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jeasiq-1409
مقارنة طرائق تقدير معلمات توزيع كاما ذي المعلمتين في حالة البيانات المفقودة باستخدام المحاكاة
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The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best method through simulation by using the Monte Carlo Method. Several experimentations have been made by using the important statistical measure: Mean Square Error (MSE).

 

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Scopus (10)
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Biodegradation of Diesel Contaminated Soil Using Single Bacterial Strains and a Mixed Bacterial Consortium
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This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel  88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detecting Keratoconus by Using SVM and Decision Tree Classifiers with the Aid of Image Processing
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 Researchers 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

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Scopus (12)
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Biosynthesis, Characterization, Adsorption and Antimicrobial studies of Manganese oxide Nanoparticles Using Punica Granatum Extract
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie

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Scopus (3)
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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Beneficiation of Iraqi Akash at Phosphate Ore Using Organic Acids for the Production of Wet Process Phosphoric Acid
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In the present work, leaching process studiedusing organic acids (acetic acid and lactic acid) to extract phosphate from the Iraqi Akashat phosphate ore by separation of calcareous materials (mainly calcite). This approach characterized by energy conservation, environmental enhancement by recovery of calcite as calcium sulfate (gypsum), keeping the physical and chemical properties of apatite. Samples were analyzed using X-ray diffraction and FTIR spectrophotometer. From the obtained experimental data it was found that using the two organic acids yields closed purity values of the produced apatite at the optimum conditions, while at different acid concentrations, it was found that the efficiency of acetic acid is higher at the low acid co

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Sealing Depth of Q-Switched Nd:YAG 1064nm Laser in the Treatment of Patients with Hypersensitive Teeth: An In Vitro Study
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The purpose of this work was to study the effects of the Nd:YAG laser on exposed dentinal
tubules of human extracted teeth using a scanning electron microscope (SEM). Eighty 2.5mm-thick
slices were cut at the cementoenamel junction from 20 extracted human teeth with an electric saw. A
diamond bur was used to remove the cementum layer to expose the dentinal tubules. Each slice was
sectioned into four equal quadrants and the specimens were randomly divided into four groups (A to D ).
Groups B to D were lased for 2 mins using an Nd:YAG laser at 6 pulses per second at energy outputs of
80 , 100 and 120 mJ. Group A served as control. Under SEM observation, nonlased specimens showed
numerous exposed dentinal tubules. SEM o

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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Scopus (8)
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Mobility Models over UDP Traffic Pattern for MANET Using NS-2
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  The current study presents the simulative study and evaluation of MANET mobility models over UDP traffic pattern to determine the effects of this traffic pattern on mobility models in MANET which is implemented in NS-2.35 according to various performance metri (Throughput, AED (Average End-2-end Delay), drop packets, NRL (Normalize Routing Load) and PDF (Packet Delivery Fraction)) with various parameters such as different velocities, different environment areas, different number of nodes,  different traffic rates, different traffic sources, different pause times and different simulation times .  A routing protocol.…was exploited AODV(Adhoc On demand Distance Vector) and RWP (Random Waypoint), GMM (Gauss Markov Model), RPGM (Refere

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