Disable CD Burning

Exciting isnt it?

The user cant burn any CDs by this trick. This restriction will disable the use of the inbuilt CD recording functions of Windows.

Open your registry and follow this path: HKEY_CURRENT_USER>Software>Microsoft>Windows>Current Version>Policies>Explorer and
create this key: "NoCDBurning" and set its value to 1. Close you registry and logout/restart your system for the change to take the effect.
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Croudfunding for a computer history display IBM 5080

The Computer Science Department at The University of Auckland maintains displays on the history of computing that are open for public viewing. This is not an activity that a University would normally fund out of its budget, which is for teaching and research. Right now we have the opportunity to mount a display of engineering Computer Aided Design terminals from the 1980s - these were expensive machines that were required before Computer Graphics became commonplace. The new display will show an IBM 5080 work station set up as it was in use - there will also be other terminals in the display. We need to have a cabinet built to display and protect these items but have no funds to spare at present, hence this first attempt at crowdfunding. If you might be interested in supporting this new display please visit our site on pledgeme.co.nz.

from The Universal Machine http://universal-machine.blogspot.com/

IFTTT

Put the internet to work for you.

via Personal Recipe 895909

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Get Smart exhibition at MOTAT

MOTAT in Auckland has a new exhibition called Get Smart - NZ Wired in the Digital World. The museum says "Get Smart will take visitors on an immersive journey of discovery and nostalgia as they explore the origins of the smart devices that surround us today. Learn about how networks and computing have come tog ether to provide instant connectivity and take a closer look at the Kiwi innovators and entrepreneurs who have contributed to this thrilling digital age. Get Smart investigates the growth of computing, gaming and communications to illustrate how the powerful machines now carried in pockets and purses have become faster, cheaper, and smarter." If youve never visited MOTAT perhaps now you should and if youve not been for years its obviously time to return. MOTAT is located at Western Springs, a short bus ride from downtown Auckland.

from The Universal Machine http://universal-machine.blogspot.com/

IFTTT

Put the internet to work for you.

Delete or edit this Recipe

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Tim Berners Lee didnt expect kittens to take over the web


You may have noticed that its the 25th anniversary of the World Wide Web. Its inventor, Sir Tim Berners-Lee, has naturally been receiving quite a lot of media attention. At an Ask Me Anything event for Reddit last week Tim Berners-Lee was asked the following question:

Q: "What was one of the things you never thought the internet would be used for, but has actually become one of the main reasons people use the internet?"
"Porn," several Redditors prompted.
Tim Berners-Lee replied: "Kittens."

And its true that the Web, and YouTube in particular, have been taken over by cats: kittens, small cats, big cats, LOLcats, Grumpy Cats. So I cant really end this blog post without a cat photo can I.



from The Universal Machine http://universal-machine.blogspot.com/

IFTTT

Put the internet to work for you.

via Personal Recipe 895909

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Error Reporting in XP


If error reporting in XP is bugging you then turn it off.

When a system error occurs in XP, a little dialog box appears asking if you want to report the error to Microsoft. Click the message box to make it disappear. You dont have to report the error if you dont want to and on todays "Call for Help" Leo shows you how to turn off the feature if you find it distracting.

To disable error reporting, follow these directions:

1. Right-click My Computer and choose Properties.
2. Click the Advanced tab on your System Properties dialog box.
3. Click the Error Reporting button on the Advanced tab.
4. Place a checkmark next to "Disable error reporting."
5. Leave the other radio button unchecked next to the text labeled, "But notify me when critical errors occur."
6. Click OK.
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TuneUp Utilities 2009 Free Download with Full Personal Registration Product Key

TuneUp Utilities 2009 is a all-in-one system management and optimization utility that optimizes the computer machine for faster, healthier, and smoother performance. TuneUp Utilities 2009 provides a well-integrated collection of tools that saves time and hassle when dealing with various system issues over alternative methods, including startup, uninstall, and performance optimization procedures.

TuneUp Utilities 2009 features new redesigned Start page which status summary, TuneUp Speed Optimizer to identify which settings slow computer down, TuneUp Shortcut Cleaner to remove invalid shortcuts from the Start menu, the Desktop and the Quick Launch bar, TuneUp Styler to customize appearance such as logo animation and logon screen, TuneUp Uninstall Manager, TuneUp StartUp Manager to identify unnecessary autostart applications<, and allows user to free up disk space. TuneUp Utilities 2009 also adds support for the Opera browser.

