Background: Determination of sex and estimation of stature from the skeleton is vital to medicolegal investigations. Skull is composed of hard tissue and is the best preserved part of skeleton after death, hence, in many cases it is the only available part for forensic examination. Lateral cephalogram is ideal for the skull examination as it gives details of various anatomical points in a single radiograph. This study was undertaken to evaluate the accuracy of digital cephalometric system as quick, easy and reproducible supplement tool in sex determination in Iraqi samples in different age range using certain linear and angular craniofacial measurements in predicting sex. Materials and Method The sample consisted of 113of true lateral cephalometric radiographs for adults with age range from 22-43 years old (51 males, 62 females), using certain linear and angular craniofacial measurements with the aid of computer program “AutoCAD 2007” Results: The eleven parameters measured for males and females when compared are statistically significantly different. All cranio-cephalometric measurements gave overall predictive accuracy of sex determination by discriminant analysis (86.7%). The stepwise selection method gave overall predictive accuracy of sex determination by discriminant analysis (85.8%). Age showed no statistical difference among the studied age range except for the distance from Mastoid to Frankfort plane. Conclusion: The lateral cephalometric measurements of craniofacial bones are useful to support sex determination of Iraqi population in forensic radiographic medicine.
During the period from September 2013 till the end of July 2014 ,a total of 340 birds Passer domesticus were collected from Tikrit city . The study revealed the infection of birds with seven species of cestoda helminthes , belonging to the genus Raillietin . These species included R. tetragona , R. echinobothrida , R. cesticellus and R. ransomi with prevalence infection of 36.1% , 30.1% . 15.0 % and 1.8 % respectively . And the genus Choanotaenia . These species included C. infundibulum and C. passerine with pervatence infection of 15.0% and 0.6% respectively . And the genus Anonchotuenia . The species included A.globate with prevantence infection 1.2% .
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
The aim of this paper is to find a new method for solving a system of linear initial value problems of ordinary differential equation using approximation technique by two-point osculatory interpolation with the fit equal numbers of derivatives at the end points of an interval [0, 1] and compared the results with conventional methods and is shown to be that seems to converge faster and more accurately than the conventional methods.
This study documented the role of blowfly Chrysomya albiceps and Chrysomya megacephala as carriers of 15 species of intestinal parasites eggs, cysts and Oocysts as a primary effort of Iraq, by external and internal techniques: 10 species of different parasites were reported in this study that transmitted mechanically by Calliphoridae fly ,eight of them are nematode eggs (Ancylostoma duodenal, Ascaridia sp., Ascaris lumbricoides, Parascaris equirum, Strongyloides stericoralis , Strongylus sp., Trichostrongylus sp. and Toxocara canis)and cysts of two species of protozoa ( Entamoba sp.and Iodomaba butschlii). Internal technique by stained the fluid gut of flies with Zael Nelson stain, was app
... Show MoreResearchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The
... Show MoreFG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2
Pan sharpening (fusion image) is the procedure of merging suitable information from two or more images into a single image. The image fusion techniques allow the combination of different information sources to improve the quality of image and increase its utility for a particular application. In this research, six pan-sharpening method have been implemented between the panchromatic and multispectral images, these methods include Ehlers, color normalize, Gram-Schmidt, local mean and variance matching, Daubechies of rank two and Symlets of rank four wavelet transform. Two images captured by two different sensors such as landsat-8 and world view-2 have been adopted to achieve the fusion purpose. Different fidelity metric like MS
... Show MoreMultispectral remote sensing image segmentation can be achieved using a multithresholding technique. This paper studies the effect of changing the window size of the two dimensional (2D) fast Otsu algorithm that presented by Zhang. From the results, it shown that this method behaves as a search machine for the valleys (an automatic threshold), between the gray levels of the histogram with changing the size of slide window.
Keywords Image Segmentation, (2D) Fast Otsu method, Multithresholding, Automatic thresholding, (2D) histogram image.
A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.