Near-bottom Multibeam Survey Capabilities in the US National Deep Submergence Facility (Invited)

Science.gov (United States)

Yoerger, D. R.; McCue, S. J.; Jason; Sentry Operations Groups

2010-12-01

The US National Deep Submergence Facility (NDSF) provides near-bottom multibeam mapping capabilities from the autonomous underwater vehicle Sentry and the remotely operated vehicle Jason. These vehicles can be used to depths of 4500 and 6500m respectively. Both vehicles are equipped with Reson 7125 400khz multibeam sonars as well as compatible navigation equipment (inertial navigation systems, doppler velocity logs, and acoustic navigation systems). These vehicles have produced maps of rugged Mid-Ocean Ridge terrain in the Galapagos Rift, natural oil and gas seeps off the coast of Southern California, deep coral sites in the Gulf of Mexico, and sites for the Ocean Observing Initiative off the coast of Oregon. Multibeam surveys are conducted from heights between 20 and 80 meters, allowing the scientific user to select the tradeoff between resolution and coverage rate. In addition to conventional bathymetric mapping, the systems have used to image methane bubble plumes from natural seeps. This talk will provide summaries of these mapping efforts and describe the data processing pipeline used to produce maps shortly after each dive. Development efforts to reduce navigational errors and reconcile discrepancies between adjacent swaths will also be described.

Temporal characteristics of coherent flow structures generated over alluvial sand dunes, Mississippi River, revealed by acoustic doppler current profiling and multibeam echo sounding

Science.gov (United States)

Czuba, John A.; Oberg, Kevin A.; Best, Jim L.; Parsons, Daniel R.; Simmons, S. M.; Johnson, K.K.; Malzone, C.

2009-01-01

This paper investigates the flow in the lee of a large sand dune located at the confluence of the Mississippi and Missouri Rivers, USA. Stationary profiles collected from an anchored boat using an acoustic Doppler current profiler (ADCP) were georeferenced with data from a real-time kinematic differential global positioning system. A multibeam echo sounder was used to map the bathymetry of the confluence and provided a morphological context for the ADCP measurements. The flow in the lee of a low-angle dune shows good correspondence with current conceptual models of flow over dunes. As expected, quadrant 2 events (upwellings of low-momentum fluid) are associated with high backscatter intensity. Turbulent events generated in the lower lee of a dune near the bed are associated with periods of vortex shedding and wake flapping. Remnant coherent structures that advect over the lower lee of the dune in the upper portion of the water column, have mostly dissipated and contribute little to turbulence intensities. The turbulent events that occupy most of the water column in the upper lee of the dune are associated with periods of wake flapping.

The Multibeam Advisory Committee (MAC): a search for solutions for collecting consistent high quality multibeam data across multiple ships, systems, and operators in the U.S. Academic Fleet.

Science.gov (United States)

Johnson, P. D.; Ferrini, V. L.; Jerram, K.

2016-12-01

In 2015 the National Science Foundation funded the University of New Hampshire's Center for Coastal and Ocean Mapping and Lamont-Doherty Earth Observatory, for the second time, to coordinate the effort of standardizing the quality of multibeam echosounder (MBES) data across the U.S. academic fleet. This effort supports 9 different ship operating institutions who manage a total of 12 multibeam-equipped ships carrying 6 different MBES systems, manufactured by two different companies. These MBES are designed to operate over a very wide range of depths and operational modes. The complexity of this endeavor led to the creation of the Multibeam Advisory Committee (MAC), a team of academic and industry experts whose mission is to support the needs of the U.S academic fleet's multibeam echo sounders through all of the phases of the "life" of a MBES system and its data, from initial acceptance of the system, to recommendations on at-sea acquisition of data, to validation of already installed systems, and finally to the post-survey data evaluation. The main activities of the MAC include 1.) standardizing both the Shipboard Acceptance Testing of all new systems and Quality Assurance Testing of already installed systems, 2.) working with the both the ship operators/technicians and the manufacturers of the multibeam systems to guarantee that each MBES is working at its peak performance level, 3.) developing tools that aid in the collection of data, assessment of the MBES hardware, and evaluation of the quality of the MBES data, 4.) creating "best practices" documentation concerning data acquisition and workflow, and 5.) providing a website, http://mac.unols.org, to host technical information, tools, reports, and a "help desk" for operators of the systems to ask questions concerning issues that they see with their systems.

Seabed sediment classification for monitoring underwater nourishments using time series of multi-beam echo-soundings

Science.gov (United States)

Gaida, T. C.; Snellen, M.; van Dijk, T. A. G. P.; Simons, D. G.

2017-12-01

Coastal erosion induced by natural processes, such as wind, waves, tidal currents, or human interferences endangers human beings, infrastructure, fauna and flora at the oceans and rivers all over the world. In The Netherlands, in particular the North Sea islands are strongly affected by sediment erosion. To protect and stabilize the coastline, beach and shoreface nourishments are frequently performed. Thereby, sediment reservoirs are created that replace the eroded sediments. Increasing the long-term efficiency of coastal protection requires monitoring of the temporal and spatial development of the coastal nourishments. Multi-beam echo-sounders (MBES) allow for detailed and comprehensive investigations of the seabed composition and structure. To investigate the potential of using MBES for monitoring nourishments in a tidal inlet, four MBES surveys per year are carried out at the Dutch Wadden island Ameland. A pre-nourishment MBES survey was performed in April 2017 and the subsequent post-nourishment survey will take place in September 2017. Both surveys are equipped with a Kongsberg EM 2040C dual-head MBES and are supported with extensive grab sampling. In this study the use of MBES backscatter and bathymetry data are considered as an approach for monitoring coastal nourishments. The aim is to develop a monitoring procedure that allows for comparing MBES data taken during different surveys, i.e., with variations in environmental conditions, MBES characteristics and acquisition procedures. Different unsupervised and supervised acoustic seafloor classification techniques are applied to the processed MBES data to classify the seabed sediments. The analysis of the pre-nourishment MBES data indicates that the backscatter and consequently the classification are highly driven by the abundancy of shell fragments. These results will be used as a baseline to investigate the accumulation of the underwater nourishments. Independent grab samples will be used to select the

Auv Multibeam Bathymetry and Sidescan Survey of the SS Montebello wreck Offshore Cambria CA

Science.gov (United States)

Caress, D. W.; Thomas, H.; Conlin, D.; Thompson, D.; Paull, C. K.

2010-12-01

An MBARI Mapping AUV survey of the SS Montebello wreck offshore Cambria, CA collected high-resolution multibeam bathymetry and sidescan imagery of the vessel and the surrounding seafloor. The Montebello was an oil tanker that was torpedoed and sunk about 11 km offshore in 275 m water depth by a Japanese submarine on December 23, 1941. The Montebello was loaded with 3,000,000 gallons of crude oil, and there is no evidence that significant leakage of that cargo occurred at the time of the sinking or in the 69 years since. The California Department of Fish and Game’s Office of Spill Prevention and Response (OSPR) commissioned the AUV survey as part of a multi-agency Montebello Task Force effort to assess the potential pollution threat. The survey data will be used to determine the extent and general character of the wreckage for a pending Task Force report and to guide any future ROV dive or assessment activity . The AUV surveyed the wreck site from altitudes of 75 and 25 m; the low-altitude high-resolution survey consists of a grid with a 50 m line spacing both parallel and orthogonal to the ship. The 200 kHz multibeam bathymetry images the wreck from both above and from the sides with an 0.5 m lateral resolution. The combination of soundings from all of the survey lines results in a three-dimensional distribution of soundings that delineates the external morphology and some of the internal structure of the wreck. 410 kHz chirp sidescan sonar data also image the site from both directions. The bathymetry data indicate that the Montebello was pitched forward down when it impacted the bottom, crushing and breaking off the bow section. Both forward and aft deckhouses are largely intact, and in fact the multibeam images the individual decks within those structures. About half of the forward mast remains, both amidships masts and the smokestack are missing. A good deal of the deck piping and equipment appears intact, and aside from the bow, the ship’s sides appear

Detection of active hydrothermal vent fields in the Pescadero Basin and on the Alarcon Rise using AUV multibeam and CTD data

Science.gov (United States)

Caress, D. W.; Troni, G.; Clague, D. A.; Paduan, J. B.; Martin, J. F.; Thomas, H. J.; Thompson, D.; Conlin, D.; Martin, E. J.; meneses-Quiroz, E.; Nieves-Cardoso, C.; Angel Santa Rosa del Rio, M.

2015-12-01

The MBARI AUV D. Allan B. collected high resolution bathymetry, sidescan, and subbottom profiles along the neovolcanic zone of the Alarcon Rise and across the southern Pescadero Basin during 2012 and 2015 MBARI expeditions to the Gulf of California (GOC). The combination of high resolution multibeam bathymetry and seawater temperature data has proven effective in identifying active high temperature vent fields, as validated by inspection and sampling during ROV dives. The AUV carries a 200 kHz multibeam sonar, 110 kHz chirp sidescan sonar, a 1-6 kHz chirp subbottom profiler, and a conductivity, temperature and depth (CTD) sensor for ~17-hour duration missions. Flying at 5.4 km/hr at 50 m altitude, the processed AUV bathymetry has a 0.1 m vertical precision and a 1 m lateral resolution. Chimneys taller than 1.5 m are sufficiently distinctive to allow provisional identification. The CTD temperature data have a nominal 0.002°C accuracy. Following calculation of potential temperature and correcting for average local variation of potential temperature with depth, anomalies greater than 0.05 °C can be reliably identified using a spike detection filter. MBARI AUV mapping surveys are typically planned using a 150 m survey line spacing, so the CTD data may be collected as much as 75 m away from any vent plume source. Five active high temperature vent fields were discovered in the southern GOC, with the Auka Field in the southern Pescadero Basin, and the Ja Sít, Pericú, Meyibó, and Tzab-ek Fields along the Alarcon Rise. In all five cases, hydrothermal vent chimneys are readily identifiable in the multibeam bathymetry, and temperature anomalies are observed above background variability. Other apparent hydrothermal chimneys were observed in the bathmetry that did not exhibit water temperature anomalies; most of these were visited during ROV dives and confirmed to be inactive sites. The maximum water column anomalies are 0.13°C observed above the Meyibó field and 0.25�

Multifractal detrended fluctuation analysis to compare coral bank and seafloor seepage area-related characterization along the central Western continental margin of India

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.; VishnuVardhan, Y.; Haris, K.; Menezes, A.A.A.; Karisiddaiah, S.M.; Fernandes, W.A.; Kurian, J.

], [9]. In the western continental margin off Malpe, Karnataka coast, India, two living coral banks were identified using an EM 1002 multibeam echo sounder (MBES), namely, 1) the Gaveshani bank [10] and 2) an unnamed coral bank [11]. The other important.... MATERIALS AND METHODS The MBES data system for the present study was used to acquire a dataset during a survey (in 2006) onboard coastal research vessel (CRV) Sagar Sukti. The EM 1002 system operates at a frequency of 95 kHz and acquires the bathymetry 1545...

The Application of a Multi-Beam Echo-Sounder in the Analysis of the Sedimentation Situation of a Large Reservoir after an Earthquake

Directory of Open Access Journals (Sweden)

Zhong-Luan Yan

2018-04-01

Full Text Available The Wenchuan Earthquake took place in the upper reach catchment of the Min River. It resulted in large amounts of loose materials gathering in the river channel, leading to changes in the sediment transport system in this area. The Zipingpu Reservoir is the last and the largest reservoir located in the upper reach of the Min River. It is near the epicenter and receives sediment from upstream. This paper puts forward a study on the reservoir sedimentation and storage capacity of the Zipingpu Reservoir, employing a multi-beam echo-sounder system in December 2012. Then, the data were merged with digital line graphics and shuttle radar topography mission data in ArcGIS to build a digital elevation model and triangulate the irregular network of Zipingpu Reservoir. Via the analysis of the bathymetric data, the results show the following: (1 The main channels of the reservoir gradually aggrade to a flat bottom from the deep-cutting valley. Sedimentation forms a reach with a W-shaped longitudinal thalweg profile and an almost zero slope reach in the upstream section of the reservoir due to the natural barrier induced by a landslide; (2 The loss ratios of the wetted cross-section surface are higher than 10% in the upstream section of the reservoir and higher than 40% in the natural barrier area; (3 Comparing the surveyed area storage capacity of December 2012 with March 2008, the Zipingpu Reservoir has lost 15.28% of its capacity at the dead storage water level and 10.49% of its capacity at the flood limit water level.

Investigation of echo sounding parameters for the characterisation of bottom sediments in a sub-tropical reservoir

Directory of Open Access Journals (Sweden)

Stephan Hilgert

2016-07-01

Full Text Available The increasing number of reservoirs around the world today reaches a surface area of around 500,000 km², equaling one third of that of non-artificial surface water bodies. By impounding rivers through the construction of dams, riverine systems and biochemical cycles are disrupted. Different types of transported materials are trapped behind the dams and form layers of sediment. A method to characterise the spatially extensive sediment volumes with an EA 400 echo sounder was tested in the Vossoroca reservoir in the southeast of Brazil, Paraná State. A number of core and grab samples was taken and analysed for a variety of chemical and physical parameters. These data served as ground truthing for the hydro-acoustic assessment of the sediment. Eight hydro-acoustic parameters were derived from the echo signals using the Sonar5-Pro software. The major objective of defining the optimal survey parameters for the echo sounder as well as determining the difference between core and grab samples was reached by correlating the various single parameters and identifying the best combinations. Density and grain size distribution represented the best detectable sediment features with r-values of 0.94 and 0.95. The lower 38 kHz frequency generally had a better performance than the 200 kHz frequency. Results show that core samples reached a significantly higher quality of correlation for sediment characterisation. Additionally, it is was found that shorter pulse lengths yield a better characterisation. The results underline the potential of single beam echo sounders for extensive sediment characterisation. This methodology may be used for future mass balance estimations of large reservoirs.

Validation of automated supervised segmentation of multibeam backscatter data from the Chatham Rise, New Zealand

Science.gov (United States)

Hillman, Jess I. T.; Lamarche, Geoffroy; Pallentin, Arne; Pecher, Ingo A.; Gorman, Andrew R.; Schneider von Deimling, Jens

2018-06-01

Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation.

Analysis of seafloor backscatter strength dependence on the survey azimuth using multibeam echosounder data

Science.gov (United States)

Lurton, Xavier; Eleftherakis, Dimitrios; Augustin, Jean-Marie

2018-06-01

The sediment backscatter strength measured by multibeam echosounders is a key feature for seafloor mapping either qualitative (image mosaics) or quantitative (extraction of classifying features). An important phenomenon, often underestimated, is the dependence of the backscatter level on the azimuth angle imposed by the survey line directions: strong level differences at varying azimuth can be observed in case of organized roughness of the seabed, usually caused by tide currents over sandy sediments. This paper presents a number of experimental results obtained from shallow-water cruises using a 300-kHz multibeam echosounder and specially dedicated to the study of this azimuthal effect, with a specific configuration of the survey strategy involving a systematic coverage of reference areas following "compass rose" patterns. The results show for some areas a very strong dependence of the backscatter level, up to about 10-dB differences at intermediate oblique angles, although the presence of these ripples cannot be observed directly—neither from the bathymetry data nor from the sonar image, due to the insufficient resolution capability of the sonar. An elementary modeling of backscattering from rippled interfaces explains and comforts these observations. The consequences of this backscatter dependence upon survey azimuth on the current strategies of backscatter data acquisition and exploitation are discussed.

Geomorphology, acoustic backscatter, and processes in Santa Monica Bay from multibeam mapping.

Science.gov (United States)

Gardner, James V; Dartnell, Peter; Mayer, Larry A; Hughes Clarke, John E

2003-01-01

Santa Monica Bay was mapped in 1996 using a high-resolution multibeam system, providing the first substantial update of the submarine geomorphology since the initial compilation by Shepard and Emery [(1941) Geol. Soc. Amer. Spec. Paper 31]. The multibeam mapping generated not only high-resolution bathymetry, but also coregistered, calibrated acoustic backscatter at 95 kHz. The geomorphology has been subdivided into six provinces; shelf, marginal plateau, submarine canyon, basin slope, apron, and basin. The dimensions, gradients, and backscatter characteristics of each province is described and related to a combination of tectonics, climate, sea level, and sediment supply. Fluctuations of eustatic sea level have had a profound effect on the area; by periodically eroding the surface of Santa Monica plateau, extending the mouth of the Los Angeles River to various locations along the shelf break, and by connecting submarine canyons to rivers. A wetter glacial climate undoubtedly generated more sediment to the rivers that then transported the increased sediment load to the low-stand coastline and canyon heads. The trends of Santa Monica Canyon and several bathymetric highs suggest a complex tectonic stress field that has controlled the various segments. There is no geomorphic evidence to suggest Redondo Canyon is fault controlled. The San Pedro fault can be extended more than 30 km to the northwest by the alignment of a series of bathymetric highs and abrupt changes in direction of channel thalwegs.

Determination of nodule coverage parameters using multibeam normal incidence echo characteristics: A study in the Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.; Pathak, D.; Sudhakar, M.; Raju, Y.S.N.

A study of the echo peak amplitudes from known nodule areas is initiated to observe the acoustic response for varying nodule abundances and number densities. A statistical study of the peak amplitudes from different nodule areas confirms...

Study of multibeam techniques for bathymetry and seabottom backscatter applications

Digital Repository Service at National Institute of Oceanography (India)

Nair, R.R.; Chakraborty, B.

Indian ocean is presented using Hydrosweep-multibeam installed onboard ORV Sagarkanya. A seabottom classification model is proposed which can be applied for multibeam backscatter data. Certain aspects of the multibeam backscatter signal data processing...

NASA Rat Acoustic Tolerance Test 1994-1995: 8 kHz, 16 kHz, 32 kHz Experiments

Science.gov (United States)

Mele, Gary D.; Holley, Daniel C.; Naidu, Sujata

1996-01-01

Adult male Sprague-Dawley rats were exposed to chronic applied sound (74 to 79 dB, SPL) with octave band center frequencies of either 8, 16 or 32 kHz for up to 60 days. Control cages had ambient sound levels of about 62 dB (SPL). Groups of rats (test vs. control; N=9 per group) were euthanized after 0. 5. 14, 30, and 60 days. On each euthanasia day, objective evaluation of their physiology and behavior was performed using a Stress Assessment Battery (SAB) of measures. In addition, rat hearing was assessed using the brain stem auditory evoked potential (BAER) method after 60 days of exposure. No statistically significant differences in mean daily food use could be attributed to the presence of the applied test sound. Test rats used 5% more water than control rats. In the 8 kHz and 32 kHz tests this amount was statistically significant(P less than .05). This is a minor difference of questionable physiological significance. However, it may be an indication of a small reaction to the constant applied sound. Across all test frequencies, day 5 test rats had 6% larger spleens than control rats. No other body or organ weight differences were found to be statistically significant with respect to the application of sound. This spleen effect may be a transient adaptive process related to adaptation to the constant applied noise. No significant test effect on differential white blood cell counts could be demonstrated. One group demonstrated a low eosinophil count (16 kHz experiment, day 14 test group). However this was highly suspect. Across all test frequencies studied, day 5 test rats had 17% fewer total leukocytes than day 5 control rats. Sound exposed test rats exhibited 44% lower plasma corticosterone concentrations than did control rats. Note that the plasma corticosterone concentration was lower in the sound exposed test animals than the control animals in every instance (frequency exposure and number of days exposed).

