Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Mon Mar 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Speech Enhancement Algorithm Based on a Hybrid Estimator
Abstract<p>Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra</p>
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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca
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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Hybrid Controller for a Single Flexible Link Manipulator
Flexible Link
Single Link
Hybrid Control
Fuzzy Contro
In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Emotional Intelligence in kindergarten and its relationship with some variables
This study aims at finding out the sentimental smartness of the kindergarten children
and its relationship with some variables.
1- The level of the sentimental smartness of the kindergarten children.
2- Investigating the Zero hypothesis in that there are no significant statistical differences in
the sentimental smartness between the kindergarten children according to the sex variables
(males and females).
Some statistical tools have been used in order to arrive at the results that verify the
hypotheses of this study. The researcher uses (1) the distinctive power between two
distinctive groups; (2) the relationship between the item and the total degree (Pearson
correlation factor); and (3) Elfakronbach formula t
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
Wed Nov 01 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
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Publication Date
Thu Jan 01 2026
Journal Name
Malaysian Journal Of Nursing
Pediatric Nursing Students and Artificial Intelligence: A Cross-Sectional Study
Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates that nursing education evolves to equip students with essential technological competencies. Objectives: To explore pediatric nursing students' perceptions of AI in nursing and analyze associations with sociodemographic factors and prior AI knowledge. Methods: A descriptive cross-sectional study was conducted from December 2024 to March 2025 across five universities in Baghdad. A non-probability sample of 500 pediatric nursing students completed the Shinners Artificial Intelligence Perception (SAIP) tool. Data were analyzed using descriptive statistics and inferential comparisons (t-tests/ANOVA) via SPSS. Results: Participants had a mean ag
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Entrepreneurial performance in accordance with the competitive intelligence and strategic
/ الاداء الريادي- الذكاء التنافسي- الذكاء الاستراتيجي- الاستباقية- الكفاءة والفاعلية
performance- leadership - competitive intelligence - strategic intelligence – proactive - efficiency and effectiveness.
The research aims to study the entrepreneurial performance of the banks, according to the intelligence of competitive and strategic as the entrepreneurial performance is the one who does not stand the benefits of excellence in accomplished when just achieving the bank's objectives planned, but exceed it down to creativity in accomplishing these goals in a manner leads to making a entrepreneurial bank in the markets and the focus the eyes of competitors and the banks and other Following his example.
Was chosen the subject of research and strategic intelligence and competitive because of its impact on the strategic success of the banking sector, the fact is the entrepreneurial in the Iraqi banking mar
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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
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
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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