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DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms represented by Iteratively Weighted Kalman Filter Smoothing (IWKFS) algorithm and in combination with the Expectation Maximization (EM) algorithm. Average Mean Square Error (AMSE) and Cross Entropy Error (CEE) were used as comparison’s criteria. The methods and procedures were applied to data generated by simulation using a different combination of sample sizes and the number of intervals.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Discrete wavelet based estimator for the Hurst parameter of multivariate fractional Brownian motion
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Abstract<p>In this paper, wavelets were used to study the multivariate fractional Brownian motion through the deviations of the random process to find an efficient estimation of Hurst exponent. The results of simulations experiments were shown that the performance of the proposed estimator was efficient. The estimation process was made by taking advantage of the detail coefficients stationarity from the wavelet transform, as the variance of this coefficient showed the power-low behavior. We use two wavelet filters (Haar and db5) to manage minimizing the mean square error of the model.</p>
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods of Estimating the Parameters and Survival Function of a Log-logistic Distribution with a Practical Application
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The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study the Characteristic Performance of Trickling Filter for Pharmaceutical Waste Treatment
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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison between diode laser and scalpel for lip lengthening in patients with gummy smile
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Background: lip lengthening procedure is one of the surgical options for the correction of gummy smile in patients with short upper lip. Methods: A comparative clinical study was conducted on 15 patients requiring lip lengthening procedure for the esthetic correction of excessive gingival exposure with gummy smile. Scalpel was used in seven patients and diode laser in the remaining eight patients. Under infiltration anesthesia, about one cm strip of mucosa was excised at the vestibular depth and the mucosa of the lip was sutured to the alveolar mucosa. Results: The diode laser group demonstrated less postoperative pain and swelling. Regarding postoperative ecchymosis, three patients in the scalpel group developed ecchymosis and no cases

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
The Approximation of Weighted Hölder Functions by Fourier-Jacobi Polynomials to the Singular Sturm-Liouville Operator
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      In this work, a weighted H lder function that approximates a Jacobi polynomial which solves the second order singular Sturm-Liouville equation is discussed. This is generally equivalent to the Jacobean translations and the moduli of smoothness. This paper aims to focus on improving methods of approximation and finding the upper and lower estimates for the degree of approximation in weighted H lder spaces by modifying the modulus of continuity and smoothness. Moreover, some properties for the moduli of smoothness with direct and inverse results are considered.

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
The Direct Gene Injection Using of Egg Yolk Emulsion as Carrier and its Comparison with Liposomes.
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The efficiency of egg yolk emulsion in coating DNA and its delivery across cellular membranes was evaluated in comparison with liposomes DOPE . The murine leukemia viral oncogene v-abl , cloned on pBR322 was used as a DNA substrate for direct injection into mice tissue . the DNA complexes were prepared by mixing the DNA with egg yolk emulsion and liposome . Each was directly injected into mice peritoneal cavity with proper control. The gene delivery was examined phenotypically by blood analysis and cytogenetic analysis . Chromosomal changes were detected in the bone marrow as from the fourth day post inoculation through the eleventh day when chromosomal ring s could be seen . this was accompanied by decrease in the WBC count ,

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Publication Date
Mon Jun 01 2026
Journal Name
Iraqi Journal For Computers And Informatics
Explainable Federated Learning for Brain Tumor Classification Using Multi-Source MRI Data
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Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

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Publication Date
Thu Jan 06 2022
Journal Name
Kuwait Journal Of Science
AVO analysis for high amplitude anomalies using 2D pre-stack seismic data
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Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

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Publication Date
Thu Jul 17 2025
Journal Name
International Journal Of Environmental Sciences
Inverse Kinematic Analysis For A 5 DOF Robotic Arm Using Deep Neural Network
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In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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