Sometimes incorrectly referred to as an “Aux cable”, RCA is the most common type of unbalanced plug a DJ is likely to come across. The RCA (short for Radio Corporation of America) plug may be as familiar to you as mini-jack plugs, as these are used frequently in hi-fi and home audio equipment. RCA RCA is the most common type of unbalanced audio cable a DJ is likely to come across. Some unbalanced cables are stereo (such as those found in your DJ headphones’ lead), and so only need one socket connection. Most home and personal music devices such as the iPhone use unbalanced audio because the distance between the two ends of the lead isn’t much.īalanced cables are generally mono – that means you need to connect two balanced cables to get stereo sound, just like the outputs of your DJ mixer or controller. Balanced audio cables reduce the amount of noise / interference that get picked up as audio signals travel from one end to another, say a DJ mixer to the PA system. They’re better for situations where cables are prone to noise / interference, or cover a significant distance, such as in a mobile or club DJ set-up. Let’s start with the most common analogue audio cables… Analogue cablesĪnalogue cables come in two broad categories: balanced and unbalanced. Now we will move onto the different kinds of cables that you might encounter when setting up your DJ kit at home or in a club. Analogue cables transmit electrical audio signals from one end to another, while digital cables transmit data in binary code (ie zeros and ones, the language that computers speak). If you turned up to your next gig to see the mixer unplugged, with a pile of cables nearby and only five minutes to plug them all in, how do you think you would fare? Analogue vs digital cablesįirst, let’s talk about the difference between the two categories of audio cables common in DJing: analogue and digital. Getting it wrong can be costly, you risk embarrassing yourself in front of other DJs or club owners and at worst you’re going to make everything sound awful, with the possibility of damaging your gear. In this guide, we will remove any confusion surrounding the most common DJ cables you will encounter when DJing. Working out which cables are required for your set-up is one thing, and then you have to go about connecting everything together. In this guide, we will cover the differences between balanced and unbalanced inputs, analogue and digital signals, and highlight the cables you are most likely to come across while DJing. Choosing to switch methods means choosing to disable one path, and then redo the cabling to include HDMI and the Digital AV adapter.Working out what goes where can be a real pain in the backside for the experienced, as well as the uninitiated.Ĭables are hardly the most glamorous part of a DJ set-up but without them, nothing works. There’s a confusing array of plugs and cables to deal with in a typical set-up, and many DJs (experienced or not) have no idea where to start. This is seriously messy, since you get to choose one method only. Pioneer is using the AppRadio icon alongside CarPlay to mean the Pioneer non-CarPlay interface, and when CarPlay is disabled, to mean the AppRadio apps interface. This is confusing, because AppRadio apps do not work over USB alone: they only work when CarPlay is disabled and the Digital AV Connector and Lightning and HDMI are in use. If you select Digital AV Connector, CarPlay is disabled, but AppRadio remains enabled. If you select iPhone, USB, the CarPlay icon is enabled, and so is the AppRadio icon. The Smartphone Setup screen requires you to select whether you're using an iPhone or Android phone, and whether you connect via USB, Digital AV connector, or BT Wireless.Pioneer told me it was labeled like this because the device is named AppRadio. In CarPlay, there's an icon for Pioneer, labeled "AppRadio." Tapping this doesn't let you launch AppRadio apps, it takes you to the non-CarPlay Pioneer interface.
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In pytorch, we use: nn.conv2d (inputchannel, outputchannel, kernelsize) in order to define the convolutional layers. This is an approach derived from convolutional layers. From now on, you can learn and build the rest of the network as you see fit. Finally, we’ll train our CNN model on the Fashion MNIST dataset, evaluate it, and review the results. I know there are conv RNN structures in visions and nlp, but haven't seen the same in music except this. From there we’ll define a simple CNN network using the Keras deep learning library. I think this permutation and reshape is necessary to make them as a time-series representation. Thus giving you a hidden layer whose values are permutation invariant from the input. In the first part of this tutorial, we will review the Fashion MNIST dataset, including how to download it to your system. 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Debug: sieve: binary /var/qmail/popuser/warden-learn-spam.svbin: save: not saving binary, because it is already storedĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: sieve: Script binary /var/qmail/popuser/warden-learn-spam.svbin successfully loadedĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: sieve: Loading script /var/qmail/popuser/warden-learn-spam.sieveĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: sieve: Opening script 1 of 1 from `/var/qmail/popuser/warden-learn-spam.sieve'Īug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: sieve: file storage: script: Opened script `warden-learn-spam' from `/var/qmail/popuser/warden-learn-spam.sieve'Īug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: sieve: file storage: Using Sieve script path: /var/qmail/popuser/warden-learn-spam.sieveĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: imapsieve: Matched static mailbox rule Īug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: imapsieve: mailbox INBOX.Spam: MOVE eventĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Debug: Mailbox INBOX.Spam: Mailbox opened because: UID moveĪug 21 11:20:32 el7p17 dovecot: service=imap, ip=. With debug mode enabled this is what you will see in the /var/log/maillog when a user marks a message as spam: Aug 21 11:20:32 el7p17 dovecot: service=imap, ip=. Restart dovecot after enabling debug mode: systemctl restart dovecot To turn on debug mode for dovecot edit the file /etc/dovecot/nf and search for the mail_debug parameter: mail_debug = yes You can check that your SpamAssassin config has no errors using the command (It should not return any errors): spamassassin -lint The dovecot learning sieve filter also expects that SpamAssassin and sa-learn is in working order. If your learning statistics are not working you can go though the setup wizard again under Settings -> Application Setup to try and fix the problem (It will re-add database connection information to /etc/mail/spamassassin/local.cf which is used by the real-time learning). When a user marks a message as spam or ham in their email client you should see the Anti-spam - Learning Statistics increment the spam or ham learned values. All Bayes and Txrep data is stored in the Warden database for improved maintenance and performance. You can view the number of trained items on the Dashboard or in the Reports area under Anti-spam - Learning Statistics. Warden will log this training in dashboard under the Anti-spam - Learning Statistics dashboard widget.īy default BAYES rules will be enabled once 200 spam and ham message are trained. If a message is marked as not spam Warden will train the message as HAM (good email). When a user marks a message as spam in their email client (or though webmail) Warden will use a dovecot IMAP service sieve filter to train SpamAssassin (the message is fed though the spamassassin sa-learn binary). |