A series of laboratory experiments were conducted in the Multiphase Flow Research Laboratory (MFRL) at Lakehead University to investigate the effect of release height on themotion of particle clouds produced from rela...
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A series of laboratory experiments were conducted in the Multiphase Flow Research Laboratory (MFRL) at Lakehead University to investigate the effect of release height on themotion of particle clouds produced from relatively large mass of sand particles. Sand particles with median diameters of D-50 = 0.507 mm and an initial volumetric sand concentration of co = 60% were released through a 6-mm nozzle. Different release heights were tested in this study providing non-dimensional release heights ranged from eta = 1 to 21. A wide range of sand masses was tested and the effect of sand mass and nozzle diameter was represented by an aspect ratio ranged between 46 and 93. The velocity fluctuations and turbulent intensity of sand particles in the cloud were calculated from the time-series data. It was found that particle velocity fluctuations increase with increasing the mass of sand particles and reducing nozzle diameter. The variations of penetration length and width of particle clouds with time were measured and the frontal velocity of particle clouds were calculated from the measurements. The characteristics of particle cloud released above the water surface were compared with that of sand particles released from the water surface as a benchmark test. For sand particles with high sand mass and small nozzle size (i.e., large aspect ratio), cloud's width increased dramatically when sand particles were released above the water surface (i.e., eta > 1). In addition, the horizontal dispersion of sand particles began earlier when sand particles were released above the water surface, and particle clouds reached the cloud's deeper penetration length and width.
Traffic signs, which provide visual representation, play key role in autonomous navigation. Thus, detection and classification of traffic signs are one of the key requirements in autonomous vehicles (AVs). AVs heavily...
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ISBN:
(纸本)9781728163390
Traffic signs, which provide visual representation, play key role in autonomous navigation. Thus, detection and classification of traffic signs are one of the key requirements in autonomous vehicles (AVs). AVs heavily rely on object detection techniques to classify the traffic signs. In recent years, deep convolutional neural networks (CNNs) such as Faster R-CNN have achieved incredible success on objectdetection such as traffic signs. This paper focuses on the evaluation of state-of-the-art traffic signs detectiontechniques using deep learning algorithms and determination of the optimal one that can efficiently detect the traffic signs in real-time. Applying Faster R-CNN, the real-time traffic sign detection shall allow the autonomous vehicles to make decisions in real-time.
detection of object and recognition of objects in real world computing environment is one of the challenging tasks in computer vision. To solve this task there are many challenges in designing algorithm, we have to in...
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ISBN:
(纸本)9781538681909
detection of object and recognition of objects in real world computing environment is one of the challenging tasks in computer vision. To solve this task there are many challenges in designing algorithm, we have to introduce different and innovative techniques to detect objects in natural environments. Image security is of high importance in various applications including military, medical and many others. Security is one of the most challenging aspects in the internet and network applications. Encrypting entire image is very slow. Selective encryption is a scheme which intends to save computational power, network resources, and execution time. To encrypt object selectively object detection techniques are used. This technique is one of the most promising solutions to increase the speed of encryption as compared to the traditional encryption techniques. Selective encryption is helpful for the multimedia contents like image, video and audio. The compression ratio achieved is very high, since we store only the residues of extracted pixel of an image. So this paper discussed about Selective encryption with object detection technique.
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