Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the Maximum Likelihood method. Monte Carlo simulation was used with different skewness levels and sample sizes, and the superiority of the results was compared. It was concluded that (SND) model estimation using (GA) is the best when the samples sizes are small and medium, while large samples indicate that the (IR) algorithm is the best. The study was also done using real data to find the parameter estimation and a comparison between the superiority of the results based on (AIC, BIC, Mse and Def) criteria.
Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreAlternative distribution to estimate the Dose – Response model in bioassay excrement
This research concern to study five different distribution (Probit , Logistic, Arc sine , extreme value , One hit ), to estimate dose –response model by using m.l.e and probit method This is done by determining different weights in each distribution in addition find all particular statistics for vital model .
The current study aimed to determine the relation between the lead levels in the blood traffic men and the nature of their traffic work in Baghdad governorate. Blood samples were collected from 10 traffic men and the age about from 20-39 year from Directorate of Traffic Al Rusafa/ Baghdad and 10 samples another control from traffic men too with age 30-49 year and they livedrelatively in the clear cities or contained of Very few traffic areas. The levels of lead in blood estimated by used Atomic Absorption Spectrometry.
The result stated that there is no rising of the levels of lead in blood of traffic men Lead concentration was with more a range from 14 ppm in Traffic police are not healthy They are within the permissible limits, Ap
Background: Waterpipe and cigarette are two products of tobacco consumption, tobacco use has detrimental effects on the oral cavity, numerous studies around the world have reported a significant relationship between smoking and increase dental caries and viable count of cariogenic bacteria, Materials and Methods: unstimulated saliva was collected from 84 subjects and divided equally into three groups waterpipe smokers, cigarette smokers, and non-smokers all of the participants are adult male aged between 25-60 years, dental caries was measured by use DMFT index, while S.mutans and S.sobrinus were isolated by using a selective medium SB 20M (Sugar bacitracin-20 modified) agar Results: this present study showed a significant (p≤0.01)
... Show MoreOptimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol
Exposing the dorsal superficial skin of rats to partial-depth burn leads to bacterial and microbes Invasion. Topical treatment is required in most superficial burn cases Moist exposed burn ointment (MEBO) protects wounds from infection and enhances healing without any harmful effects of purified chemicals is caused. The topical using of HA gel in rat models with full and partial thickness surgical wounds shows enhancement in wound repair. In this study, we compared the healing efficacy of topical use of hyaluronic acid gel products with MEBO as standard management in rats that were exposed to a partial-thickness burn. The experiment included twenty-four (24) adult albino rats of male sex with weight (150-220 gm) of 3 months’ age divided i
... Show MoreWith the premise that effective use of online instructional practices is of vital importance in classrooms, the current study aimed to examine the effects of using Moodle applications to develop instructors’ skills in designing electronic tests at Dhofar University. The sample of this study consisted of (25) instructors participated in the experimental group. The researchers implemented a quasi-experimental design with one group pre- and post-test; in addition, an observation card was implemented to measure the target skills related to test design. The research instruments were subjected to validity and reliability measures to ensure valid and reliable data and results. The study results showed that those instructors who participated i
... Show MoreThe aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting
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