TuneUp Utilities listed price is normally $49.95. As part of Christmas Advent Calender promotion, Chip.de magazine is giving away full version TuneUp Utilities 2009 for free.

Do note that TuneUp Utilities 2009 is an older version of TuneUp Utilities, and it does not officially support Windows 7. So, install TuneUp Utilities 2009 in Windows 7 is prohibited, although user can get it installed on Windows 7 with Compatibility Mode workaround, but its settings and recommendations may not work best in Windows 7. Only TuneUp Utilities 2010 is compatible with Windows 7.

Here’s how to get the free TuneUp Utilities 2009:

  1. Visit the follwoing Chip.de promotional page, and then click on “Zum Download” button:

    http://www.chip.de/downloads/Vollversion-TuneUp-Utilities-2009_38430607.html

    Alternatively, visit the following web page directly:

    http://www.tuneup.de/promo/chipxmas09

  2. At the German TuneUp Utilities key registration page, enter a valid email address, and then enter the Captcha code appear on the web page.
  3. Check email Inbox for a confirmation email from “TuneUp Promotion ” with the subject of “TuneUp Utilities 2009 Freischaltlink”. Click on the confirmation link in the email.
  4. The link in email will be forwarded to open up a web page with TuneUp Utilities 2009 Personal Product Registration Key Number. Note down the genuine serial number for TuneUp Utilities 2009.
  5. Download the setup installer for English version of TuneUp Utilities 2009: TU2009TrialEN-US.exe
  6. Install TuneUp Utilities, and use the personal registration code to register and activate the full version product by clicking on “Enter Product Key” when prompted.
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TensorFlow Google’s latest machine learning system open sourced for everyone



Deep Learning has had a huge impact on computer science, making it possible to explore new frontiers of research and to develop amazingly useful products that millions of people use every day. Our internal deep learning infrastructure DistBelief, developed in 2011, has allowed Googlers to build ever larger neural networks and scale training to thousands of cores in our datacenters. We’ve used it to demonstrate that concepts like “cat” can be learned from unlabeled YouTube images, to improve speech recognition in the Google app by 25%, and to build image search in Google Photos. DistBelief also trained the Inception model that won Imagenet’s Large Scale Visual Recognition Challenge in 2014, and drove our experiments in automated image captioning as well as DeepDream.

While DistBelief was very successful, it had some limitations. It was narrowly targeted to neural networks, it was difficult to configure, and it was tightly coupled to Google’s internal infrastructure - making it nearly impossible to share research code externally.

Today we’re proud to announce the open source release of TensorFlow -- our second-generation machine learning system, specifically designed to correct these shortcomings. TensorFlow is general, flexible, portable, easy-to-use, and completely open source. We added all this while improving upon DistBelief’s speed, scalability, and production readiness -- in fact, on some benchmarks, TensorFlow is twice as fast as DistBelief (see the whitepaper for details of TensorFlow’s programming model and implementation).
TensorFlow has extensive built-in support for deep learning, but is far more general than that -- any computation that you can express as a computational flow graph, you can compute with TensorFlow (see some examples). Any gradient-based machine learning algorithm will benefit from TensorFlow’s auto-differentiation and suite of first-rate optimizers. And it’s easy to express your new ideas in TensorFlow via the flexible Python interface.
Inspecting a model with TensorBoard, the visualization tool
TensorFlow is great for research, but it’s ready for use in real products too. TensorFlow was built from the ground up to be fast, portable, and ready for production service. You can move your idea seamlessly from training on your desktop GPU to running on your mobile phone. And you can get started quickly with powerful machine learning tech by using our state-of-the-art example model architectures. For example, we plan to release our complete, top shelf ImageNet computer vision model on TensorFlow soon.

But the most important thing about TensorFlow is that it’s yours. We’ve open-sourced TensorFlow as a standalone library and associated tools, tutorials, and examples with the Apache 2.0 license so you’re free to use TensorFlow at your institution (no matter where you work).

Our deep learning researchers all use TensorFlow in their experiments. Our engineers use it to infuse Google Search with signals derived from deep neural networks, and to power the magic features of tomorrow. We’ll continue to use TensorFlow to serve machine learning in products, and our research team is committed to sharing TensorFlow implementations of our published ideas. We hope you’ll join us at www.tensorflow.org.
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Easiest way to find out Which Graphics card in your Pc


Easiest way to find out Which Graphics card in your Pc



Follow my image instruction then you can easily find out which graphics card in your pc lets go....

