An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification, including ResNet50, VGG19, and InceptionV4; They were trained and tested on an open-source satellite image dataset to analyze the algorithms' efficiency and performance and correlated the classification accuracy, precisions, recall, and f1-score. The result shows that InceptionV4 gives the best classification accuracy of 97% for cloudy, desert, green areas, and water, followed by VGG19 with approximately 96% and ResNet50 with 93%. The findings proved that the InceptionV4 algorithm is suitable for classifying oil spills and no spill with satellite images on a validated dataset.
This study aims to identify the role of satellite channels in imparting behavior to children from the point of view of their parents in Tulkarm city. The researcher used a descriptive technique. A sample of (18000) males and females married couples was used above 20 years old in the city of Tulkarm. The study sample size is (201) married couples. It took place in September 2020. The questionnaire was the main tool for collecting data. The study found that the total degree of satellite channels contribution in imparting negative behaviors to children was high, as it reached (72.20%). The total degree of the role of satellite channels in imparting positive behaviors to children was medium, reaching (69.20%). Moreover, the results also indi
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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The problem of research on the study of political debate programs in the Iraqi satellite channels, in the "People decide" program by Afaq channel and " electoral competition " by Fallujah channel), and its importance for the community and researchers in the scientific field, as new programs to enter the Iraqi media after we have been the world media a lot in this area at the academic and practical levels (The field), and seeks to find out what the technical construction of the programs of political debates in Iraqi satellite channels and methods of construction and methods of employment used by the technical elements in the presentation of the programs and The study adopted the surve |
In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreThe proliferation of manipulated multimedia content poses a significant threat in an era heavily reliant on social networks as primary information sources. Despite numerous countermeasures targeting specific attack types, the seamless nature of image manipulation challenges the differentiation between authentic and altered visuals. This study aims to detect fake images generated by StyleGAN2-ADA using watermark analysis and image content analysis techniques. The first experiment evaluates the performance of watermarking techniques in the spatial (Least Significant Bit (LSB)) and frequency (Discrete Cosine Transform (DCT)) domains using real-life imagery. Then, watermarked images are used as input to the StyleGAN2-ADA model to genera
... Show MoreThis research deals with issues of peaceful coexistence in foreign satellite channels directed in the Arabic language, trying to get acquainted with the most prominent of these topics dealt with the programs subject to analysis and the method of dealing with them and the most used journalistic arts in that.
The research adopted the descriptive approach and the method of content analysis for the purpose of studying the research community represented by the program «Shabab Talk» “Youth Talk” in the German channel Deutsche Welle (DW) and the program «Beina Sam wa Amar» “between Sam and Ammar” in the American free channel, by designing the content analysis form to subject
... Show MoreThe selection and assessment of single-photon detection modules is a crucial problem in satellite-based QKD systems. The system's overall efficiency, secure key rate and quantum bit error rate are all significantly influenced by single-photon detection modules. There is a knowledge gap about the practical performance of commercially available single-photon detectors because existing research frequently relies on theoretical characteristics. This paper introduces a study on the effect of the parameters of three commercial single photon detection modules from ID Quantique company: ID Qube, ID100, and ID281 on certain Bennett-Brassard 1984 protocol parameters such as secure key rate, mean photon number per pulse, quantum bit error rate
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
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