Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density v

Genetic polymorphisms of genes whose products are responsible for activities, such as xenobiotic metabolism, mutagen detoxification and DNA-repair, have been predicted to be associated with the risk of developing lung cancer (LC). The association of LC with tobacco smoking has been extensively investigated, but no studies have focused on the Arab ethnic- ity. Previously, we examined the association between genetic polymorphisms among Phase I and Phase II metabolism genes and the risk of LC. Here, we extend the data by examining the correlation of OGG1 Ser326Cys combined with CYP1A1 (Ile462Val and MspI) and GSTP1 (Ile105Val and Ala103Val) polymorphisms with the risk of LC. Polymerase chain reaction- restriction fragment length polymorphism (

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

In this paper Zener diode was designed by mixing three mixing ratios of Ag₂O_(1-x)ZnO_(x), where x is 0.5, 0.3, and 0.1, that are deposited on a p-type porous silicon using laser induced plasma technique at room temperature (RT). The results of the Zener diode showed a decrease in knee and Zener voltage when the mixing ratio of Ag₂O_(1-x)ZnO_(x) structure was increased. Nanofilms of 200nm thickness were prepared from pure ZnO and Ag₂O as well as Ag₂O_(1-x)ZnO_(x) with three maxing ratios and deposited on glass slides at RT to analyze the structure and optical properties. The structures of Ag₂O and Ag₂O

 Neuroimaging is a description, whether in two-dimensions (2D) or three-dimensions (3D), of the structure and functions of the brain. Neuroimaging provides a valuable diagnostic tool, in which a limited approach is used to create images of the focal sensory system by medicine professionals. For the clinical diagnosis of patients with Alzheimer's Disease (AD) or Mild Cognitive Impairs (MCI), the accurate identification of patients from normal control persons (NCs) is critical. Recently, numerous researches have been undertaken on the identification of AD based on neuroimaging data, including images with radiographs and algorithms for master learning. In the previous decade, these techniques were also used slowly to differentiate AD a

      Iodine-131 has become an essential radionuclide used in nuclear medicine for clinical and research purposes. The increase use of this radionuclide in medicine for diagnostic and treatment of thyroid diseases creates a demand to obtain a feasible methodology for occupational or accidental monitoring of internal contamination. In this study, two techniques were employed to find an appropriate one of in vivo bioassay for evaluating Iodine-131 body content. A scanning Whole Body Counter (WBC) equipped with 6NaI (Tl) scintillation detector, an anthropomorphic phantom and point source were used. The results showed that the counter sensitivity, as a first approach (conventional method), had a logarithmic and significant correlation w

The autocorrelation function calculations have been carried out on photon-limited computer-simulated images of binary stars that recorded through kolmogorov atmospheric turbulence. The effect of the parameters of photon limited binary star on the variation of signal to noise, signal to background ratios, number of images that processed and the magnitude of binary stars are studied and mathematic equations are given to investigate this effect. The result indicates that signal to background ratio of photon limited images of a binary star is independent of the total number of recorded photons.