1st step: pressing "windows button+ R"

GRAPHICS 1


2nd step: then open a window and type "dxdiag". Then click ok 
g2


3rd step : click display display option then get details about your graphics drives










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2015 The Year Wearables Became More Than a Bad Word

Happy New Year. This blog is back from its annual holiday. Some of you will probably have received a fitness tracker, such as a Fitbit, for a Xmas present. So-called "wearables" had a very good year in 2015 and 2016 look to be even better. This article in Wired explores the trends and suggests that wearables are soon to become even more wearable.


from The Universal Machine http://universal-machine.blogspot.com/

IFTTT

Put the internet to work for you.

Turn off or edit this Recipe

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Download Cool apple mac logo wallpaper for Desktop 2

Set-1 Set-2 Set -3

Apple or Apple Logo Wallpaper 28Apple or Apple Logo Wallpaper 29Apple or Apple Logo Wallpaper 30


Apple or Apple Logo Wallpaper 31Apple or Apple Logo Wallpaper 32Apple or Apple Logo Wallpaper 34


Apple or Apple Logo Wallpaper 35Apple or Apple Logo Wallpaper 36Apple or Apple Logo Wallpaper 38


Apple or Apple Logo Wallpaper 40Apple or Apple Logo Wallpaper 41Apple or Apple Logo Wallpaper 43


Apple or Apple Logo Wallpaper 45Apple or Apple Logo Wallpaper 46Apple or Apple Logo Wallpaper 47


Apple or Apple Logo Wallpaper 49Apple or Apple Logo Wallpaper 50

Set-1 Set-2 Set -3
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Use of PrintScreen for some fun

You know the use of Print screen button on the keyboard [present on top right above insert] .
It captures the screen , right ?
But now I will tell you how to use it for some fun .
Take screen shot of the desktop by pressing Print Screen on the desktop .
Go to Paint and paste this .
Save it .
For Windows XP users

1) On the desktop right click -----> arrange icons by ----> De-select Show Desktop Icons .
2) Now right click the taskbar and select properties .
3) Check auto hide the taskbar. Click OK.
4) Now change your wallpaper and keep the one you saved earlier.
5) If paint is not closed, select File ---------> Set as background (Centered) .
Now on the desktop even if you click any icon nothing will happen !!!
Now do I need to tell youhow you can use it for fun on someone elses PC ?
To revert back to normalcy change the wallpaper and select show desktop icons on the right click menu .
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PowerShell v3 PowerShell And Its World

Okay, weird title, again, I know. In the past few weeks I have really seen a lot of scripts that go far past the prepackaged notion of a PowerShell instance into the mechanics of the  [PowerShell] object. Im just using the type accelerator here, but, underneath, the full type is  System.Management.Automation.PowerShell. As shown below, the  [PowerShell]  type accelator is the same thing as the full name.
PS>[PowerShell]

IsPublic IsSerial Name                                     BaseType
-------- -------- ----                                     --------
True     False    PowerShell                               System.Object

PS>[System.Management.Automation.PowerShell]

IsPublic IsSerial Name                                     BaseType
-------- -------- ----                                     --------
True     False    PowerShell                               System.Object
So, when we work with the  [PowerShell] type accelerator, we know what we are hitting against. To get more of an idea of what lives in this namespace:
PS>[powershell].GetMembers() | ft name, membertype -AutoSize

