Journal articles: 'Depth of field'

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Baylin, Eric. "Depth of Field/Depth of Understanding." Schools 7, no. 1 (May 2010): 86–100. http://dx.doi.org/10.1086/651297.

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Harper, Graeme. "Depth of Field." Creative Industries Journal 11, no. 3 (September 2, 2018): 223–24. http://dx.doi.org/10.1080/17510694.2018.1534414.

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Değirmenci, Koray. "Depth of field." Philosophy of Photography 5, no. 2 (December 1, 2014): 123–29. http://dx.doi.org/10.1386/pop.5.2.123_7.

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Vasudevan, Krishnan. "Depth of Field." Journalism Practice 13, no. 2 (January 4, 2018): 229–46. http://dx.doi.org/10.1080/17512786.2017.1419826.

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Brown, Deeadra. "Depth of field." Dialectical Anthropology 33, no. 2 (June 2009): 201–2. http://dx.doi.org/10.1007/s10624-009-9115-8.

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Soler, Cyril, Kartic Subr, Frédo Durand, Nicolas Holzschuch, and François Sillion. "Fourier depth of field." ACM Transactions on Graphics 28, no. 2 (April 2009): 1–12. http://dx.doi.org/10.1145/1516522.1516529.

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Zhang, Tingting, Louise O’hare, Paul B. Hibbard, Harold T. Nefs, and Ingrid Heynderickx. "Depth of Field Affects Perceived Depth in Stereographs." ACM Transactions on Applied Perception 11, no. 4 (January 9, 2015): 1–18. http://dx.doi.org/10.1145/2667227.

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Landers, Mark N., and David S. Mueller. "Evaluation of Selected Pier-Scour Equations Using Field Data." Transportation Research Record: Journal of the Transportation Research Board 1523, no. 1 (January 1996): 186–95. http://dx.doi.org/10.1177/0361198196152300123.

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Field measurements of channel scour at bridges are needed to improve the understanding of scour processes and the ability to accurately predict scour depths. An extensive data base of pier-scour measurements has been developed over the last several years in cooperative studies between state highway departments, the Federal Highway Administration, and the U.S. Geological Survey. Selected scour processes and scour design equations are evaluated using 139 measurements of local scour in live-bed and clear-water conditions. Pier-scour measurements were made at 44 bridges around 90 bridge piers in 12 states. The influence of pier width on scour depth is linear in logarithmic space. The maximum observed ratio of pier width to scour depth is 2.1 for piers aligned to the flow. Flow depth and scour depth were found to have a relation that is linear in logarithmic space and that is not bounded by some critical ratio of flow depth to pier width. Comparisons of computed and observed scour depths indicate that none of the selected equations accurately estimate the depth of scour for all of the measured conditions. Some of the equations performed well as conservative design equations; however, they overpredict many observed scour depths by large amounts. Some equations fit the data well for observed scour depths less than about 3 m (9.8 ft), but significantly underpredict larger observed scour depths.

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Moon, Won-Leep. "Depth of field and magnification." journal of the moving image technology associon of korea 1, no. 12 (June 2010): 25–41. http://dx.doi.org/10.34269/mitak.2010.1.12.002.

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Geuens, Jean-Pierre. "The Depth of the Field." Quarterly Review of Film and Video 31, no. 6 (June 2, 2014): 572–85. http://dx.doi.org/10.1080/10509208.2012.686812.

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Kuthirummal, S., H. Nagahara, Changyin Zhou, and S. K. Nayar. "Flexible Depth of Field Photography." IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 1 (January 2011): 58–71. http://dx.doi.org/10.1109/tpami.2010.66.

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12

Birkerts, Sven. "Reading and Depth of Field." Philosophy and Literature 20, no. 1 (1996): 122–29. http://dx.doi.org/10.1353/phl.1996.0004.

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13

Langan, Robert. "The Depth of the Field." Contemporary Psychoanalysis 29, no. 4 (October 1993): 628–44. http://dx.doi.org/10.1080/00107530.1993.10746829.

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Kim, Jaewon, Roarke Horstmeyer, Ig-Jae Kim, and Ramesh Raskar. "Highlighted depth-of-field photography." ACM Transactions on Graphics 30, no. 3 (May 2011): 1–9. http://dx.doi.org/10.1145/1966394.1966403.

