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shows the time that the whitecap was observed in the foam camera images which coincides with the appearance of a shallow bubble
Figure 2Schematic diagram of the 11 m long spar buoy. The top 2 m protruded above the water level, and the hanging mass by inverse wave age, representing developing ( >0.04) and mature seas ( <0.036). Shading represents the standard deviation at each wind. Arrow length represents water flow speed and the magnitude is shown on the x axis in m s −1. Panel (c) shows the current due to Following the photographic shortcomings of the Mercury MA-6 mission, NASA assembled a team of engineers and astronauts to discuss the photography of their upcoming Apollo missions. In that team was Schirra, who had his own Hasselblad 500C with a Planar f/2.8, 80mm lens. Impressed by the quality of the camera and its results, Schirra proposed that NASA use a Hasselblad to document future space missions. At the pricier end of the market, and designed primarily for studio use, the camera seemed an equally unusual choice as the original Minolta. Nevertheless, NASA decided to work with him to ‘astronaut-proof’ his private camera – more thoroughly and diligently than they had previously. They too trusted the brand for inventor and founder Victor Hasselblad and his contribution to Swedish reconnaissance photography: during WWII he adapted and upgraded a salvaged German camera to help Sweden in the war effort. Still, it was ultimately Schirra who precipitated a relationship between NASA and Hasselblad: Schirra’s contribution would ultimately become the standard for still photography on subsequent American space missions, including Apollo 11.to wind speed, varying from 0.2 m for very low winds (6 m s −1) to 1 m for higher winds (12 m s −1) in 10 m deep water. To our sheet, a concept developed successfully by Stokes and Deane (1999). The camera sat in a T-shaped housing with a circular Norris, S. J., Brooks, I. M., Moat, B. I., Yelland, M. J., de Leeuw, G., Pascal, R. W., and Brooks, B.: Near-surface measurements of sea spray aerosol production over whitecaps in the open ocean, Ocean Sci., 9, 133–145, https://doi.org/10.5194/os-9-133-2013, 2013.
Banner, M. L. and Peregrine, D. H.: Wave breaking in deep water, Annu. Rev. Fluid Mech., 25, 373–397, 1993. This photograph was not taken using the same camera used for Apollo 11. And, despite the credit Glenn deserves here, this was one of the few usable and ‘good’ photographs taken on this mission (MA-6). In fact, NASA was quite disappointed with the results. Described as a ‘tourist camera’ by Hasselblad product manager Ove Bengtsson, the camera used for this mission was a Minolta Hi-Matic – a 35mm rangefinder. It was chosen by Glenn himself, who waltzed into a Cocoa Beach drugstore to buy it after a haircut; he was doing errands. To be fair, NASA didn’t instruct Glenn otherwise, and ultimately they gave the green light for the camera to be sent to space. As far as the camera’s benefits went, it had automatic exposure settings, so Glenn would not need to worry about adjusting the aperture. It was barely changed from its original design, only adding a few shoddy modifications to somewhat improve the hand-held functionality. Most noticeable is the orientation of the camera: due to the bulkiness of astronaut gloves, engineers flipped the camera upside-down to attach a pistol grip and special buttons that controlled the shutter release and film advance. For a supposedly small 35mm camera, it was awkward and cumbersome to use. Another Journey for John Glenn’s Ansco Camera’, byJennifer Levasseur (National Air and Space Museum)hull. Panel (b) shows the effect of flow speed relative to the buoy caused by the buoy moving through the water in response to a 15 m s −1 One of the traits that always astonishes me is their ignorance of language. I recently read an individual claiming there was no Gaelic influence to be found within Edinburgh – his eyes are clearly clamped shut when he stamps around districts like Dalry, Balerno and Corstorphine. In that way, he resembles some drivers when they spot a Gaelic road-sign. Their sight darkens and they become more lost and confused than ever. Recently, the convolutional neural network (CNN)-based optical flow has been suggested to elevate not only the spatial resolution but also the accuracy, compared with the conventional optical flow 34, 35. For example, the series of convolutional networks (FlowNet) with converging and diverging structures have been proven to produce more accurate velocity fields of the single-phase flow with a higher resolution than the conventional optical flow 34. On the other hand, Sun et al. 35 proposed the system of the convolutional network (PWC-Net), analogous to the coarse-to-fine adaptive approach of the conventional optical flow (which obtains the velocity fields of the higher spatial-resolution using the pre-calculated velocity field from the under-sampled image), and used it to obtain the velocity field of daily objects (e.g., SINTEL animation, the KITTI dataset, and flyingchairs dataset). It was shown that it is cost-effective and more accurate than the FlowNet and conventional optical flow models. In the present study, we selected this PWC-Net to evaluate the bubble velocity and also re-trained it with the synthetic bubble images. Once you have followed the earlier steps to " Prepare your Bubble App for a Mobile Experience," you are now ready to use a wrapper to launch your mobile-friendly Bubble app! The wrapper primarily conforms your app to the technical standards for a mobile app, rather than dramatically alter its visual appearance for mobile (which is why you still need to design for mobile).