Comparison of multi-echo and single-echo gradient-recalled echo sequences for SPIO-enhanced Liver MRI at 3 T

International Nuclear Information System (INIS)

Choi, J.S.; Kim, M.-J.; Kim, J.H.; Choi, J.-Y.; Chung, Y.E.; Park, M.-S.; Kim, K.W.

2010-01-01

Aim: To assess the utility of a T2*-weighted, multi-echo data imaging combination sequenced on superparamagnetic iron oxide (SPIO)-enhanced liver magnetic resonance imaging (MRI) using a 3 T system. Materials and methods: Fifty patients underwent SPIO-enhanced MRI at 3 T using T2*-weighted, single-echo, gradient-recalled echo (GRE) sequences [fast imaging with steady precession; repetition time (TR)/echo time (TE), 126 ms/9 ms; flip angle, 30 o ] and multi-echo GRE (multi-echo data image combination) sequences (TR/TE, 186 ms/9 ms; flip angle, 30 o ). Three radiologists independently reviewed the images in a random order. The sensitivity and accuracy for the detection of focal hepatic lesions (a total of 76 lesions in 33 patients; 48 solid lesions, 28 non-solid lesions) were compared by analysing the area under the receiver operating characteristic curves. Image artefacts (flow artefacts, susceptibility artefacts, dielectric artefacts, and motion artefacts), lesion conspicuity, and overall image quality were evaluated according to a four-point scale: 1, poor; 2, fair; 3, good; 4, excellent. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the lesions were compared. Results: Image artefacts were more frequent with single-echo GRE (p < 0.05). The mean scale of image quality assessment for flow, susceptibility, dielectric, and motion artefacts were 2.76, 3.13, 3.42, and 2.89 with singe-echo, respectively, compared with 3.47, 3.43, 3.47, and 3.39, respectively, with multi-echo GRE. There was no significant difference in lesion conspicuity between single-echo (3.15) and multi-echo (3.30) GRE sequences. The overall image quality was significantly (p < 0.05) better with multi-echo (3.37) than with single-echo GRE (2.89). The mean SNR and CNR of the lesions were significantly (p < 0.05) higher on multi-echo (79 ± 23 and 128 ± 59, respectively) images than on single-echo (38 ± 11 and 102 ± 44, respectively) images. Lesion detection accuracy and

Independence of echo-threshold and echo-delay in the barn owl.

Directory of Open Access Journals (Sweden)

Brian S Nelson

Full Text Available Despite their prevalence in nature, echoes are not perceived as events separate from the sounds arriving directly from an active source, until the echo's delay is long. We measured the head-saccades of barn owls and the responses of neurons in their auditory space-maps while presenting a long duration noise-burst and a simulated echo. Under this paradigm, there were two possible stimulus segments that could potentially signal the location of the echo. One was at the onset of the echo; the other, after the offset of the direct (leading sound, when only the echo was present. By lengthening the echo's duration, independently of its delay, spikes and saccades were evoked by the source of the echo even at delays that normally evoked saccades to only the direct source. An echo's location thus appears to be signaled by the neural response evoked after the offset of the direct sound.

Quantitative seafloor characterization using angular backscatter data of the multi-beam echo-sounding system - Use of models and model free techniques

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.

processing gain, bottom slope corrections, and bottom insonification area normalisation were proposed to generate angular backscattering strength for modelling to infer bottom roughness parameters. A software package (NORGCOR) for similar purpose... bottom backscatter data from multibeam system. For each seafloor area, processed backscatter strength values [presented in Fig.: I(c)], are binned at intervals of 1° from --45° to +45°, and averaged over the entire dataset (approximately around 100...

ROV seafloor surveys combining 5-cm lateral resolution multibeam bathymetry with color stereo photographic imagery

Science.gov (United States)

Caress, D. W.; Hobson, B.; Thomas, H. J.; Henthorn, R.; Martin, E. J.; Bird, L.; Rock, S. M.; Risi, M.; Padial, J. A.

2013-12-01

The Monterey Bay Aquarium Research Institute is developing a low altitude, high-resolution seafloor mapping capability that combines multibeam sonar with stereo photographic imagery. The goal is to obtain spatially quantitative, repeatable renderings of the seafloor with fidelity at scales of 5 cm or better from altitudes of 2-3 m. The initial test surveys using this sensor system are being conducted from a remotely operated vehicle (ROV). Ultimately we intend to field this survey system from an autonomous underwater vehicle (AUV). This presentation focuses on the current sensor configuration, methods for data processing, and results from recent test surveys. Bathymetry data are collected using a 400-kHz Reson 7125 multibeam sonar. This configuration produces 512 beams across a 135° wide swath; each beam has a 0.5° acrosstrack by 1.0° alongtrack angular width. At a 2-m altitude, the nadir beams have a 1.7-cm acrosstrack and 3.5 cm alongtrack footprint. Dual Allied Vision Technology GX1920 2.8 Mpixel color cameras provide color stereo photography of the seafloor. The camera housings have been fitted with corrective optics achieving a 90° field of view through a dome port. Illumination is provided by dual 100J xenon strobes. Position, depth, and attitude data are provided by a Kearfott SeaDevil Inertial Navigation System (INS) integrated with a 300 kHz RDI Doppler velocity log (DVL). A separate Paroscientific pressure sensor is mounted adjacent to the INS. The INS Kalman filter is aided by the DVL velocity and pressure data, achieving navigational drift rates less than 0.05% of the distance traveled during surveys. The sensors are mounted onto a toolsled fitted below MBARI's ROV Doc Ricketts with the sonars, cameras and strobes all pointed vertically down. During surveys the ROV flies at a 2-m altitude at speeds of 0.1-0.2 m/s. During a four-day R/V Western Flyer cruise in June 2013, we successfully collected multibeam and camera survey data from a 2-m altitude

Comparing microbubble cavitation at 500 kHz and 70 kHz related to micellar drug delivery using ultrasound.

Science.gov (United States)

Diaz de la Rosa, Mario A; Husseini, Ghaleb A; Pitt, William G

2013-02-01

We have previously reported that ultrasonic drug release at 70kHz was found to correlate with the presence of subharmonic emissions. No evidence of drug release or of the subharmonic emissions were detected in experiments at 500kHz. In an attempt to understand the difference in drug release behavior between low- and mid-frequency ultrasound, a mathematical model of a bubble oscillator was developed to explore the difference in the behavior of a single 10-μm bubble under 500- and 70-kHz ultrasound. The dynamics were found to be fundamentally different; the 500-kHz bubble follows a period-doubling route to chaos while a 70-kHz bubble follows an intermittent route to chaos. We propose that this type of "intermittent subharmonic" oscillation behavior is associated with the drug release observed experimentally. Copyright © 2012 Elsevier B.V. All rights reserved.

Model-based seafloor characterization employing multi-beam angular backscatter data - A comparative study with dual-frequency single beam

Digital Repository Service at National Institute of Oceanography (India)

Haris, K.; Chakraborty, B.; De, C.; Desai, R.G.P.; Fernandes, W.A.

developed by Jackson et al., 3 has been extensively applied to this approach. 4-6 In this work, characterization of seafloor sediments is achieved by employing a MB system (Simrad EM 1002) operable at 95 kHz. Here, the seafloor parameters are estimated... pre-formed beams data were acquired during two cruises using the EM1002 echo-sounding system installed onboard CRV Sagar Sukti (cruises: SASU-108 and 134). 13,14 Besides calculating the angular backscatter strengths using the MB system, the modeled...

Echo

Energy Technology Data Exchange (ETDEWEB)

Harvey, Dustin Yewell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-01-25

This document is a white paper marketing proposal for Echo™ is a data analysis platform designed for efficient, robust, and scalable creation and execution of complex workflows. Echo’s analysis management system refers to the ability to track, understand, and reproduce workflows used for arriving at results and decisions. Echo improves on traditional scripted data analysis in MATLAB, Python, R, and other languages to allow analysts to make better use of their time. Additionally, the Echo platform provides a powerful data management and curation solution allowing analysts to quickly find, access, and consume datasets. After two years of development and a first release in early 2016, Echo is now available for use with many data types in a wide range of application domains. Echo provides tools that allow users to focus on data analysis and decisions with confidence that results are reported accurately.

Seasonal and diel patterns in sedimentary flux of krill fecal pellets recorded by an echo sounder

KAUST Repository

Røstad, Anders

2013-11-01

We used a moored upward-facing 200 kHz echo sounder to address sedimentation of fecal pellets (FPs) from dielly migrating Meganyctiphanes norvegica. The echo sounder was located on the bottom at 150 m depth in the Oslofjord, Norway, and was cabled to shore for continuous measurements during winter and spring. Records of sinking pellets were for the first time observed with an echo sounder. Seasonal patterns of sedimentation of krill FPs were strongly correlated with data from continuous measurement of fluorescence, which illustrate the development of the spring bloom. Sedimenting particles were first observed as fluorescence values started to increase at the end of February and continued to increase until the bloom suddenly culminated at the end of March. This collapse of the bloom was detected on the echo sounder as a pulse of slowly sinking acoustic targets over a 2 d period. Prior to this event, there was a strong diel pattern in sedimentation, which correlated, with some time lag, with the diel migration of krill foraging at night near the surface. Pellet average sinking speeds ranged between 423 m d−1 and 804 m d−1, with a strong relation to pellet target strength, which is an acoustic proxy for size. This novel approach shows that echo sounders may be a valuable tool in studies of vertical pellet flux and, thereby, carbon flux, providing temporal resolution and direct observation of the sedimentation process, which are not obtained from standard methods.

Multibeam Bathymetry Database (MBBDB)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Originally designed for military use, the multibeam echosounder has proved very useful for nautical charting, oceanographic research and modeling, habitat...

AFSC/ABL: Multibeam Database

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Seafloor habitat maps have been created using high resolution multibeam sonar with co-registered backscatter at various locations throughout the Alaska Region. Most...

Multibeam sonar backscatter data processing

Science.gov (United States)

Schimel, Alexandre C. G.; Beaudoin, Jonathan; Parnum, Iain M.; Le Bas, Tim; Schmidt, Val; Keith, Gordon; Ierodiaconou, Daniel

2018-06-01

Multibeam sonar systems now routinely record seafloor backscatter data, which are processed into backscatter mosaics and angular responses, both of which can assist in identifying seafloor types and morphology. Those data products are obtained from the multibeam sonar raw data files through a sequence of data processing stages that follows a basic plan, but the implementation of which varies greatly between sonar systems and software. In this article, we provide a comprehensive review of this backscatter data processing chain, with a focus on the variability in the possible implementation of each processing stage. Our objective for undertaking this task is twofold: (1) to provide an overview of backscatter data processing for the consideration of the general user and (2) to provide suggestions to multibeam sonar manufacturers, software providers and the operators of these systems and software for eventually reducing the lack of control, uncertainty and variability associated with current data processing implementations and the resulting backscatter data products. One such suggestion is the adoption of a nomenclature for increasingly refined levels of processing, akin to the nomenclature adopted for satellite remote-sensing data deliverables.

Hydroacoustic detection of dumped ammunition in the Ocean with multibeam snippet backscatter analyses. A case study from the 'Kolberger Heide' ammunition dump site (Baltic Sea, Germany)

Science.gov (United States)

Kunde, Tina; Schneider von Deimling, Jens

2016-04-01

Dumped ammunition in the sea is a matter of great concern in terms of safe navigation and environmental threads. Because corrosion of the dumped ammunition's hull is ongoing, future contamination of the ambient water by their toxic interior is likely to occur. The location of such dump sites is approximately known from historical research and ship log book analyses. Subsequent remote sensing of ammunition dumping sites (e.g. mines) on the seafloor is preferentially performed with hydro-acoustic methods such as high resolution towed side scan or by the sophisticated synthetic aperture sonar approach with autonomous underwater vehicles. However, these are time consuming and expensive procedures, while determining the precise position of individual mines remains a challenging task. To mitigate these shortcomings we suggest using ship-born high-frequency multibeam sonar in shallow water to address the task of mine detection and precise localization on the seabed. Multibeam sonar systems have improved their potential in regard to backscatter analyses significantly over the past years and nowadays present fast and accurate tools for shallow water surveying to (1) detect mines in multibeam snippet backscatter data (2) determine their precise location with high accuracy intertial navigation systems. A case study was performed at the prominent ammunition dumping site 'Kolberger Heide' (Baltic Sea, Germany) in the year 2014 using a modern hydro-acoustic multibeam echosounder system with 200-400 kHz (KONGSBERG EM2040c). With an average water depth of not even 20 m and the proximity to the shore line and dense waterways, this investigated area requires permanent navigational care. Previously, the study area was surveyed by the Navy with the very sophisticated HUGIN AUV equipped with a synthetic aperture sonar with best resolution by current technology. Following an evaluation of the collected data, various ammunition bodies on the sea floor could be clearly detected. Analyses

Arabidopsis KHZ1 and KHZ2, two novel non-tandem CCCH zinc-finger and K-homolog domain proteins, have redundant roles in the regulation of flowering and senescence.

Science.gov (United States)

Yan, Zongyun; Jia, Jianheng; Yan, Xiaoyuan; Shi, Huiying; Han, Yuzhen

2017-12-01

The two novel CCCH zinc-finger and K-homolog (KH) proteins, KHZ1 and KHZ2, play important roles in regulating flowering and senescence redundantly in Arabidopsis. The CCCH zinc-finger proteins and K-homolog (KH) proteins play important roles in plant development and stress responses. However, the biological functions of many CCCH zinc-finger proteins and KH proteins remain uncharacterized. In Arabidopsis, KHZ1 and KHZ2 are characterized as two novel CCCH zinc-finger and KH domain proteins which belong to subfamily VII in CCCH family. We obtained khz1, khz2 mutants and khz1 khz2 double mutants, as well as overexpression (OE) lines of KHZ1 and KHZ2. Compared with the wild type (WT), the khz2 mutants displayed no defects in growth and development, and the khz1 mutants were slightly late flowering, whereas the khz1 khz2 double mutants showed a pronounced late flowering phenotype. In contrast, artificially overexpressing KHZ1 and KHZ2 led to the early flowering. Consistent with the late flowering phenotype, the expression of flowering repressor gene FLC was up-regulated, while the expression of flowering integrator and floral meristem identity (FMI) genes were down-regulated significantly in khz1 khz2. In addition, we also observed that the OE plants of KHZ1 and KHZ2 showed early leaf senescence significantly, whereas the khz1 khz2 double mutants showed delayed senescence of leaf and the whole plant. Both KHZ1 and KHZ2 were ubiquitously expressed throughout the tissues of Arabidopsis. KHZ1 and KHZ2 were localized to the nucleus, and possessed both transactivation activities and RNA-binding abilities. Taken together, we conclude that KHZ1 and KHZ2 have redundant roles in the regulation of flowering and senescence in Arabidopsis.

ECHO Gov Login | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Comparison of third-order plasma wave echoes with ballistic second-order plasma wave echoes

International Nuclear Information System (INIS)

Leppert, H.D.; Schuelter, H.; Wiesemann, K.

1982-01-01

The apparent dispersion of third-order plasma wave echoes observed in a high frequency plasma is compared with that of simultaneously observed ballistic second-order echoes. Amplitude and wavelength of third-order echoes are found to be always smaller than those of second-order echoes, however, the dispersion curves of both types of echoes are very similar. These observations are in qualitative agreement with calculations of special ballistic third-order echoes. The ballistic nature of the observed third-order echoes may, therefore, be concluded from these measurements. (author)

Topology Control in Aerial Multi-Beam Directional Networks

Science.gov (United States)

2017-04-24

Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology ...underlying challenges to topology control in multi-beam direction networks. Two topology control algorithms are developed: a centralized algorithm

ECHO virus

Science.gov (United States)

... page: //medlineplus.gov/ency/article/001340.htm ECHO virus To use the sharing features on this page, please enable JavaScript. Enteric cytopathic human orphan (ECHO) viruses are a group of viruses that can lead ...

Gridded multibeam bathymetry of Apra Harbor, Guam U.S. Territory

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry from Apra Harbor, Guam U.S. Territory. The netCDF and Arc ASCII grids include multibeam bathymetry from the Reson SeaBat 8125 multibeam sonar...

Fast spin-echo imaging

International Nuclear Information System (INIS)

Mackey, K.; Zoarski, G.; Bentson, J.R.; Lufkin, R.B.; Melki, P.; Jolesz, F.

1991-01-01

This paper reports on a partial radio-frequency (RF) echo-planar pulse sequence called contiguous slice fast spin echo (CSFSE) which is undergoing clinical trials for spine MR imaging. In this variation of rapid acquisition relaxation enhanced (RARE) spin-echo imaging, rapid 180 degrees RF pulse generated refocused echoes, producing T2-weighted images in about one-third the time of conventional double-echo technique. Forty patients with suspected pathology of the spine were imaged with conventional double-echo and closely matched CSFSE techniques on a GE Signa 1.5-T Advantage system. Cases were reviewed by two board-certified neuroradiologists. In all cases the CSFSE images were of equal or superior quality compared with those obtained with the conventional double-echo technique. Pathologic processes that were imaged consisted of inflammatory, neoplastic, posttraumatic, and degenerative conditions

Effects on atmospherics at 6 kHz and 9 kHz recorded at Tripura during the India-Pakistan Border earthquake

Directory of Open Access Journals (Sweden)

S. S. De

2010-04-01

Full Text Available The outcome of the results of some analyses of electromagnetic emissions recorded by VLF receivers at 6 kHz and 9 kHz over Agartala, Tripura, the North-Eastern state of India (Lat. 23° N, Long. 91.4° E during the large earthquake at Muzaffarabad (Lat. 34.53° N, Long. 73.58° E at Kashmir under Pakistan have been presented here. Spiky variations in integrated field intensity of atmospherics (IFIA at 6 and 9 kHz have been observed 10 days prior (from midnight of 28 September 2005 to the day of occurrence of the earthquake on 8 October 2005 and the effect continued, decayed gradually and eventually ceased on 16 October 2005. The spikes distinctly superimposed on the ambient level with mutual separation of 2–5 min. Occurrence number of spikes per hour and total duration of their occurrence have been found remarkably high on the day of occurrence of the earthquake. The spike heights are higher at 6 kHz than at 9 kHz. The results have been explained on the basis of generation of electromagnetic radiation associated with fracture of rocks, their subsequent penetration into the Earth's atmosphere and finally their propagation between Earth-ionosphere waveguide. The present observation shows that VLF anomaly is well-confined between 6 and 9 kHz.

Grating stimulated echo

International Nuclear Information System (INIS)

Dubetsky, B.; Berman, P.R.; Sleator, T.