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Poncet, Aurelie M., John P. Fulton, Timothy P. McDonald, Thorsten Knappenberger, Joey N. Shaw, and Rees W. Bridges. "Effect of Heterogeneous Field Conditions on Corn Seeding Depth Accuracy and Uniformity." Applied Engineering in Agriculture 34, no. 5 (2018): 819–30. http://dx.doi.org/10.13031/aea.12238.

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Abstract. Optimization of planter performance such as uniform seeding depth is required to maximize crop yield potential. Typically, seeding depth is manually adjusted prior to planting by selecting a row-unit depth and a row-unit downforce to ensure proper seed-soil contact. Once set, row-unit depth and downforce are usually not adjusted again for a field although soil conditions may vary. Optimization of planter performance requires automated adjustments of planter settings to varying soil conditions, but development of precision technologies with such capabilities requires a better understanding of soil-planter interactions. The objective of this study was to evaluate seeding depth response to varying soil conditions between and within fields and to discuss implications for development and implementation of active planting technologies. A 6-row John Deere MaxEmerge Plus planter equipped with heavy-duty downforce springs was used to plant corn ( L.) in central Alabama during the 2014 and 2015 growing seasons. Three depths (4.4, 7.0, and 9.5 cm) and three downforces (corresponding to an additional row-unit weight of 0.0, 1.1, and 1.8 kN) were selected to represent common practices. Depth and downforce were not readjusted between fields and growing seasons. Seeding depth was measured after emergence. Corn seeding depth significantly varied with heterogeneous soil conditions between and within fields and the planter failed to achieve uniform seeding depth across a field. Differences in corn seeding depth between fields and growing seasons were as high as 2.1 cm for a given depth and downforce combination. Corn seeding depth significantly co-varied with field elevation but not with volumetric soil water content. Seeding depth varied with elevation at a rate ranging from -0.1 cm/m to -0.6 cm/m. Seeding depth co-variation to field elevation account for some but not all site-specific seeding depth variability identified within each field trial. These findings provide a better understanding of site-specific seeding depth variability and issues to address for the development of site-specific planting technologies to control seeding depth accuracy and improve uniformity. Keywords: Depth control, Downforce, Planter, Precision agriculture, Seeding depth, Uniformity.

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Pidhorskyi, Stanislav, Timur Bagautdinov, Shugao Ma, Jason Saragih, Gabriel Schwartz, Yaser Sheikh, and Tomas Simon. "Depth of Field Aware Differentiable Rendering." ACM Transactions on Graphics 41, no. 6 (November 30, 2022): 1–18. http://dx.doi.org/10.1145/3550454.3555521.

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Cameras with a finite aperture diameter exhibit defocus for scene elements that are not at the focus distance, and have only a limited depth of field within which objects appear acceptably sharp. In this work we address the problem of applying inverse rendering techniques to input data that exhibits such defocus blurring. We present differentiable depth-of-field rendering techniques that are applicable to both rasterization-based methods using mesh representations, as well as ray-marching-based methods using either explicit [Yu et al. 2021] or implicit volumetric radiance fields [Mildenhall et al. 2020]. Our approach learns significantly sharper scene reconstructions on data containing blur due to depth of field, and recovers aperture and focus distance parameters that result in plausible forward-rendered images. We show applications to macro photography, where typical lens configurations result in a very narrow depth of field, and to multi-camera video capture, where maintaining sharp focus across a large capture volume for a moving subject is difficult.

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Mauderer, M., S. I. Conte, M. A. Nacenta, and D. Vishwanath. "Using Gaze-Contingent Depth of Field to Facilitate Depth Perception." i-Perception 5, no. 5 (August 2014): 473. http://dx.doi.org/10.1068/ii42.

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18

Li, B. "Simulation analysis of temperature field of permafrost roadbed." E3S Web of Conferences 136 (2019): 04077. http://dx.doi.org/10.1051/e3sconf/201913604077.

