Background: Since the periodontal disease Index of Ramfjord (Ramfjord index) can potentially shorten the examination time by almost half, many studies evaluated Ramfjord teeth in predicting full-mouth periodontal status of an adult population. The aim of this study was to evaluate the benefit of Ramfjord teeth in predicting the full-mouth clinical attachment level of an adult population in patients attending the college of dentistry- Baghdad University. Materials and methods: The study participants were 100 patients with age range from 30-60 years old which represent group zero. The patients were divided into three main groups according to the age of the patients. Group I and group II each of them composed of 30 patients while group III composed of 40 patients. In the first time clinical attachment level (CAL) was measured from the full mouth (FM) and then from the Ramfjord teeth (RT) (teeth number: 16, 21, 24, 36, 41, 44) in all groups. Clinical attachment level (CAL) was measured in millimeters using periodontal probe. Results: The difference in the mean clinical attachment level measured from the full mouth (FM) and Ramfjord teeth (RT) by using paired t - test was non significant in all the groups. Also in all groups the correlation coefficient as well as beta coefficient was high. Conclusion: The high agreement between Ramfjord teeth and full mouth CAL confirm the epidemiological validity of Ramfjord teeth to represent the full mouth.
In this paper, a new analytical method is introduced to find the general solution of linear partial differential equations. In this method, each Laplace transform (LT) and Sumudu transform (ST) is used independently along with canonical coordinates. The strength of this method is that it is easy to implement and does not require initial conditions.
The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone
... Show MoreNowadays, the robotic arm is fast becoming the most popular robotic form used in the industry among others. Therefore, the issues regarding remote monitoring and controlling system are very important, which measures different environmental parameters at a distance away from the room and sets various condition for a desired environment through a wireless communication system operated from a central room. Thus, it is crucial to create a programming system which can control the movement of each part of the industrial robot in order to ensure it functions properly. EDARM ED-7100 is one of the simplest models of the robotic arm, which has a manual controller to control the movement of the robotic arm. In order to improve this control s
... Show MoreThere is no doubt that optical fiber technology is one of the most important stages of the communications revolution at all and it is of utmost importance in our daily life. In this work, five fibers with core radii 2.5, 4.5 and 6.5–8.5 μm were designed. The properties of all guided modes have been calculated at a wavelength of 1550 nm by using RP Fiber Calculator. A single-mode fiber is obtained when the core radius approaches the wavelength. As the core radius is increased, the fiber becomes a multimode. The percentage power in the core increases with increasing core radius. The modes profiles were illustrated and compared with the modern references.
Anatomical changes in internal tissue of stem and leaf when seed and plant treated with acids to enhance growth and development in maize was studied during the spring seasons of 2019 and 2020. Randomized complete block design was used with three replications. Main plots received foliar nutrition treatments, including ascorbic acid (AA), citric acid (CA), and humic acid (HA) at concentrations of 100 mg L−1, alongside HA at 1 ml L−1, with distilled water as the control. Sub-plots underwent corresponding treatments for seed soaking. Results indicated variations in vascular bundle size among treatments, with foliar CA treatment showing superior results in both years, as well as seed soaking in CA and HA. Interaction effects were observed, n
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreImage compression is a serious issue in computer storage and transmission, that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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