Name                          MemberType
----                          ----------
get_Commands                      Method
set_Commands                      Method
get_Streams                       Method
get_InstanceId                    Method
get_InvocationStateInfo           Method
get_IsNested                      Method
get_HadErrors                     Method
get_Runspace                      Method
set_Runspace                      Method
set_RunspacePool                  Method
get_RunspacePool                  Method
get_HistoryString                 Method
set_HistoryString                 Method
Create                            Method
Create                            Method
Create                            Method
CreateNestedPowerShell            Method
AddCommand                        Method
AddCommand                        Method
AddScript                         Method
AddScript                         Method
AddCommand                        Method
AddParameter                      Method
AddParameter                      Method
AddParameters                     Method
AddParameters                     Method
AddArgument                       Method
AddStatement                      Method
add_InvocationStateChanged        Method
remove_InvocationStateChanged     Method
Connect                           Method
ConnectAsync                      Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
Invoke                            Method
BeginInvoke                       Method
BeginInvoke                       Method
BeginInvoke                       Method
BeginInvoke                       Method
BeginInvoke                       Method
EndInvoke                         Method
Stop                              Method
BeginStop                         Method
EndStop                           Method
Dispose                           Method
AsJobProxy                        Method
ToString                          Method
Equals                            Method
GetHashCode                       Method
GetType                           Method
Commands                        Property
Streams                         Property
InstanceId                      Property
InvocationStateInfo             Property
IsNested                        Property
HadErrors                       Property
Runspace                        Property
RunspacePool                    Property
HistoryString                   Property
InvocationStateChanged             Event
Quite a few things live in here. Eliminating duplicates shows this narrowed down list:
[powershell].GetMembers() | select name, membertype -Unique | ft -AutoSize
Name                          MemberType
----                          ----------
get_Commands                      Method
set_Commands                      Method
get_Streams                       Method
get_InstanceId                    Method
get_InvocationStateInfo           Method
get_IsNested                      Method
get_HadErrors                     Method
get_Runspace                      Method
set_Runspace                      Method
set_RunspacePool                  Method
get_RunspacePool                  Method
get_HistoryString                 Method
set_HistoryString                 Method
Create                            Method
CreateNestedPowerShell            Method
AddCommand                        Method
AddScript                         Method
AddParameter                      Method
AddParameters                     Method
AddArgument                       Method
AddStatement                      Method
add_InvocationStateChanged        Method
remove_InvocationStateChanged     Method
Connect                           Method
ConnectAsync                      Method
Invoke                            Method
BeginInvoke                       Method
EndInvoke                         Method
Stop                              Method
BeginStop                         Method
EndStop                           Method
Dispose                          
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CyberLink PowerDirector 8 Tutorials By PowerDirector University



Tutorials & demos of Cyberlink PowerDirector 8 Ultra By PowerDirector University.


SHARE BY GK
Computer Knowledge
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High Quality Object Detection at Scale



Update - 26/02/2015
We recently discovered a bug in the evaluation methodology of our object detector. Consequently, the large numbers we initially reported below are not realistic, due to the fact that our separately trained context extractor was contaminated with half of the validation set images. Therefore, our initial results were overly optimistic and were not attainable by the methodology described in the paper. Re-evaluating our initial results, we have restricted ourselves to reporting only the single-model results on the other half of the dedicated validation set without retraining the models. With the updated evaluation, we are still able to report the best single-model result on the ILSVRC 2014 detection challenge data set, with 0.43 mAP when combining both Selective Search and MultiBox proposals with our post-classification model. The original draft of our paper "Scalable, High Quality Object Detection" has been updated to reflect this information. We are deeply sorry if our initial reported results caused any confusion in the community. Original post follows below. 
-C. Szegedy, S. Reed, D. Erhan, and D. Anguelov

The ILSVRC detection challenge is an influential academic benchmark for measuring the quality of object detection. This summer, the GoogLeNet team reported top results in the 2014 edition of the challenge, with ~2X improvement over the previous year’s best results. However, the quality of our results came at a high computational cost: processing each image took about two minutes on a state-of-the-art workstation.

Naturally, we began to think of how we could both improve the accuracy and reduce the computation time needed. Given the already high quality of previous results like those of GoogLeNet[6], we expected that further improvements to detection quality would be increasingly hard to achieve. In our recent paper Scalable, High Quality Object Detection[7], we detail advances that instead have resulted in an accelerated rate of progress in object detection:
Evolution of detection quality over time. On the y axis is the mean average precision of the best published results at any given time. The blue line shows result using individual models, the red line is multi-model ensembles. Overfeat[8] was the state-of-the-art at end of last year, followed by R-CNN[1] published in May. The later measurement points are the results of our team.[6,7]
As seen in the plot above, the mean average precision has been improved since August from 0.45 to 0.56: a 23% relative gain. The new approach can also match the quality of the former best solution with 140X reduced computational resources.

Most current approaches for object detection employ two phases[1]: in the first phase, some hand-engineered algorithm proposes regions of interest in the image. In the second phase, each proposed region is run through a deep neural network, identifying which proposed patches correspond to an object (and what that object is).

For the first phase, the common wisdom[1,2,3,4] was that it took skillfully crafted code to produce high quality region proposals. This has come with a drawback though: these methods don’t produce reliable scoring for the proposed regions. This forces the second phase to evaluate most of the proposed patches in order to achieve good results.