1992-01-01

A theory of a grating simulated echo (GTE) is developed. The GSE involves the sequential excitation of atoms by two counterpropagating traveling waves, a standing wave, and a third traveling wave. It is shown that the echo signal is very sensitive to small changes in atomic velocity, much more sensitive than the normal stimulated echo. Use of the GSE as a collisional probe or accelerometer is discussed

Rapid Gradient-Echo Imaging

Science.gov (United States)

Hargreaves, Brian

2012-01-01

Gradient echo sequences are widely used in magnetic resonance imaging (MRI) for numerous applications ranging from angiography to perfusion to functional MRI. Compared with spin-echo techniques, the very short repetition times of gradient-echo methods enable very rapid 2D and 3D imaging, but also lead to complicated “steady states.” Signal and contrast behavior can be described graphically and mathematically, and depends strongly on the type of spoiling: fully balanced (no spoiling), gradient spoiling, or RF-spoiling. These spoiling options trade off between high signal and pure T1 contrast while the flip angle also affects image contrast in all cases, both of which can be demonstrated theoretically and in image examples. As with spin-echo sequences, magnetization preparation can be added to gradient-echo sequences to alter image contrast. Gradient echo sequences are widely used for numerous applications such as 3D perfusion imaging, functional MRI, cardiac imaging and MR angiography. PMID:23097185

ECHO-UseFY17.png | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Help Content for ECHO Reports | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Rotary spin echoes

Energy Technology Data Exchange (ETDEWEB)

Solomon, I. [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Saclay, BP2, Gif-sur-Yvette (France)

1959-07-01

Torrey has observed the free precession of nuclear spins around an r-f field H{sub 1}, fixed in a frame rotating at the Larmor frequency ω{sub 0} = γH{sub 0} around a large d-c magnetic field H{sub 0}. He showed that for an H{sub 1}, much larger than inhomogeneity of H{sub 0}, the latter has a negligible effect on the decay of the spin magnetization which is mainly due to the inhomogeneity of H{sub 1}. We report here on a method of overcoming the inhomogeneity of H{sub 1}, by production of echoes in the rotating frame ('rotary echoes'). These echoes are obtained by a 180 deg. phase shift at t = τ on the r-f field so that H{sub 1}, is suddenly reversed, producing a re-focussing of the magnetization vectors at the time t = 2 τ. The rotary echoes so obtained are very similar to the usual spin-echoes with, however some specific features that make them particularly suitable for the measurement of long relaxation times. Reprint of a paper published in Physical Review Letters, vol. 2, no. 7, Apr 1959, p. 301-302.

Rotary spin echoes

International Nuclear Information System (INIS)

Solomon, I.

1959-01-01

Torrey has observed the free precession of nuclear spins around an r-f field H 1 , fixed in a frame rotating at the Larmor frequency ω 0 = γH 0 around a large d-c magnetic field H 0 . He showed that for an H 1 , much larger than inhomogeneity of H 0 , the latter has a negligible effect on the decay of the spin magnetization which is mainly due to the inhomogeneity of H 1 . We report here on a method of overcoming the inhomogeneity of H 1 , by production of echoes in the rotating frame ('rotary echoes'). These echoes are obtained by a 180 deg. phase shift at t = τ on the r-f field so that H 1 , is suddenly reversed, producing a re-focussing of the magnetization vectors at the time t = 2 τ. The rotary echoes so obtained are very similar to the usual spin-echoes with, however some specific features that make them particularly suitable for the measurement of long relaxation times. Reprint of a paper published in Physical Review Letters, vol. 2, no. 7, Apr 1959, p. 301-302

Vibration piezoelectric energy harvester with multi-beam

Energy Technology Data Exchange (ETDEWEB)

Cui, Yan, E-mail: yanc@dlut.edu.cn; Zhang, Qunying, E-mail: zhangqunying89@126.com; Yao, Minglei, E-mail: yaomingleiok@126.com [Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, 116024, Dalian, Liaoning Province (China); Dong, Weijie, E-mail: dongwj@dlut.edu.cn [School of Electronic and Information Engineering, Dalian University of Technology, 116024, Dalian, Liaoning Province (China); Gao, Shiqiao, E-mail: gaoshq@bit.edu.cn [State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, 100081, Beijing Province (China)

2015-04-15

This work presents a novel vibration piezoelectric energy harvester, which is a micro piezoelectric cantilever with multi-beam. The characteristics of the PZT (Pb(Zr{sub 0.53}Ti{sub 0.47})O{sub 3}) thin film were measured; XRD (X-ray diffraction) pattern and AFM (Atomic Force Microscope) image of the PZT thin film were measured, and show that the PZT (Pb(Zr{sub 0.53}Ti{sub 0.47})O{sub 3}) thin film is highly (110) crystal oriented; the leakage current is maintained in nA magnitude, the residual polarisation Pr is 37.037 μC/cm{sup 2}, the coercive field voltage Ec is 27.083 kV/cm, and the piezoelectric constant d{sub 33} is 28 pC/N. In order to test the dynamic performance of the energy harvester, a new measuring system was set up. The maximum output voltage of the single beam of the multi-beam can achieve 80.78 mV under an acceleration of 1 g at 260 Hz of frequency; the maximum output voltage of the single beam of the multi-beam is almost 20 mV at 1400 Hz frequency. .

Shallow water acoustic backscatter and reverberation measurements using a 68-kHz cylindrical array

Science.gov (United States)

Gallaudet, Timothy Cole

2001-10-01

The characterization of high frequency, shallow water acoustic backscatter and reverberation is important because acoustic systems are used in many scientific, commercial, and military applications. The approach taken is to use data collected by the Toroidal Volume Search Sonar (TVSS), a 68 kHz multibeam sonar capable of 360° imaging in a vertical plane perpendicular to its direction of travel. With this unique capability, acoustic backscatter imagery of the seafloor, sea surface, and horizontal and vertical planes in the volume are constructed from data obtained in 200m deep waters in the Northeastern Gulf of Mexico when the TVSS was towed 78m below the surface, 735m astern of a towship. The processed imagery provide a quasi-synoptic characterization of the spatial and temporal structure of boundary and volume acoustic backscatter and reverberation. Diffraction, element patterns, and high sidelobe levels are shown to be the most serious problems affecting cylindrical arrays such as the TVSS, and an amplitude shading method is presented for reducing the peak sidelobe levels of irregular-line and non-coplanar arrays. Errors in the towfish's attitude and motion sensor, and irregularities in the TVSS's transmitted beampattern produce artifacts in the TVSS-derived bathymetry and seafloor acoustic backscatter imagery. Correction strategies for these problems are described, which are unique in that they use environmental information extracted from both ocean boundaries. Sea surface and volume acoustic backscatter imagery are used to explore and characterize the structure of near-surface bubble clouds, schooling fish, and zooplankton. The simultaneous horizontal and vertical coverage provided by the TVSS is shown to be a primary advantage, motivating further use of multibeam sonars in these applications. Whereas boundary backscatter fluctuations are well described by Weibull, K, and Rayleigh mixture probability distributions, those corresponding to volume backscatter are

How can dolphins recognize fish according to their echoes? A statistical analysis of fish echoes.

Directory of Open Access Journals (Sweden)

Yossi Yovel

Full Text Available Echo-based object classification is a fundamental task of animals that use a biosonar system. Dolphins and porpoises should be able to rely on echoes to discriminate a predator from a prey or to select a desired prey from an undesired object. Many studies have shown that dolphins and porpoises can discriminate between objects according to their echoes. All of these studies however, used unnatural objects that can be easily characterized in human terminologies (e.g., metallic spheres, disks, cylinders. In this work, we collected real fish echoes from many angles of acquisition using a sonar system that mimics the emission properties of dolphins and porpoises. We then tested two alternative statistical approaches in classifying these echoes. Our results suggest that fish species can be classified according to echoes returning from porpoise- and dolphin-like signals. These results suggest how dolphins and porpoises can classify fish based on their echoes and provide some insight as to which features might enable the classification.

Wind yield forecast with Echo State Networks; Windertragsprognose mit Echo State Networks

Energy Technology Data Exchange (ETDEWEB)

Kobialka, Hans-Ulrich [Fraunhofer IAIS, Sankt Augustin (Germany)

2012-07-01

Statistical methods are able to create models of complex system dynamics which are difficult to capture analytically. This paper describes a wind energy prediction system based on a machine learning method, called Echo State Networks. Echo State Networks enable the training of large recurrent neural networks which are able to model and predict highly non-linear system dynamics. This paper gives a short description of Echo State Networks and the realization of the wind energy prediction system. (orig.)

A DC excited waveguide multibeam CO2 laser using high frequency ...

Indian Academy of Sciences (India)

High power industrial multibeam CO2 lasers consist of a large number of closely packed ... by producing pre-ionization using an auxiliary high frequency pulsed ... of few kilowatts output power, multibeam technique is used [2]. .... gas mixture of CO2, N2 and He enters in each discharge tube individually from .... Commercial.

Happy birthday Echo!

CERN Document Server

Staff Association

2010-01-01

You are reading the number hundred and one (no. 101) edition of our bulletin Echo. Just over four years ago, on 27th March 2006, the first untitled edition was published (Fig. 1 on the left). The title Echo appeared on the second edition on 10th April 2006 (Fig. 1 in the centre). Today (see Fig. 1 on the right), the layout is slightly different, but the structure of each edition has remained more or less the same: an editorial informing you of the important issues, followed by articles on club life, cultural activities (exhibitions and conferences), information from GAC-EPA, and special offers for our members.     Fig. 1 : Nos. 1, 2 and 100 of our twice-monthly publication Echo Echo was created in March 2006 when, much to our regret, CERN official communication and that of your representatives were separated. November 2009 saw a return to normal practice, and since then the CERN st...

Mosaic of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

A comparison of multi-echo spin-echo and triple-echo steady-state T2 mapping for in vivo evaluation of articular cartilage

International Nuclear Information System (INIS)

Juras, Vladimir; Szomolanyi, Pavol; Bohndorf, Klaus; Kronnerwetter, Claudia; Hager, Benedikt; Zbyn, Stefan; Heule, Rahel; Bieri, Oliver; Trattnig, Siegfried

2016-01-01

To assess the clinical relevance of T 2 relaxation times, measured by 3D triple-echo steady-state (3D-TESS), in knee articular cartilage compared to conventional multi-echo spin-echo T 2 -mapping. Thirteen volunteers and ten patients with focal cartilage lesions were included in this prospective study. All subjects underwent 3-Tesla MRI consisting of a multi-echo multi-slice spin-echo sequence (CPMG) as a reference method for T 2 mapping, and 3D TESS with the same geometry settings, but variable acquisition times: standard (TESSs 4:35min) and quick (TESSq 2:05min). T 2 values were compared in six different regions in the femoral and tibial cartilage using a Wilcoxon signed ranks test and the Pearson correlation coefficient (r). The local ethics committee approved this study, and all participants gave written informed consent. The mean quantitative T 2 values measured by CPMG (mean: 46±9ms) in volunteers were significantly higher compared to those measured with TESS (mean: 31±5ms) in all regions. Both methods performed similarly in patients, but CPMG provided a slightly higher difference between lesions and native cartilage (CPMG: 90ms→61ms [31%],p=0.0125;TESS 32ms→24ms [24%],p=0.0839). 3D-TESS provides results similar to those of a conventional multi-echo spin-echo sequence with many benefits, such as shortening of total acquisition time and insensitivity to B 1 and B 0 changes. (orig.)

Acoustic Multi-Beam Echosounder Data (ME70)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Southeast Fisheries Science Center Mississippi Laboratories collects data using a Simrad ME70 scientific multibeam acoustic echosounder during resource...

Air puff-induced 22-kHz calls in F344 rats.

Science.gov (United States)

Inagaki, Hideaki; Sato, Jun

2016-03-01

Air puff-induced ultrasonic vocalizations in adult rats, termed "22-kHz calls," have been applied as a useful animal model to develop psychoneurological and psychopharmacological studies focusing on human aversive affective disorders. To date, all previous studies on air puff-induced 22-kHz calls have used outbred rats. Furthermore, newly developed gene targeting technologies, which are essential for further advancement of biomedical experiments using air puff-induced 22-kHz calls, have enabled the production of genetically modified rats using inbred rat strains. Therefore, we considered it necessary to assess air puff-induced 22-kHz calls in inbred rats. In this study, we assessed differences in air puff-induced 22-kHz calls between inbred F344 rats and outbred Wistar rats. Male F344 rats displayed similar total (summed) duration of air puff-induced 22 kHz vocalizations to that of male Wistar rats, however, Wistar rats emitted fewer calls of longer duration, while F344 rats emitted higher number of vocalizations of shorter duration. Additionally, female F344 rats emitted fewer air puff-induced 22-kHz calls than did males, thus confirming the existence of a sex difference that was previously reported for outbred Wistar rats. The results of this study could confirm the reliability of air puff stimulus for induction of a similar amount of emissions of 22-kHz calls in different rat strains, enabling the use of air puff-induced 22-kHz calls in inbred F344 rats and derived genetically modified animals in future studies concerning human aversive affective disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

A comparison of multi-echo spin-echo and triple-echo steady-state T2 mapping for in vivo evaluation of articular cartilage

Energy Technology Data Exchange (ETDEWEB)

Juras, Vladimir; Szomolanyi, Pavol [Medical University of Vienna, High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Vienna (Austria); Institute of Measurement Science, Department of Imaging Methods, Bratislava (Slovakia); Bohndorf, Klaus; Kronnerwetter, Claudia; Hager, Benedikt; Zbyn, Stefan [Medical University of Vienna, High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Vienna (Austria); Heule, Rahel; Bieri, Oliver [University of Basel Hospital, Division of Radiological Physics, Department of Radiology, Basel (Switzerland); Trattnig, Siegfried [Medical University of Vienna, High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Vienna (Austria); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna (Austria); Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Austrian Cluster for Tissue Regeneration, Vienna (Austria)

2016-06-15

To assess the clinical relevance of T{sub 2} relaxation times, measured by 3D triple-echo steady-state (3D-TESS), in knee articular cartilage compared to conventional multi-echo spin-echo T{sub 2}-mapping. Thirteen volunteers and ten patients with focal cartilage lesions were included in this prospective study. All subjects underwent 3-Tesla MRI consisting of a multi-echo multi-slice spin-echo sequence (CPMG) as a reference method for T{sub 2} mapping, and 3D TESS with the same geometry settings, but variable acquisition times: standard (TESSs 4:35min) and quick (TESSq 2:05min). T{sub 2} values were compared in six different regions in the femoral and tibial cartilage using a Wilcoxon signed ranks test and the Pearson correlation coefficient (r). The local ethics committee approved this study, and all participants gave written informed consent. The mean quantitative T{sub 2} values measured by CPMG (mean: 46±9ms) in volunteers were significantly higher compared to those measured with TESS (mean: 31±5ms) in all regions. Both methods performed similarly in patients, but CPMG provided a slightly higher difference between lesions and native cartilage (CPMG: 90ms→61ms [31%],p=0.0125;TESS 32ms→24ms [24%],p=0.0839). 3D-TESS provides results similar to those of a conventional multi-echo spin-echo sequence with many benefits, such as shortening of total acquisition time and insensitivity to B{sub 1} and B{sub 0} changes. (orig.)

Seabottom characterization using multibeam echosounder angular backscatter: An application of the composite roughness theory

Digital Repository Service at National Institute of Oceanography (India)

Chakraborty, B.; Schenke, H.W.; Kodagali, V.N.; Hagen, R.

multibeam echosounding systems reveal significant results related to seabottom geological processes ([3] and references therein). Jackson et al., [1] had proposed simultaneous application of the two backscatter theories related to the large and small-scale... to acquire multibeam deep ocean seabottom backscatter data of higher angular range (62 20 14 incidence angle). However, with the commercial availability of the multibeam-Hydrosweep system [4], which operates at a 45 14 half fan width, it has become possible...

Coverage map of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

Alarm pheromone does not modulate 22-kHz calls in male rats.

Science.gov (United States)

Muyama, Hiromi; Kiyokawa, Yasushi; Inagaki, Hideaki; Takeuchi, Yukari; Mori, Yuji

2016-03-15

Rats are known to emit a series of ultrasonic vocalizations, termed 22-kHz calls, when exposed to distressing stimuli. Pharmacological studies have indicated that anxiety mediates 22-kHz calls in distressed rats. We previously found that exposure to the rat alarm pheromone increases anxiety in rats. Therefore, we hypothesized that the alarm pheromone would increase 22-kHz calls in pheromone-exposed rats. Accordingly, we tested whether exposure to the alarm pheromone induced 22-kHz calls, as well as whether the alarm pheromone increased 22-kHz calls in response to an aversive conditioned stimulus (CS). Rats were first fear-conditioned to an auditory and contextual CS. On the following day, the rats were either exposed to the alarm pheromone or a control odor that was released from the neck region of odor-donor rats. Then, the rats were re-exposed to the aversive CS. The alarm pheromone neither induced 22-kHz calls nor increased 22-kHz calls in response to the aversive CS. In contrast, the control odor unexpectedly reduced the total number and duration of 22-kHz calls elicited by the aversive CS, as well as the duration of freezing. These results suggest that the alarm pheromone does not affect 22-kHz calls in rats. However, we may have found evidence for an appeasing olfactory signal, released from the neck region of odor-donor rats. Copyright © 2016 Elsevier Inc. All rights reserved.

Classification of radar echoes using fractal geometry

International Nuclear Information System (INIS)

Azzaz, Nafissa; Haddad, Boualem

2017-01-01

Highlights: • Implementation of two concepts of fractal geometry to classify two types of meteorological radar echoes. • A new approach, called a multi-scale fractal dimension is used for classification between fixed echoes and rain echoes. • An Automatic identification system of meteorological radar echoes was proposed using fractal geometry. - Abstract: This paper deals with the discrimination between the precipitation echoes and the ground echoes in meteorological radar images using fractal geometry. This study aims to improve the measurement of precipitations by weather radars. For this, we considered three radar sites: Bordeaux (France), Dakar (Senegal) and Me lbourne (USA). We showed that the fractal dimension based on contourlet and the fractal lacunarity are pertinent to discriminate between ground and precipitation echoes. We also demonstrated that the ground echoes have a multifractal structure but the precipitations are more homogeneous than ground echoes whatever the prevailing climate. Thereby, we developed an automatic classification system of radar using a graphic interface. This interface, based on the fractal geometry makes possible the identification of radar echoes type in real time. This system can be inserted in weather radar for the improvement of precipitation estimations.

A comparison of multi-echo spin-echo and triple-echo steady-state T2 mapping for in vivo evaluation of articular cartilage.

