Sorry, I misunderstood, as the word "upgrade" has a slightly different meaning. If you open any message and move your mouse just to the left of the text near the top, you should see two coloured arrows. A green one pointing up, and a red one pointing down. Click the green one to upvote the message, or the red one to downvote (means you think it is not a good message).
As to your other problem, I think we need to see the code, so I suggest you open a new question.
Whoa! before i thought i know Java but when i saw your code about serialization i realized i need to study more. I have never come across it. may be because I am just at intermediate level. your organization of class is what so much impress me about your codes. thank you so much. I wish I can get the complete source code for this.
The app needs to have drag and drop function to build tool with workflow like visio for business users. Easy access for members via web or mobile devices. Internet may not available but mobile can sync data when internet is available.
I'm setting up new application with the following architecture, so need your advice.
html5+JS on frontend on web, and swift on mobile.
Java - MVC webservices provide for both web and mobile front end.
bigdata on the back end.
you know any code generation should be used for Java?
Looking at the headers is the only way to do this.
However, bear in mind that the headers can easily be spoofed. Each server in the chain adds it's own Received header to indicate which computer it received the message from, but it has no way to verify the previous Received headers. As you trace the path back from your server to the sender, once you get beyond the servers that you trust, the headers could be entirely fictitious.
"These people looked deep within my soul and assigned me a number based on the order in which I joined." - Homer
I would release an application in java that allows an offline recognition of old arabic handwritten using neural networks(PMC, back propagation, activation function sigmoide).
so I have extracted with hand the characters from an old scanned handwritten picture and applicate for each of them the pretraitement step, in result it generates a matrix of 8*8 that gives the percentage of black pixels in the character.
Next I have to release the learning step using neural networks, so I have normalized each the values of each matrix between 0 and 1(to use the sigmoide function) and transforme this matrix for a line vector so that it correnpends like input for the neural network(so now I have a line vector of 64 elements like input data for the neural network).
like output I have the same vector correspending for the good written character of each character.
I save the results(the error of each epoch, and the error activation of the neural output for each input) in a wampserver database for esch character.
Now I would go to the step of recognition, but I have no idea of how starting implementing it using the results of the learning step.
This is not a matter of a few simple lines of code; image and character recognition is more complex. You should do some research (via Google) into both subjects to see some of the algorithms and processes that are commonly used.
Thank you for answring, Yes this is true, and I'm searching in google since months. But as I have understood about what I have read of neural networks documents, the recognition is integrated in the learning step(I don't know if what I have understood is true or false). Do you have websites or links to suggest for me?
Last Visit: 31-Dec-99 19:00 Last Update: 2-Mar-24 16:53