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Tooth agenesis and palatal dimensions associated with craniofacial deformity- Cone Beam Computed Tomography based study
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Cleft / palate is one of the common congenital deformities in craniofacial region, associated with different types of dental anomalies like (Tooth agenesis, impaction, and supernumerary teeth) with marked changes in palatal dimensions. This study aimed to determine the prevalence of teeth agenesis and dental anomalies in cleft lip/palate patients using CBCT, and to compare the palatal dimension of cleft group with control subjects. Twenty-eight cleft cases collected during the period from 2015 to 2022, CBCT images evaluated, the study sample classified into two groups (14 bilateral and 14 unilateral cleft lip/palate) and the non-cleft control group (14 CBCT images). The presence of dental anomalies was assessed in relation to cleft type, and then palatal width, arch width, and palatal depth measurements were performed. All linear measurements in mm compared with control group. Tooth agenesis was the most frequent dental anomalies in groups, 71.4% missing lateral incisors and 57.1% in bilateral and unilateral cleft groups respectively. Impacted canine and supernumerary teeth were more frequent in unilateral than bilateral cleft. Male had higher frequency of tooth agenesis and other anomalies. Palatal dimensions were higher in bilateral cleft group with very significant differences in palatal width and arch width. Accurate assessment of maxilla for tooth agenesis, dental anomalies and palatal dimensions is mandatory. Team workrequired for full rehabilitation of children with cleft lip/palate.

Publication Date
Sat Apr 01 2017
Journal Name
Image & Video Processing
Enhancement of LBP-based face identification system by adopting preprocessing techniques
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Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Bionics-Based Approach for Object Tracking to Implement in Robot Applications
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In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based

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Publication Date
Sat Apr 30 2016
Journal Name
Environmental Science And Pollution Research
Risk-based prioritization of pharmaceuticals in the natural environment in Iraq
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Comparison of Different DEM Generation Methods based on Open Source Datasets
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Digital Elevation Model (DEM) is one of the developed techniques for relief representation.  The definition of a DEM construction is the modeling technique of earth surface from existing data. DEM plays a role as one of the fundamental information requirement that has been generally utilized in GIS data structures. The main aim of this research is to present a methodology for assessing DEMs generation methods. The DEMs data will be extracted from open source data e.g. Google Earth. The tested data will be compared with data produced from formal institutions such as General Directorate of Surveying. The study area has been chosen in south of Iraq (Al-Gharraf / Dhi Qar governorate. The methods of DEMs creation are kriging, IDW (inver

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
National Grid Connected 3-Phase Inverter based on Photovoltaic Solar System
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In this paper, a national grid-connected photovoltaic (PV) system is proposed. It extracts the maximum power point (MPP) using three-incremental-steps perturb and observe (TISP&O) maximum power point tracking (MPPT) method. It improves the classic P&O by using three incremental duty ratio (ΔD) instead of a single one in the conventional P and O MPPT method. Therefore, the system's performance is improved to a higher speed and less power fluctuation around the MPP. The Boost converter controls the MPPT and then is connected to a three-phase voltage source inverter (VSI). This type of inverter needs a high and constant input voltage. A second-order low pass (LC) filter is connected to the output of VSI to reduce t

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
On Estimation of the Stress – Strength Reliability Based on Lomax Distribution
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Abstract<p>The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.</p>
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Publication Date
Sun Feb 13 2022
Journal Name
Petroleum & Coal
Laboratory-Based Correlations to Estimate Geomechanical Properties for Carbonate Tight Reservoir.
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Rock mechanical properties are critical parameters for many development techniques related to tight reservoirs, such as hydraulic fracturing design and detecting failure criteria in wellbore instability assessment. When direct measurements of mechanical properties are not available, it is helpful to find sufficient correlations to estimate these parameters. This study summarized experimentally derived correlations for estimating the shear velocity, Young's modulus, Poisson's ratio, and compressive strength. Also, a useful correlation is introduced to convert dynamic elastic properties from log data to static elastic properties. Most of the derived equations in this paper show good fitting to measured data, while some equations show scatters

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Publication Date
Wed Oct 10 2018
Journal Name
Commun.fac.sci.univ.ank.series A2-a3
ULTRAHIGH SENSITIVE REFRACTIVE INDEX SENSOR BASED ON TAPERED MULTICORE OPTICAL FIBER
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The refractive index sensors based on tapered optical fiber are attractive for many industries due to sensing capability in a variety of application. In this paper, we proposed a refractive index sensor based on multicore fiber (MCF) sandwiched between two standard single mode fibers (SMF). The sensor consisting of three sections, SMF- MCF-SMF is structurally simple and can be easily produced by joining these parts. The MFC contains seven cores and these cores are surrounded by a single cladding. The sensing region is obtained by tapering the MCF section where the evanescent field is generated. The single mode propagating along the SMF is stimulated at the first joint and is coupled to the cladding modes. These modes interfere with the core

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