Hard Drive – Can I use Time Machine on a Mac, but still access deleted files on my Mac?

Normally, I only copy important files to my external hard drive or move the big files there because I do not have much space on my Mac.

But I want to try Time Machine because it may be less susceptible to hard drive failures. Because recently I just got a roasted hard drive and now all my important files are lost.

The question is if I just want to move a large file from my Mac to my external hard drive to free up space on my Mac (local storage space is always in short supply). Can Time Machine do that?

DFA Detterministic Finite State Machine – Computer Science Stack Exchange

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Machine Learning – Request for stored data and statistics

I am currently working on a project to optimize the memory algorithm of memcached using machine learning.

Since I do not own / use large memcached servers, someone would be willing to share the stats from:

a] Which * data sizes * are normally entered? {average value size}

b] what kind of distribution of sizes takes place? {Normal distribution, Poisson distribution, etc.}

If someone just wants to send raw data so that I can find out these two myself, I would be very grateful!

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Machine Learning – How do I express the similarity between a Bing and a Google search result?

I'm working on a "semantic" browser engine that should make all search engines look the same. One way to do this is to hard-code parsing rules for each site. another is machine learning. The latter alternative is of course the hip and cool. 😉

I need a way to group links from search results from Bing, Google, and other popular search engines. Menu shortcuts, pagination, etc. should be in a different cluster than the listed search results. I tried KMeans, it did not work so well. DBSCAN worked well with Google, but I could not easily transfer the result to Bing.

In my case, there are many different functions that can be considered for HTML elements Anchor. I tried to combine the number of children (recursive), the text length, the number of attributes and much more. Can you guess in which direction to go? I have no prior experience with machine learning so it is not trivial to tune an algorithm by hand.

Thankful for any feedback.

animation – How do I activate ENABLE ROOT MOTION on the state machine?

In this (also asked by me) question, I had problems putting the animation on my object:


Basically, the position and size of the character have changed.

It should look like this:

Enter image description here

But it looked like this:

Enter image description here

I could solve this by activating this option:

Enter image description here

Not just by directly inserting into the character, but also by using BlendSpace.

However, when using the state machine, the following error occurred:

Enter image description here

The transition between the animations works correctly, but in the game this error now occurs:

Enter image description here

Target c – state machine for handling sequential and asynchronous events

I created that state machine To handle events. I'm not sure about my implementation first Since I do not use a transition table or the like, I simply enter the next event / state that must happen. I think that is cleaner than calling method event b to treat within the method event a, Law?

Secondlybecause some of the methods have parameters – and that's not swift where enum members can have mapped values, I've added a parameter about it withObj Dispute. I do not see any problem with that, but I would like to know if this is a bit confusing / hurting from your point of view.

I also found this useful for asynchronous tasksAfter the task completes, I set the resulting value to a local variable and update the status packData Use this stored value among many other existing values. This value is packed in a byte array that can not be used in blocks. So this was a useful workaround – although I have not tested it yet.

States are defined via enum how so:

typedef NS_ENUM(NSUInteger, ExampleState) {

Here I define a method to treat each event using helper methods. I also have an additional argument for every state that could have one associated value,

- (void)updateState:(ExampleState)state withObj:(id)obj  {

    self.currentState = state;

    switch (state) {
        case ExampleStateWaitingForAsyncTask:
            (self getAsyncInfo);
        case ExampleStateReadyToPack:
            (self packData);
        case ExampleStateRespond:
            (self respond:obj);
        case ExampleStateComplete:
            (self showPopup);

Example use:

-(void)packData {
    NSData *data = (NSData dataWithBytes:&result length:resultIndex);
    // next step is to respond to `client`/`central` with data
    (self updateState:ExampleStateRespond withObj:data);

docker – How do I set up a Linux machine on a performance basis based on a large amount of unused RAM?

I have a test box (CentOS7) with 192 GB of RAM, which usually only uses ~ 7 GB, maybe with some spikes of up to ~ 32, but nothing more.

Most of the time I used Docker, it has a big 2 TB SSD (xfs) which is used ~ 10, but I still want to make it faster.

Most load-securing operations involve installing system packages in containers or the like with pip packages. I already have a local http proxy, which is partially used due to the MITM / SSL challenges, but the internet connection is also good, so the rest of the question assumes we just have to focus on it Maximize hard drive speed with free RAM,

Since this is a test box, I do not care about the potential loss of data when the system reboots randomly. I prefer to consider this view available.

I'm not very interested in making / tmp a tmpfs because I'm worried that a temporary tmp download might be too small. Also many temporary files are created in containers or in other folders like .tox (Extensively test Python code).

It would be really cool if the file system knew how to save folders with the same name in RAM, but I do not know of a file system that can do that.

With regard to the Docker aspect, the memory is configured as follows:

Storage Driver: overlay2
  Backing Filesystem: xfs
  Supports d_type: true
  Native Overlay Diff: true

ddos – Fundamental difference in security research in cloud platform VM and normal machine

I'm trying to investigate the effects of various network-based attacks in an OpenStack cloud environment that I've set up with just a few computers. But what would be the fundamental difference between an OpenStack VM and a regular VM created with a single computer?

Both VMs should have the same specifications. The main difference I see is that attacks on VMs in OpenStack would take a different network path (due to resource sharing) than direct attacks on a VM on a single physical machine, but the effects on both targets are not the same ?