So we revisited our prior “MultiBox” work[5], in which we let the computer learn to pick the proposals to see whether we could avoid relying on any of the hand-crafted methods above. Although the MultiBox method, using previous generation vision network architectures, could not compete with hand-engineered proposal approaches, there were several advantages of fully relying on machine learning only. First, the quality of proposals increases with each new improved network architecture or training methodology without additional programming effort. Second, the regions come with confidence scores which are used for trading off running time versus quality. Additionally, the implementation is simplified.

Once we used new variants of the network architecture introduced in [6], MultiBox also started to perform much better; Now, we could match the coverage of alternative methods with half as many proposal patches. Also, we changed our networks to take the context of objects into account, fueling additional quality gains for the second phase. Furthermore, we came up with a new way to train deep networks to learn more robustly even when some objects are not annotated in the training set, which improved both phases.

Besides the significant gains in mean average precision, we can now cut the number of evaluated patches dramatically at a modest loss of quality: the task that used to take 2 minutes of processing time for a single image on a workstation by the GoogLeNet ensemble (of 6 networks), is now performed under a second using a single network without using GPUs. If we constrain ourselves to a single category like “dog”, we can now process 50 images/second on the same machine by a more streamlined approach[7] that skips the proposal generation step altogether.

As a core area of research in computer vision, object detection is used for providing strong signals for photo and video search, while high quality detection could prove useful for self-driving cars and automatically generated image captions. We look forward to the continuing research in this field.

References:

[1]  Rich feature hierarchies for accurate object detection and semantic segmentation
by Ross Girshick and Jeff Donahue and Trevor Darrell and Jitendra Malik (CVPR, 2014)

[2]  Prime Object Proposals with Randomized Prim’s Algorithm
by Santiago Manen, Matthieu Guillaumin and Luc Van Gool

[3]  Edge boxes: Locating object proposals from edges
by Lawrence C Zitnick, and Piotr Dollàr (ECCV 2014)

[4]  BING: Binarized normed gradients for objectness estimation at 300fps
by Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin and Philip Torr (CVPR 2014)

[5]  Scalable Object Detection using Deep Neural Networks
by Dumitru Erhan, Christian Szegedy, Alexander Toshev, and Dragomir Anguelov

[6]  Going deeper with convolutions
by Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke and Andrew Rabinovich

[7]  Scalable, high quality object detection
by Christian Szegedy, Scott Reed, Dumitru Erhan and Dragomir Anguelov

[8]  OverFeat: Integrated Recognition, Localization and Detection using Convolutional Network by Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus and Yann LeCun


* A PhD student at University of Michigan -- Ann Arbor and Software Engineering Intern at Google?
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PowerShell v3 Adding SACL Auditing to a File

Security, in Windows, can be a pretty large, complex subject, particularly from a developers perspective. A few years ago I started exploring security, and, found some great resources. However, when I recently went to figure out how to add a SACL to a file for monitoring I came up short. So, the post below is an exploration of just what SACLs are and how to add them in Windows.

Security is controlled, in NTFS based file systems, on just a few key concepts. Two of the main concepts are: ACEs (access control entry) and ACLs (access control list). An ACE is a structure applied to an object indicated a specific right required by the object to be accessed. An ACL is a composite list of ACEs used to indicate the full permissions required/applied to an object. In short, an ACE belongs to an ACL; conversely, an ACL is composed of ACEs.

ACLs come in two flavors: 1) DACL (discretionary access control list) and SACL (system access control list). Keith Brown gives a great description of the two structures, in The .NET Developers Guide to Windows Security,
The discretionary access control list (DACL) contains a list of permissions granted or denied to various users and groups. The reason its called "discretionary" is that the owner of the object is always allowed to control its contents. Contrast this to the system access control list (SACL), over which the owner has no special control. In fact, the owner of an object isnt even allowed to read it. The SCAL is designed for use by security officers, and it specifies what actions will be audited by the system. I like to think of the SACL as the "Big Brother" bits.
In usage, SACLs are great for tracking who accesses a file. They provide a way to keep track of who works with a given object. One thing to note is that ACLs are not stored in the object, but, rather in the $MFT (master file table). For example, using Access Datas FTK Imager, you can see, below, two permission sets: 1) Take ownership and 2) Full permission.