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The finite element analysis model of roadbed temperature field in permafrost region is established with finite element software platform. By using this model, the temperature field of roadbed is compared and analysed, and the freezing-thawing depth and variation rule of roadbed are studied. The results showed that the actual freezing depth was 1.8m. With the increase of the climate warming temperature, the temperature field in the roadbed changes slowly, and the temperature at different depths increases. Due to the influence of climate warming, the roadbed was in a complete positive temperature state when the maximum freezing depth appeared after 20 years. The result shown that the time of the roadbed appeared in the maximum freezing depth was earlier, the time of the roadbed in the seasonal freezing area became shorter, and the maximum freezing depth decreased.

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19

Johnston, Adrian M., and F. Craig Stevenson. "Field pea response to seeding depth and P fertilization." Canadian Journal of Plant Science 81, no. 3 (July 1, 2001): 573–75. http://dx.doi.org/10.4141/p00-166.

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A study was conducted at Melfort, SK, in 1998 and 1999 to determine whether seeding depth and P fertilization affect field pea (Pisum sativum L.) seedling emergence and grain yield. Treatments included a factorial combination of three seeding depths (38 mm, 76 mm, and 114 mm) with and without 25 kg P2O5 ha–1 as monoammonium phosphate. While seedling density was not affected by seeding depth at 3 wk after planting, the deepest seeding depth produced significantly fewer seedlings than the two shallower depths at 5 wk post-seeding. A year-by-seeding-depth interaction was recorded for grain yield, with deep seeding (114 mm) reducing yield by 8.5% in 1998, while no significant differences were recorded due to depth in 1999. Side-banded phosphorus fertilizer applications reduced seedling emergence at 3 wk; however, no difference was recorded by 5 wk after seeding. At harvest, addition of P fertilizer significantly increased grain yields on this high P testing soil; however, this response was small, averaging 138 kg ha–1. Results of this trial indicate that while field peas can tolerate deep seeding there appears to be little benefit from seeding deeper than 76 mm. Key words: Field pea, seeding depth, P fertilizer

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Hu, Jing, Sunzheng Li, Yibing Shen, JinLei Zhang, and Zhenrong Zheng. "Extended depth of field reconstruction with complex field estimation." Optics & Laser Technology 152 (August 2022): 108118. http://dx.doi.org/10.1016/j.optlastec.2022.108118.

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21

Abdelaal, Ahmed M., Ehab M. Attalla, and Wael M. Elshemey. "Estimation of Out-of-Field Dose Variation using Markus Ionization Chamber Detector." SciMedicine Journal 2, no. 1 (March 1, 2020): 8–15. http://dx.doi.org/10.28991/scimedj-2020-0201-2.

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Objective: The aim of This work to provide evaluation for the out-of-field dose with different plan parameters as field size and depth using Markus ionization chamber detector in the measurement that are frequently used in electron and superficial dosimetery, in radiotherapy. Methods: This is carried out through the application of these detector in estimation of the out-of-field dose with important dosimetric parameters such as field size (from 5×5 to 30×30 cm2) and depth (from 1.5 to 30 cm) at energy 6 MV and collimator angle 0° at SSD 100 cm. Results: Results show that, the Markus detector reported an increase in out-of-field dose with field size, depth in almost all measurements. For 6 MV and 0° collimator angle, the out-of-field dose at field size of 5×5 cm2 (depth of 1.5 cm) is 1.1% and at field size of 30×30 cm2 (depth of 1.5 cm) is 4.4% . The out-of-field dose for a depth of 1.5 cm (field size of 10×10 cm2) is 2.3% and for a depth of 30 cm (field size of 10×10 cm) is 5.5%. the measured out-of-field dose by Markus detector overestimated in the calculated at different field sizes (2.7% instead of 2.3% at field size of 10×10 cm2 and 5.2% instead of 4.4% at field size of 30×30 cm2) and different depths (2.7% instead of 1.1% at depth of 1.5 cm and 4.1% instead of 3.4% at depth of 30 cm). Analysis: The result reported an increase in mean out-of-field dose with field size, depth, energy and SSD. Markus ionization chamber detector show overestimation of the measured out-of-field dose in the calculated values at all field sizes and depths, this may be attributed to the poor detection of out-of-field dose by TPS.

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Higginbotham, J. H., Y. Shin, and D. V. Sukup. "Directional depth migration." GEOPHYSICS 50, no. 11 (November 1985): 1784–89. http://dx.doi.org/10.1190/1.1441867.

