similar to: Problem Using Windows XP Pro w/Samba

Hello, I'm having problems using Samba as an primary domain controller. I am using debian woody as our platform. The version of samba is "2.2.3a-12.3 for Debian" and i followed the instructions which can be found on the following url: http://www-106.ibm.com/developerworks/eserver/tutorials/samba/. In short this covers: - creating the config file - creating the users /

I have installed samba for the first time and I try to start it in a windows 95 environement. I started nmbd and smbd with the config file listed at the end of this mail (I remove all comment for clarity) I expect to use samba with the SHARE protocol of Windows 95 (No WINS) The new server (sdmpcsv02) is recognised by the other pc's but the can list the exported files The smbclient -L

I read the topics i.e very enjoyable.But I really filled-if your computer is slow,then you use registry cleaners.Because registry cleaners protects your important documents and delete unnecessary data and keeps fast.. :PRegistry Cleaners (http://www.repairregistrycleaners.com/)

Hi all, I'm about to change my Debian mailserver setup from Postfix/dovecot1/procmail to Postfix/dovecot2/sieve with lmtp enabled. After enabling lmtp the virtual users can receive e-mails but not the local users: Mar 21 14:21:40 orange postfix/lmtp[4119]: DE62226216: to=<user at orange.domain.de>, relay=orange.domain.de[private/dovecot-lmtp], delay=7627, delays=7627/0/0/0.02,

Hi all, I'm setting a mailserver using dovecot version: 2.1.7. On the server I have a couple of system users using PAM authentication and a lot of virtual users using SQL authentication. When a virtual user (e.g. david at virtdomain.de) logs in dovecot tries to authenticate the user via PAM and after failing it uses SQL: Mar 19 11:39:42 orange dovecot: auth-worker(7815): pam(david at

I am writing a function for the purposes of a simulation. Due to memory problems, the function sometimes crashes. In order to get around this problem, I would like to include to be able to save the "last" seed, so I can pick up with the next run of the simulation after a "crash". I am having trouble understanding what is going on with .Random.seed! For each run of the

I'm running into problems with set.seed--maybe I'm misunderstanding something. I'm running R 1.5.1 on Windows 2000. I'm basically trying to capture the random seed so that I can reproduce a simulation if it's necessary later. Using set.seed, I can certainly get reproducible results, but not the results I get on the first pass. Here's an example: # Generate a random

We commit a similar sin in the help pages, e.g. example(set.seed) ; runif(2) example(set.seed) ; runif(2) gives you the same random uniforms both times. (Of course it isn't that much of an issue, since you would rarely be running examples before any serious simulations.) You can fairly easily work around that by saving and restoring .Random.seed. I wonder if that isn't also true of the

Dear All, The editor of a journal to which I had submitted a publication asked whether R has a "tested random number generator." My paper included Monte Carlo simulations generating random normal and random chi-square values. help(rnorm) lists Wichura, M. J. (1988) Algorithm AS 241: The Percentage Points of the Normal Distribution. Applied Statistics, 37, 477-484. as a

Morning Everyone, I'm busy doing a rebuild of my home server and am tossing between VMware and KVM for this build. I already have experience with ESX, we use it at work, but I'm debating trying out KVM for a while. The server itself is a budget build using a Supermicro X8SAX board w/ i7-950 & 12GB RAM, LSI 3081 SAS RAID (1068e based), rolled into a NorcoTek 16 Bay SAS case. Not fancy

Morning Everyone, I'm busy doing a rebuild of my home server and am tossing between VMware and KVM for this build. I already have experience with ESX, we use it at work, but I'm debating trying out KVM for a while. The server itself is a budget build using a Supermicro X8SAX board w/ i7-950 & 12GB RAM, LSI 3081 SAS RAID (1068e based), rolled into a NorcoTek 16 Bay SAS case. Not fancy

Everyone, There is non-determinism in LLVM codegen in the following scenarios: 1. Between back-to-back runs of the same LLVM toolchain 2. Between Release vs Release+Asserts toolchains 3. Between Linux vs Windows toolchains The main reasons for the non-determinism in codegen are: 1. Iteration of unordered containers (like SmallPtrSet, DenseMap, etc) where the iteration order is undefined 2.

> On 2016-Nov-15, at 15:16, Hal Finkel <hfinkel at anl.gov> wrote: > > ----- Original Message ----- >> From: "Mandeep Singh via llvm-dev Grang" <llvm-dev at lists.llvm.org> >> To: llvm-dev at lists.llvm.org, "mehdi amini" <mehdi.amini at apple.com>, dexonsmith at apple.com, zinob at codeaurora.org >> Sent: Tuesday, November 15, 2016

I was installing a game, and I made the mistake of agreeing to install DirectX. I'm guessing this can screw up your WINE. Is there any way to clean up my WINE after doing something like that without having to reinstall all my software? Owen Stairs

> On 30/10/2019 9:08 a.m., peter dalgaard wrote: > > You can fairly easily work around that by saving and restoring .Random.seed. This is actually quite tedious to get correct; it requires you to under how and when .Random.seed is set, and what are valid values on .Random.seed. For instance, a common mistake (me too) is to reset to .GlobalEnv$.Random.seed <- NULL in a fresh R

Hi, I've been modelling some data over the past few days, of my work, repeatedly challenging microbes to a certain concentration of cleaner, until the required concentration to inhibit or kill them increaces, at which point they are challenged to a slightly higher concentration each day. I'm doing ths for two different cleaners and I'm collecting the required concentration to

I want to create the mixture formulation of a discrete uniform ie, say f(x) = 1/10, for i = 1,2,3,4,5,6,7,8,9 and 10 and another discrete distribution which has the same values of x, but he probabilities can vary. Can this be done on any package in R? an if so, can the package estimate the 'probabilities' of each of the x value as well as the mixing proportion if I have the data?

> On Oct 8, 2014, at 1:55 AM, Renato Golin <renato.golin at linaro.org> wrote: > > On 8 October 2014 05:25, Chris Lattner <clattner at apple.com> wrote: >>> Up until now the thread has been about “formatting”. You suggested renaming >>> every variable in the project! >> >> If that's what it takes. > > If we're still talking about

Hi: I was wondering why Marsaglia's new ziggurat method for generating deviates from the standard normal distribution has not been implemented in the R base package. I know that it is available in SuppDists pacakage of Bob Wheeler, as "rziggurat". According my timing tests, it is about 6 to 7 times faster (on a Pentium 2.4 MHz) machine than the default Inversion method used in

RubyStuf.com, the premiere place for Ruby stuff, has some new, um, stuff. http://www.rubystuff.com/ Profoundly inspired by a series of ruby-talk threads on just how "dangerous" is Ruby comes "Ruby: You''ll shoot your eye out" shirts and mugs: http://www.cafepress.com/ruby_dangerous http://www.cafepress.com/rubyshootout (A big shout-out to David Koontz for the