Same here. Only, my compressed folders are from 1 to 116 MB. Not very large... I can't open any of the files when extracted, all broken. Pictures, txt files, pdf files, html files, mp3 files, nothing opens...

I'm sending full resolution photo files to clients instead of burning them on a disc, but I want to make sure they are the full resolution. I had a client that had pictures made at Walgreens, and they were pixely..I told her not to resize them at all o her end, but now I'm wondering if they are compressed at all and no longer full resolution. If so, I need to go back to discs.

Thanks!

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Someone's done some research on the images uploaded to dropbox and it appears that the images are being re-compressed upon upload. Hopefully the images on the original device aren't being harmed, too.

Running a quick test against some sample data ( -TIFF/2016-06/tubhiswt-4D/) and the LZW provided slightly better compression (157MB vs 192MB) but substantially better processing time (Uncompressed took 11s, LZW took 21s, JPEG-2000 took 90 min). The compression sizes will all be very dependent on the actual data source though but I think its fair to see that in terms of processing time JPEG-2000 performs much worse.

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Besides advantage regarding texture size, RAM usage and CPU on loading, my question is do you think there will be significant performance improvements of the scene once loaded with this texture compressed instead of a JPG file ? Or once loaded on the GPU it is the same ?

That said the biggest improvement came from using power of two texture actually, as it was required for the compressed texture I then did the same for the png file. And it improves drastically the perfs.

Zipped (compressed) files take up less storage space and can be transferred to other computers more quickly than uncompressed files. In Windows, you work with zipped files and folders in the same way that you work with uncompressed files and folders. Combine several files into a single zipped folder to more easily share a group of files.

Some types of files, like JPEG images, are already highly compressed. If you zip several JPEG pictures into a folder, the total size of the folder will be about the same as the original collection of pictures.

First: in Splunk 5.0.1 in the outputs.conf what is the difference between compressed and useClientSSLCompression? I though that useClientSSLCompression must be used when forwarding encrypted data to indexers; however I've noticed that while using this settings the indexer says it expected compression but forward is not configured. If I used compressed in my outputs.conf under my ssl stanza it works just fine. Is useClientSSLCompression depricated or a bug?

Second: In the documentation Configure_your_forwarders_to_use_your_certificates the compressed setting is used and in output.conf documentation under compressed it states *the following Applies to non-SSL forwarding only. For SSL useClientSSLCompression setting is use. Why is that?

The compressed attribute only matters if you are forwarding without SSL. It determines whether Splunk will or not perform "native" compression on a per-data chunk (UF, LWF) or per-event (HWF) basis for outgoing data. This must be enabled on both ends for things to work.

So that not what I have been experiancing. If I use useClientSSLCompression on the forwarder Indexer closes the connection and the HWF say connection timed out. Though ifI use the compressed settings it works just fine. I'll post my conf shortly.

Panda says: Excellent question! When you upload a JPEG file, the image is analyzed. Textures, patterns and colors are automatically identified. The encoder creates an optimally compressed JPEG file based on that information. The final result is compared with the original and fine-tuned. Distracting JPEG artifacts are minimized without big sacrifices in file size. Unnecessary metadata is stripped as well. You will get an optimal image, every time!

Additionally I have compressed and converted my gltf-basis Models using DRACO, but this doesnt affect your Cube.

Im not using Extensions, These lines are Missing in my Models - do you mind Sharing some information about this?

Many advertisers have spent the past several months operating on compressed schedules because they cannot do long-term planning, said Erik Requidan, the cofounder of the site monetization services consultancy Media Tradecraft.

Unlike gasoline or diesel stations, compressed natural gas (CNG) stations are not "one size fits all." Building a CNG station for a retail application or a fleet requires calculating the right combination of pressure and storage needed for the types of vehicles being fueled. Making the right choices about the size of the compressor and the amount of storage at the station will impact the cost of fuel and range for vehicles.

Fast-fill: Generally, fast-fill stations are best suited for retail situations where vehicles arrive randomly and need to fill up quickly. All public CNG stations have a fast-fill option. Fast-fill stations receive fuel from a local utility line at a low pressure and then use a compressor on site to compress the gas to a high pressure. Once compressed, the CNG moves to a series of storage vessels so the fuel is available for a quick fill-up. CNG can also be delivered via dispensers alongside gasoline or other fuel dispensers.

A compressed work schedule allows an employee to work a traditional 35-40 hour workweek in less than five workdays. For example, a full-time employee could work four 10-hour days instead of five 8-hour days.

This option is more easily applied to non-exempt (bi-weekly paid) staff for whom maximum work hours are identified, but it is not ruled out for monthly paid staff who may work more than 40 hours during the work week. Duke Payroll practices require non-exempt staff that agree to a compressed work week arrangement to be paid overtime based on all hours over 40 in a workweek.

Another popular option is a nine day/two week work arrangement, which allows for two weeks of work to be compressed into nine or nine and a half days of work. This is popular with staff members who want some flexibility in their schedule and do not mind extra time built into the beginning or end of the work day, but do not want the long days compressed work week require.

John wanted to find a way to integrate more personal time into his life while continuing to meet his responsibilities at work. After assessing the situation with his supervisor, they agreed that a compressed work schedule could be beneficial for him. Working a compressed work schedule permits John to work four 10-hour days, giving him an extra day off during the workweek to handle responsibilities he has outside of the workplace.

We work with image, audio and video files and are concerned about fidelity. Are they compressed on upload to an update or the Files folder and uncompressed before (single file) download? I realize they are zipped when downloaded in a group.

When I print a PDF from my computer it is compressed. If I give a PDF to another user, and they printed it's not. I have double checked all of my settings in the print dialog box, Page Scaling is set to either none or "fit to printable area" with no effect.

It should work. Are you sure you are generating the compressed .sof file? In Quartus go to Assignments->Settings... click on the "Device and Pin Options..." button. If you go to the Configuration tab and check the box next to "Generate compressed bitstreams" (also make sure the other settings are correct).

As far as I can see if I select 'Active serial configuration' it generates a POF (which can be compresed if I select this option) and a SOF (which doesn't get compressed irrespective of the check-box).

The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This article presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and nonlinear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the article discusses current challenges and future opportunities. 0852c4b9a8

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