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.
In this current work, Purpose; to clearly the fundamental idea for constructing a design and
investigation of spur gear made of composite material its comes from the combination of (high
speeds, low noise, oil-les running, light weight, high strength, and more load capability)
encountered in modern engineering applications of the gear drives, when the usual metallic gear
cannot too overwhelming these combinations.
An analyzing of stresses and deformation under static and dynamic loading for spur gear tooth
by finite element method with isoparametric eight-nodded in total of 200 brick element with 340
nods in three degree of freedom per node was selected for this analysis. This is responsible for the
catastropic fa
The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element
... Show MoreThe cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 MeV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for eac
... Show MoreThe influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
... Show MoreA hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreThis research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr
... Show MoreBackground: The discriminative power of the classical WHO parameters in relation to male fertility is quite low, because they only address few aspects of sperm quality and function. This has led investigators to focus their attention on the male gamete and in particular its genome.Objective: To explore which of the sperm DNA damage parameters measured by comet assay are more reliable, and their relations with the standard semen parameters.Methods: Study was done on 40 infertile men selected from couples attending the Institute of Embryo Reasearch and Infertility Treatment at Al-Kadhimiya City/ Baghdad in the period between February 2009 and May 2009, with a history of infertility of ≥1 years; and 15 healthy volunteers of proven fertili
... Show MoreBackground: Bacterial DNA released upon bacterial autolysis or killed by antibiotics, hence, many inflammatogenic reactions will be established leading to serious tissue damage. Aim: the present work aimed to elucidate the histopathological changes caused by prokaryotic (bacterial) DNA and eukaryotic (candidal) DNA. Materials and methods: twenty one Staphylococcus aureus and 36 Candida albicans isolates were isolated from UTI patients. Viable cells and DNA of the highest antibiotic sensitive isolates were injected, intraurethraly, in mice. Results were evaluated via histopathological examination. Results: Mildest reactions were obtained from mice challenged with viable C. albicans compared with those challenged with viable S. aureus. Dos
... Show MoreAkaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).