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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
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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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Mon Oct 07 2024
Journal Name
Semiconductor Science And Technology
A facile method of deriving solar selective nickel-cobalt oxide thin films via spraying process
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Abstract<p>The present study focuses on synthesizing solar selective absorber thin films, combining nanostructured, binary transition metal spinel features and a composite oxide of Co and Ni. Single-layered designs of crystalline spinel-type oxides using a facile, easy and relatively cost-effective wet chemical spray pyrolysis method were prepared with a crystalline structure of M<sub>x</sub>Co<sub>3−x</sub>O<sub>4</sub>. The role of the annealing temperature on the solar selective performance of nickel-cobalt oxide thin films (∼725 ± 20 nm thick) was investigated. XRD analysis confirmed the formation of high crystalline quality thin films with a crystallite si</p> ... Show More
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Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The extent of the industrial company's response to blue market strategy indicators: Applied research
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The current research aims to describe the level of responsiveness and awareness of the officials of the General Company for Construction Industries to the indicators of the blue market strategy of (1. reduction 2. exclusion 3. increase 4. innovation) and the degree of prioritization according to their importance as well as the differences in the responses of the sample investigated according to the personal variables. As a main tool in the collection of data from the sample, which consisted of(34) officers (Associate, Manager, Section Manager, Division Officer) in the company being investigated, and computed mean, standard deviations, percentage weights,and test (x2 )  based on the SPSS. The research reached the following

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Publication Date
Wed Apr 01 2020
Journal Name
Plant Archives
Determination of heavy metals in tattoo inks from the local market in Baghdad city
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