Science.gov (United States)

Juras, Vladimir; Bohndorf, Klaus; Heule, Rahel; Kronnerwetter, Claudia; Szomolanyi, Pavol; Hager, Benedikt; Bieri, Oliver; Zbyn, Stefan; Trattnig, Siegfried

2016-06-01

To assess the clinical relevance of T2 relaxation times, measured by 3D triple-echo steady-state (3D-TESS), in knee articular cartilage compared to conventional multi-echo spin-echo T2-mapping. Thirteen volunteers and ten patients with focal cartilage lesions were included in this prospective study. All subjects underwent 3-Tesla MRI consisting of a multi-echo multi-slice spin-echo sequence (CPMG) as a reference method for T2 mapping, and 3D TESS with the same geometry settings, but variable acquisition times: standard (TESSs 4:35min) and quick (TESSq 2:05min). T2 values were compared in six different regions in the femoral and tibial cartilage using a Wilcoxon signed ranks test and the Pearson correlation coefficient (r). The local ethics committee approved this study, and all participants gave written informed consent. The mean quantitative T2 values measured by CPMG (mean: 46±9ms) in volunteers were significantly higher compared to those measured with TESS (mean: 31±5ms) in all regions. Both methods performed similarly in patients, but CPMG provided a slightly higher difference between lesions and native cartilage (CPMG: 90ms→61ms [31%],p=0.0125;TESS 32ms→24ms [24%],p=0.0839). 3D-TESS provides results similar to those of a conventional multi-echo spin-echo sequence with many benefits, such as shortening of total acquisition time and insensitivity to B1 and B0 changes. • 3D-TESS T 2 mapping provides clinically comparable results to CPMG in shorter scan-time. • Clinical and investigational studies may benefit from high temporal resolution of 3D-TESS. • 3D-TESS T 2 values are able to differentiate between healthy and damaged cartilage.

Short echo time, fast gradient-echo imaging

International Nuclear Information System (INIS)

Haacke, E.M.; Lenz, G.W.

1987-01-01

Present fast-gradient-echoes schemes can acquire volume data rapidly and are flexible in T1 or T1/T2 contrast behavior. However, sequences used to date employ echo time (TE) values of about 15 ms +- 5 and, because of in vivo field inhomogeneities (short T2), they suffer badly from signal loss near sinuses and tissue boundaries. The authors implemented sequences with TE = 4-6 ms and found significant improvement in image quality, especially at high fields. Examples with long TEs vs. short TEs are given in the knee, spine, head, and orbits. Further advantages include (1) faster repetition times (15 ms), (2) higher-quality spin-density or T1-weighted images, and (3) reduction of blood motion artifacts

Longitudinal collective echoes in coasting particle beams

Directory of Open Access Journals (Sweden)

Ahmed Al-Khateeb

2003-01-01

Full Text Available Longitudinal ballistic and collective beam echoes with diffusion effects are investigated theoretically. In the presence of the space-charge impedance, the collective echo amplitude is obtained as a closed form expression. In contrast to the ballistic case, the collective echo amplitude consists of one maximum at time t_{echo}. The echo amplitude grows up and damps down with a rate proportional to the Landau damping rate of space-charge waves. The effect of weak diffusion is found to modify the ballistic and the collective echo amplitudes in the same manner. This effect of diffusion was confirmed using a “noiseless,” grid-based simulation code. As a first application the amount of numerical diffusion in our simulation code was determined using the echo effect.

Multibeam 3D Underwater SLAM with Probabilistic Registration

Directory of Open Access Journals (Sweden)

Albert Palomer

2016-04-01

Full Text Available This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds. An Iterative Closest Point (ICP with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1 point-to-point association for coarse registration and (2 point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O ( n 2 to O ( n . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit.

Simulation and design of omni-directional high speed multibeam transmitter system

Science.gov (United States)

Tang, Jaw-Luen; Jui, Ping-Chang; Wang, Sun-Chen

2006-09-01

For future high speed indoor wireless communication, diffuse wireless optical communications offer more robust optical links against shadowing than line-of-sight links. However, their performance may be degraded by multipath dispersion resulting from surface reflections. We have developed a multipath diffusive propagation model capable of providing channel impulse responses data. It is aimed to design and simulate any multi-beam transmitter under a variety of indoor environments. In this paper, a multi-beam transmitter system with semi-sphere structure is proposed to combat the diverse effects of multipath distortion albeit, at the cost of increased laser power and cost. Simulation results of multiple impulse responses showed that this type of multi-beam transmitter can significantly improve the performance of BER suitable for high bit rate application. We present the performance and simulation results for both line-of-sight and diffuse link configurations.

Bathymetric surveys at highway bridges crossing the Missouri River in Kansas City, Missouri, using a multibeam echo sounder, 2010

Science.gov (United States)

Huizinga, Richard J.

2010-01-01

Bathymetric surveys were conducted by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, on the Missouri River in the vicinity of nine bridges at seven highway crossings in Kansas City, Missouri, in March 2010. A multibeam echo sounder mapping system was used to obtain channel-bed elevations for river reaches that ranged from 1,640 to 1,800 feet long and extending from bank to bank in the main channel of the Missouri River. These bathymetric scans will be used by the Missouri Department of Transportation to assess the condition of the bridges for stability and integrity with respect to bridge scour. Bathymetric data were collected around every pier that was in water, except those at the edge of the water or in extremely shallow water, and one pier that was surrounded by a large debris raft. A scour hole was present at every pier for which bathymetric data could be obtained. The scour hole at a given pier varied in depth relative to the upstream channel bed, depending on the presence and proximity of other piers or structures upstream from the pier in question. The surveyed channel bed at the bottom of the scour hole was between 5 and 50 feet above bedrock. At bridges with drilled shaft foundations, generally there was exposure of the upstream end of the seal course and the seal course often was undermined to some extent. At one site, the minimum elevation of the scour hole at the main channel pier was about 10 feet below the bottom of the seal course, and the sides of the drilled shafts were evident in a point cloud visualization of the data at that pier. However, drilled shafts generally penetrated 20 feet into bedrock. Undermining of the seal course was evident as a sonic 'shadow' in the point cloud visualization of several of the piers. Large dune features were present in the channel at nearly all of the surveyed sites, as were numerous smaller dunes and many ripples. Several of the sites are on or near bends in the river

Theory of single-photon echo (SP-echo) and the possibility of its experimental study in the gamma-region

International Nuclear Information System (INIS)

Moiseev, S.A.

1997-01-01

The single-photon echo (SP-echo) effect is predicted to appear in the case of three-level medium excitation by means of a single photon propagating to the medium along two optical paths with a mutual time delay surpassing the temporal duration of the photon wave packet. The quantum electrodynamical theory describing this interaction is presented and the S-matrix of the field is shown for infinite time (t=∞). Using the S-matrix approach, physical properties of the scattering field are studied. Hence, it is shown that the field has an echo signal at the ω 32 0 carrier frequency. It has been shown that the echo signal exists only in the field amplitude while being absent in its intensity behaviour. Thus, SP-echo is an interference effect and is not influenced by the energy irradiation. The problems of SP-echo detection in the gamma-region (where special generation difficulties appear) are discussed. The influence of the additional detection of theω 21 0 frequency field on the echo signal has been shown. A special case is the EPR-paradox which can appear within the echo phenomenon

Theory of single-photon echo (SP-echo) and the possibility of its experimental study in the gamma-region

Energy Technology Data Exchange (ETDEWEB)

Moiseev, S.A

1997-05-15

The single-photon echo (SP-echo) effect is predicted to appear in the case of three-level medium excitation by means of a single photon propagating to the medium along two optical paths with a mutual time delay surpassing the temporal duration of the photon wave packet. The quantum electrodynamical theory describing this interaction is presented and the S-matrix of the field is shown for infinite time (t={infinity}). Using the S-matrix approach, physical properties of the scattering field are studied. Hence, it is shown that the field has an echo signal at the {omega}{sub 32}{sup 0} carrier frequency. It has been shown that the echo signal exists only in the field amplitude while being absent in its intensity behaviour. Thus, SP-echo is an interference effect and is not influenced by the energy irradiation. The problems of SP-echo detection in the gamma-region (where special generation difficulties appear) are discussed. The influence of the additional detection of the{omega}{sub 21}{sup 0} frequency field on the echo signal has been shown. A special case is the EPR-paradox which can appear within the echo phenomenon.

A radar-echo model for Mars

International Nuclear Information System (INIS)

Thompson, T.W.; Moore, H.J.

1990-01-01

Researchers developed a radar-echo model for Mars based on 12.6 cm continuous wave radio transmissions backscattered from the planet. The model broadly matches the variations in depolarized and polarized total radar cross sections with longitude observed by Goldstone in 1986 along 7 degrees S. and yields echo spectra that are generally similiar to the observed spectra. Radar map units in the model include an extensive cratered uplands unit with weak depolarized echo cross sections, average thermal inertias, moderate normal refelectivities, and moderate rms slopes; the volcanic units of Tharsis, Elysium, and Amazonis regions with strong depolarized echo cross sections, low thermal inertia, low normal reflectivities, and large rms slopes; and the northern planes units with moderate to strong depolarized echo cross sections, moderate to very high thermal inertias, moderate to large normal reflectivities, and moderate rms slopes. The relevance of the model to the interpretation of radar echoes from Mars is discussed

The acoustics of the echo cornet

Science.gov (United States)

Pyle, Robert W., Jr.; Klaus, Sabine K.

2002-11-01

The echo cornet was an instrument produced by a number of makers in several countries from about the middle of the nineteenth to the early twentieth centuries. It consists of an ordinary three-valve cornet to which a fourth valve has been added, downstream of the three normal valves. The extra valve diverts the airstream from the normal bell to an ''echo'' bell that gives a muted tone quality. Although the air column through the echo bell is typically 15 cm longer than the path through the normal bell, there is no appreciable change of playing pitch when the echo bell is in use. Acoustic input impedance and impulse response measurements and consideration of the standing-wave pattern within the echo bell show how this can be so. Acoustically, the echo bell is more closely related to hand-stopping on the French horn than to the mutes commonly used on the trumpet and cornet.

Automatic classification techniques for type of sediment map from multibeam sonar data

Science.gov (United States)

Zakariya, R.; Abdullah, M. A.; Che Hasan, R.; Khalil, I.

2018-02-01

Sediment map can be important information for various applications such as oil drilling, environmental and pollution study. A study on sediment mapping was conducted at a natural reef (rock) in Pulau Payar using Sound Navigation and Ranging (SONAR) technology which is Multibeam Echosounder R2-Sonic. This study aims to determine sediment type by obtaining backscatter and bathymetry data from multibeam echosounder. Ground truth data were used to verify the classification produced. The method used to analyze ground truth samples consists of particle size analysis (PSA) and dry sieving methods. Different analysis being carried out due to different sizes of sediment sample obtained. The smaller size was analyzed using PSA with the brand CILAS while bigger size sediment was analyzed using sieve. For multibeam, data acquisition includes backscatter strength and bathymetry data were processed using QINSy, Qimera, and ArcGIS. This study shows the capability of multibeam data to differentiate the four types of sediments which are i) very coarse sand, ii) coarse sand, iii) very coarse silt and coarse silt. The accuracy was reported as 92.31% overall accuracy and 0.88 kappa coefficient.

THE SPECTRAL-TIMING PROPERTIES OF UPPER AND LOWER kHz QPOs

Energy Technology Data Exchange (ETDEWEB)

Peille, Philippe; Barret, Didier [Université de Toulouse, UPS-OMP, IRAP, Toulouse (France); Uttley, Phil, E-mail: philippe.peille@irap.omp.eu [Anton Pannekoek Institute, University of Amsterdam, Postbus 94249, 1090 GE Amsterdam (Netherlands)

2015-10-01

Soft lags from the emission of the lower kilohertz quasi-periodic oscillations (kHz QPOs) of neutron star low-mass X-ray binaries have been reported from 4U1608-522 and 4U1636-536. Those lags hold prospects for constraining the origin of the QPO emission. In this paper, we investigate the spectral-timing properties of both the lower and upper kHz QPOs from the neutron star binary 4U1728-34, using the entire Rossi X-Ray Timing Explorer archive on this source. We show that the lag-energy spectra of the two QPOs are systematically different: while the lower kHz QPO shows soft lags, the upper kHz QPO shows either a flat lag-energy spectrum or hard variations lagging softer variations. This suggests two different QPO-generation mechanisms. We also performed the first spectral deconvolution of the covariance spectra of both kHz QPOs. The QPO spectra are consistent with Comptonized blackbody emission, similar to the one found in the time-averaged spectrum, but with a higher seed-photon temperature, suggesting that a more compact inner region of the Comptonization layer (boundary/spreading layer, corona) is responsible for the QPO emission. Considering our results together with other recent findings, this leads us to the hypothesis that the lower kHz QPO signal is generated by coherent oscillations of the compact boundary layer region itself. The upper kHz QPO signal may then be linked to less-coherent accretion-rate variations produced in the inner accretion disk, and is then detected when they reach the boundary layer.

Multibeam smart antenna field trial experiments in mobile radio environments

Science.gov (United States)

Perini, Patrick

1996-01-01

Several types of high gain multibeam antennas were tested and compared to traditional sector and omni antennas in various mobile radio environments. A vehicle equipped with a mobile transmitter drove in several mobile radio environments while the received signal strength (RSS) was recorded on multiple antenna channels attached to multibeam, sector and omni directional antennas. The RSS data recorded included the fast (rayleigh) fading and was averaged into local means based on the mobile's position/speed. Description of the experiment and analysis of the gain improvement, average RSS, diversity gain are presented.

Multibeam collection for Marianas: Multibeam data collected aboard Onnuri from 2003-09-18 to 2003-09-23, Guam to Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Effects of the India–Pakistan border earthquake on the atmospherics at 6 kHz and 9 kHz recorded at Tripura

Directory of Open Access Journals (Sweden)

Sudarsan Barui

2011-04-01

Full Text Available The unusual variations observed in the records of the integrated field intensity of the atmospherics (IFIA at 6 kHz and 9 kHz at Agartala, Tripura, in the north-eastern state of India (latitude, 23˚ N; longitude, 91.4˚ E during the large earthquake on October 8, 2005 at Muzaffarabad (latitude, 34.53˚ N; longitude, 73.58˚ E in Kashmir in Pakistan are here analyzed. Spiky variations in the IFIA at 6 kHz and 9 kHz were observed several days previous to the day of the earthquake (from midnight, September 28, 2005. The effects persisted for some days, decayed gradually, and eventually ceased on October 31, 2005. The spikes are distinctly superimposed on the ambient level

Lithium ion diffusion measurements on a garnet-type solid conductor Li6.6La3Zr1.6Ta0.4O12 by using a pulsed-gradient spin-echo NMR method.

Science.gov (United States)

Hayamizu, Kikuko; Matsuda, Yasuaki; Matsui, Masaki; Imanishi, Nobuyuki

2015-09-01

The garnet-type solid conductor Li7-xLa3Zr2-xTaxO12 is known to have high ionic conductivity. We synthesized a series of compositions of this conductor and found that cubic Li6.6La3Zr1.6Ta0.4O12 (LLZO-Ta) has a high ionic conductivity of 3.7×10(-4)Scm(-1) at room temperature. The (7)Li NMR spectrum of LLZO-Ta was composed of narrow and broad components, and the linewidth of the narrow component varied from 0.69kHz (300K) to 0.32kHz (400K). We carried out lithium ion diffusion measurements using pulsed-field spin-echo (PGSE) NMR spectroscopy and found that echo signals were observed at T≥313K with reasonable sensitivity. The lithium diffusion behavior was measured by varying the observation time and pulsed-field gradient (PFG) strength between 313 and 384K. We found that lithium diffusion depended significantly on the observation time and strength of the PFG, which is quite different from lithium ion diffusion in liquids. It was shown that lithium ion migration in the solid conductor was distributed widely in both time and space. Copyright © 2015 Elsevier Inc. All rights reserved.

Experimental separation of a frequency spin echo signal

International Nuclear Information System (INIS)

Bun'kov, Yu.M.; Dmitriev, V.V.

1981-01-01

To study systems with bound nuclear-electron precession CsMnF 2 antiferromagnetic light-plane monocrystal was investigated. Crystal orientation was carried out by roentgenoscopy. Measurements were performed at helium temperatures in the 500-700 MHz frequency range. A NMR pulsed spectrometer with generators of both resonance and doubled frequency was used to produce an echo signal (to study by the parametric echo method). It was shown that the theory of the formation of a frequency modulated echo (FM echo) did not fully describe the properties of the echo signals in systems with dynamic frequency shift (DFS). An intense spin echo signal, which formation was apparently connected with other nonlinear properties of the systems with nuclear-electron precession, was observed. The spin echo signal in magnetics with DFS, which properties correspond to notions of the frequency mechanism of echo formation, was experimentally separated. As a result of the investigations it had been possible to settle contradictions between the theory of FM echo formation and the experimental results for the last 9 years. It turned out that the mechanism of FM echo formation in the magnetics with bound nuclear-electron precession was effective only at large delay times between the pulses. In the range of small delays the FM echo is ''jammed'' by a gigantic echo signal of a nature different from that of the traditional FM signal. The constant of gigantic echo intensity drop at increasing delay between the pulses weakly depends on spin-spin relaxation time [ru

Single-shot echo-planar imaging of multiple sclerosis: effects of varying echo time

International Nuclear Information System (INIS)

Wolansky, L.J.; Chong, S.; Liu, W.C.; Kang, E.; Simpson, S.W.; Karimi, S.; Akbari, H.

1999-01-01

Our aim was to determine the relative merits of short and long echo times (TE) with single-shot echo-planar imaging for imaging cerebral lesions such as multiple sclerosis. We examined seven patients with clinically definite multiple sclerosis were imaged at 1.5 T. Patients were scanned with spin-echo, single-shot echo-planar imaging, using TEs of 45, 75, 105, and 135 ms. Region of interest (ROI) measurements were performed on 36 lesions at or above the level of the corona radiata. The mean image contrast (IC) was highest (231.1) for a TE of 45 ms, followed by 75 ms (218.9), 105 ms (217.9), and 135 ms (191.6). When mean contrast-to-noise ratios (C/N) were compared, the value was again highest (29.7) for TE 45 ms, followed by 75 ms (28.9), 105 ms (28.5), and 135 ms (26.3). In a lesion-by-lesion comparison, TE 45 ms had the highest IC and C/N in the largest number of cases (50 % and 47.2 %, respectively). IC and C/N for TE 45 ms were superior to those of 75 ms in 64 % and 58 %, respectively. These results support the use of relatively short TEs for single-shot echo-planar imaging in the setting of cerebral lesions such as multiple sclerosis. (orig.) (orig.)

Wavelet-LMS algorithm-based echo cancellers

Science.gov (United States)

Seetharaman, Lalith K.; Rao, Sathyanarayana S.

