The current study uses the flame fragment deposition (FFD) method to synthesize carbon nanotubes (CNTs) from Iraqi liquefied petroleum gas (LPG), which is used as a carbon source. To carry out the synthesis steps, a homemade reactor was used. To eliminate amorphous impurities, the CNTs were sonicated in a 30 percent hydrogen peroxide (H₂O₂) solution at ambient temperature. To remove the polycyclic aromatic hydrocarbons (PAHs) generated during LPG combustion, sonication in an acetone bath is used. The produced products were investigated and compared with standard Multi-walled carbon nanotube MWCNTs (95%), Sigma, Aldrich, using X-ray diffraction (XRD), thermo gravimetric analysis (TGA), Raman spectroscopy, scanning el

The researcher identified the objective of this research Do you know the impact of the way to solve problems in the achievement of the students in the fourth grade prep Islamic Education, and the researcher has identified the limits of the search, and the terms contained in the title researched and then offered the researcher previous studies relate to the subject studied, introduced Studies in Arab and foreign countries dealt with how to solve problems, the researcher identified the methodology discussed public represented by experimental method, and the sample consisted of two groups, one experimental and the other officer, and worked on the set of variables that may affect the results between the two groups in vkavot changers task, th

Leishmaniasis is one of the important parasitic diseases, affecting mainly low social class people indeveloping countries, and is more prevalent and endemic in the tropical and subtropical regions of old worldand new world. Despite ofbroad distribution in Iraq,little known about the geneticcharacteristics of thecausative agents. So this study was aimed to evaluate the genetic varietyoftwo IraqiLeishmaniatropicaisolatesbased on heat shock protein gene sequence 70 (HSP70) in comparison with universal isolates recordedsequences data. After amplification and sequencing of HSP70 gene,the obtainedresults were alignment alongwith homologous Leishmania sequences retrieved from NCBI by using BLAST. The analysis results showedpresence of particular g

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

As a result of the increase in wireless applications, this led to a spectrum problem, which was often a significant restriction. However, a wide bandwidth (more than two-thirds of the available) remains wasted due to inappropriate usage. As a consequence, the quality of the service of the system was impacted. This problem was resolved by using cognitive radio that provides opportunistic sharing or utilization of the spectrum. This paper analyzes the performance of the cognitive radio spectrum sensing algorithm for the energy detector, which implemented by using a MATLAB Mfile version (2018b). The signal to noise ratio SNR vs. Pd probability of detection for OFDM and SNR vs. BER with CP cyclic prefix with energy dete