Predicting biochemical oxygen demand at Al-Rustumiya wastewater treatment plant inlet using the artificial neural network
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
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle
PAM
Sliding Mode Controller.
In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.
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
Wed Nov 01 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
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Publication Date
Sun Nov 30 2025
Journal Name
بدبي اعمال وقائع المؤتمر الدولي الاول لعلوم المكتبات والمعلومات جامعة الوصل Ùˆ مكتبة Ù…Øمد بن راشد
Artificial Intelligence Skills of Information Institutions Workers: A Descriptive Study
Skills
Artificial intelligence
Information institutions
University libraries
Objectives: This research aims to study the artificial intelligence (AI) skills re-quired by employees in information institutions, specifically university libraries in Iraq, to enhance their services and align with modern technological advancements. It highlights the gap between the current knowledge of employees in Al technologies and their practical applications to improve the services of information institutions. Methodology: The research adopted a descriptive survey method, targeting em- ployees in three prestigious university libraries in Baghdad: the Central Library of the University of Baghdad, the Central Library and House of Books of Al-Mustansiriyah University, and the Central Library of the Iraqi University. A sample of (160)
... Show MorePublication 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 (ô€€”ô€€›ô€€”ô€€›)
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 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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Publication Date
Fri Sep 05 2014
Journal Name
International Journal Of Pharmacy And Pharmaceutical Sciences0975-1491
THE CORRELATION BETWEEN FRAMINGHAM RISK SCORE AND THE CLINICAL AND
BIOCHEMICAL PARAMETERS THAT MEASURE FUNCTIONAL DISABILITY AND DISEASE
ACTIVITY IN IRAQI PATIENTS WITH RHEUMATOID ARTHRITIS
: Rheumatoid arthritis (RA)
Framingham risk score (FRS)
Objective: Rheumatoid arthritis (RA) patients have increased morbidity and mortality from premature cardiovascular (CV) disease (CVD). Framingham risk score (FRS) is a simplified coronary prediction tool developed to enable clinicians to assess the risk of a cardiovascular event and to identify candidate patients for risk factors modifications worldwide. The predictive ability of the FRS varies between populations, ethnic groups, and socio-economic status. The aim of this study is to find if there is any correlation between the Framingham risk score and the inflammatory and biochemical parameters used to measure disease activity and functional ability in Iraqi patients with active RA.
Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Designing Primers with a Plant Signal Peptide to Enhance the Expression of GBA1 in Transgenic Soybean Plants
signal peptide
Hu-GBA gene
pCAMBIA1304 vector
Soybean
Agrobacterium- mediated transformation
Transgenic plants offer advantages for the manufacture of recombinant proteins with terminal
mannose residues on their glycan chains. So plants are chosen as source of pharmaceutical products and for
the development of alternative expression systems to produce recombinant lysosomal enzymes. In the
present study the sequence of the natural cDNA encoding for the human lysosomal enzyme
glucocerebrosidase (GCD) was modified to enhance its expression in soybean plants. The glucocerebrosidase
gene signal peptide was substituted with that signal peptide for the Arabidopsis thaliana basic endochitinase
gene to support the co-translational translocation into the endoplasmic reticulum (ER), and the storage
vacuol
Publication Date
Thu Apr 01 2021
Journal Name
Biochemical And Cellular Archives
Improvement in the Growth of Cumin Plant, Cuminum Cyminum L. with Spraying Tryptophan and Iq Combi Nanofertilizer
Cumin plant
amino acids
tryptophan
nanotechnology
The experiment was carried out in the Department of Biology, College of Education for Pure Science –Ibn AL Haitham, University of Baghdad, Iraq, during the growing season 2017 – 2018. The objective was to find out the effect of foliar spraying of tryptophan and IQ COMBI nano fertilizer on cumin plants. The obtained results show that both tryptophan and IQ COMBI nano fertilizer increased plant height, root length, shoot dry weight, the content of nitrogen, phosphorus, potassium, protein percentage, no. compound umbel.plant-1, wt. seeds. plant-1. The optimum treatment combination was calculated as 30 mg.L-1 tryptophan, 1000mg.L-1 IQ COMBI nano fertilizer, which gave the highest values for most of the parameters studied
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