MacOSX: Office for Mac 2011 glitches

Read Only and the Disk Utility.app wasn’t correcting it.
Staring with ~/Library/Preferences/Microsoft and its subfolders, make sure they are all Read/Write for your profile.
Also check ~/Library/Application Support/Microsoft.
If the problem is not related to Read/Write permissions then my guess is that the problem is in your preference files or an office cache file. I would start with the preference files. To do this ALL office applications must be shutdown completely, not closed.
Open ~/Library/Preferences (paste that path and include the ~ symbol into Finder > Go > Go to folder) and make sure the list of files and folders are in alphabetical order. Locate all files that start with “com.microsoft.x” and drag them to the trash. Then in the same Preference folder locate the Microsoft subfolder. In this folder you will see a few more “com.microsoft.x” file, drag them to the trash.
Final step is to go to ~/Library/Application Support/Microsoft/Office/User Templates and locate your Normal.dotm file. Rename this file to oldNormal.dotm. The reason you rename it versus trashing it is to save former AutoText, Styles, Macros, etc that you might want to bring over to the new template that gets generated.
This should clear any glitches that Office for Mac 2011 can experience.

MacOSX reset VNC and LMI

sudo /System/Library/CoreServices/RemoteManagement/ARDAgent.app/Contents/Resources/kickstart -restart –agent
then
sudo ps auxwww | grep loginwindow | grep -v grep | awk ‘{print $2}’ | xargs sudo kill -9

CISA is coming into Force, dark side of the Force

If you missed this important news check this out:
http://bit.ly/1QxMOOV
http://bit.ly/1PNZy3s

Eric Schmidt (Google) said:
“If you have something that you don’t want anyone to know, maybe you shouldn’t be doing it in the first place.”

“In the world of pattern recognition, we talk about “feature extraction”. That’s the process whereby we measure things, so if we were interested in classifying motor vehicles, one of the features we might extract is “number of axles”. Another might be “number of wheels”, and still another might be “number of doors”.

The idea, of course, is to use those features to figure out what kind of vehicle we’ve got. But not all features are equally useful: if we’re trying to tell the difference between a Mercedes sedan and a Toyota sedan, “number of wheels” won’t help.

So the next step is “feature selection”: what’s actually useful? Which features will enable us to make decisions?

And the step after that is “feature weighting”, because even if we’ve decided that there are 22 features useful for decision-making, they’re almost certainly not all equally useful.

There is no doubt that by now extensive theoretical and experimental analysis has been carried out on the Facebook data corpus and that algorithms have been written which perform this process, at scale, and quickly. Facebook themselves have no doubt done this because processing the data in this fashion yields saleable output, and we all know that Facebook sells everything that it can to anyone with cash in hand. And any government in possession of Facebook’s data has undoubtedly done the same thing — with their own purposes in mind.

The combination of this approach with machine learning yields code that cuts right through the “5,000 friends” problem like it isn’t even there.” author: Anonymous

Can you imagine yourself browsing the Internet without being logged into Facebook or Google at the same time?

Feel free to share any non US based alternatives to those technology moguls.

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