2002-12-01

This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

Assessment of diagnosing metastatic bone tumor on T2*-weighted images. Comparison between turbo spin echo (TSE) method and gradient echo (GE) method

International Nuclear Information System (INIS)

Hayashi, Takahiko; Sugiyama, Akira; Katayama, Motoyuki

1996-01-01

We examined the usefulness of T2 * weighted gradient field echo images for diagnosis for metastatic bone tumors in comparison with T2 weighted turbo spin echo (fast spin echo) images. In T2 * weighted gradient field echo sequence to obtain maximum contrast-to-noise ratio (CNR), we experimentally manipulated flip angle (FA) (5deg-90deg), repetition time (TR) (400, 700 msec), and echo time (TE) (10-50 msec). The best CNR was 16.4 in fast low angle shot (FLASH) (TE: 24 msec, TR: 700 msec, FA: 40deg). Magnetic resonance imaging was carried out in 28 patients with metastatic bone tumors. In addition to conventional T1 weighted spin echo images, T2 weighted turbo spin echo (fast spin echo images) and T2 * weighted gradient field echo images were obtained. T2 * weighted gradient field echo images were superior to T2 weighted turbo spin echo (fast spin echo) images in delineating the tumors, adjacent fat tissues, and bone marrow. (author)

San Francisco Bay Multi-beam Bathymetry: Area A

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These multi-beam bathymetric data were collected over shallow subtidal areas in the San Francisco Bay estuary system. Bathymetric and acoustic backscatter data were...

Electric Dipole Echoes and Noise-Induced Coherence

International Nuclear Information System (INIS)

Mestayer, J.J.; Zhao, W.; Lancaster, J.C.; Dunning, F.B.; Yoshida, S.; Reinhold, Carlos O.; Burgdorfer, J.

2007-01-01

The generation of echoes in the electric dipole moment of a Rydberg wavepacket precessing in an external electric field by reversal of the field is described. When the wavepacket experiences reversible dephasing, large echoes are observed pointing to strong refocusing of the wavepacket. The presence of irreversible dephasing leads to a reduction in the size of the echoes. The effect of irreversible dynamics on echoes is investigated using artificially synthesized noise. Methods to determine the decoherence rate are discussed

Beam echoes in the presence of coupling

Energy Technology Data Exchange (ETDEWEB)

Gross, Axel [Case Western Reserve U.

2017-10-03

Transverse beam echoes could provide a new technique of measuring diusion characteristics orders of magnitude faster than the current methods; however, their interaction with many accelerator parameters is poorly understood. Using a program written in C, we explored the relationship between coupling and echo strength. We found that echoes could be generated in both dimensions, even with a dipole kick in only one dimension. We found that the echo eects are not destroyed even when there is strong coupling, falling o only at extremely high coupling values. We found that at intermediate values of skew quadrupole strength, the decoherence time of the beam is greatly increased, causing a destruction of the echo eects. We found that this is caused by a narrowing of the tune width of the particles. Results from this study will help to provide recommendations to IOTA (Integrable Optics Test Accelerator) for their upcoming echo experiment.

Use of Multibeam and Dual-Beam Sonar Systems to Observe Cavitating Flow Produced by Ferryboats: In a Marine Renewable Energy Perspective

Directory of Open Access Journals (Sweden)

Francisco Francisco

2017-07-01

Full Text Available With the prospect to deploy hydrokinetic energy converters in areas with heavy boat traffic, a study was conducted to observe and assess the depth range of cavitating flow produced by ferryboats in narrow channels. This study was conducted in the vicinity of Finnhamn Island in Stockholm Archipelago. The objectives of the survey were to assess whether the sonar systems were able to observe and measure the depth of what can be cavitating flow (in a form of convected cloud cavitation produced by one specific type of ferryboats frequently operating in that route, as well as investigate if the cavitating flow within the wake would propagate deep enough to disturb the water column underneath the surface. A multibeam and a dual-beam sonar systems were used as measurement instruments. The hypothesis was that strong and deep wake can disturb the optimal operation of a hydrokinetic energy converter, therefore causing damages to its rotors and hydrofoils. The results showed that both sonar system could detect cavitating flows including its strength, part of the geometrical shape and propagation depth. Moreover, the boat with a propeller thruster produced cavitating flow with an intense core reaching 4 m of depth while lasting approximately 90 s. The ferry with waterjet thruster produced a less intense cavitating flow; the core reached depths of approximately 6 m, and lasted about 90 s. From this study, it was concluded that multibeam and dual-beam sonar systems with operating frequencies higher than 200 kHz were able to detect cavitating flows in real conditions, as long as they are properly deployed and the data properly analyzed.

Multi-beam synchronous measurement based on PSD phase detection using frequency-domain multiplexing

Science.gov (United States)

Duan, Ying; Qin, Lan; Xue, Lian; Xi, Feng; Mao, Jiubing

2013-10-01

According to the principle of centroid measurement, position-sensitive detectors (PSD) are commonly used for micro displacement detection. However, single-beam detection method cannot satisfy such tasks as multi-dimension position measurement, three dimension vision reconstruction, and robot precision positioning, which require synchronous measurement of multiple light beams. Consequently, we designed PSD phase detection method using frequency-domain multiplexing for synchronous detection of multiple modulated light beams. Compared to previous PSD amplitude detection method, the phase detection method using FDM has advantages of simplified measuring system, low cost, high capability of resistance to light interference as well as improved resolution. The feasibility of multi-beam synchronous measurement based on PSD phase detection using FDM was validated by multi-beam measuring experiments. The maximum non-linearity error of the multi-beam synchronous measurement is 6.62%.

In vivo endoscopic multi-beam optical coherence tomography

Energy Technology Data Exchange (ETDEWEB)

Standish, Beau A; Mariampillai, Adrian; Munce, Nigel R; Leung, Michael K K; Vitkin, I Alex [Deptartment of Medical Biophysics, University of Toronto, Toronto (Canada); Lee, Kenneth K C; Yang, Victor X D [Ontario Cancer Institute/University Health Network, Toronto (Canada)], E-mail: standish@ee.ryerson.ca

2010-02-07

A multichannel optical coherence tomography (multi-beam OCT) system and an in vivo endoscopic imaging probe were developed using a swept-source OCT system. The distal optics were micro-machined to produce a high numerical aperture, multi-focus fibre optic array. This combination resulted in a transverse design resolution of <10 {mu}m full width half maximum (FWHM) throughout the entire imaging range, while also increasing the signal intensity within the focus of the individual channels. The system was used in a pre-clinical rabbit study to acquire in vivo structural images of the colon and ex vivo images of the oesophagus and trachea. A good correlation between the structural multi-beam OCT images and H and E histology was achieved, demonstrating the feasibility of this high-resolution system and its potential for in vivo human endoscopic imaging.

In vivo endoscopic multi-beam optical coherence tomography

International Nuclear Information System (INIS)

Standish, Beau A; Mariampillai, Adrian; Munce, Nigel R; Leung, Michael K K; Vitkin, I Alex; Lee, Kenneth K C; Yang, Victor X D

2010-01-01

A multichannel optical coherence tomography (multi-beam OCT) system and an in vivo endoscopic imaging probe were developed using a swept-source OCT system. The distal optics were micro-machined to produce a high numerical aperture, multi-focus fibre optic array. This combination resulted in a transverse design resolution of <10 μm full width half maximum (FWHM) throughout the entire imaging range, while also increasing the signal intensity within the focus of the individual channels. The system was used in a pre-clinical rabbit study to acquire in vivo structural images of the colon and ex vivo images of the oesophagus and trachea. A good correlation between the structural multi-beam OCT images and H and E histology was achieved, demonstrating the feasibility of this high-resolution system and its potential for in vivo human endoscopic imaging.

U 1608-52: a Cornerstone in Our Understanding of the Khz Qpos

Science.gov (United States)

Mendez, Mariano

We propose a series of ASM-triggered TOO observations of the atoll source 4U 1608-52 in outburst for a total of 450 ksec. These triggers are planned to maximize the probability of observing kHz QPOs and type- I X-ray bursts in this source. This is one of only 2 sources where the separation between the 2 simultaneous kHz QPOs varies significantly as a function of mass accretion rate. The detection of near-coherent oscillations during the bursts will provide a strong clue to the nature of the kHz QPOs in LMXBs, as it would make clear at which mass accretion level, if any, the kHz peak separation does approach the inferred spin rate.

Multibeam collection for GEOMETEP: Multibeam data collected aboard Sonne from 1985-12-17 to 1986-01-07, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0202: Multibeam data collected aboard Maurice Ewing from 2002-02-24 to 2002-03-26, Guam to Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0203: Multibeam data collected aboard Maurice Ewing from 2002-03-28 to 2002-04-25, Guam to Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

X-ray echoes from gamma-ray bursts

International Nuclear Information System (INIS)

Dermer, C.D.; Hurley, K.C.; Hartmann, D.H.

1991-01-01

The identification of an echo of reflected radiation in time histories of gamma-ray burst spectra can provide important information about the existence of binary companions or accretion disks in gamma-ray burst systems. Because of the nature of Compton scattering, the spectrum of the echo will be attenuated at gamma-ray energies compared with the spectrum of the primary burst emission. The expected temporal and spectral signatures of the echo and a search for such echoes are described, and implications for gamma-ray burst models are discussed. 35 refs

Novel multi-beam radiometers for accurate ocean surveillance

DEFF Research Database (Denmark)

Cappellin, C.; Pontoppidan, K.; Nielsen, P. H.

2014-01-01

Novel antenna architectures for real aperture multi-beam radiometers providing high resolution and high sensitivity for accurate sea surface temperature (SST) and ocean vector wind (OVW) measurements are investigated. On the basis of the radiometer requirements set for future SST/OVW missions...

Advanced Communication Technology Satellite (ACTS) multibeam antenna technology verification experiments

Science.gov (United States)

Acosta, Roberto J.; Larko, Jeffrey M.; Lagin, Alan R.

1992-01-01

The Advanced Communication Technology Satellite (ACTS) is a key to reaching NASA's goal of developing high-risk, advanced communications technology using multiple frequency bands to support the nation's future communication needs. Using the multiple, dynamic hopping spot beams, and advanced on board switching and processing systems, ACTS will open a new era in communications satellite technology. One of the key technologies to be validated as part of the ACTS program is the multibeam antenna with rapidly reconfigurable hopping and fixed spot beam to serve users equipped with small-aperature terminals within the coverage areas. The proposed antenna technology experiments are designed to evaluate in-orbit ACTS multibeam antenna performance (radiation pattern, gain, cross pol levels, etc.).

Multibeam collection for KN162L13: Multibeam data collected aboard Knorr from 2001-03-30 to 2001-05-01, Mauritius to Mauritius

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00086: Multibeam data collected aboard Surveyor from 1986-10-25 to 1986-11-03, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1304: Multibeam data collected aboard Melville from 2013-02-25 to 2013-03-17, Yokohama, Japan to Yokohama, Japan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00076: Multibeam data collected aboard Discoverer from 1986-10-03 to 1986-10-13, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Tecfluc: Multibeam data collected aboard Ocean Alert from 1998-05-23 to 1998-05-26, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00289: Multibeam data collected aboard Surveyor from 1991-07-24 to 1991-08-03, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK150523: Multibeam data collected aboard Falkor from 2015-05-23 to 2015-06-22, Singapore, Singapore to Padang, Indonesia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for BD0601: Multibeam data collected aboard Bowditch from 2006-10-16 to 2006-11-11, Okinawa, Japan to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK151221: Multibeam data collected aboard Falkor from 2015-12-21 to 2016-01-05, Apra, Guam to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK141109: Multibeam data collected aboard Falkor from 2014-11-09 to 2014-12-09, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK151121: Multibeam data collected aboard Falkor from 2015-11-21 to 2015-12-17, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK141215: Multibeam data collected aboard Falkor from 2014-12-15 to 2014-12-21, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1301: Multibeam data collected aboard Melville from 2013-01-16 to 2013-01-29, Honolulu, HI to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Heceta: Multibeam data collected aboard Ocean Alert from 1998-05-18 to 1998-05-23, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK140625: Multibeam data collected aboard Falkor from 2014-06-25 to 2014-07-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1302: Multibeam data collected aboard Melville from 2013-02-01 to 2013-02-15, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00027: Multibeam data collected aboard Surveyor from 1985-09-03 to 1985-09-15, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK150324: Multibeam data collected aboard Falkor from 2015-03-24 to 2015-04-06, Broome, Australia to Broome, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00025: Multibeam data collected aboard Surveyor from 1985-08-29 to 1985-09-18, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0805: Multibeam data collected aboard Healy from 2008-08-14 to 2008-09-05, Barrow, AK to Barrow, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00144: Multibeam data collected aboard Surveyor from 1988-06-08 to 1988-06-15, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1302: Multibeam data collected aboard Healy from 2013-08-16 to 2013-09-07, Barrow, AK to Barrow, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00118: Multibeam data collected aboard Davidson from 1987-11-09 to 1987-11-23, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for USF1999: Multibeam data collected aboard Bellows from 1999-02-17 to 1999-10-08, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK141015: Multibeam data collected aboard Falkor from 2014-10-15 to 2014-11-03, Pohnpei, Micronesia to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00009: Multibeam data collected aboard Surveyor from 1984-11-10 to 1984-11-13, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Tralee_bay: Multibeam data collected aboard Aircraft from 2008-05-29 to 2008-06-02, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SO99: Multibeam data collected aboard Sonne from 1995-01-07 to 1995-01-14, Manila, Philippines to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1104: Multibeam data collected aboard Melville from 2011-03-23 to 2011-04-23, Valparaiso, Chile to Arica, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0112: Multibeam data collected aboard Maurice Ewing from 2001-10-06 to 2001-10-23, Seychelles to Fremantle, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0102: Multibeam data collected aboard Healy from 2001-08-02 to 2001-09-29, Tromso, Norway to Tromso, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0103: Multibeam data collected aboard Healy from 2001-10-27 to 2001-11-28, Tromso, Norway to Tromso, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0111: Multibeam data collected aboard Maurice Ewing from 2001-09-13 to 2001-09-20, Djibouti, Djibouti to Seychelles

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK140418: Multibeam data collected aboard Falkor from 2014-04-18 to 2014-04-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for 8900031183: Multibeam data collected aboard Jean Charcot from 1989-03-01 to 1989-03-29, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TN153: Multibeam data collected aboard Thomas G. Thompson from 2003-02-09 to 2003-03-05, Guam to Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN162L12: Multibeam data collected aboard Knorr from 2001-03-24 to 2001-03-27, Seychelles to Mauritius

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KR1998: Multibeam data collected aboard Kairei from 1998-08-24 to 1998-09-18, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for YK1999: Multibeam data collected aboard Yokosuka from 1999-08-01 to 1999-09-22, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KR2001: Multibeam data collected aboard Kairei from 2001-08-16 to 2001-09-19, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK151005: Multibeam data collected aboard Falkor from 2015-10-05 to 2015-11-10, Honolulu, HI to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00002: Multibeam data collected aboard Surveyor from 1984-05-24 to 1984-05-29, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00067: Multibeam data collected aboard Davidson from 1986-08-20 to 1986-08-24, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00094: Multibeam data collected aboard Davidson from 1986-11-10 to 1986-11-12, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00038: Multibeam data collected aboard Surveyor from 1985-10-29 to 1985-11-13, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00183: Multibeam data collected aboard Whiting from 1989-06-22 to 1989-08-02, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00292: Multibeam data collected aboard Surveyor from 1991-08-03 to 1991-08-16, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00177: Multibeam data collected aboard Discoverer from 1989-05-21 to 1989-06-17, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK150301: Multibeam data collected aboard Falkor from 2015-03-01 to 2015-03-12, Henderson, Australia to Henderson, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK150410: Multibeam data collected aboard Falkor from 2015-04-10 to 2015-05-04, Broome, Australia to Darwin, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1004: Multibeam data collected aboard Melville from 2010-03-17 to 2010-03-25, Valparaiso, Chile to Valparaiso, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1103: Multibeam data collected aboard Melville from 2011-03-15 to 2011-03-20, Valparaiso, Chile to Valparaiso, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00085: Multibeam data collected aboard Davidson from 1986-10-26 to 1986-11-10, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00037: Multibeam data collected aboard Surveyor from 1985-11-09 to 1985-11-15, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00010: Multibeam data collected aboard Surveyor from 1984-11-14 to 1985-03-31, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00065: Multibeam data collected aboard Surveyor from 1986-07-02 to 1986-07-08, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1305: Multibeam data collected aboard Melville from 2013-03-21 to 2013-05-05, Yokohama, Japan to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00005: Multibeam data collected aboard Surveyor from 1984-10-16 to 1985-04-22, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00236: Multibeam data collected aboard Surveyor from 1990-08-03 to 1990-08-09, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Oahu: Multibeam data collected aboard Ocean Alert from 1998-02-24 to 1998-02-24, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00274: Multibeam data collected aboard Whiting from 1991-05-24 to 1991-05-29, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1109: Multibeam data collected aboard Melville from 2011-08-24 to 2011-08-30, Balboa, Panama to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1110: Multibeam data collected aboard Melville from 2011-09-03 to 2011-10-08, Bridgetown, Barbados to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KRY1202: Multibeam data collected aboard Keary from 2012-02-01 to 2012-02-28, Bunmahon, Ireland to Cork, Ireland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for YK2002: Multibeam data collected aboard Yokosuka from 2002-07-13 to 2002-09-02, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00276: Multibeam data collected aboard Whiting from 1991-05-29 to 1991-05-30, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for DI9301: Multibeam data collected aboard Discoverer from 1993-02-26 to 1993-04-04, American Samoa to Hilo, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for DI9203: Multibeam data collected aboard Discoverer from 1992-08-09 to 1992-08-09, Hilo, HI to Hilo, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Hilo: Multibeam data collected aboard Ocean Alert from 1998-02-28 to 1998-03-03, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TOGA92: Multibeam data collected aboard Discoverer from 1992-03-03 to 1992-09-30, Hilo, HI to Manzanillo, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

MEASUREMENT OF TRANSVERSE ECHOES IN RHIC

International Nuclear Information System (INIS)

FISCHER, W.; SATOGATA, T.; TOMAS, R.

2005-01-01

Beam echoes are a very sensitive method to measure diffusion, and longitudinal echo measurements were performed in a number of machines. In RHIC, for the first time, a transverse beam echo was observed after applying a dipole kick followed by a quadrupole .kick. After application of the dipole kick, the dipole moment decohered completely due to lattice nonlinearities. When a quadrupole kick is applied at time τ after the dipole kick, the beam re-cohered at time 2τ thus showing an echo response. We describe the experimental setup and measurement results. In the measurements the dipole and quadrupole kick amplitudes, amplitude dependent tune shift, and the time between dipole and quadrupole kick were varied. In addition, measurements were taken with gold bunches of different intensities. These should exhibit different transverse diffusion rates due to intra-beam scattering

Time-resolved Femtosecond Photon Echo Probes Bimodal Solvent Dynamics

NARCIS (Netherlands)

Pshenichnikov, M.S; Duppen, K.; Wiersma, D. A.

1995-01-01

We report on time-resolved femtosecond photon echo experiments of a dye molecule in a polar solution. The photon echo is time resolved by mixing the echo with a femtosecond gate pulse in a nonlinear crystal. It is shown that the temporal profile of the photon echo allows separation of the

Gravitational wave sources: reflections and echoes

Science.gov (United States)

Price, Richard H.; Khanna, Gaurav

2017-11-01

The recent detection of gravitational waves has generated interest in alternatives to the black hole interpretation of sources. A subset of such alternatives involves a prediction of gravitational wave ‘echoes’. We consider two aspects of possible echoes: first, general features of echoes coming from spacetime reflecting conditions. We find that the detailed nature of such echoes does not bear any clear relationship to quasi-normal frequencies. Second, we point out the pitfalls in the analysis of local reflecting ‘walls’ near the horizon of rapidly rotating black holes.