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Complicated geologic structures such as folds, overthrusts, and salt domes can produce reflectors with dips as great as 90 degrees. Because oil and gas accumulations are often associated with these steeply dipping interfaces, accurate processing of reflection seismic information from such areas becomes an important though challenging task. The proper imaging of steeply dipping reflectors requires accurate knowledge of the velocity field through which the wavefronts propagate. Thus, velocity analysis becomes extremely important. In addition to this problem, most migration algorithms have serious difficulties when dip is greater than about 50 degrees. In this discussion, we assume the velocity field is known, the data may be stacked correctly before migration, and the chief concern is migration accuracy. We describe a method for depth migration of very steeply inclined wavefronts through inhomogeneous velocity fields. The extension of the proposed technique to migration before stack is obvious.

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23

O'Hare, Louise, Tingting Zhang, Harold T. Nefs, and Paul B. Hibbard. "Visual Discomfort and Depth-of-Field." i-Perception 4, no. 3 (January 2013): 156–69. http://dx.doi.org/10.1068/i0566.

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Grobbe, Niels, Joost van der Neut, Evert Slob, Kees Wapenaar, Carlos Almagro Vidal, and Guy Drijkoningen. "Unified multi-depth-level field decomposition." Geophysical Prospecting 64, no. 2 (July 22, 2015): 361–91. http://dx.doi.org/10.1111/1365-2478.12290.

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Ledesma-Carrillo, Luis, Rafael Guzmán-Cabrera, Cristina M. Gómez-Sarabia, Miguel Torres-Cisneros, and Jorge Ojeda-Castañeda. "Tunable field depth: hyperbolic optical masks." Applied Optics 56, no. 1 (November 29, 2016): A104. http://dx.doi.org/10.1364/ao.56.00a104.

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Maurer, Christian, Saranjam Khan, Stephanie Fassl, Stefan Bernet, and Monika Ritsch-Marte. "Depth of field multiplexing in microscopy." Optics Express 18, no. 3 (January 28, 2010): 3023. http://dx.doi.org/10.1364/oe.18.003023.

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27

Higbie, Jack. "Depth of field in hologram images." Physics Teacher 35, no. 7 (October 1997): 418–19. http://dx.doi.org/10.1119/1.2344743.

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Gori, Paola, Gabriella Cincotti, and Massimo Pappalardo. "Beams with large depth of field." Journal of the Acoustical Society of America 107, no. 5 (May 2000): 2782. http://dx.doi.org/10.1121/1.428945.

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Meck, E., and V. Sirivivatnanon. "Field indicator of chloride penetration depth." Cement and Concrete Research 33, no. 8 (August 2003): 1113–17. http://dx.doi.org/10.1016/s0008-8846(03)00012-7.

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30

Sheppard, C. J. R. "Depth of field in optical microscopy." Journal of Microscopy 149, no. 1 (January 1988): 73–75. http://dx.doi.org/10.1111/j.1365-2818.1988.tb04563.x.

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31

Zhang, Lei, Jianpeng Fan, and Jungang Yang. "Blind-Depth Light Field Super-Resolution." Journal of Physics: Conference Series 1575 (June 2020): 012051. http://dx.doi.org/10.1088/1742-6596/1575/1/012051.

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Gómez-Sarabia, Cristina M., Luis Ledesma-Carrillo, and Jorge Ojeda-Castañeda. "Reducing field depth: annular Hadamard masks." Applied Optics 59, no. 22 (July 28, 2020): 6632. http://dx.doi.org/10.1364/ao.397862.

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Kim, Hyun Myung, Min Seok Kim, Sehui Chang, Jiseong Jeong, Hae-Gon Jeon, and Young Min Song. "Vari-Focal Light Field Camera for Extended Depth of Field." Micromachines 12, no. 12 (November 26, 2021): 1453. http://dx.doi.org/10.3390/mi12121453.

