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Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs
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Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent Hur and amplitude-aware permutation entropy AAPE features were extracted from the EEG dataset. k -nearest neighbors kNN and support vector machine (SVM) classification techniques were considered for automatic gender recognition from emotional-based EEGs. The main novelty of this paper is twofold: first, to investigate Hur as a complexity feature and AAPE as an irregularity parameter for the emotional-based EEGs using two-way analysis of variance (ANOVA) and then integrating these features to propose a new CompEn hybrid feature fusion method towards developing the novel WT _ CompEn gender recognition framework as a core for an automated gender recognition model to be sensitive for identifying gender roles in the brain-emotion relationship for females and males. The results illustrated the effectiveness of Hur and AAPE features as remarkable indices for investigating gender-based anger, sadness, happiness, and neutral emotional state. Moreover, the proposed WT _ CompEn framework achieved significant enhancement in SVM classification accuracy of 100%, indicating that the novel WT _ CompEn may offer a useful way for reliable enhancement of gender recognition of different emotional states. Therefore, the novel WT _ CompEn framework is a crucial goal for improving the process of automatic gender recognition from emotional-based EEG signals allowing for more comprehensive insights to understand various gender differences and human behavior effects of an intervention on the brain.

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Publication Date
Thu Jul 03 2025
Journal Name
Circular Economy And Sustainability
Green Supplier Selection in the Iraqi Food Industry: Criteria Analysis and Barriers to Implementation
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This study explores the barriers to adopting green environmental criteria in Supplier Selection (SS) within the Iraqi food industry. It aims to enhance the understanding of sustainable supply chain management in developing nations, with a particular focus on the Iraqi context. A case study approach was utilized to identify eleven key green environmental criteria and 54 sub-criteria, alongside seven major barriers to their adoption. The Best–Worst Method (BWM) was employed to rank the criteria, and Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) was used to prioritize the barriers. The analysis revealed that Environmental Management Systems are the most critical criterion for SS. On the other hand, legislation and policies emerged

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Publication Date
Fri Oct 01 2021
Journal Name
Theory And Practice In Language Studies
Critical Discourse Analysis and Rhetorical Tropes in Donald Trump’s First Speech to the UN
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Language and politics go hand in hand and learning and comprehending political genre is to learn a language created for codifying, extending and transmitting political discourse in any text/talk. Drawing upon the theoretical framework of Fairclough’s CDA and Rhetoric, the current study aims at investigating Donald Trump’s First Speech, from the point of frequency and functions of some rhetorical strategies (Parallelism, Anaphora and the Power of Three, Antithesis and Expletive, etc.), Nominalization, Passivization, We-groups and Modality as well as Lexical and Textual Analysis, presented to the UN delivered on Sep. 19, 2017. Specifically, the study seeks to determine: (1) how President Trump succeeded in conveying his notions an

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Analysis for Hybrid Massive MIMO FSO/RF Links Based on Efficient Channel Codes
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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program to Improve some Aspects of Sensory Integration Disorder and Its Effect on Self-Direction Among a Sample of Children with Intellectual Disabilities
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The present research was conducted to investigate the effectiveness of a training program to improve some aspects of sensory integration disorder and its effect on self-direction among a sample of children with intellectual disabilities. The study sample consists of (10 subjects as an experimental group) were exposed to the training program، and the control group consists of (10 subjects as a control group) were not exposed to the training program. The study included the following tools: A scale of self-direction for intellectual disability (prepared by the researcher). Training program (prepared by the researcher). The Results of the study showed the following: There are no statistically significant differences between the means ranks

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Bilinear System Identification Using Subspace Method
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In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Laplacian Operator as Speaker Identification Parameter
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New speaker identification test’s feature, extracted from the differentiated form of the wave file, is presented. Differentiation operation is performed by an operator similar to the Laplacian operator. From the differentiated record’s, two parametric measures have been extracted and used as identifiers for the speaker; i.e. mean-value and number of zero-crossing points.

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Publication Date
Mon Feb 01 2021
Journal Name
Pakistan Journal Of Medical & Health Sciences
Entamoeba histolytica, identification in asymptomatic infection
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Background: Reliable detection the etiological agent of amoebic dysentery and extra-intestinal amoebiasis have Public health importance specially in asymptomatic human and animals, Since the acquisition of pet dogs in the recent period has become widespread in our city. Aim: To give correct perception of infection rate in asymptomatic individuals (human and domestic dogs) for the first aspect and about detection and diagnosis of the pathogenic species of Entamoeba histolytica from another morphologically similar and commensal one using the molecular technique in stool samples of asymptomatic individuals the second aspect. Methods: During the study period from the beginning of September 2020 to the end of February 2021, a total of 95 stool s

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Publication Date
Tue Oct 19 2021
Journal Name
Big Data Summit 2: Hpc & Ai Empowering Data Analytics 2018 | Conference Paper
Deep Bayesian for Opinion-target identification
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The use of deep learning.

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Identification Party of University Students
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The Political loyalties of the individual considered as the most important democracies through direct psychological identification in a particular party. The political parties regarded as the important elements and the foundations of the democratic system. They have effective interaction between the voters and the government institutions. The aim of the current research is to identify the quality of Islamic, the Civilian parties, and the most preferred for students. also, the research attempt to identify the level of identification  party that the  university students have, and the difference of identification party  according to the gender (male, female), the difference of of social class (upper, middle, poor). The sample

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