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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
Tue Dec 29 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Separation and Identification of Phenolic Acid from Borago officinalis (F:Boraginaceae) Cultivated in Iraq
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    The plant Borago officinalis, which belongs to the Boraginaceae family and Celebrated as borage, is one of the useful medicinal plants cultivated in Iraq. It was used in olde medicine in Iraq, Irane, Syria and Europe for management of various diseases. It is commonly used as an atonic, tranquilliser, management of cough, sore throat, pneumonia, swelling, inflammatory diseases, antioxidant, and anticancer. This project provides the first comprehensive research done in Iraq to study the phytochemicals and the methods of extraction and isolation of active constituents from Borago officinalis cultivated in Iraq. The plant was harvested in spring from AL-Rifai, Nassiriyah city, IRAQ in February 2019.were w

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Publication Date
Wed Jun 08 2022
Journal Name
International Journal Of Health Sciences
Isolation and identification of Aspergillus fumigatus from feline respiratory infection in Baghdad province
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Aspergillus fumigatus considered to be the most important species to cause respiratory infection cases in both humans and animals especially in cats in the last decades. In this study, we focused on the isolation and identification of Aspergillus fumigates by collecting 40 samples in deferent veterinary clinics and stray cats in Baghdad city, during the period (October 2021 to January 2022), all samples were cultured on Sabouraud dextrose agar and malt extract agar. The isolates identified by the laboratory methods, it’s depend on macroscopic and microscopic appearance. The results showed that (40) swaps taken from the pharynx of infected cats, included: Aspergillus fumigatus 16 (40%), Aspergillus spp. 7 (17.5%), Aspergillus niger

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Publication Date
Thu Mar 06 2014
Journal Name
Isolation, Screening, Identification And Improvement The Production Of Cellulase Produced From Iraqi Soil
Isolation, screening, identification and improvement the production of cellulase produced from Iraqi soil
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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Extraction and Identification of Phenolic Compounds from the Iraqi Heliotropium europaeum L. plant
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           The plants of genus Heliotropium L. (Boraginaceae) are well-known for containing the toxic metabolites called pyrrolizidine alkaloids (PAs) in addition to the other secondary metabolites. Its spread in the Mediterranean area northwards to central and southern Europe, Asia, South Russia, Caucasia, Afghanistan, Iran, Pakistan, and India, Saudi Arabia, Turkey, and over lower Iraq, Western desert. The present study includes the preparation of various extracts from aerial parts of the Iraqi plant. Fractionation, screening the active constituent, and identification by chromatographic techniques were carried out.Heliotropium  europaeum

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Identification and Purification of Cholera Like Toxin from Environmental Isolate of Vibrio cholerae
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The presence and prevalence of V. cholerae were investigated in forty five water samples collected from different locations of Tiger River/ Baghdad city. Twenty one isolates were isolated by adopting a simple isolation techniques. The final identification revealed that only three isolates were confirmed as V. cholerae. They were named 1J, 1R and Dial 131 which are all serogrouped as non-O1. Toxin Coregulated Pili (TCP) and heat labile enterotoxin (LT) were determined in only the environmental isolate 1J while non of the isolates produced heat stabile toxin (ST). The purification scheme was improved, few steps were adopted to include back extraction of ammonium sulfate, saturation between 80-20%, desalting through Sephadex G25, and gel filt

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
An Improved Diffie-Hellman Protocol Security Using Video Entropy
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The Diffie-Hellman is a key exchange protocol to provide a way to transfer shared secret keys between two parties, although those parties might never have communicated together. This paper suggested a new way to transfer keys through public or non-secure channels depending on the sent video files over the channel and then extract keys. The proposed method of key generation depends on the video file content by using the entropy value of the video frames. The proposed system solves the weaknesses in the Diffie-Hellman key exchange algorithm, which is MIMA (Man-in-the-Middle attack) and DLA( Discrete logarithm attack). When the method used high definition videos with a vast amount of data, the keys generated with a large number up to 5

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The psychometric Properties of Emotional Stability scale among university students according to the response theory
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The current research aims at extracting the standard characteristics of the emotional balance of the university students according to the response theory. This was accomplished by following accredited scientific steps, to achieve this goal, the researcher followed scientific steps in the procedures of the analysis of the scale. She translated the scale from English to Arabic and then made a reverse translation. it was presented to a committee of experts in English to ensure and verify the validity of the paragraphs logically and prove the face validity of the scale, which consists of (30) paragraphs, it was presented to (6) experts who are specialists in the educational and psychological sciences and in the light of their observations ha

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Publication Date
Fri Aug 10 2018
Journal Name
Ceramics International
Application of zirconia surface coating to improve fracture resistance and stress distribution of zirconia ceramic restorations
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Zirconia ceramic restoration (ZCR) has a higher fracture incidence rate than metal ceramic restoration. Different surface treatments were used to improve fracture performance of ZCR such as grit blasting (GB) by aluminium oxide powder. This type of surface treatment generate residual stresses on veneering ceramic causing crack initiation and ending with a fracture. In order to overcome the stress generated by GB, zirconia surface coating is used as a surface treatment to improve fracture resistance and to accommodate stresses along the ZCR layers. Fifty zirconia ceramic crowns were fabricated and divided according to the type of surface treatment into three groups; the first group is (ZG), involving 20 cores were coated with a mixture of pa

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Publication Date
Tue Sep 01 2020
Journal Name
Acta Polytechnica
COMPLEXITY REDUCTION OF CYCLOSTATIONARY SENSING TECHNIQUE USING IMPROVED HYBRID SENSING METHOD
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In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Slid

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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