The present study included the microscopic and molecular identification of Entamoeba histolytica by using specific primers to detect four virulence factors possessed by Entamoeba histolytica. Virulence factors included Active Cysteine proteinase, Galactose/N-acetyl-D-galactose-lectin, Amoeba pore C and Phospholipase. Titanium dioxide nanoparticles (TiO2NPs) were synthesized from Pseudomonas aeruginosa which producing Pyocyanin pigment as a reducing agent to form it. After that we studied the ability ofTiO2NPs to inhibit virulence factors production and curing the genes responsible for encoding them by using four different dose 2 ,3, 4, 6 mg/Kg and administered by intraperitoneal injection to laboratory mice Mus musculus. The infection was molecularly confirmed, then the treatment for a period of ten days, as it was given on the third, fifth, seventh, and tenth days. The results of the study showed the inability of dose 2, 3 mg/Kg of TiO2NPs to curing the gene responsible for active cysteine proteinase and Gal/Gal NAC lectin upon treatment on the third to the tenth day, but was able to curing the genes when using dose (4,6) mg/Kg, Statistical analysis was performed , it was found that there were significant differences between the use of different dose and days of treatment. While Amoeba pore C, it was found that the four dose did not affect the inhibition on the third day of treatment. While dose 4,6 mg/Kg were able to curing the gene responsible for its encoding. Statistical analysis showed significant differences between the use of TiO2NPs and the days of treatment. Finally, the results showed that the four doses do not affect on phospholipase. Once, performing the statistical analysis it was found that there were no significant differences.
Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto
... Show MoreFor several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.
The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz
... Show MoreIndividuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect
... Show MoreThe seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
... Show MorePavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit
... Show MoreGlaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to other eye illness such as myopia and cataracts. The impact of glaucoma can’t be cured; The Disc Damage Likelihood Scale (DDLS) can be used to assess the Glaucoma. The proposed methodology suggested simple method to extract Neuroretinal rim (NRM) region then dividing the region into four sectors after that calculate the width for each sector and select the minimum value to use it in DDLS factor. The feature was fed to the SVM classification algorithm, the DDLS successfully classified Glaucoma d
HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
The aim of this study is to identify the effectiveness of a rational, emotional, behavioral program in developing self-efficacy to reduce the level of Burnout in 20 teachers of students with autism disorder in Jazan, Saudi Arabia. The proposed program included 12 training sessions. The researcher found that the proposed program has contributed significantly to the development of self-efficacy and reduce the level of Burnout for the targeted subject in this study.
The research aims to measure the psychological security of social working in the courts, to measure the motivation of achievement for social researchers working in the courts. In addition to, identify the Psychological security and its relation to the motivation of achievement for social researchers working in the courts. To achieve these aims, the researcher adopted two scales: Maslow scale for Psychological security, which was translated to Arabic by Dwany and Dirany 1983 consisted of (75) items. The second scale is Othman scale for achievement motivation 2014 consisted of (24) items. The two scales had been applied to a sample consisted of (100) social researchers working in the courts of Baghdad with its two branches Al-karkh and Al-
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