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jih-2617
Parametric Models in Survival Analysis for Lung Cancer Patients
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    The aim of this study is to estimate the survival function for the data of lung cancer patients, using parametric methods (Weibull, Gumbel, exponential and log-logistic).

Comparisons between the proposed estimation method have been performed using statistical indicator Akaike information Criterion, Akaike information criterion corrected and Bayesian information Criterion, concluding that the survival function for the lung cancer by using Gumbel distribution model is the best. The expected values of the survival function of all estimation methods that are proposed in this study have been decreasing gradually with increasing failure times for lung cancer patients, which means that there is an opposite relationship failure times and survival function.

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Economic Analysis for Construction in Ibn Khalduon s’ Muqaddimah
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The specialist researcher  fined the relations between economic ideas with economic facts in his theory which called humanity building it is appeared clearly ( in Ibn Khalduons’ Muqaddimah) in a clothe of economic  social  phenomenon's as a systematical analysis in all fifty chapters of al Muqaddimah ,therefore this paper deal with  Ibn Khalduon economic thoughts as important says which describe the society building in its economic subjective  and  examine the relationship between The dissert and the city within economic says which are cover  the social analysis ,and determinate   the analysis objects  which clearly in this dualism  model ,between the state and economic bas

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare to the conditional logistic regression models with fixed and mixed effects for longitudinal data
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Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Evaluation of some Virulence Factors and Drug Resistance of Bacteria Isolated from the Urine of Patients with TCC-Bladder Cancer
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Urinary tract infections (UTIs) mean microbial pathogens in the urethra or bladder (lower urinary tract). Important risk factors for recurrent UTI include obstruction of the urinary tract, use of a bladder catheter or a suppressed immune system. This study aims to isolate and identify bacteria from patients with TCC-bladder cancer or patients with a negative cystoscope and estimate antibiotic susceptibility patterns and evaluate some of the virulence factors. From a total of 62 patients with TCC-BC or negative cystoscope, only 35 favorable bacterial growths were obtained, including Escherichia coli (UPEC), a significant bacterial isolate, and Stenotrophomonas maltophilia. The percentage of multi drug-resistance bacteria

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The 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

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Publication Date
Mon Mar 23 2020
Journal Name
International Journal Of Nanoscience
Gold Nanoparticles Synthesis Using Environmentally Friendly Approach for Inhibition Human Breast Cancer
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In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Small Nuclear RNA 64 (snoRNA64): A novel Tumor Biomarker for Pancreatic Cancer
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The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Low-Rate High-Quality Parametric Audio Coder based on Sinusoidal plus Noise Representations
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This paper presents a parametric audio compression scheme intended for scalable audio coding applications, and is particularly well suited for operation at low rates, in the vicinity of 5 to 32 Kbps. The model consists of two complementary components: Sines plus Noise (SN). The principal component of the system is an. overlap-add analysis-by-synthesis sinusoidal model based on conjugate matching pursuits. Perceptual information about human hearing is explicitly included into the model by psychoacoustically weighting the pursuit metric. Once analyzed, SN parameters are efficiently quantized and coded. Our informal listening tests demonstrated that our coder gave competitive performance to the-state-of-the- art HelixTM Producer Plus 9 from

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Publication Date
Thu Apr 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solution of Population Growth Rate Linear Differential Model via Two Parametric SEE Transformation
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The integral transformations is a complicated function from a function space into a simple function in transformed space. Where the function being characterized easily and manipulated through integration in transformed function space. The two parametric form of SEE transformation and its basic characteristics have been demonstrated in this study. The transformed function of a few fundamental functions along with its time derivative rule is shown. It has been demonstrated how two parametric SEE transformations can be used to solve linear differential equations. This research provides a solution to population growth rate equation. One can contrast these outcomes with different Laplace type transformations

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