Gravitational wave sources: reflections and echoes

International Nuclear Information System (INIS)

Price, Richard H; Khanna, Gaurav

2017-01-01

The recent detection of gravitational waves has generated interest in alternatives to the black hole interpretation of sources. A subset of such alternatives involves a prediction of gravitational wave ‘echoes’. We consider two aspects of possible echoes: first, general features of echoes coming from spacetime reflecting conditions. We find that the detailed nature of such echoes does not bear any clear relationship to quasi-normal frequencies. Second, we point out the pitfalls in the analysis of local reflecting ‘walls’ near the horizon of rapidly rotating black holes. (paper)

Sparse adaptive filters for echo cancellation

CERN Document Server

Paleologu, Constantin

2011-01-01

Adaptive filters with a large number of coefficients are usually involved in both network and acoustic echo cancellation. Consequently, it is important to improve the convergence rate and tracking of the conventional algorithms used for these applications. This can be achieved by exploiting the sparseness character of the echo paths. Identification of sparse impulse responses was addressed mainly in the last decade with the development of the so-called ``proportionate''-type algorithms. The goal of this book is to present the most important sparse adaptive filters developed for echo cancellati

Liver iron content determined by MRI. Spin-echo vs. gradient-echo

Energy Technology Data Exchange (ETDEWEB)

Juchems, M.S.; Wunderlich, A.P. [Universitaetskliniken Ulm (Germany). Klinik fuer Diagnostische und Interventionelle Radiologie; Cario, H. [Universitaetskliniken Ulm (Germany). Klinik fuer Kinder- und Jugendmedizin; Schmid, M. [Stadtspital Triemli, Zuerich (Switzerland). Medizinische Onkologie und Haematologie

2012-05-15

Purpose: Liver iron content (LIC) measurement plays a central role in the management of patients with transfusional iron overload. Calculating the LIC with data obtained from standardized MRI sequences represents an attractive alternative diagnostic possibility. The purpose of this study was to compare the LIC measurement obtained with gradient-echo (GRE) sequences to the mean liver proton transverse relaxation (R2) acquired with SE sequences. Materials and Methods: 68 patients with iron overload (median age: 24, range: 3 - 88) underwent 1.5 T MRI for liver iron content measurement. All patients received spin-echo (SE) and gradient-echo (GRE) sequences. Results: The two MRI methods revealed different liver iron content results although a significant correlation was found (r = 0.85, p < 0.001). Values evaluated using GRE sequences (median: 260 {mu}mol/g dry weight [d.w.], range: 6 - 732) were generally higher than those obtained by SE examinations (median: 161 {mu}mol /g d.w., range: 5 - 830). Conclusion: In conclusion, our study revealed different results for both MRI measurements, which could lead to different decisions concerning the management of chelation therapy in individual patients. (orig.)

Evaluation of cardiac function using multi-shot echo planar imaging

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Tadashi; Tanitame, Nobuko; Hata, Ryoichiro; Hirai, Nobuhiko; Ikeda, Midori; Ono, Chiaki; Fukuoka, Haruhito; Ito, Katsuhide [Hiroshima Univ. (Japan). School of Medicine

1998-01-01

In this study, we performed multi-shot echo planar imaging (8 shot, TR/TE/FL=55 ms/18 ms/60 degrees) and k-space segmented fast gradient echo sequence (8 views per segment, TR/TE/FL=9.9 ms/1.8 ms/30 degrees) to assess cardiac function in healthy volunteers. Transaxial sections of the entire heart were obtained with both sequences in ECG triggered, breath hold, and with a 256 x 128 matrix. Resulting temporal resolution was 55 ms for echo planar imaging, and 71 ms for k-space segmented fast gradient echo sequence, respectively. Ventricular volume and ejection fraction of both ventricles and left ventricular mass obtained with multi-shot echo planar imaging were assessed in comparison with k-space segmented fast gradient echo sequence. Measurements of left ventricular volume, ejection fraction and mass obtained with multi-shot echo planar imaging demonstrated close correlation with those obtained with k-space segmented fast gradient echo sequence. Right ventricular volumes obtained with echo planar imaging were significantly higher than those obtained with k-space segmented fast gradient echo sequence. This tendency is considered to be due to differing contrast between right ventricular myocardium and fat tissue observed with echo planar imaging relative to that observed with fast gradient echo sequence, because fat suppression is always performed in echo planar images. Multi-shot echo planar imaging can be a reliable tool for measurement of cardiac functional parameters, although wall motion analysis of the left ventricle requires higher temporal resolution and a short axial section. (K.H.)

Mock ECHO: A Simulation-Based Medical Education Method.

Science.gov (United States)

Fowler, Rebecca C; Katzman, Joanna G; Comerci, George D; Shelley, Brian M; Duhigg, Daniel; Olivas, Cynthia; Arnold, Thomas; Kalishman, Summers; Monnette, Rebecca; Arora, Sanjeev

2018-04-16

This study was designed to develop a deeper understanding of the learning and social processes that take place during the simulation-based medical education for practicing providers as part of the Project ECHO® model, known as Mock ECHO training. The ECHO model is utilized to expand access to care of common and complex diseases by supporting the education of primary care providers with an interprofessional team of specialists via videoconferencing networks. Mock ECHO trainings are conducted through a train the trainer model targeted at leaders replicating the ECHO model at their organizations. Trainers conduct simulated teleECHO clinics while participants gain skills to improve communication and self-efficacy. Three focus groups, conducted between May 2015 and January 2016 with a total of 26 participants, were deductively analyzed to identify common themes related to simulation-based medical education and interdisciplinary education. Principal themes generated from the analysis included (a) the role of empathy in community development, (b) the value of training tools as guides for learning, (c) Mock ECHO design components to optimize learning, (d) the role of interdisciplinary education to build community and improve care delivery, (e) improving care integration through collaboration, and (f) development of soft skills to facilitate learning. Mock ECHO trainings offer clinicians the freedom to learn in a noncritical environment while emphasizing real-time multidirectional feedback and encouraging knowledge and skill transfer. The success of the ECHO model depends on training interprofessional healthcare providers in behaviors needed to lead a teleECHO clinic and to collaborate in the educational process. While building a community of practice, Mock ECHO provides a safe opportunity for a diverse group of clinician experts to practice learned skills and receive feedback from coparticipants and facilitators.

NOAA Ship Pisces Cruise PC1106 (14) Multibeam Sonar Workshop

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The overall objective is to familiarize participating scientists with PISCES multibeam echosounder (Simrad ME70) configuration, operation, calibration and data...

MR imaging of articular cartilage : comparison of magnetization transfer contrast and fat-suppression in multiplanar and 3D gradient-echo, spin-echo, turbo spin-echo techniques

International Nuclear Information System (INIS)

Lee, Young Joon; Joo, Eun Young; Eun, Choong Ki

1999-01-01

The purpose of this study was to evaluate the effects of magnetization transfer contrast(MTC) and fat-suppression(FS) in variable spin-echo and gradient-echo sequences for articular cartilage imaging and to determine the optimal pulse sequences. Using variable 7-pulse sequences, the knees of 15 pigs were imaged Axial images were obtained using proton density and T2-weighted spin-echo (PDWSE and T2WSE), turbo spin-echo (TSE), multiplanar gradient-echo (MPGR), and 3D steady-state gradient-echo (3DGRE) sequences, and the same pulse sequences were then repeated using MTC. Also T1-weighted spin-echo(T1WSE) and 3D spoiled gradient-echo(3DSPGR) images of knees were also acquired, and the procedure was repeated using FS. For each knee, a total of 14 axial images were acquired, and using a 6-band scoring system, the visibility of and the visibilities of the the articular cartilage was analyzed. The visual effect of MTC and FS was scored using a 4-band scale. For each image, the signal intensities of articular cartilage, subchondral bone, muscles, and saline were measured, and signal-to-noise ratios(SNR) and contrast-to-noise ratios(CNR) were also calculated. Visibility of the cartilage was best when 3DSPGR and T1WSE sequences were used. MTC imaging increased the negative contrast between cartilage and saline, but FS imaging provided more positive contrast. CNR between cartilage and saline was highest when using TSE with FS(-351.1±15.3), though CNR between cartilage and bone then fell to -14.7±10.8. In MTC imaging using MPGR showed the greatest increase of negative contrast between cartilage and saline(CNR change=-74.7); the next highest was when 3DGRE was used(CNR change=-34.3). CNR between cartilage and bone was highest with MPGR(161.9±17.7), but with MTC, the greatest CNR decrease(-81.8) was observed. The greatest CNR increase between cartilage and bone was noted in T1WSE with FS. In all scans, FS provided a cartilage-only positive contrast image, though the absolute

Systems analysis for modular versus multi-beam HIF drivers

International Nuclear Information System (INIS)

Meier, W.R.; Logan, B.G.

2004-01-01

Previous modeling for HIF drivers concentrated on designs in which 100 or more beams are grouped in an array and accelerated through a common set of induction cores. The total beam energy required by the target is achieved by the combination of final ion energy, current per beam and number of beams. Economic scaling favors a large number of small (∼1 cm dia.) beams. An alternative architecture has now been investigated, which we refer to as a modular driver. In this case, the driver is subdivided into many (>10) independent accelerators with one or many beams each. A key objective of the modular driver approach is to be able to demonstrate all aspects of the driver (source-to-target) by building a single, lower cost module compared to a full-scale, multi-beam driver. We consider and compare several design options for the modular driver including single-beam designs with solenoid instead of quadrupole magnets in order to transport the required current per module in a single beam, solenoid/quad combinations, and multi-beam, all-quad designs. The drivers are designed to meet the requirements of the hybrid target, which can accommodate a larger spot size than the distributed radiator target that was used for the Robust Point Design. We compare the multi-beam and modular driver configuration for a variety and assumptions and identify key technology advances needed for the modular design

February 2007 Multibeam Mapping of Pulley Ridge, southwest Florida

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This disk or set of disks contain high-resolution multibeam and backscatter maps of the Pulley Ridge Area, near the Tortugas, in the Gulf of Mexico. It includes the...

The effect of strong pitch angle scattering on the use of artificial auroral streaks for echo detection - Echo 5

International Nuclear Information System (INIS)

Swanson, R.L.; Steffen, J.E.; Winckler, J.R.

1986-01-01

During the Echo 5 experiment launched 13 November 1979 from the Poker Flat Research Range (Fairbanks, Alaska), a 0.75 A, 37 keV electron beam was injected both up and down the field line to test the use of optical and X-ray methods to detect the beam as it interacted with the atmosphere below the rocket for both the downward injections (markers) and the upward injected electrons which mirrored at the Southern Hemisphere and returned echoes. The artificial auroral streaks created by the markers were easily visible on the ground TV system but the large intensity of photons produced around the rocket masked any response to the markers by the on-board photometers and X-ray detectors. No echoes were detected with any of the detection systems although the power in some of the upward injections was 7.6 times the power in a detected downward injection thus setting an upper limit on the loss-cone echo flux. The magnitude of the bounce averaged pitch angle diffusion coefficient necessary to explain the lack of observable echoes was found to be 4 x 10 -4 S -1 . It was found that an equatorial wave electric field of 11 mVm -1 would account for the lack of echoes. Such fields should cause strong pitch angle scattering of up to 10 keV natural electrons and thus be consistent with the presence of diffuse aurora on the Echo 5 trajectory. (author)

Design of an Omnidirectional Multibeam Transmitter for High-Speed Indoor Wireless Communications

Directory of Open Access Journals (Sweden)

Tang Jaw-Luen

2010-01-01

Full Text Available For future high speed indoor wireless communication, diffuse wireless optical communications offer more robust optical links against shadowing than line-of-sight links. However, their performance may be degraded by multipath dispersion arising from surface reflections. We have developed a multipath diffusive propagation model capable of providing channel impulse responses data. It is aimed to design and simulate any multibeam transmitter under a variety of indoor environments. In this paper, a multi-beam transmitter system associated with hemisphere structure is proposed to fight against the diverse effects of multipath distortion albeit, at the cost of increased laser power and cost. Simulation results of multiple impulse responses showed that this type of multi-beam transmitter can significantly improve the performance of BER suitable for high bit rate application. We present the performance and simulation results for both line-of-sight and diffuse link configurations. We propose a design of power radiation pattern for a transmitter in achieving uniform and full coverage of power distributions for diffuse indoor optical wireless systems.

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

Multibeam collection for MV1002: Multibeam data collected aboard Melville from 2010-02-18 to 2010-02-22, Valparaiso, Chile to Puerto Montt, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9403: Multibeam data collected aboard Maurice Ewing from 1994-03-21 to 1994-03-27, Cayenne, French Guiana to Martinique

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY06TI: Multibeam data collected aboard Healy from 2006-08-30 to 2006-09-03, Kodiak, AK to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY07TI: Multibeam data collected aboard Healy from 2007-09-26 to 2007-09-30, Juneau, AK to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1405: Multibeam data collected aboard Kilo Moana from 2014-01-30 to 2014-01-31, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX0901: Multibeam data collected aboard Okeanos Explorer from 2009-03-29 to 2009-04-03, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX0801: Multibeam data collected aboard Okeanos Explorer from 2008-09-08 to 2008-09-22, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1005: Multibeam data collected aboard Melville from 2010-03-25 to 2010-04-03, Valparaiso, Chile to Puntarenas, Costa Rica

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1109: Multibeam data collected aboard Kilo Moana from 2011-03-04 to 2011-03-10, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1316: Multibeam data collected aboard Kilo Moana from 2013-09-16 to 2013-09-28, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0317: Multibeam data collected aboard Kilo Moana from 2003-10-19 to 2003-10-23, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1116: Multibeam data collected aboard Roger Revelle from 2011-11-06 to 2011-12-11, Phuket, Thailand to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SUM0108A: Multibeam data collected aboard Sumner from 2001-06-17 to 2001-06-22, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX1505: Multibeam data collected aboard Okeanos Explorer from 2015-10-05 to 2015-10-16, Honolulu, HI to Alameda, CA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1106: Multibeam data collected aboard Kilo Moana from 2011-02-19 to 2011-02-23, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1113: Multibeam data collected aboard Kilo Moana from 2011-04-10 to 2011-04-14, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0824: Multibeam data collected aboard Kilo Moana from 2008-12-15 to 2008-12-16, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9507: Multibeam data collected aboard Maurice Ewing from 1995-07-28 to 1995-08-02, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0319: Multibeam data collected aboard Kilo Moana from 2003-10-26 to 2003-10-31, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT26-19: Multibeam data collected aboard Atlantis from 2014-08-28 to 2014-09-11, Astoria, OR to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0417: Multibeam data collected aboard Kilo Moana from 2004-09-09 to 2004-10-17, Suva, Fiji to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-12: Multibeam data collected aboard Natsushima from 2006-06-24 to 2006-06-26, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RC2912: Multibeam data collected aboard Robert D. Conrad from 1988-12-02 to 1989-01-07, Cadiz, Spain to Azores

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0410: Multibeam data collected aboard Kilo Moana from 2004-04-06 to 2004-05-09, Suva, Fiji to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0305: Multibeam data collected aboard Kilo Moana from 2003-03-22 to 2003-03-24, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9417: Multibeam data collected aboard Maurice Ewing from 1994-11-27 to 1994-12-08, Balboa, Panama to Tampa, FL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-10: Multibeam data collected aboard Natsushima from 2005-07-06 to 2005-07-13, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-12: Multibeam data collected aboard Natsushima from 2005-07-27 to 2005-07-31, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN162L11: Multibeam data collected aboard Knorr from 2001-02-11 to 2001-03-15, Mombassa, Kenya to Seychelles

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT18-08: Multibeam data collected aboard Atlantis from 2011-07-19 to 2011-08-01, Astoria, OR to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT18-14: Multibeam data collected aboard Atlantis from 2011-11-25 to 2011-12-08, Piraievs, Greece to Piraievs, Greece

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1201: Multibeam data collected aboard Kilo Moana from 2012-01-04 to 2012-01-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0303: Multibeam data collected aboard Maurice Ewing from 2003-05-28 to 2003-06-24, Gulfport, MS to Galveston, TX

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX1004: Multibeam data collected aboard Okeanos Explorer from 2010-06-08 to 2010-08-19, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX1005: Multibeam data collected aboard Okeanos Explorer from 2010-08-23 to 2010-09-05, Apra, Guam to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN36MV: Multibeam data collected aboard Melville from 2008-04-05 to 2008-04-26, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1004: Multibeam data collected aboard Kilo Moana from 2010-02-26 to 2010-03-11, Honolulu, HI to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0913: Multibeam data collected aboard Kilo Moana from 2009-06-07 to 2009-06-18, Apra, Guam to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX1003: Multibeam data collected aboard Okeanos Explorer from 2010-05-19 to 2010-06-03, Honolulu, HI to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1021: Multibeam data collected aboard Kilo Moana from 2010-10-17 to 2010-11-09, Honolulu, HI to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1208: Multibeam data collected aboard Roger Revelle from 2012-06-28 to 2012-07-17, Danang, Vietnam to Apia, Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT21-02: Multibeam data collected aboard Atlantis from 2012-06-01 to 2012-06-17, Bridgetown, Barbados to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for VANC04MV: Multibeam data collected aboard Melville from 2002-11-02 to 2002-12-05, Arica, Chile to Valparaiso, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1218: Multibeam data collected aboard Melville from 2012-12-18 to 2013-01-14, San Diego, CA to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK23MV: Multibeam data collected aboard Melville from 2002-05-01 to 2002-06-06, Osaka, Japan to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9908: Multibeam data collected aboard Maurice Ewing from 1999-07-21 to 1999-08-18, Kochi, Japan to Yokohama, Japan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0415: Multibeam data collected aboard Kilo Moana from 2004-07-16 to 2004-08-24, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY03DF: Multibeam data collected aboard Healy from 2003-01-31 to 2003-04-01, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN11MV: Multibeam data collected aboard Melville from 2006-11-15 to 2006-12-17, Honolulu, HI to Brisbane, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0701: Multibeam data collected aboard Kilo Moana from 2007-01-03 to 2007-02-12, Honolulu, HI to Brisbane, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for WEST10MV: Multibeam data collected aboard Melville from 1995-01-29 to 1995-03-12, Fremantle, Australia to Hobart, Tasmania

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KRY14_04: Multibeam data collected aboard Keary from 2014-08-22 to 2014-09-07, Blacksod, Ireland to Blacksod, Ireland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0518: Multibeam data collected aboard Kilo Moana from 2005-10-15 to 2005-11-05, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1520: Multibeam data collected aboard Kilo Moana from 2015-11-20 to 2015-12-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for M26-2: Multibeam data collected aboard Meteor from 1993-10-03 to 1993-10-21, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0620: Multibeam data collected aboard Kilo Moana from 2006-07-05 to 2006-07-10, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00255: Multibeam data collected aboard Mt. Mitchell from 1990-11-17 to 1990-11-20, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0716: Multibeam data collected aboard Kilo Moana from 2007-08-23 to 2007-08-30, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY13TC: Multibeam data collected aboard Healy from 2013-09-08 to 2013-09-21, Barrow, AK to Seward, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0918: Multibeam data collected aboard Kilo Moana from 2009-07-23 to 2009-07-27, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0205: Multibeam data collected aboard Kilo Moana from 2002-09-22 to 2002-10-18, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9805: Multibeam data collected aboard Maurice Ewing from 1998-05-16 to 1998-07-01, Halifax, Canada to Halifax, Canada