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The light field camera provides a robust way to capture both spatial and angular information within a single shot. One of its important applications is in 3D depth sensing, which can extract depth information from the acquired scene. However, conventional light field cameras suffer from shallow depth of field (DoF). Here, a vari-focal light field camera (VF-LFC) with an extended DoF is newly proposed for mid-range 3D depth sensing applications. As a main lens of the system, a vari-focal lens with four different focal lengths is adopted to extend the DoF up to ~15 m. The focal length of the micro-lens array (MLA) is optimized by considering the DoF both in the image plane and in the object plane for each focal length. By dividing measurement regions with each focal length, depth estimation with high reliability is available within the entire DoF. The proposed VF-LFC is evaluated by the disparity data extracted from images with different distances. Moreover, the depth measurement in an outdoor environment demonstrates that our VF-LFC could be applied in various fields such as delivery robots, autonomous vehicles, and remote sensing drones.

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Lee, Fong-Zuo, Jihn-Sung Lai, Yuan-Bin Lin, Kuo-Chun Chang, Xiaoqin Liu, and Cheng-Chia Huang. "Prediction of Bridge Pier Scour Depth and Field Scour Depth Monitoring." E3S Web of Conferences 40 (2018): 03007. http://dx.doi.org/10.1051/e3sconf/20184003007.

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In practice, it is a major challenge in real-time simulation and prediction of bridge pier scour depth, especially using 3-D numerical model. The simulation time spend too much to use 3-D numerical model simulation and inefficiently to predict bridge pier scour depth in real-time. With heavy rainfall during flood season in Taiwan, abundant sediment with flash flood from upstream watershed is transported to downstream river reaches and transportation time is limited within one day. The flood flow tends to damage bridge structures and affect channel stabilization in fluvial rivers. In addition, the main factors affecting the erosional depth around bridge piers and river bed stabilization are hydrological and hydrographic characteristics in river basin, the scouring and silting of river bed section near the bridge piers, the bridge geometry and protection works of bridge piers. Therefore, based on the observed rainfall data provided by the Central Weather Bureau and the hydrological conditions provided by the Water Resources Agency during flood event as the boundary condition, we develop an effective simulation system for scour depth of bridge piers. The scour depth at the bridge pier is observed by the National Center for Research on Earthquake Engineering for model calibration. In this study, an innovative scour monitoring system using vibration-based Micro-Electro Mechanical Systems (MEMS) sensors was applied. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. It has demonstrated that the measurement system for monitoring bridge scour depth evolution is quite successful in the field.

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Navarro, Hector, Genaro Saavedra, Manuel Martinez-Corral, Marten Sjostrom, and Roger Olsson. "Depth-of-Field Enhancement in Integral Imaging by Selective Depth-Deconvolution." Journal of Display Technology 10, no. 3 (March 2014): 182–88. http://dx.doi.org/10.1109/jdt.2013.2291110.

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Choi, Sungwon, and Sung-wook Min. "Depth estimation method using depth-of-field imaging with a retroreflector." Optics Express 26, no. 5 (February 26, 2018): 5655. http://dx.doi.org/10.1364/oe.26.005655.

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Jin, Xin, Zhouping Wang, Xiaoyu Wang, and Qionghai Dai. "Depth of field extended scattering imaging by light field estimation." Optics Letters 43, no. 20 (October 3, 2018): 4871. http://dx.doi.org/10.1364/ol.43.004871.

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Ji, Jiaxin, Pengfei Xu, Jiying Chen, Jing Li, and Yonggang Meng. "High Depth-of-Field Nanostructures by Rotational Near-Field Photolithography." Plasmonics 15, no. 1 (September 4, 2019): 209–15. http://dx.doi.org/10.1007/s11468-019-01026-4.

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Mottram, Ruth H., and Douglas I. Benn. "Testing crevasse-depth models: a field study at Breiðamerkurjökull, Iceland." Journal of Glaciology 55, no. 192 (2009): 746–52. http://dx.doi.org/10.3189/002214309789470905.

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AbstractInterest in crevasses and associated ice-fracture processes has recently increased due to recognition of the importance of calving glaciers to the mass balance of the cryosphere, as well as the importance of fractures in glacier hydrology. Recently developed calving criteria make use of models which predict crevasse depth from surface strain rates, but these models have rarely been tested against observations. In this study, we present data on crevasse depth and surface strain rates, and compare the measured values with results of two crevasse-depth models: a simple function proposed by Nye and a linear elastic fracture mechanics (LEFM) model developed by Van der Veen. Our results indicate that both models predict crevasse depths within the correct order of magnitude. The LEFM model, incorporating measured values of crevasse spacing and tuned for fracture toughness, performs better in predicting crevasse depths, but where lack of input data precludes such tuning, the results are similar to Nye’s model predictions. We conclude that both models may be used to calculate crevasse depths in calving models, although the Nye function is undoubtedly much simpler to implement within an ice-dynamics model.

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Cushman, Kent E., Muhammad Maqbool, and Patrick D. Gerard. "Mulch Type, Mulch Depth, and Rhizome Planting Depth for Field-grown American Mayapple." HortScience 40, no. 3 (June 2005): 635–39. http://dx.doi.org/10.21273/hortsci.40.3.635.

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American mayapple (Podophyllum peltatum L.) is a rhizomatous herbaceous perennial found in wooded areas of eastern North America and is a source of the pharmaceutical compound podophyllotoxin. To explore the possible domestication of this species, this research examined strategies for establishing mayapple in field plantings using organic mulches. Mayapple rhizome segments were harvested from the wild and transplanted to raised beds in northern Mississippi in Fall 2001. Two types of mulch (pine bark or wheat straw), two depths of mulch (7.5 or 15 cm), and two planting depths (0 or 5 cm) of rhizome segments were examined in a factorial arrangement and randomized complete block design. Data were recorded during spring of 2002 and 2003. Shoot number was not affected by mulch depth, but there was a significant interaction between mulch type and rhizome planting depth. Rhizome segments planted 0 cm deep and covered with straw mulch produced about 30% fewer shoots compared to any of the other treatment combinations. Number of emerging shoots was also affected by year, with a 33% increase in shoots from 2002 to 2003. Total leaf area and total leaf dry weight were not affected by mulch depth, but there was a significant three-way interaction between mulch type, rhizome planting depth, and year. During 2002, treatment combinations were not different, but during 2003 rhizome segments planted 0 cm deep and covered with straw mulch produced less leaf area and leaf dry weight than any of the other treatment combinations. The ratio of sexual shoots to total shoots was affected by year, with a higher ratio of sexual shoots occurring in 2002 than 2003. Grasses established in bark mulch to a greater extent than in straw mulch in 2002, but weed control was excellent for all treatments in 2003. These results indicate that rhizome segments planted 0 cm deep and covered with straw mulch consistently produced fewer shoots with less leaf area and dry mass compared to any other treatment combination. We preferred bark mulch, but we can recommend either bark or straw mulch for the purpose of establishing field plantings of american mayapple in full sun as long as rhizome planting depth is 5 cm. There was no difference between the two mulching depths used in this study; therefore, a mulch depth of 7.5 cm can be recommended because of its lower cost.

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Esehaghbeygi, Ali, Milad Abedi, Jalil Razavi, and Abbass Hemmat. "Field evaluation of a vibrating dual bent-share cultivator." Research in Agricultural Engineering 66, No. 4 (December 30, 2020): 123–30. http://dx.doi.org/10.17221/49/2020-rae.

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In this research, the suitability of a vibrating dual bent-share cultivator was studied. Therefore, an eccentric pin-slider mechanism was designed to vibrate the two shanks laterally, using a tractor power take-off. The present study investigates the field performance of the vibrating dual bent-share cultivator with three different vibration frequencies (0, 0.88, and 2 Hz) in a clay loam soil at two working depths (100 and 200 mm) and having a water content of a 0.7 or 0.9 plastic limit. The lowest values of the draught, specific draught, and MWD were recorded at a vibration frequency of 2 Hz and a working depth of 100 mm. The draught force, specific draught, and MWD of the non-vibration implement were reduced by using a vibration frequency of 2 Hz. The coefficient of determination and F-values proved that the vibration frequency was more effective than the soil water content and the working depth on the draught, specific draught, and MWD. Although a dual bent-share cultivator needs low energy compared with a mould-board plough, the vibration of the dual bent-share cultivator may be recommended as an efficient energy-demanding implement in the soil manipulation process.

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42

Xu, Lei, Terry Olson, Byron Lengsfield, Masato Shiimoto, Mikito Sugiyama, and Adam Torabi. "The Importance of Depth-Varying Fields for MAMR Switching-Field Reduction." IEEE Transactions on Magnetics 51, no. 11 (November 2015): 1–3. http://dx.doi.org/10.1109/tmag.2015.2437074.

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Fedi, Maurizio, and Mark Pilkington. "Understanding imaging methods for potential field data." GEOPHYSICS 77, no. 1 (January 2012): G13—G24. http://dx.doi.org/10.1190/geo2011-0078.1.

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Several noniterative, imaging methods for potential field data have been proposed that provide an estimate of the 3D magnetization/density distribution within the subsurface or that produce images of quantities related or proportional to such distributions. They have been derived in various ways, using generalized linear inversion, Wiener filtering, wavelet and depth from extreme points (DEXP) transformations, crosscorrelation, and migration. We demonstrated that the resulting images from each of these approaches are equivalent to an upward continuation of the data, weighted by a (possibly) depth-dependent function. Source distributions or related quantities imaged by all of these methods are smeared, diffuse versions of the true distributions; but owing to the stability of upward continuation, resolution may be substantially increased by coupling derivative and upward continuation operators. These imaging techniques appeared most effective in the case of isolated, compact, and depth-limited sources. Because all the approaches were noniterative, computationally fast, and in some cases, produced a fit to the data, they did provide a quick, but approximate picture of physical property distributions. We have found that inherent or explicit depth-weighting is necessary to image sources at their correct depths, and that the best scaling law or weighting function has to be physically based, for instance, using the theory of homogeneous fields. A major advantage of these techniques was their speed, efficiently providing a basis for further detailed, follow-up modelling.

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Lee, Jeseon, and Sungkil Lee. "Real-Time Depth-of-Field Rendering Using Depth Range Shift and Compression." Journal of KIISE 46, no. 11 (November 30, 2019): 1106–12. http://dx.doi.org/10.5626/jok.2019.46.11.1106.

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Zhao, Mandan, Gaochang Wu, Yebin Liu, and Xiangyang Hao. "How depth estimation in light fields can benefit from super-resolution?" International Journal of Advanced Robotic Systems 15, no. 1 (January 1, 2018): 172988141774844. http://dx.doi.org/10.1177/1729881417748446.

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With the development of consumer light field cameras, the light field imaging has become an extensively used method for capturing the three-dimensional appearance of a scene. The depth estimation often requires a dense sampled light field in the angular domain or a high resolution in the spatial domain. However, there is an inherent trade-off between the angular and spatial resolutions of the light field. Recently, some studies for super-resolving the trade-off light field have been introduced. Rather than the conventional approaches that optimize the depth maps, these approaches focus on maximizing the quality of the super-resolved light field. In this article, we investigate how the depth estimation can benefit from these super-resolution methods. Specifically, we compare the qualities of the estimated depth using (a) the original sparse sampled light fields and the reconstructed dense sampled light fields, and (b) the original low-resolution light fields and the high-resolution light fields. Experiment results evaluate the enhanced depth maps using different super-resolution approaches.

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Kumar, Hemendra, Puneet Srivastava, Brenda V. Ortiz, Guilherme Morata, Bijoychandra S. Takhellambam, Jasmeet Lamba, and Luca Bondesan. "Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands." Transactions of the ASABE 64, no. 4 (2021): 1277–94. http://dx.doi.org/10.13031/trans.14335.

