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DIRICHLET PROCESS ANALYSIS USING BIORTHOGONAL WAVELET: A STATISTICAL STUDY OF FINANCIAL MARKET
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The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depends greatly on the choice of base distribution. The higher the value of α (a concentration parameter), the better the clustering and noise suppression. The distributional behavior of data can be approximated rigorously by the biorthogonal wavelet analysis. Since the Dirichlet process is an interesting object of observation, we computed it for a few wavelet bases and among them, we found that the Cohen-Daubechies-Feauveau (CDF) basis is the one that captures the Dirichlet process most accurately. Our results may be useful in applying the Dirichlet process to real-world experimental data and in developing Bayesian non-parametric methods.

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Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Tetracycline removal from aqueous solution through photo-anodic oxidation process using rotating graphite cylinder anode
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   In the present work, tetracycline (TC) was removed from a simulated wastewater through a new photo-anodic oxidation process with a rotating graphite cylinder anode. The effects of current density, pH, rotation speed, and NaCl addition were evaluated. The results confirmed that increasing the current density results in improving the removal of TC. However, increasing the current density beyond 5 mA/cm2 had little effect on TC removal. Results revealed that TC removal using photoanodic oxidation can be achieved at high performance with an initial pH of 5. Increasing or decreasing pH beyond this value has a negative effect on TC removal. Increasing rotation speed gave better performance for TC removal due to the increase in mass t

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Crossref
Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Analysis of actuarial experience and acceptance of individual life insurance: A case study in the Iraqi General Insurance Company
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This research seeks through the adoption of two basic variables, where he considered the actuarial experience as an independent variable, while the process of accepting the risk and dimensions related to it is a dependent variable, the research was adopted to present the data achieved by the company during the life insurance business during the adoption of actuarial experience at the beginning of its work where Adoption of the historical method in the analysis of those data to prove the researcher's opinion, through the analysis of data (5 years) for the first period, which extends between (1975-1979), the period during which the company adopted the actuarial experience at the time, also taken data for the same dimensions related to the

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of operational efficiency on some financial indicators according to the CAMEL model of banking financial stability: An applied research on a sample of Iraqi private banks for the period 2010-2020
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Abstract

          The research aims to determine the nature of the Iraqi market in terms of banking financial stability and the extent impact of the operational efficiency on it, Accordingly, chosen 15 relational banks were chosen as an intentional sample that could represent the Iraqi banking system for the period 2010-2020. The operational efficiency variable was measured according to the data envelope model, and banking financial stability used  CAMELS model which includes five indicators (capital adequacy, asset quality, management quality, profitability, and liquidity), so for testing the research hypotheses used the random regression model by adopting the S

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.: ELEMENTS OF MARKETING MIX AND THEIR ROLE IN CONSUMER PERCEPTION OF BRAND IMAGE: A SURVEY OF SAMPLE OPINIONS FROM CONSUMERS OF ENIEM BRAND IN THE ALGERIAN MARKET.
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The current research aimed to analyze the importance, correlation and the effect of independent variables represented by marketing variables on the dependent variable represented by local brand, through taking ENIEM as a model for this study, which represents a sensitive sector for the Algerian consumer. The results of the study evinced that the Algerian consumer has a positive image toward the brand ENIEM given marketing variables which has acquired considerable importance to this consumer. Also, the results of this study showed a statistically significant correlation between marketing variables and good perception toward the brand ENIEM, at the same time, the existence of a statistically significant effect for each of these variables o

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Measuring The Level of Complexity In The Process University – Case Study At The Southern Technical University.
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    Complexity is the inherent characteristic of contemporary organizations. It is characterized by the intertwining and expansion of its relations, by the severe disorder and rapid change in its environment, which makes it suffer from a state of uncertainty in determining the direction of its future or the assessment of the rules governing its paths. All organizations tend to evolve with increasing sophistication, And to take measures that contribute to the simplification of the system as it moves towards complexity, allowing the administration to easily control its movement and directions, and the problem of complexity in the university is based on the entanglement and overlap in the goals and processes betwe

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
A Prevalence study of Entamoeba spp. in Basrah Province using Different Detection Methods
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This study aims to determine the prevalence of Entamoeba histolytica, Entamoeba dispar and
Entamoeba moshkovskii by three methods of diagnosis (microscopic examination, cultivation and PCR) that
were compared to obtain an accurate diagnosis of Entamoeba spp. during amoebiasis. Total (n=150) stool
samples related to patients were (n = 100) and healthy controls (n= 50). Clinically diagnosed stool samples
(n=100) were collected from patients attending the consultant clinics of different hospitals in Basrah during
the period from January 2018 to January 2019. The results showed that 60% of collected samples were
positive in a direct microscopic examination. All samples were cultivated on different media; the Bra

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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