Full permissions - explorer properties


Full permissions - FTK Imager ($MFT) view


Take ownership - explorer properties


Take ownership - FTK Imager ($MFT) view


When you start working with PowerShell, the Access Masks are displayed in terms of .NET enumerations. Below is a quick example to create a new file and return the SACL (Audit) permissions of the file listed above.
# Start afresh
Clear-Host

# Create new directory if it doesnt already exist
if(!(Test-Path ($path = C: est)))
{
      md $path
}

# Pipe dir contents to test.log
dir C: > ($file = "$path est.log")

# Get ACL information for new file
Get-Acl $file -Audit | select *
When I run this I get the following output in PowerShell:
PSPath                  : Microsoft.PowerShell.CoreFileSystem::C: est est.log
PSParentPath            : Microsoft.PowerShell.CoreFileSystem::C: est
PSChildName             : test.log
PSDrive                 : C
PSProvider              : Microsoft.PowerShell.CoreFileSystem
Audit                   : {}
AccessToString          : BUILTINAdministrators Allow  FullControl
                          NT AUTHORITYSYSTEM Allow  FullControl
                          BUILTINUsers Allow  ReadAndExecute, Synchronize
                          NT AUTHORITYAuthenticated Users Allow  Modify, Synchronize
AuditToString           :
Path                    : Microsoft.PowerShell.CoreFileSystem::C: est est.log
Owner                   : BUILTINAdministrators
Group                   : DOMAINDomain Users
Access                  : {System.Security.AccessControl.FileSystemAccessRule, System.Security.Ac                          cessControl.FileSystemAccessRule, System.Security.AccessControl.FileSys                          temAccessRule, System.Security.AccessControl.FileSystemAccessRule}
Sddl                    : O:BAG:DUD:AI(A;ID;FA;;;BA)(A;ID;FA;;;SY)(A;ID;0x1200a9;;;BU)(A;ID;0x1301bf;;;AU)S:AI(AU;SA;WO;;;S-1-5-21-1234567890-1234567890 -1234567890 -1000)
AccessRightType         : System.Security.AccessControl.FileSystemRights
AccessRuleType          : System.Security.AccessControl.FileSystemAccessRule
AuditRuleType           : System.Security.AccessControl.FileSystemAuditRule
AreAccessRulesProtected : False
AreAuditRulesProtected  : False
AreAccessRulesCanonical : True
AreAuditRulesCanonical  : True
What is important to note here is the Sddl values. For more information on SDDL, check out this link:
Understanding SDDL Syntax
As I start playing around with Get-Acl and the various options I wanted to know what all was available to work with, so, I did a Get-Member:
Get-Acl C: est est.log |
Get-Member |
ft name,membertype -AutoSize

Name                                MemberType
----                                ----------
Access                            CodeProperty
Group                             CodeProperty
Owner                             CodeProperty
Path                              CodeProperty
Sddl                              CodeProperty
AccessRuleFactory                       Method
AddAccessRule                           Method
AddAuditRule                            Method
AuditRuleFactory                        Method
Equals                                  Method
GetAccessRules                          Method
GetAuditRules                           Method
GetGroup                                Method
GetHashCode                             Method
GetOwner                                Method
GetSecurityDescriptorBinaryForm         Method
GetSecurityDescriptorSddlForm           Method
GetType                                 Method
ModifyAccessRule                        Method
ModifyAuditRule                         Method
PurgeAccessRules                        Method
PurgeAuditRules                         Method
RemoveAccessRule                        Method
RemoveAccessRuleAll                     Method
RemoveAccessRuleSpecific                Method
RemoveAuditRule                         Method
RemoveAuditRuleAll                      Method
RemoveAuditRuleSpecific                 Method
ResetAccessRule                         Method
SetAccessRule                           Method
SetAccessRuleProtection                 Method
SetAuditRule                            Method
SetAuditRuleProtection                  Method
SetGroup                                Method
SetOwner                                Method
SetSecurityDescriptorBinaryForm         Method
SetSecurityDescriptorSddlForm           Method
ToString                                Method
PSChildName                       NoteProperty
PSDrive                           NoteProperty
PSParentPath                      NoteProperty
PSPath                            NoteProperty
PSProvider                        NoteProperty
AccessRightType                       Property
AccessRuleType                        Property
AreAccessRulesCanonical               Property
AreAccessRulesProtected               Property
AreAuditRulesCanonical                Property
AreAuditRulesProtected                Property
AuditRuleType                         Property
AccessToString                  ScriptProperty
AuditToString                   ScriptProperty
Theres quite a bit to work with, so, I decide to try and map out some options in order to figure out how to manually create a SACL. This link helps me get a few starting steps:
How to Handle NTFS Folder Permissions, Security Descriptors and ACLs in PowerShell 
To get a more explicit breakdown of what I am working with currently, I run this command: