이 문서가 여기저기 알려짐에 따라, 이곳에 여러가지 댓글이 달리고 있습니다. 개인적으로는 댓글창을 없애버리고 싶지만 그럴 수 없는 터라, 댓글을 달기 전에 한번씩만 더 생각해주셨으면 합니다.
- 개인적인 감상은 이곳이 아닌 다른 곳에 적어주세요.
- 동성애 혐오적인 댓글을 달지 마세요.
- 기타 "난해한 혀엉... 언어"와 관련없는 댓글을 달지 말아주세요.
위 사항들을 포함해 제 마음에 안 드는 댓글들은 임의로 삭제하고 있습니다. 양해 부탁드립니다.
이 문서가 여기저기 알려짐에 따라, 이곳에 여러가지 댓글이 달리고 있습니다. 개인적으로는 댓글창을 없애버리고 싶지만 그럴 수 없는 터라, 댓글을 달기 전에 한번씩만 더 생각해주셨으면 합니다.
위 사항들을 포함해 제 마음에 안 드는 댓글들은 임의로 삭제하고 있습니다. 양해 부탁드립니다.
This is a guide that I wrote to improve the default security of my website https://fortran.io , which has a certificate from LetsEncrypt. I'm choosing to improve HTTPS security and transparency without consideration for legacy browser support.
I would recommend these steps only if you have a specific need for information security, privacy, and trust with your users, and/or maintain a separate secure.example.com domain which won't mess up your main site. If you've been thinking about hosting a site on Tor, then this might be a good option, too.
The best resources that I've found for explaining these steps are https://https.cio.gov , https://certificate-transparency.org , and https://twitter.com/konklone
This procedure explains how to install MySQL using Homebrew on macOS Sierra 10.12
$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
At this time of writing, Homebrew has MySQL version 5.7.15 as default formulae in its main repository :
package codejam | |
import java.io.{PrintStream, File} | |
import scala.annotation.tailrec | |
import scala.io.Source | |
object CountingSheep { |
#!/usr/bin/env python2 | |
# -*- coding: UTF-8 -*- | |
# Note: A newer version of this script is located at https://github.com/trustin/smi2ass | |
# | |
# Copyright (C) 2018 Trustin Heuiseung Lee and other contributors | |
# | |
# This program is free software; you can redistribute it and/or | |
# modify it under the terms of the GNU General Public License | |
# as published by the Free Software Foundation; either version 2 | |
# of the License, or (at your option) any later version. |
#!/usr/bin/env python2 | |
# -*- coding: utf-8 -*- | |
from __future__ import division | |
import numpy as np | |
from math import cos, sin, pi, sqrt, atan2 | |
d2r = pi/180 | |
class Geometry(object): | |
def circle_intersection(self, circle1, circle2): |
#!/bin/bash | |
# Centos 7/8 John the Ripper Installation | |
#release=(j 1.8.0) | |
release=(k 1.9.0) | |
# Check Centos version | |
if [ -f /etc/redhat-release ] ; then | |
source /etc/os-release | |
if [ $VERSION_ID == "8" ] ; then | |
packager=dnf | |
elif [ $VERSION_ID == "7" ] ; then |
# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set. | |
# Requires: numpy, sklearn>=0.18.1, tensorflow>=1.0 | |
# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1' | |
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's. | |
# Similarly, for h * W_2 + b_2 | |
import tensorflow as tf | |
import numpy as np | |
from sklearn import datasets | |
from sklearn.model_selection import train_test_split |
import android.os.Build; | |
/** | |
* Utility methods related to physical devies and emulators. | |
*/ | |
public class DeviceUtil { | |
public static boolean isEmulator() { | |
return Build.FINGERPRINT.startsWith("generic") | |
|| Build.FINGERPRINT.startsWith("unknown") |
with table_stats as ( | |
select psut.relname, | |
psut.n_live_tup, | |
1.0 * psut.idx_scan / greatest(1, psut.seq_scan + psut.idx_scan) as index_use_ratio | |
from pg_stat_user_tables psut | |
order by psut.n_live_tup desc | |
), | |
table_io as ( | |
select psiut.relname, | |
sum(psiut.heap_blks_read) as table_page_read, |