Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

In this study water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals) using N-acetyl cysteine as a stabilizer were prepared to investigate the utility of quantum dots (QDs) in distinguishing damaged DNA, (extracted from blood samples of leukaemia patients), from intact DNA (extracted from blood samples of healthy individuals) to be used for biosensing application. Based on the optical characterization of the prepared QDs, the XRD results revealed the formation of the NAC-CdTe-QDs with a grain size of 7.1nm. Whereas, the SEM test showed that the spherical size of the NAC-CdTe-QDs lies within 11~33nm. NAC-CdTe-QDs have superior PL emission properties at of 550nm and UV-Vis absorption peak at 300nm. The energy gap

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro

The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio