Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Krawtchouk-Tchebichef transform (DKTT) has a high energy compaction and provides a high matching between Laplacian density and its coefficients distribution that affects positively on reducing residual noise without sacrificing speech components. Moreover, a cascade combination of hybrid speech estimator is proposed by using two stages filters (non-linear and linear) based on DKTT domain to lessen the residual noise effectively without distorting the speech signal. The linear estimator is considered as a post processing filter that reinforces the suppression of noise by regenerate speech components. To this end, the output results have been compared with existing work in terms of different quality and intelligibility measures. The comparative evaluation confirms the superior achievements of the proposed SEA in various noisy environments. The improvement ratio of the presented algorithm in terms of PESQ measure are 5.8% and 1.8% for white and babble noise environments, respectively. In addition, the improvement ratio of the presented algorithm in terms of OVL measure are 15.7% and 9.8% for white and babble noise environments, respectively.
In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
... Show MoreThis study investigated the cubic intuitionistic fuzzy set of TM-algebra as a generalization of the cubic set. First, a cubic intuitionistic ideal and a cubic intuitionistic T-ideal are defined, followed by a discussion of their properties. Furthermore, the level set of a cubic intuitionistic TM-algebra is defined, and the relationship between a cubic intuitionistic level set and the cubic intuitionistic T-ideal is established. A novel definition of a cubic intuitionistic set under homomorphism is proposed, and several significant results are demonstrated.
This paper refers to studying some types of ideals, specifically cubic bipolar ideals and cubic bipolar T-ideals of TM algebra. It also introduces a cubic bipolar sub-TM-algebra and several important properties of these concepts. The relationships between these ideals and characterizations of cubic bipolar T-ideals are investigated.
Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing
... Show MoreAfamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum
... Show MoreThe personal drama in particular, and one of the key elements underlying the dramatic structure to convey ideas and visions presented by the author when writing the text of the dramatic fall after that on the way out the submission form that suits the proposals of the text and processors directorial would push the wheel of dramatic structure to the front. So take the maker of the artwork (writer) undertook the transfer of those events and personalities in art presumed sometimes real and sometimes, in order to enrich the art inspired by the human reality through the ages, and full of its themes and ideas that led to the development experiences of peoples experiences of living. Therefore, we find it important to research in the characters
... Show MoreThe 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
... Show MoreThe research problem revolves around the Iraqi public's use of digital television and cinematic websites، and their importance to the academic study and society، as it examines the public's relationship with these websites، usage habits، and the reasons for their interaction with them. And for the prevalence of this phenomenon of use، it was necessary to address the intensity، intentionality، and timing of use to theoretically root the subject of the study، which is one of the modern studies in Iraq and the Arab world. The survey approach، where the research was based on the theory of uses and gratifications that confer positivity and activity on the mass media audience.
The researchers designed
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