yuikns

class Solution {
public:
    // 
    int minOfNext(vector<int>& v1, vector<int>& v2, int n1, int n2, int o1, int o2) {
        if(n1 > o1 && n2 > o2) {
            return min(v1[o1],v2[o2]);
        } else if(n1 > o1) {
            return v1[o1];
        } else {
            return v2[o2];

yuikns

//
//
//

#include <stdlib.h>
#include <stdio.h>

//
//
//

yuikns

JsonData = [ 
             {
               key: "Serie1",
               values: [
                         {'Data1':  1, 
                          'Data2':  2, 
                          'Data3':  3,
                          'Data4':  4,
                          'Data5':  5
                         },

yuikns

<?php
/**
 *Plugin Name: SomeMoreSentence
 *Version:     0.1
 *Plugin URI:  http://argcv.com
 *Description:  append some more sentence after the end of your post
 *Author:      Yu Jing
 *Author URI:  http://argcv.com/about
 */

yuikns

package com.argcv.util;

import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;

yuikns

# Example config file /etc/vsftpd/vsftpd.conf
#
# The default compiled in settings are fairly paranoid. This sample file
# loosens things up a bit, to make the ftp daemon more usable.
# Please see vsftpd.conf.5 for all compiled in defaults.
#
# READ THIS: This example file is NOT an exhaustive list of vsftpd options.
# Please read the vsftpd.conf.5 manual page to get a full idea of vsftpd's
# capabilities.
#

yuikns

CC               := cc
CXX              := c++

CP               := @cp
MV               := @mv
DEL              := @rm -rf

LIBS             := -ldl -lpthread  -lm #-L lib/ 
INFLAGS          := -I include/

yuikns

• https://jira.mongodb.org/browse/SERVER-27701

yuikns

from numpy import exp, array, random, dot
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]])
training_set_outputs = array([[0, 1, 1, 0]]).T
random.seed(1)
synaptic_weights = 2 * random.random((3, 1)) - 1
for iteration in range(100):
    output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights))))
    synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output))
print (1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights)))))

yuikns

dnf install https://download1.rpmfusion.org/free/fedora/rpmfusion-free-release-$(rpm -E %fedora).noarch.rpm https://download1.rpmfusion.org/nonfree/fedora/rpmfusion-nonfree-release-$(rpm -E %fedora).noarch.rpm
dnf -y install ffmpeg ffmpeg-libs ffmpeg-devel gstreamer-ffmpeg