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HighlightsThe greatest heterogeneity in soil water was observed at 30-60 cm depth in a corn field and 0-15 cm in a cotton field.Spatiotemporal soil water variability did not increase with increasing soil water in all soil layers in both croplands during the growing season.Water excess and water stress locations were identified in both fields. A single, temporally stable location was identified in each field, which can be used for precise uniform irrigation.Knowledge of variability and stability in soil water can be useful in determining the number and location of sensors to install in crop fields to assist irrigation scheduling decisions.Abstract. This study investigated the spatiotemporal variability and temporal stability of soil water at various depths in two croplands sown in corn and cotton during the 2018 growing season in the Tennessee Valley Region (TVR) of northern Alabama. Classical statistics and relative difference approaches were used to analyze soil water data in this study. In the corn field, the 30-60 cm depth showed the greatest variability, while the cotton field showed the greatest variability at 0-15 cm depth. A decreasing trend was noticed between mean soil water and coefficient of variation for all depths in the cotton field and at 30-60 cm depth in the corn field. However, convex upward, exponential decreasing, or no trends were found between mean soil water and standard deviation at different depths in both fields. The temporal stability analysis showed one representative sensor (S8 in corn and S1 in cotton) for the entire soil profile in both fields. Different statistical tests, i.e., Spearman’s correlation (rs), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), etc., were used to reduce uncertainty or increase confidence in the performance of representative sensors. Among various field attributes, topography in corn and soil properties in cotton were determined as significant factors responsible for soil water variability. Crop evapotranspiration (ETc) showed significant negative weak and moderate correlations with soil water in the corn and cotton fields, respectively. However, the mean air temperature showed a significant positive correlation with soil water in the corn field and a significant negative correlation in the cotton field. Solar radiation had a significant negative correlation with soil water in the cotton field and a non-significant correlation in the corn field. Accumulated growing degree days (accGDD) showed a significant negative correlation with soil water in the corn field and a positive correlation in the cotton field. This study gives insights into soil water variability, provides useful information about temporal stability, and identifies significant factors for precision uniform irrigation scheduling. Keywords: Corn, Cotton, Croplands, Growing season, Irrigation, Soil water, Spatial and temporal variability, Temporal stability.

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Palmieri, Luca, Gabriele Scrofani, Nicolò Incardona, Genaro Saavedra, Manuel Martínez-Corral, and Reinhard Koch. "Robust Depth Estimation for Light Field Microscopy." Sensors 19, no. 3 (January 25, 2019): 500. http://dx.doi.org/10.3390/s19030500.

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Light field technologies have seen a rise in recent years and microscopy is a field where such technology has had a deep impact. The possibility to provide spatial and angular information at the same time and in a single shot brings several advantages and allows for new applications. A common goal in these applications is the calculation of a depth map to reconstruct the three-dimensional geometry of the scene. Many approaches are applicable, but most of them cannot achieve high accuracy because of the nature of such images: biological samples are usually poor in features and do not exhibit sharp colors like natural scene. Due to such conditions, standard approaches result in noisy depth maps. In this work, a robust approach is proposed where accurate depth maps can be produced exploiting the information recorded in the light field, in particular, images produced with Fourier integral Microscope. The proposed approach can be divided into three main parts. Initially, it creates two cost volumes using different focal cues, namely correspondences and defocus. Secondly, it applies filtering methods that exploit multi-scale and super-pixels cost aggregation to reduce noise and enhance the accuracy. Finally, it merges the two cost volumes and extracts a depth map through multi-label optimization.

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Xiaomin, LIU, MA Zhibang, WANG Qiancheng, DU Mengzhu, ZHU Yunfei, MA Fengying, and LIANG Erjun. "Compression light field reconstruction and depth estimation." Journal of Applied Optics 40, no. 2 (2019): 1–8. http://dx.doi.org/10.5768/jao201940.0201001.

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Mishiba, Kazu. "Fast Depth Estimation for Light Field Cameras." IEEE Transactions on Image Processing 29 (2020): 4232–42. http://dx.doi.org/10.1109/tip.2020.2970814.

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Cowley, R. G. "Depth conversion problems of the SKUA field." Exploration Geophysics 20, no. 2 (1989): 297. http://dx.doi.org/10.1071/eg989297.

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Before oil volumes and economics can be calculated for an oil field, the seismic time map must be converted to a depth map. The Skua Field, located in Permit AC/P2 in the Timor Sea, has proved particularly difficult to depth convert. Velocity anomalies and inconsistencies in the seismic times, termed 'lags', have created distortions in the seismic time map which require compensation. Beneath a velocity anomaly, both seismic undershoot and increased velocity, which are difficult to determine, must be compensated for during depth conversion. The current depth map was produced by smoothing through the pull-up regions on the time map, which required judgement, then depth, converting using a regional average velocity field. The seismic lag, which is the difference between the seismic time and an ideal vertical path travel time, can only be measured at the wells and appears to be unpredictable. The seismic lag between Skua-4 and Skua-5 was assumed to change linearly in order to produce the depth map. Large lags can be introduced into the data in the common depth point stack stage of data processing. The stacking velocity with the largest stack response does not necessarily result in the smallest lag error.

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Journal articles on the topic 'Depth of field'

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