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0108: Multibeam data collected aboard Maurice Ewing from 2001-07-23 to 2001-08-01, Patras, Greece to Piraeus, Greece

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0208: Multibeam data collected aboard Maurice Ewing from 2002-08-12 to 2002-09-06, Newport, OR to Newport, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9704: Multibeam data collected aboard Maurice Ewing from 1997-06-01 to 1997-07-04, Jacksonville, FL to Lisbon, Portugal

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9902: Multibeam data collected aboard Maurice Ewing from 1999-02-28 to 1999-03-05, Bridgetown, Barbados to Cristobal, Panama

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0401: Multibeam data collected aboard Maurice Ewing from 2004-02-20 to 2004-02-26, Norfolk, VA to Progresso, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY09TD: Multibeam data collected aboard Healy from 2009-07-06 to 2009-07-25, Seattle, WA to Barrow, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Puna-rid: Multibeam data collected aboard Ocean Alert from 1998-03-01 to 1998-03-03, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1116: Multibeam data collected aboard Kilo Moana from 2011-05-20 to 2011-06-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0405: Multibeam data collected aboard Kilo Moana from 2004-02-24 to 2004-03-03, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK25MV: Multibeam data collected aboard Melville from 2002-06-20 to 2002-07-16, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT21-04: Multibeam data collected aboard Atlantis from 2012-07-13 to 2012-07-29, Bridgetown, Barbados to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9007: Multibeam data collected aboard Maurice Ewing from 1990-08-26 to 1990-09-23, Bergen, Norway to Bergen, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1404: Multibeam data collected aboard Melville from 2014-06-10 to 2014-06-29, Seattle, WA to San Diego, CA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0201: Multibeam data collected aboard Maurice Ewing from 2002-01-31 to 2002-02-14, Hobart, Tasmania to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9416: Multibeam data collected aboard Maurice Ewing from 1994-11-03 to 1994-11-08, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9309: Multibeam data collected aboard Maurice Ewing from 1993-11-20 to 1993-12-26, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9706: Multibeam data collected aboard Maurice Ewing from 1997-08-20 to 1997-09-05, Lisbon, Portugal to Cristobal, Panama

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9803: Multibeam data collected aboard Maurice Ewing from 1998-03-15 to 1998-04-06, Bridgetown, Barbados to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9501: Multibeam data collected aboard Maurice Ewing from 1995-02-16 to 1995-03-21, Tampa, FL to Balboa, Panama

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0206: Multibeam data collected aboard Maurice Ewing from 2002-06-14 to 2002-07-02, Kodiak, AK to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0409: Multibeam data collected aboard Maurice Ewing from 2004-09-28 to 2004-10-14, Kodiak, AK to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9806: Multibeam data collected aboard Maurice Ewing from 1998-07-02 to 1998-08-13, Halifax, Canada to Halifax, Canada

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0008: Multibeam data collected aboard Maurice Ewing from 2000-09-02 to 2000-10-17, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0402: Multibeam data collected aboard Maurice Ewing from 2004-02-27 to 2004-03-01, Progresso, Mexico to Gulfport, MS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9608: Multibeam data collected aboard Maurice Ewing from 1996-10-18 to 1996-11-16, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9707: Multibeam data collected aboard Maurice Ewing from 1997-09-09 to 1997-10-24, Balboa, Panama to Manzanillo, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9404: Multibeam data collected aboard Maurice Ewing from 1994-04-09 to 1994-04-14, Bridgetown, Barbados to Cristobal, Panama

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9907: Multibeam data collected aboard Maurice Ewing from 1999-06-18 to 1999-07-19, Yokohama, Japan to Kochi, Japan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9802: Multibeam data collected aboard Maurice Ewing from 1998-02-15 to 1998-03-12, Honolulu, HI to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9502: Multibeam data collected aboard Maurice Ewing from 1995-03-27 to 1995-04-27, Balboa, Panama to Manzanillo, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9405: Multibeam data collected aboard Maurice Ewing from 1994-04-20 to 1994-05-14, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9206: Multibeam data collected aboard Maurice Ewing from 1992-05-27 to 1992-05-31, Cristobal, Panama to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0104: Multibeam data collected aboard Maurice Ewing from 2001-04-14 to 2001-05-19, Cristobal, Panama to Costa Rica

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1006: Multibeam data collected aboard Kilo Moana from 2010-04-04 to 2010-04-14, Apra, Guam to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0416: Multibeam data collected aboard Kilo Moana from 2004-08-28 to 2004-09-07, Honolulu, HI to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0704: Multibeam data collected aboard Kilo Moana from 2007-04-19 to 2007-04-30, Suva, Fiji to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TUIM08MV: Multibeam data collected aboard Melville from 2005-07-01 to 2005-07-11, Suva, Fiji to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TUIM06MV: Multibeam data collected aboard Melville from 2005-05-15 to 2005-06-02, Suva, Fiji to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0409: Multibeam data collected aboard Kilo Moana from 2004-03-24 to 2004-04-03, Honolulu, HI to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1007: Multibeam data collected aboard Kilo Moana from 2010-04-16 to 2010-04-25, Suva, Fiji to Apia, Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1310: Multibeam data collected aboard Roger Revelle from 2013-07-22 to 2013-08-25, Apra, Guam to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1211: Multibeam data collected aboard Roger Revelle from 2012-09-09 to 2012-09-26, Suva, Fiji to Apia, Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN08MV: Multibeam data collected aboard Melville from 2006-10-04 to 2006-10-10, Suva, Fiji to Apia, Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0703: Multibeam data collected aboard Kilo Moana from 2007-03-14 to 2007-04-18, Townsville, Australia to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1022: Multibeam data collected aboard Kilo Moana from 2010-11-11 to 2010-11-21, Apra, Guam to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT15-61: Multibeam data collected aboard Atlantis from 2010-01-29 to 2010-03-03, Iquique, Chile to Arica, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KNOX06RR: Multibeam data collected aboard Roger Revelle from 2007-06-18 to 2007-08-06, Phuket, Thailand to Singapore

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN162L15: Multibeam data collected aboard Knorr from 2001-05-07 to 2001-05-20, Seychelles to Istanbul, Turkey

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9901: Multibeam data collected aboard Maurice Ewing from 1999-01-30 to 1999-02-24, Norfolk, VA to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN203-02: Multibeam data collected aboard Knorr from 2011-08-22 to 2011-09-22, Reykjavik, Iceland to Isafjorour, Iceland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV0904: Multibeam data collected aboard Melville from 2009-03-23 to 2009-03-28, Manila, Philippines to Kao-hsiung, Taiwan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV0909: Multibeam data collected aboard Melville from 2009-05-20 to 2009-05-25, Brisbane, Australia to Papeete, French Polynesia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1128: Multibeam data collected aboard Kilo Moana from 2011-10-01 to 2011-10-25, Honolulu, HI to Apia, Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SO92: Multibeam data collected aboard Sonne from 1993-12-15 to 1993-12-27, Singapore, Singapore to Colombo, Sri Lanka

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0414: Multibeam data collected aboard Kilo Moana from 2004-06-20 to 2004-07-10, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0401: Multibeam data collected aboard Kilo Moana from 2004-01-07 to 2004-01-14, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK02MV: Multibeam data collected aboard Melville from 2000-10-02 to 2000-10-14, Arica, Chile to Arica, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK24MV: Multibeam data collected aboard Melville from 2002-06-09 to 2002-06-16, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK07MV: Multibeam data collected aboard Melville from 2001-03-04 to 2001-04-12, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for CRUISE10: Multibeam data collected aboard Nikolaj Strakhov from 1990-03-29 to 1990-06-01, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for CRUISE5: Multibeam data collected aboard Nikolaj Strakhov from 1987-05-18 to 1987-07-05, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0718: Multibeam data collected aboard Kilo Moana from 2007-09-10 to 2007-10-08, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1412: Multibeam data collected aboard Roger Revelle from 2014-10-29 to 2014-11-23, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT15-16: Multibeam data collected aboard Atlantis from 2007-02-13 to 2007-03-19, Manzanillo, Mexico to Manzanillo, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0501: Multibeam data collected aboard Maurice Ewing from 2005-01-07 to 2005-02-01, Colon, Panama to Progresso, Mexico

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1114: Multibeam data collected aboard Roger Revelle from 2011-08-29 to 2011-09-26, Darwin, Australia to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1115: Multibeam data collected aboard Roger Revelle from 2011-09-29 to 2011-11-02, Phuket, Thailand to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1605: Multibeam data collected aboard Roger Revelle from 2016-05-01 to 2016-05-16, Phuket, Thailand to Palau, Palau

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1604: Multibeam data collected aboard Roger Revelle from 2016-03-21 to 2016-04-28, Fremantle, Australia to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0404: Multibeam data collected aboard Healy from 2004-09-02 to 2004-09-30, Dutch Harbor, AK to Nome, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0202: Multibeam data collected aboard Healy from 2002-06-16 to 2002-07-07, Nome, AK to Dutch Harbor, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0901: Multibeam data collected aboard Healy from 2009-03-10 to 2009-03-31, Kodiak, AK to Dutch Harbor, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1003: Multibeam data collected aboard Healy from 2010-09-07 to 2010-09-27, Barrow, AK to Dutch Harbor, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0813: Multibeam data collected aboard Kilo Moana from 2008-07-25 to 2008-07-29, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1211: Multibeam data collected aboard Kilo Moana from 2012-06-11 to 2012-06-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX1001: Multibeam data collected aboard Okeanos Explorer from 2010-01-26 to 2010-02-19, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TUIM09MV: Multibeam data collected aboard Melville from 2005-07-15 to 2005-07-19, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0812: Multibeam data collected aboard Kilo Moana from 2008-07-01 to 2008-07-22, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1213: Multibeam data collected aboard Kilo Moana from 2012-06-25 to 2012-06-29, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0601: Multibeam data collected aboard Kilo Moana from 2006-01-24 to 2006-01-28, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0314: Multibeam data collected aboard Kilo Moana from 2003-10-01 to 2003-10-10, Kodiak, AK to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN194-04: Multibeam data collected aboard Knorr from 2008-10-03 to 2008-10-31, Reykjavik, Iceland to Reykjavik, Iceland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0308: Multibeam data collected aboard Maurice Ewing from 2003-10-02 to 2003-10-18, Bergen, Norway to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0306: Multibeam data collected aboard Maurice Ewing from 2003-08-01 to 2003-08-19, Balboa, Panama to Bergen, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0307: Multibeam data collected aboard Maurice Ewing from 2003-08-29 to 2003-09-25, Bergen, Norway to Bergen, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY05TE: Multibeam data collected aboard Healy from 2005-09-29 to 2005-11-03, Tromso, Norway to Dublin, Ireland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9008: Multibeam data collected aboard Maurice Ewing from 1990-09-29 to 1990-10-26, Bergen, Norway to Newark, NJ

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0503: Multibeam data collected aboard Healy from 2005-08-04 to 2005-09-29, Dutch Harbor, AK to Tromso, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9006: Multibeam data collected aboard Maurice Ewing from 1990-07-25 to 1990-08-22, Reykjavik, Iceland to Bergen, Norway

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1005: Multibeam data collected aboard Kilo Moana from 2010-03-16 to 2010-03-30, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN189-04: Multibeam data collected aboard Knorr from 2007-06-15 to 2007-07-15, Reykjavik, Iceland to Reykjavik, Iceland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN18MV: Multibeam data collected aboard Melville from 2007-05-02 to 2007-05-24, Yokohama, Japan to Yokohama, Japan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0110: Multibeam data collected aboard Maurice Ewing from 2001-08-20 to 2001-09-12, Djibouti, Djibouti to Djibouti, Djibouti

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0109: Multibeam data collected aboard Maurice Ewing from 2001-08-04 to 2001-08-19, Piraeus, Greece to Djibouti, Djibouti

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1210: Multibeam data collected aboard Roger Revelle from 2012-08-31 to 2012-09-06, Apia, Samoa to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0607: Multibeam data collected aboard Kilo Moana from 2006-03-05 to 2006-03-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for VANC12MV: Multibeam data collected aboard Melville from 2003-08-08 to 2003-08-16, Darwin, Australia to Cairns, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SKQ201502T: Multibeam data collected aboard Sikuliaq from 2015-02-12 to 2015-02-18, Ketchikan, AK to Juneau, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1226: Multibeam data collected aboard Kilo Moana from 2012-11-19 to 2012-11-30, Pohnpei, Micronesia to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0310: Multibeam data collected aboard Kilo Moana from 2003-05-22 to 2003-06-10, Kodiak, AK to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1301: Multibeam data collected aboard Kilo Moana from 2013-01-10 to 2013-02-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN192-07: Multibeam data collected aboard Knorr from 2007-12-31 to 2008-01-17, Natal, Brazil to Ascension Island

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN210-04: Multibeam data collected aboard Knorr from 2013-03-25 to 2013-05-09, Montevideo, Uruguay to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN182L05: Multibeam data collected aboard Knorr from 2005-07-14 to 2005-08-02, Panama to Galapagos, Ecuador

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN172L16: Multibeam data collected aboard Knorr from 2003-08-09 to 2003-08-18, Istanbul, Turkey to Malta

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0301: Multibeam data collected aboard Healy from 2003-07-20 to 2003-08-13, St. John's, Canada to Thule, Greenland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1407: Multibeam data collected aboard Kilo Moana from 2014-02-19 to 2014-02-28, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-17: Multibeam data collected aboard Natsushima from 2005-10-08 to 2005-10-18, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-14: Multibeam data collected aboard Natsushima from 2006-07-23 to 2006-07-30, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-16: Multibeam data collected aboard Natsushima from 2005-09-27 to 2005-10-03, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-22: Multibeam data collected aboard Natsushima from 2006-12-08 to 2006-12-14, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-16: Multibeam data collected aboard Natsushima from 2006-08-11 to 2006-08-15, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-21: Multibeam data collected aboard Natsushima from 2006-11-21 to 2006-12-04, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-11: Multibeam data collected aboard Natsushima from 2006-06-04 to 2006-06-18, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-13: Multibeam data collected aboard Natsushima from 2005-08-14 to 2005-08-15, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-03: Multibeam data collected aboard Natsushima from 2005-04-15 to 2005-04-27, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-06: Multibeam data collected aboard Natsushima from 2005-05-22 to 2005-05-27, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-15: Multibeam data collected aboard Natsushima from 2005-09-06 to 2005-09-12, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-23: Multibeam data collected aboard Natsushima from 2006-12-19 to 2006-12-24, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-04: Multibeam data collected aboard Natsushima from 2005-04-29 to 2005-05-07, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-08: Multibeam data collected aboard Natsushima from 2005-06-22 to 2005-06-26, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-07: Multibeam data collected aboard Natsushima from 2006-04-12 to 2006-04-23, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-14: Multibeam data collected aboard Natsushima from 2005-08-19 to 2005-08-27, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00233: Multibeam data collected aboard Mt. Mitchell from 1990-08-15 to 1990-08-28, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AHI-05-04: Multibeam data collected aboard Ahi from 2005-06-13 to 2005-07-08, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for WEST09MV: Multibeam data collected aboard Melville from 1994-12-10 to 1995-01-22, Fremantle, Australia to Fremantle, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1503: Multibeam data collected aboard Roger Revelle from 2015-02-28 to 2015-03-11, Hobart, Australia to Hobart, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9912: Multibeam data collected aboard Maurice Ewing from 1999-10-27 to 1999-11-28, Townsville, Australia to Townsville, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV0911: Multibeam data collected aboard Melville from 2009-11-21 to 2010-01-02, Brisbane, Australia to Papeete, French Polynesia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0113: Multibeam data collected aboard Maurice Ewing from 2001-10-29 to 2001-12-02, Fremantle, Australia to Fremantle, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV0910: Multibeam data collected aboard Melville from 2009-10-29 to 2009-11-12, Chi-Lung, Taiwan to Brisbane, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1501: Multibeam data collected aboard Roger Revelle from 2015-01-09 to 2015-02-03, Hobart, Australia to Hobart, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for PANR02MV: Multibeam data collected aboard Melville from 1997-12-14 to 1997-12-29, Acapulco, Mexico to Callao, Peru

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT26-14: Multibeam data collected aboard Atlantis from 2014-04-27 to 2014-05-16, Gulfport, MS to Gulfport, MS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MCD0212: Multibeam data collected aboard McDonnell from 2002-11-27 to 2002-12-19, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SKQ201510S: Multibeam data collected aboard Sikuliaq from 2015-07-20 to 2015-08-22, Nome, AK to Nome, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00204: Multibeam data collected aboard Mt. Mitchell from 1989-11-08 to 1989-11-10, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0629: Multibeam data collected aboard Kilo Moana from 2006-11-04 to 2006-11-06, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for FK006B: Multibeam data collected aboard Falkor from 2012-11-06 to 2012-11-28, Pascagoula, MS to Pascagoula, MS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN195-12: Multibeam data collected aboard Knorr from 2009-07-27 to 2009-08-09, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0631: Multibeam data collected aboard Kilo Moana from 2006-11-16 to 2006-11-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for BMRG05MV: Multibeam data collected aboard Melville from 1996-01-16 to 1996-02-16, Hobart, Tasmania to Fremantle, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KRY11_01: Multibeam data collected aboard Keary from 2011-04-13 to 2011-06-14, Waterford, Ireland to Waterford, Ireland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0606: Multibeam data collected aboard Kilo Moana from 2006-02-18 to 2006-02-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0616: Multibeam data collected aboard Kilo Moana from 2006-06-07 to 2006-06-09, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT26-17: Multibeam data collected aboard Atlantis from 2014-07-14 to 2014-08-06, Astoria, OR to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0816: Multibeam data collected aboard Kilo Moana from 2008-08-21 to 2008-08-23, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SU-94-06: Multibeam data collected aboard Surveyor from 1994-09-03 to 1994-09-27, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SU10-1: Multibeam data collected aboard Sumner from 2010-08-06 to 2010-09-05, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EX0802: Multibeam data collected aboard Okeanos Explorer from 2008-10-30 to 2008-11-06, Seattle, WA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1514: Multibeam data collected aboard Roger Revelle from 2015-09-22 to 2015-10-07, Chennai, India to Palau, Palau

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1513: Multibeam data collected aboard Roger Revelle from 2015-08-23 to 2015-09-21, Chennai, India to Chennai, India

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KNOX07RR: Multibeam data collected aboard Roger Revelle from 2007-08-14 to 2007-08-21, Singapore to Mormugao, India

