aynka

uint16_t snprint_stm32_serialno(char* p, uint16_t maxlen)
{
  uint32_t uid0 = *(uint32_t*) (UID_BASE);
  uint32_t uid1 = *(uint32_t*) (UID_BASE + 0x4);
  uint32_t uid2 = *(uint32_t*) (UID_BASE + 0x8);

  uint16_t n = 0;

  if (maxlen > 16)
  {

osy

Thanks to the work of @agraf, @KhaosT, @imbushuo, and others, we have Virtualization.framework working on M1 Macs. These [changes][1] have been merged with QEMU v5.2.0 RC3 (will rebase once the final release is out) and integrated with UTM, a brand new QEMU frontend designed in SwiftUI for iOS 14 and macOS 11.

Downloads

• UTM
• Windows for ARM
• Windows 10 ARM.utm
• VirtIO Drivers

mmillar-bolis

#!/bin/bash

# I have managed to map out some undesirable daemons and agents. Most of these
# can be disabled without too much consequence.

## Daemons
# com.apple.analyticsd                        - Anonymized application analytics daemon
# com.apple.appleseed.fbahelperd              - Feedback Assistant Helper Daemon
# com.apple.awacsd                            - Apple Wide Area Connectivity Service Daemon
# com.apple.backupd                           - Apple TimeMachine service

junkblocker

#!/bin/bash

############################################################################################
#    WARNING:        THESE SCRIPTS AND CHANGES ARE NOT MEANT FOR ANYBODY BUT ME.
#    RUNNING THESE WILL MESS UP YOUR COMPUTER IN MYSTERIOUS AND USUALLY UNRECOVERABLE WAYS.
############################################################################################

if [[ "$(sw_vers -productVersion)" != 10\.15* ]]; then
    echo "This is only meant to run on macOS 10.15.* Catalina" >&2
    exit 1

alexellis

You'll need

• Raspberry Pi 3, 3+ or 2 (only)
• A Linux PC, laptop or Raspberry with SD card reader/slot
• A number of Raspberry Pis configured with Ethernet

You must have an SSH key, if you don't know what this is then type in ssh-keygen and follow the instructions.

Prepare to provision RPis:

endolith

"""
Train a neural network to implement the discrete Fourier transform
"""
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import numpy as np
import matplotlib.pyplot as plt

N = 32
batch = 10000

buptliuwei

Kubernetes cluster setup based on amd64 && NVIDIA JETSON TX2

Thanks to @luxas create the Kubernetes on ARM project. But my project has some different, i have a VM on x86 as master node and two nvidia tx2 development kits as work node. So my kubernetes cluster are multi-platform. I use kubeadm as a deployment method.Some basic information of my platform is as follows.

Versions

kubeadm version (use kubeadm version):1.10.0

Environment:

• Kubernetes version (use kubectl version):1.10.0
• Cloud provider or hardware configuration:an amd64 master and 1 arm nodes (nvidia tagra TX2)

AbsoluteDestiny

Where to get FFMpeg

Windows

https://ffmpeg.zeranoe.com/builds/

OSX

https://evermeet.cx/ffmpeg/

boseji

Raspberry Pi InfluxDB: The solution for IoT Data storage

Raspberry Pi is costeffect linux computer very commonly used for IoT home automation projects.

Here are the 3 problems with conventional databases for IoT data store applications:

• Too much or complex configuration
• Unable to expire data / set retentional policies
• Not tailor made of Time Series Data

FabianInostroza

package main

import "fmt"
import "golang.org/x/sys/unix"
import "net"
import "log"
import "encoding/binary"
import "flag"

// CANMsg almacena un mensaje de la red CAN