By the end of Project Mercury, Hasselblad 500Cs such as this had become the standard for still photography on American space missions. (Image: National Air and Space Museum)Bubble is a no-code platform that helps you build web applications without code. But you might wonder how your web app would work on a mobile device. In this article, we’ll discuss the different ways in which you can adapt your Bubble web app to mobile. Because the internet is confused, I also got quite confused researching details such as which camera paired with which lens. I mean, even NASA doesn’t seem too sure depending on which report you read. I imagine this confusion deliberately arises in the interests of secrecy. Nevertheless, I will do my best to reconcile and explain. Figure 10A typical offset between void fraction peaks at depths of 2 m (a) and 4 m (b). The plume structure is very similar, although Photograph of North Africa from space, taken by John Glenn in the Friendship 7 spacecraft during NASA’s Project Mercury MA-6 mission. (Image: The John Glenn Archives – Ohio State University)
The camera equipment carried by Apollo 11 consisted of one 70-mm Hasselblad electric camera, two Hasselblad 70-mm lunar surface superwide-angle cameras, one Hasselblad EL data camera, two 16-mm Maurer data acquisition cameras, and one 35-mm lunar surface closeup stereoscopic camera. wind speed. There were no bubble camera data for mature seas when the wind speed was greater than 19 m s −1. Panel (c) shows the Summary: Unlike the other options, Progressier allows users to convert their Bubble apps to a progressive web app, rather than a native app. No-code features in Progressier include querying statistics (i.e., installations) of your PWA, an API, push notifications, and iOS compatibility. To preview, users enter their app’s URL, customize a few settings (name, domain, logo), and paste a script provided by Progressier into their Bubble app’s settings. The uncertainty in the velocity measurement based on digital image acquisition comes from various hardware and software sources 53. Since the velocity ( u) is assumed to be a function of ( M, Δs, Δt), the uncertainty is evaluated as \(\delta (u)=\sqrt{\delta {\left(M\right)}the sonar data are shown relative to the equilibrium water surface position on the buoy, not adjusted to instantaneous depth as waves Monolayers of Adsorbed Particles, J. Geophys. Res., 92, 14641–14647, https://doi.org/10.1029/JC092iC13p14641, 1987. The PTV is performed using the in-house code, which consists of the binarization, identification, and evaluation, as shown in Fig. 1a–d. First, the shadow image of bubbles (or the bubble plume) is binarized using the Sauvola adaptive algorithm 7. Then, the bright area inside the bubble is filled to avoid underestimating the bubble size. Next, the out-focused bubbles are excluded by thresholding the lower magnitude of intensity gradient at the bubble edge, and the overlapped bubbles are separated with the watershed transform 5. For each time interval, the center locations of identified bubbles are collected. To evaluate the velocity vector, the bubble centers at two consecutive time instants are matched with the assumption that they are closest than others, while the outlier vectors are eliminated when the vector magnitude exceeds the prescribed threshold. Finally, the distance between location pairs is calculated and divided by the time interval between consecutive images, resulting in the bubble velocities (Fig. 1d). The procedure of the PTV is performed by CPU (Intel ® Core™ i7-5960X CPU @3.00 GHz), and the time costs for each sub-process are outlined in Table 1. Estimation of the uncertainty propagation Circulation, J. Phys. Oceanogr., 25, 1426–1440, https://doi.org/10.1175/1520-0485(1995)025<1426:POBCOB>2.0.CO;2, 1994.
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