RWP (Random Waypoint), GMM (Gauss Markov Model), RPGM (Refere
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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some of Robust the Non-Parametric Methods for Semi-Parametric Regression Models Estimation
Semi-Parametric Regression
M-Estimation
S-Estimation
Robust Semiparametric Methods
Nonparametric Estimation Method
Kernel Method.
طريقة M-estimation
طريقة S-estimation
انموذج الانحدار شبه المعلمي
طرائق التقدير الحصينة
طرائق التقدير اللامعلمية الحصينة
طريقة Kernel
In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.
The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the
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(2)
Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
نماذج البقاء
أنموذج باريتو العام للمخاطرة النسبية
معيار امثل- CB
معيار امثل- AB
التصميم الامثل
مصفوفة المعلومات
طريقة الامكان الاعظم الكاملة.
Survival Models
The Generalized Pareto Proportional Hazards Model
CB- Optimal Criterion
AB- Optimal Criterion
Optimal Design
Information Matrix
Complete Maximum Likelihood Method.
The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as
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