Preferred Language
Articles
/
joe-1946
FINITE ELEMENT ANALYSIS OF HUMAN AND ARTIFICIAL ARTICULAR CARTILAGE
...Show More Authors

Joint diseases, such as osteoarthritis, induce pain and loss of mobility to millions of people around the world. Current clinical methods for the diagnosis of osteoarthritis include X-ray, magnetic resonance imaging, and arthroscopy. These methods may be insensitive to the earliest signs of osteoarthritis. This study investigates a new procedure that was developed and validated numerically for use in the evaluation of cartilage quality. This finite element model of the human articular cartilage could be helpful in providing insight into mechanisms of injury, effects of treatment, and the role of mechanical factors in degenerative
conditions, this three-dimensional finite element model is a useful tool for understanding of the stress distributions within articular cartilage in response to external loads and investigating both the prevention of injury and the pathological degeneration of the joints.
In this study, 21 models were analysed by using ANSYS workbench v12.1: four normal articular cartilage models (distal femur, patella, medial and lateral tibia). A redesign to the distal femur model was done to get osteoarthritis articular cartilage (simple and deep) seven models by making partial cut without affecting the subchondral bone, and full cut with part of the subchondral bone in different diameters. Finally a treatment done by replacing the defective parts with artificial articular cartilages with different types of treatment. The finite element analysis studied depending on a Von Mises criteria and total deformation in different activities. The results shows that Autologous Chondrocyte Implementation is the best treatment way and it is close by 87.50% to normal cartilage. This procedure can be used as a diagnostic procedure for osteoarthritic patients and to choose the best treatment options.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
...Show More Authors

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

... Show More
Crossref
Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
...Show More Authors
Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
View Publication
Crossref (9)
Crossref
Publication Date
Fri Apr 30 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
...Show More Authors

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

... Show More
View Publication
Scopus (17)
Crossref (6)
Scopus Crossref
Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Water Quality Assessment and Total Dissolved Solids Prediction using Artificial Neural Network in Al-Hawizeh Marsh South of Iraq
...Show More Authors

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

... Show More
Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
...Show More Authors

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

... Show More
Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
FLOW INJECTION ANALYSIS AND SPECTROPHOTOMETRIC DETERMINATION OF NIFEDIPINEIN PHARMACEUTICAL FORMULATION: FLOW INJECTION ANALYSIS AND SPECTROPHOTOMETRIC DETERMINATION OF NIFEDIPINEIN PHARMACEUTICAL FORMULATION
...Show More Authors

A new simple and sensitive spectrophotometric method is described for quantification of Nifedipine (NIF) and their pharmaceutical formulation. The selective method was performed by the reduction of NIF nitro group to yield primary amino group using zinc powder with hydrochloric acid. The produced aromatic amine was submitted to oxidative coupling reaction with pyrocatechol and ammonium ceric nitrate to form orange color product measured spectrophotometrically with maximum absorption at 467nm. The product was determined through flow injection analysis (FIA) system and all the chemical and physical parameters were optimized. The concentration range from 5.0 to 140.0 μg.mL-1 was obeyed Beer’s law with a limit of detection and quantitatio

... Show More
View Publication Preview PDF
Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
...Show More Authors

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using the Artificial Gas Lift to Increase the Productivity of Noor Oil Field / Mishrif Formation
...Show More Authors

Noor Oil Field is one of Iraqi oil fields located in Missan province / Amarah city. This field is not subjected to licensing rounds, but depends on the national effort of  Missan Oil Company. The first two wells in the field were drilled in seventies and were  not opened to production until 2009. The aim of this study is to study the possibility of using the method of gas lift to increase the productivity of this field . PROSPER software was used to design the continuous  gas lift by using maximum production rate in the design.

   The design was made after comparing  the measured pressure with the calculated pressure, this comparison  show  that the method of Beggs-Brill and Petroleum Exper

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI
...Show More Authors

“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

... Show More
View Publication
Crossref
Publication Date
Wed Jul 01 2015
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
GEOSTATISTICAL ANALYSIS AND MAPPING OF OZONE OVER IRAQ
...Show More Authors

    The Ozone Monitoring Instrument (OMI) measures the reflected solar radiation in the ultraviolet and visible part in the spectral range that is between 270 and 500 nm, using two channels with a spectral resolution of about 0.5 nm. Ground-level tropospheric ozone is one of the air pollutants of most concern. In the troposphere, near the Earth's surface, human activities lead to ozone concentrations several times higher than the natural background level. To evaluate the ozone distribution over Iraq, the ozone data from OMI were analyzed using geostatistical techniques. Theoretical spherical models provided the best fit for all monthly experimental variograms. The parameters of these variograms (sill, range and nugget) wer

... Show More
View Publication Preview PDF