similar to: Remote Differential Compression comparative run

On 06/25/2015 01:20 PM, Chris Adams wrote: > ...It's basically a way to assemble one arbitrary set of block devices > and then divide them into another arbitrary set of block devices, but > now separate from the underlying physical structure. > Regular partitions have various limitations (one big one on Linux > being that modifying the partition table of a disk with in-use

Hi, I am using Samba (v2.2.3a-12.3 on stable Debian Woody) on a bi-cpu server (named MYSRV) acting as a primary domain controller. All works well except for printers where I have severals little problems. I use LPRng (v3.8.10-1.2 on stable Debian Woody) as my linux lpd spooler on my server. I have 2 printers : one HP LaserJet 4000N (named nss.1er) and one HP LaserJet 4050N (named nss.rdc).

I've been running some tests on files created by rsync and noticing fragmentation issues. I started the testing because our 5TB array started performing very slowly and it appears fragmentation was the culprit. The test I conducted was straighforward: 1. Copy over a 49GB file. Analyzed with contig (from sysinternals), no fragments. 2. Ran rsync and the file was recreated normally (rsync

I've noticed a correlation the past several time I've restored a Windows 7 workstation ... After doing an image restore (using Acronis) to a Windows 7 domain member, the restored computer boots fine and authenticates with AD credentials fine. But is no longer able to accept RDC connections. The remote system properties are set to allow remote connections, but those settings are controlled

Hi everyone, CUDA allows to call some runtime functions also from the device code. On a multi-GPU system this allows the GPU to determine its device id on its own via cudaGetDevice(). Unfortunately i cannot get it working when compiling with clang. When compiling with nvcc relocatable device code needs to be set to true (-rdc=true) and the cudadevrt is needed when linking [0]. I did not

- introduce local variables (shortcuts for frequently used <dom>->grant_table) - adjust first parameter of mapcount() - drop lock acquisition from gnttab_get_version() - remove hard tabs and adjust formatting Signed-off-by: Jan Beulich <jbeulich@suse.com> Tested-by: Andrew Thomas <andrew.thomas@oracle.com> --- a/xen/common/grant_table.c +++ b/xen/common/grant_table.c @@

Hi All Apologies if this is obvious, but I''m a bit flaky around SSL certificates. NB puppet version 0.25.5 We use the brilliant feature of certificates where you can have Alternate DNS names for a certificate which is manifested in the puppet master config file as certdnsnames. All our clients connect to puppet-$ location.example.com, and if $location is down, we can point the CNAME to

Hello, Does anyone know of a way I can speed this up? Basically I'm attempting to get the data item on the same row as the report date for each report date available. In reality, I have over 11k of columns, not just A, B, C, D and I have to do that over 100 times. My solution is slow, but it works. The loop is slow because of merge. # create sample data z.dates =

On 11/09/2015 08:01 AM, Alessandro Baggi wrote: > how to perform a differential backup using rsync? rsync backups are always incremental against the most recent backup (assuming you're copying to the same location). > Users says diff because it copy only differences. For me differential > is backup from last full backup. I don't see the distinction you're making. rsync

This is applicable to either using optim or the differential equation solver or any similar solver Suppose I want to use the differential equation solver and this is my code d<-y[2] vdpol<-function(t,y) { list(c(1, d, 3, 4 ) } stiff<-ode(y=rep(0,4),times=c(0,1),func=dvdpol,parms=1) The thing is I want d to be composed of one of state variables in the

On 11/9/2015 9:50 AM, Gordon Messmer wrote: > > I don't see the distinction you're making. a incremental backup copies everything since the last incremental a differential copies everything since the last full. rsync is NOT a backup system, its just a incremental file copy with the full/incremental/differential approach, a restore to a given date would need to restore the last

On Wed, Nov 11, 2015 at 5:39 AM, Gordon Messmer <gordon.messmer at gmail.com> wrote: > On 11/10/2015 03:38 PM, J Martin Rushton wrote: >> >> That's plain bad system analysis. Read the start date, record the >> current date and THEN start processing. You will get the odd extra >> file but will not loose any. > > > That's my point.

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Hello, I am trying to find the analytical solution to this differential equation dR/dt = k1*R (1-(R/Rmax)^k2); R(0) = Ro k1, k2, and Rmax are parameters that need to fitted, while Ro is the baseline value (which can be fitted or fixed). The response (R) increases initially at an exponential rate governed by the rate constant k1. Response has a S-shaped curve as a function of time and it

Hi! There are a lot of accepted but not closed revisions in Differential. Many of them were actually committed, but without Differential revision link or when it was specified in wrong way. I think will be good idea to create script which will match committed revisions with those in Differential: file list should be same and hashes of changed line could be calculated for each file. In case of

Hi All, This is more of a general statistics question that I am not so sure about so I need some thoughts from you experts out there. I have Chip-Seq read count data for 2 different treatments (T1 and T2) and my final aim is to calculate differential expression between them. I also have Chip-Seq read count data from a "control / wild type (C)" experiment. I have 3 replicates (2

Hello everyone, I have programmed a function and, among other things, it has to compute the differential of a function. I have been using the function grad() and I have programmed some simulated studies. I have testes with 72,576 different combinations of the initial values and now I got an error in only 4 situations. The error comes from the function grad() and I don't understand why. This

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i am trying to solve a partial differential equation analytically(PDE) in R . i have found some functions that do the stuff numerically. But that will not meet my purpose. is there any function to solve PDE analytically. please help. -- View this message in context: http://r.789695.n4.nabble.com/analytical-solution-of-partial-differential-equation-tp4291618p4291618.html Sent from the R help

Hello list I have a theoretical differential equation model (two coupled differential equations) describing the acidification of dairy cultures in milk: dX/dt = f(H, param)*X dH/dt = g(param)*dX/dt pH = -log10(H) I also have actual data of the same. I would like to estimate the parameters of the theoretical model from real data, but don't know how to go about it in R (I'm fairly new