(BootIt BM and BootIt UEFI) has it all, partition manager, boot manager, and disk imaging. Easily resize, copy, slide, and delete partitions. Configure booting of multiple operating systems, including Windows and Linux. Quickly fix Windows BCD booting problems using the built-in BCD file editor. Use the included full version of Image for DOS/UEFI to create and restore backup images of your hard drives.
The TeraByte drive image files produced by Image for Windows are compatible across all TeraByte Unlimited disk imaging products of the same major version number (i.e. all 3.x products are compatible with other 3.x products). This gives you the flexibility to restore disk images using your component of choice.
The TeraByte Drive Image Backup and Restore Suite includes Image for Windows, Image for Linux, Image for DOS, and the OSD Tool Suite. Image for DOS and Image for Linux support the same powerful drive image functionality without requiring a working Windows installation.
TBIView allows you to open, browse, and extract files or folders from TeraByte Unlimited image files that are based on a EXT2/3/4, FAT, FAT32 or NTFS partition. TBIMount allows mounting of .TBI image files to drive letters. TBIHD allows loading of .TBI image files as a hard drive.
A new "dark energy" camera in Chile captured a mind-bending image of the galactic plane of the Milky Way. The new image reveals a massive three billion objects that were previously uncharted, according to a press statement.
The new image is the second data release of the Dark Energy Camera Plane Survey (DECaPS2), which was compiled over two years of observations of the plane of the Milky Way observed from the southern hemisphere. The observations were made in near-infrared wavelengths, much like the James Webb Space Telescope, which is able to peer through dust clouds and unveil the stellar nurseries hiding beneath.
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In its advanced edition, you still can deploy system image to dissimilar hardware, clone all brands of disks, such as SanDisk, WD, Samsung, Seagate, etc, create a portable version of AOMEI Backupper, and more. Check the edition comparison page and select a suitable version.
#2: Restore disk image from recovery environment. In this way, you need to connect the previously created recovery boot disk, restart your computer to BIOS and set it as the first boot option, press F10 or other prompted keys to save changes and boot into the recovery environment.
In addition to create a disk backup, recovery boot disk, and restore disk image, you may want to copy boot drive to another one, perform dissimilar hardware restore, create a portable version of backup software, and more. To enjoy them, you need to upgrade to the Professional version or higher first.
The steps are similar to restore a disk image and the only difference is to be sure the Universal Restore (supported by the Professional version) feature is checked before clicking Start Restore. In general, if this software detects you restore disk image to a computer with dissimilar hardware, it will check this feature by default.
If you want to create and manage backup image on multiple computers without installing this software from time to time, try Create Portable Version feature in AOMEI Backupper Technician or TechPlus edition. It allows you to copy the installation package to a removable device, such as a USB drive, and run AOMEI Backupper from it, then perform any operation you want.
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Optical imaging is a common technique in ocean research. Diving robots, towed cameras, drop-cameras and TV-guided sampling gear: all produce image data of the underwater environment. Technological advances like 4K cameras, autonomous robots, high-capacity batteries and LED lighting now allow systematic optical monitoring at large spatial scale and shorter time but with increased data volume and velocity. Volume and velocity are further increased by growing fleets and emerging swarms of autonomous vehicles creating big data sets in parallel. This generates a need for automated data processing to harvest maximum information. Systematic data analysis benefits from calibrated, geo-referenced data with clear metadata description, particularly for machine vision and machine learning. Hence, the expensive data acquisition must be documented, data should be curated as soon as possible, backed up and made publicly available. Here, we present a workflow towards sustainable marine image analysis. We describe guidelines for data acquisition, curation and management and apply it to the use case of a multi-terabyte deep-sea data set acquired by an autonomous underwater vehicle.
Modern ocean science gear for underwater sampling is commonly equipped with optical imaging devices like photo and video cameras. These record valuable data for navigation, exploration and monitoring purposes. A multitude of strategies have been developed for various marine data acquisition and data management aspects. These include the design and deployment of underwater camera gear for scientific and industrial applications1, the curation and management of oceanographic data2, the acquisition of all data required for a full biological assessment of a habitat3 and references for manually annotating marine imagery4. Currently though, protocols are lacking for the steps following the marine image acquisition, namely these are: i) image data curation to quality control the recorded raw data and ii) image data management to publish the data sets in a sustainable way in work repositories and long-term data archives. Subsequent steps like manual image annotation and automated image analysis are even less standardized. Together this often leads to un-managed data in the form of dispersed copies on mobile hard disks which unnecessarily duplicate the data, prevent access controls and easily get lost or corrupted.
An additional need for more standardization exists due to the increasing popularity of autonomous underwater vehicles (AUVs). These can record large volumes of image data at an unprecedented acquisition velocity. AUVs are being deployed for large-scale assessments of the seafloor which require specific data processing workflows5. The trend towards parallel deployment of multiple AUVs will further increase the pressure in being able to efficiently curate and manage those big image data sets.
The scale of the image data management challenge is governed by the required image resolution and the area to be surveyed. An uncompressed, color ortho-photo of the entire seafloor, acquired at 1px/mm resolution, would require ca. 1 zettabyte of storage space (71%5.10108km23 bytes/mm21.091021 bytes). This is about 1/10th of all hard disk storage produced in 2017 and does not consider repeated monitoring for time series observations. Even a single imaging survey of 1 km2 seafloor coverage typically produces 0.5 TB of imagery.
While some marine data archives have been set up, they are usually being used to publish one-dimensional or below-gigabyte data rather than hundred-thousands of high-resolution images. Furthermore, long-term accessibility is challenging to achieve. In a recent publication shallow water seafloor images-also acquired by an AUV-and manually created expert annotations for those images were published in an open access format8. While the annotations are still available in a long-term archive, the link to the imagery is already broken ( ). This points out the need for long-term maintenance of data products and data archives-especially in times of global change when time-series studies of the natural environment need to be conducted and when scientific results are being questioned because of political motivation.
Here, we propose a marine image data acquisition, curation and management workflow (see Fig. 1). An AUV-based deep seafloor image data set is presented as a use case for the workflow. We elaborate the specific acquisition, curation and management steps for this use case in detail to explain the steps of the general workflow.
Various robots (autonomous underwater vehicles (AUVs), landers, remotely operated vehicles (ROVs), towed platforms) create stacks of imagery (a) and metadata tables (b). Erroneous metadata values (here marked in red) and corrupt imagery (e.g. black images where the flash did not fire) might occur. Metadata are attached to the image data, image processing is applied and corrupt and erroneous data are flagged and filtered out (c). The resulting curated data set is the quality controlled data product that is suitable for publication and analysis. Metadata and image data are stored in suitable databases (public or private). Image data items should be linked to their corresponding metadata at archiving. The individual steps from pre-cruise planning to publication are discussed in the text. For a specific use case, see Fig. 3.
The image data of this use case, combined with its metadata and environmental data have been published in the long-term information system PANGAEA for earth and environmental science9, (Data Citation 1). This is the first time that a workflow for terabyte-scale deep-sea image data has been published and the first time that PANGAEA has been used for such large volumes of optical image data.