Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for de-noising noisy CCTV images. Data-store is used tomanage our dataset, which is an object or collection of data that are huge to enter in memory, it allows to read, manage, and process data located in multiple files as a single entity. The CAN architecture provides integral deep learning layers such as input, convolution, back normalization, and Leaky ReLu layers to construct multi-scale. It is also possible to add custom layers like adaptor normalization (µ) and adaptive normalization (Lambda) to the network. The performance of the developed CAN approximation operator on the bilateral filtering noisy image is proven when improving both the noisy reference image and a CCTV foggy image. The three image evaluation metrics (SSIM, NIQE, and PSNR) evaluate the developed CAN approximation visually and quantitatively when comparing the created de-noised image over the reference image.Compared with the input noisy image, these evaluation metrics for the developed CAN de-noised image were (0.92673/0.76253, 6.18105/12.1865, and 26.786/20.3254) respectively
Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica
... Show MoreThis research focuses on the services provided by news websites (IMN, Youm7, Huffington Post Arabic) to its audience of Internet users, as well as materials posted through its pages, trying to monitor and explain them to identify their types & features, and it›s functions, whether informational or non-informational, to know the technical potential of each of the news sites, with the entry of the latest technology information. The research used the analysis method to achieve the research objectives within the period from 1/1 to 31/1/2017. The researchers used the content analysis tool as a research tool to analyze the news sites and to know the services they provide through their pages. The research was divided into three parts, the
... Show MoreThe turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreThe dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreThis paper examines the impact of flexural strengthening on the percentage of damaged strands in internally unbonded tendons in partially prestressed concrete beams (0, 14.28%, and 28.57%) and the recovering conditions using CFRP composite longitudinal laminates at the soffit, and end anchorage U-wrap sheets to restore the original flexural capacity and mitigate the delamination of the soffit of longitudinal Carbon Fiber Reinforced Polymer (CFRP) laminates. The composition of the laminates and anchors affected the stress of the CFRP, the failure mode, and thus the behavior of the beam. The experimental results revealed that the usage of CFRP laminates has a considerable impact on strand strain, particularly when anchors are employed
... Show MoreThis paper has dealing with experimentally works which includes properties of materials and testing program. The testing program includes rotine characterization tests, chemical, and physical tests for samples of gypseous soil. Samples of disturbed and undisturbed soil was obtained of seven different locations of Salah-Aldeen province. The unified classification system was adopted of study region. Except sample 7, soil categorization (as poorly graded sand) was a good graded sand soil. Samples had non plasticity rate (NP). The results of laboratory tests (by using Arc-Map GIS program) were enhanced by spatial interpolation mapping utilizing Inverse Distance Weighted Scheme.
Ultrasonic extraction is an inexpensive, simple and efficient alternative to conventional extraction techniques, as compared with other novel extraction techniques such as microwave-assisted extraction & supercritical fluid extraction techniques, the ultrasound apparatus is cheaper and its operation is easier. Ultrasound assisted extraction has risen rapidly in the latest decade, and for most applications it has proven to be effective compared to traditional extraction techniques. In this paper, a method of ultrasonic-assisted extraction was used to extract Inulin from tubers of Jerusalem artichoke, which have been reported to have several medicinal properties and uses. Inulin is a storage carbohydrate found in many plants especially
... Show MoreThe problem of generated waste as a result of the implementation of construction projects, has been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accom
... Show MoreThe concept of intertextuality was one of the problems that occupied the attention of critics and critics in targeting the structure of textual intertextuality between texts and their overlap in the process of producing meaning. Until intertextuality became a stable term and it can be monitored in the structure of the theatrical text and determining the mechanisms of this intertextuality between texts through fields and classifications agreed upon by the most important critics who wrote and considered intertextuality. Perhaps our previous research (the approach of exposure in the epistemological hallway to intertextuality) was an attempt to interview a terminology, which the researcher intended to monitor, through the mechanisms of inter
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