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1304: Multibeam data collected aboard Kilo Moana from 2013-03-01 to 2013-03-03, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for PANR07MV: Multibeam data collected aboard Melville from 1998-06-12 to 1998-06-20, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1207: Multibeam data collected aboard Melville from 2012-05-22 to 2012-06-04, Valparaiso, Chile to Puerto Ayora, Ecuador

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SO83: Multibeam data collected aboard Sonne from 1992-12-02 to 1992-12-27, Bremerhaven, Germany to Las Palmas, Spain

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1210: Multibeam data collected aboard Kilo Moana from 2012-05-30 to 2012-06-09, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN200-02: Multibeam data collected aboard Knorr from 2011-02-27 to 2011-04-01, Halifax, Canada to Halifax, Canada

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1131: Multibeam data collected aboard Kilo Moana from 2011-12-18 to 2011-12-22, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN189-03: Multibeam data collected aboard Knorr from 2007-05-28 to 2007-06-11, Bridgetown, Barbados to Reykjavik, Iceland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1308: Multibeam data collected aboard Melville from 2013-06-12 to 2013-07-11, San Diego, CA to Seattle, WA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9801: Multibeam data collected aboard Maurice Ewing from 1998-01-15 to 1998-02-12, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0624: Multibeam data collected aboard Kilo Moana from 2006-08-07 to 2006-08-11, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0320: Multibeam data collected aboard Kilo Moana from 2003-11-03 to 2003-11-07, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for COOK06MV: Multibeam data collected aboard Melville from 2001-02-10 to 2001-03-01, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1102: Multibeam data collected aboard Kilo Moana from 2011-01-14 to 2011-01-25, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN19MV: Multibeam data collected aboard Melville from 2007-05-26 to 2007-06-03, Yokohama, Japan to Manila, Philippines

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0611: Multibeam data collected aboard Kilo Moana from 2006-03-31 to 2006-04-04, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00309: Multibeam data collected aboard Mt. Mitchell from 1992-09-15 to 1992-10-01, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HEN04-3: Multibeam data collected aboard Henson from 2004-10-30 to 2004-11-28, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HEN04-1: Multibeam data collected aboard Henson from 2004-08-30 to 2004-09-18, Gulfport, MS to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HEN04-2: Multibeam data collected aboard Henson from 2004-09-25 to 2004-10-21, Newport, RI to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0702: Multibeam data collected aboard Kilo Moana from 2007-02-13 to 2007-03-10, Brisbane, Australia to Townsville, Australia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0325: Multibeam data collected aboard Kilo Moana from 2003-12-18 to 2003-12-22, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00129: Multibeam data collected aboard Mt. Mitchell from 1988-03-21 to 1988-03-24, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00294: Multibeam data collected aboard Mt. Mitchell from 1991-08-06 to 1991-08-11, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9201: Multibeam data collected aboard Maurice Ewing from 1992-01-15 to 1992-02-27, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0401: Multibeam data collected aboard Healy from 2004-04-27 to 2004-05-10, Seattle, WA to Dutch Harbor, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SU10-2: Multibeam data collected aboard Sumner from 2010-09-24 to 2010-10-21, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0622: Multibeam data collected aboard Kilo Moana from 2006-07-16 to 2006-07-21, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0713: Multibeam data collected aboard Kilo Moana from 2007-07-29 to 2007-08-01, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN197-08: Multibeam data collected aboard Knorr from 2010-05-22 to 2010-06-24, Bridgetown, Barbados to Bridgetown, Barbados

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KN197-04: Multibeam data collected aboard Knorr from 2010-02-19 to 2010-03-12, Bridgetown, Barbados to Fortaleza, Brazil

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for B00217: Multibeam data collected aboard Mt. Mitchell from 1990-04-28 to 1990-05-22, Norfolk, VA to Norfolk, VA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY0003: Multibeam data collected aboard Healy from 2000-04-24 to 2000-05-23, Halifax, Canada to St. John's, Canada

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1306: Multibeam data collected aboard Melville from 2013-05-08 to 2013-06-01, Honolulu, HI to San Diego, CA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for SKQ201501T: Multibeam data collected aboard Sikuliaq from 2015-01-19 to 2015-02-11, Apra, Guam to Ketchikan, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0318: Multibeam data collected aboard Kilo Moana from 2003-10-23 to 2003-10-26, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-19: Multibeam data collected aboard Natsushima from 2005-11-13 to 2005-11-15, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0923: Multibeam data collected aboard Kilo Moana from 2009-10-01 to 2009-10-17, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0719: Multibeam data collected aboard Kilo Moana from 2007-10-11 to 2007-10-27, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0512: Multibeam data collected aboard Kilo Moana from 2005-06-02 to 2005-06-10, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1001: Multibeam data collected aboard Healy from 2010-06-15 to 2010-07-22, Dutch Harbor, AK to Seward, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1101: Multibeam data collected aboard Healy from 2011-06-25 to 2011-07-29, Dutch Harbor, AK to Seward, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TUIM07MV: Multibeam data collected aboard Melville from 2005-06-09 to 2005-06-29, Suva, Fiji to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MGLN07MV: Multibeam data collected aboard Melville from 2006-09-05 to 2006-10-02, Suva, Fiji to Suva, Fiji

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1201: Multibeam data collected aboard Healy from 2012-08-09 to 2012-08-25, Dutch Harbor, AK to Barrow, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY1301: Multibeam data collected aboard Healy from 2013-07-29 to 2013-08-15, Dutch Harbor, AK to Barrow, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1413: Multibeam data collected aboard Roger Revelle from 2014-11-29 to 2014-12-21, Apra, Guam to Apra, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT26-18: Multibeam data collected aboard Atlantis from 2014-08-10 to 2014-08-24, Astoria, OR to Astoria, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for Cork_Harbour: Multibeam data collected aboard Celtic Voyager from 2000-08-20 to 2000-08-21, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for H11342: Multibeam data collected aboard Thomas Jefferson from 2004-05-01 to 2004-05-30, Galveston, TX to Galveston, TX

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for TN167: Multibeam data collected aboard Thomas G. Thompson from 2004-03-27 to 2004-04-17, Guam to Yokohama, Japan

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for H11324: Multibeam data collected aboard Thomas Jefferson from 2004-04-01 to 2004-04-30, Galveston, TX to Galveston, TX

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0207: Multibeam data collected aboard Maurice Ewing from 2002-07-08 to 2002-08-07, Astoria, OR to Newport, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM0406: Multibeam data collected aboard Kilo Moana from 2004-03-05 to 2004-03-14, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-05: Multibeam data collected aboard Natsushima from 2005-05-08 to 2005-05-12, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-18: Multibeam data collected aboard Natsushima from 2005-10-22 to 2005-11-03, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-19: Multibeam data collected aboard Natsushima from 2006-09-14 to 2006-09-24, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT06-08: Multibeam data collected aboard Natsushima from 2006-04-28 to 2006-05-14, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-09: Multibeam data collected aboard Natsushima from 2005-06-29 to 2005-07-03, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for NT05-11: Multibeam data collected aboard Natsushima from 2005-07-19 to 2005-07-22, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KM1125: Multibeam data collected aboard Kilo Moana from 2011-09-06 to 2011-09-21, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for 18-cruise: Multibeam data collected aboard Boris Petrov from 1991-07-04 to 1991-09-01, Unknown Port to Unknown Port

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1205: Multibeam data collected aboard Melville from 2012-04-20 to 2012-04-30, Punta Arenas, Chile to Valparaiso, Chile

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW0305: Multibeam data collected aboard Maurice Ewing from 2003-07-03 to 2003-07-28, Balboa, Panama to Balboa, Panama

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for RR1117: Multibeam data collected aboard Roger Revelle from 2011-12-15 to 2012-01-05, Phuket, Thailand to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Echo-Interleaved-Spiral MR Imaging

International Nuclear Information System (INIS)

Rosenthal, Shirrie; Azhari, Haim; Montag, Avram

1998-01-01

Interleaved-Spiral imaging is an efficient method for MRI fast scans. However, images suffer from blurring and artifacts due to field inhomogeneities and the long readout times. In this paper, we combine interleaved-spirals with spin-echo for 3D scans. The refocusing RF-pulses (echoes) refocus off-resonance spins, thus allowing longer acquisition times per excitation, by limiting inhomogeneity effects. The total number of excitations for a 3D scan is reduced by half. The 3D Fourier transform of an object is divided into pairs of slices, one slice is scanned in an outgoing interleaved-spiral, initiated after a 90 degree pulse has been applied. The second slice is scanned in an ingoing interleaved-spiral, after a 180 degree pulse has been applied, thus reaching the slice origin at the echo time. (authors)

Time Delay Estimation Algoritms for Echo Cancellation

Directory of Open Access Journals (Sweden)

Kirill Sakhnov

2011-01-01

Full Text Available The following case study describes how to eliminate echo in a VoIP network using delay estimation algorithms. It is known that echo with long transmission delays becomes more noticeable to users. Thus, time delay estimation, as a part of echo cancellation, is an important topic during transmission of voice signals over packetswitching telecommunication systems. An echo delay problem associated with IP-based transport networks is discussed in the following text. The paper introduces the comparative study of time delay estimation algorithm, used for estimation of the true time delay between two speech signals. Experimental results of MATLab simulations that describe the performance of several methods based on cross-correlation, normalized crosscorrelation and generalized cross-correlation are also presented in the paper.

summarytable.PNG | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Resources.PNG | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Custom Search | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Watershed Statistics | ECHO | US EPA

Science.gov (United States)

ECHO, Enforcement and Compliance History Online, provides compliance and enforcement information for approximately 800,000 EPA-regulated facilities nationwide. ECHO includes permit, inspection, violation, enforcement action, and penalty information about facilities regulated under the Clean Air Act (CAA) Stationary Source Program, Clean Water Act (CWA) National Pollutant Elimination Discharge System (NPDES), and/or Resource Conservation and Recovery Act (RCRA). Information also is provided on surrounding demographics when available.

Clinical characteristics in normal healthy adults with microbleeds on echo-planar gradient-echo T2*-weighted MRI

International Nuclear Information System (INIS)

Takahashi, Wakoh; Ide, Michiru; Ohnuki, Tomohide; Takagi, Shigeharu; Shinohara, Yukito

2004-01-01

The gradient-echo T 2 * -weighted sequence in magnetic resonance imaging is known to be useful for detecting microbleeds (MBs) in patients with intracranial hemorrhage or lacunar stroke. We investigated the characteristics of apparently healthy adults with MBs but without stroke, employing echo-planar gradient-echo T 2 * -weighted MRI. The subjects were recruited from among 3,537 participants who underwent brain check-ups at the HIMEDIC Imaging Center. Of the 3,537 participants, 3,296 (mean age, 55±11 years) without any history of cerebrovascular disease or apparent focal neurological manifestations were selected for the present study. MBs on echo-planar gradient-echo T 2 * -weighted MRI were observed in 74 (2.2%) of the 3,296 subjects. Of a total of 133 lesions found in these 74 persons, 31 were located in the basal ganglia or cortico-subcortical regions. Thirty were in the deep white matter, 19 in the thalamus, 16 in the cerebellum, and 6 in the brain stem. The subjects with MBs were significantly older than the subjects without MBs, and the mean values for their systolic and diastolic blood pressures were higher than those in the subjects without MBs. Asymptomatic cerebral infarction, periventricular hyperintensity, and deep and subcortical white matter hyperintensity on T 1 - and T 2 -weighted MRI were more frequent in the subjects with MBs, as compared with those without MBs. Asymptomatic cerebral infarction, periventricular hyperintensity, and deep and subcortical white matter hyperintensity on T 1 - and T 2 -weighted MRI were more frequent in the subjects with MBs of the basal ganglia or thalamus than in those with MBs in other regions. MBs on echo-planar gradient-echo T 2 * -weighted MRI were thus relatively rare in apparently healthy adults. However, MBs in the basal ganglia or thalamus are suggested to be closely related to intracerebral microangiopathy. Persons with MBs in such regions should therefore be carefully checked for cerebrovascular risk

Olympic Coast National Marine Sanctuary - mos110_0204c.tif - Multibeam backscatter mosaic from survey area 110_0204c

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A multibeam backscatter image (0-35 m water depths) mosaiced from hydrographic data collected during a August/September 2003seafloor survey. A Reson 8101 multibeam...

Olympic Coast National Marine Sanctuary - mos110_0204a.tif - Multibeam backscatter mosaic from survey area 110_0204a

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A multibeam backscatter image (0-35 m water depths) mosaiced from hydrographic data collected during a July/August 2002seafloor survey. A Reson 8101 multibeam...

Olympic Coast National Marine Sanctuary - mos110_0204b.tif - Multibeam backscatter mosaic from survey area 110_0204b

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A multibeam backscatter image (0-35 m water depths) mosaiced from hydrographic data collected during a August/September 2003seafloor survey. A Reson 8101 multibeam...

CUTLASS HF radar observations of high-velocity E-region echoes

Directory of Open Access Journals (Sweden)

M. V. Uspensky

Full Text Available A short event of high-velocity E-region echo observations by the Pykkvibaer HF radar is analysed to study echo parameters and the echo relation to the Farley-Buneman plasma instability. The echoes were detected in several beams aligned closely to the magnetic L-shell direction. Two echo groups were identified: one group corresponded to the classical type 1 echoes with velocities close to the nominal ion-acoustic speed of 400 ms^–1 , while the other group had significantly larger velocities, of the order of 700 ms^–1 . The mutual relationship between the echo power, Doppler velocity, spectral width and elevation angles for these two groups was studied. Plotting of echo parameters versus slant range showed that all ~700 ms^–1 echoes originated from larger heights and distances of 500–700 km, while all ~400 ms^–1 echoes came from lower heights and from farther distances; 700–1000 km. We argue that both observed groups of echoes occurred due to the Farley-Buneman plasma instability excited by strong ( ~70 mVm^–1 and uniformly distributed electric fields. We show that the echo velocities for the two groups were different because the echoes were received from different heights. Such a separation of echo heights occurred due to the differing amounts of ionospheric refraction at short and large ranges. Thus, the ionospheric refraction and related altitude modulation of ionospheric parameters are the most important factors to consider, when various characteristics of E-region decametre irregularities are derived from HF radar measurements.

Key words. Ionosphere (ionospheric irregularities; plasma waves and instabilities; polar ionosphere

Theory and optical design of x-ray echo spectrometers

Science.gov (United States)

Shvyd'ko, Yuri

2017-08-01

X-ray echo spectroscopy, a space-domain counterpart of neutron spin echo, is a recently proposed inelastic x-ray scattering (IXS) technique. X-ray echo spectroscopy relies on imaging IXS spectra and does not require x-ray monochromatization. Due to this, the echo-type IXS spectrometers are broadband, and thus have a potential to simultaneously provide dramatically increased signal strength, reduced measurement times, and higher resolution compared to the traditional narrow-band scanning-type IXS spectrometers. The theory of x-ray echo spectrometers presented earlier [Yu. Shvyd'ko, Phys. Rev. Lett. 116, 080801 (2016), 10.1103/PhysRevLett.116.080801] is developed here further with a focus on questions of practical importance, which could facilitate optical design and assessment of the feasibility and performance of the echo spectrometers. Among others, the following questions are addressed: spectral resolution, refocusing condition, echo spectrometer tolerances, refocusing condition adjustment, effective beam size on the sample, spectral window of imaging and scanning range, impact of the secondary source size on the spectral resolution, angular dispersive optics, focusing and collimating optics, and detector's spatial resolution. Examples of optical designs and characteristics of echo spectrometers with 1-meV and 0.1-meV resolutions are presented.

Echo-Interleaved-Spiral MR Imaging

Energy Technology Data Exchange (ETDEWEB)

Rosenthal, Shirrie; Azhari, Haim [Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa 32000 (Israel); Montag, Avram [Elscint Ltd., MRI division, Haifa (Israel)

1999-12-31

Interleaved-Spiral imaging is an efficient method for MRI fast scans. However, images suffer from blurring and artifacts due to field inhomogeneities and the long readout times. In this paper, we combine interleaved-spirals with spin-echo for 3D scans. The refocusing RF-pulses (echoes) refocus off-resonance spins, thus allowing longer acquisition times per excitation, by limiting inhomogeneity effects. The total number of excitations for a 3D scan is reduced by half. The 3D Fourier transform of an object is divided into pairs of slices, one slice is scanned in an outgoing interleaved-spiral, initiated after a 90 degree pulse has been applied. The second slice is scanned in an ingoing interleaved-spiral, after a 180 degree pulse has been applied, thus reaching the slice origin at the echo time. (authors) 4 refs., 3 figs.

Echo phenomena in a plasma

International Nuclear Information System (INIS)

Pavlenko, V.N.

1983-01-01

The mechanism of echo phenomenon in different plasma media: laboratory and cosmic plasma, metals and semiconductors is analyzed to get a more comprehensive idea on collective processes in a plasma and for practical applications in radiophysics and plasma diagnostics. The echo phenomenon permitted to confirm a reversible nature of the Landau damping, to prove the fact that the information on perturbation is conserved in a plasma (as non-damping oscillations of the distribution function) even after disappearing of the macroscopic field. The dependence of the diffusion coefficient on the velocity is measured, microturbulences in a plasma are investigated. New ways of the plasma wave conversion are suggested, as well as ''lightning'' of super-critical plasma layers and regions of plasma non-transparency. Prospective advantages of using echo for studying the mechanisms of charged particle interaction with the surface bounding a plasma are revealed

Performance appraisal of multibeam system - Hydrosweep at different seabed provinces

Digital Repository Service at National Institute of Oceanography (India)

Kodagali, V.N.; Chakraborty, B.

The performance of the multibeam sounding system (hydrosweep system) has been assessed at three varying zones of the seabed-continental shelf, continental slope, and deepsea seamount areas. Statistical studies were performed on the beamwise time...

Multibeam collection for CNTL10RR: Multibeam data collected aboard Roger Revelle from 2003-06-10 to 2003-06-15, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for CNTL12RR: Multibeam data collected aboard Roger Revelle from 2003-06-24 to 2003-07-09, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for CNTL14RR: Multibeam data collected aboard Roger Revelle from 2003-08-25 to 2003-09-02, Honolulu, HI to Newport, OR

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for CNTL13RR: Multibeam data collected aboard Roger Revelle from 2003-07-14 to 2003-08-22, Honolulu, HI to Honolulu, HI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for MV1011: Multibeam data collected aboard Melville from 2010-09-08 to 2010-09-19, San Diego, CA to San Diego, CA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for EW9302: Multibeam data collected aboard Maurice Ewing from 1993-05-27 to 1993-06-21, Woods Hole, MA to Reykjavik, Iceland

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for AT25: Multibeam data collected aboard Atlantis from 2013-05-03 to 2013-05-06, Woods Hole, MA to Woods Hole, MA

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for HLY12TC: Multibeam data collected aboard Healy from 2012-09-24 to 2012-09-27, Barrow, AK to Dutch Harbor, AK

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

Multibeam collection for KNOX05RR: Multibeam data collected aboard Roger Revelle from 2007-05-07 to 2007-06-14, Phuket, Thailand to Phuket, Thailand

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...