Preferred Language
Articles
/
jbcd-2218
Validity of Digital and Rapid Prototyped Orthodontic Study Models
...Show More Authors

Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chosen as the printing material. Twenty four linear measurements were taken from digital and prototyped models and were compared to their original stone models “the gold standard”, utilizing the paired sample t-test and Bland-Altman plots. Results: Eighteen of the twenty four variables showed non-significant differences when digital models were compared to stone models. The levels of agreement between the two methods showed that all differences were within the clinically accepted limits. For prototyped models, more than half of the variables differed in non-significant amount. The levels of agreement were also within the clinically accepted limits. Conclusion: Digital orthodontic study models are accurate in measuring the selected variables and they have the potential to replace conventional stone models. The selected rapid prototyping technique proved to be accurate in term of diagnosis and might be suitable for some appliance construction.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
...Show More Authors

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

... Show More
View Publication Preview PDF
Scopus (3)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparing traditional estimators and the estimators of (PSO) algorithm for some growth models of gross domestic product in Iraq
...Show More Authors

View Publication
Scopus
Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Clinical And Experimental Dentistry
Comparison of the accuracy of intraoral digital impression system and conventional impression techniques for multiple implants in the full-arch edentulous mandible
...Show More Authors

View Publication
Scopus (9)
Crossref (12)
Scopus Crossref
Publication Date
Sat Sep 28 2024
Journal Name
Journal Of The Pakistan Medical Association
Pulse transmission time and amplitude of digital pulse wave determined by fingertip plethysmography as a surrogate marker of brachial artery flowmediated dilatation
...Show More Authors

Objectives: To assess the changes in blood vessel stiffness and digital pulse wave amplitude because of flowmediateddilatation, and to explore how these two variables change when endothelial dysfunction isexperimentally induced.Method: The experimental study was conducted at the departments of physiology at the College of Medicine,Mustansiriyah University, and the College of Medicine, Al-Iraqia University, Baghdad, Iraq, from October 14, 2021, toMay 31, 2022, and comprised healthy young males who were subjected to the flow-mediated dilatation techniqueon the left brachial artery. Pulse transit time and the amplitude of the digital pulse wave were measured duringreactive hyperaemia for 2.5 minutes from the left middle finger using a

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Clarivate Crossref
Publication Date
Sat Jan 01 2022
Journal Name
The 2nd Universitas Lampung International Conference On Science, Technology, And Environment (ulicoste) 2021
A comparison between IRI-2016 and ASAPS models for predicting foF2 ionospheric parameter over Baghdad city
...Show More Authors

View Publication
Scopus (2)
Crossref (2)
Scopus Crossref
Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
...Show More Authors

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Baghdad City Seasonal Forecasts Of Monthly Chronic Diseases patients Numbers Using SARIMA Models
...Show More Authors

    One of the most important problems of IRAQI HEALTH MINISTRY and all healthy instruments in IRAQ is Chronic Diseases because it  have a negative effects on IRAQI population, this is the aim of our study ,to specify the important Chronic diseases which make the population fell weakly, they are six diseases as the IRAQ ministry of health specified (  Diabetes, blood pressure diseases ,Brain diseases ,  Cardiology, Asthma, epilepsy) we got these data from IRAQI HEALTH MINISTRY ,bureau of planning and studies ,for the period 2009-2012,as monthly observations , represent sum of peoples have chronic diseases in Baghdad .

     Our research obj

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Particle Swarm Algorithm to Solve Queuing Models with Practical Application
...Show More Authors

This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six  employees , and it was chosen queuing model is a single-service channel  M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and  it was composed of data collection times (arrival time , service time, departure time)

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
...Show More Authors

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Use special Erwa to determine the number of live bacteria in different models
...Show More Authors

Used in the study especially calibrated Erwa to determine the number of neighborhood or the Alayoshi number of bacteria in the count modeling and casting method dishes in addition to using the drop method yielded significant results for a match between the methods used ..

View Publication Preview PDF