How Wix use simplified chinese not traditional chinese

I’ve tried to change language to chinese
image-20200813103214059 image-20200813103244357 but system use traditional chinese not simplified chinese like below photo

Wix Chat :
我們會盡快回復 should be translated to 我们会尽快回复
技術支援 should be translated to 技术支援

enter image description here

Sorting :
名稱 should be translated to 名称


Product Quick View :
快速瀏覽 should be translated to 快速浏览
enter image description here

Product :
首頁 should be translated to 首页 enter image description here

Are there any simplified methods for character creation?

A few friends of mine are interested in RPGs after hearing me talk about them, so I’ve offered to run a single-session game for them. These people are entirely new to TTRPGs (although one has done LARP before) and are familiar with LOTR-style fantasy settings, so I asked if they wanted me to make characters for them or if they wanted to make characters themselves, and they all said they’d like to make them themselves.

That said, I don’t want to overwhelm them with the (roughly) 160 pages on character creation in the PHB. Are there any simplified methods for creating a character?

I want to write make my code in more simplified manner in C#

I want to simplify below code. That code is working but I want to simplify it more. Please forgive me if I am not allowed to ask this question then. I am happy to delete it if it needs to be then. The below code is working but I want to simplify it as much as I can. I tried this way. Can anyone please suggest me how to simplify it in more nice manner.

void CalculateTaxAndRewardPoints()         {             if (state == TEXAS)             {                 rate = TX_RATE;                 amt = baseRate * TX_RATE;                 calc = 2 * basis(amt) + extra(amt) * 1.05;             }             else if ((state == OHIO) || (state == MAINE))             {                 if (state == OHIO)                     rate = OH_RATE;                 else                     rate = MN_RATE;                 amt = baseRate * rate;                 calc = 2 * basis(amt) + extra(amt) * 1.05;                 if (state == OHIO)                     points = 2;             }             else             {                 rate = 1;                 amt = baseRate;                 calc = 2 * basis(amt) + extra(amt) * 1.05;             }         } 

Simulate simplified Circuits

I would like to simulate some simplified circuit where a wire is 1 or 0 (no amps or anything like that) and where I can place some inputs, outputs and logic gates (NOT, OR, AND, etc…) I searched for a while and can’t find how I would go about simulating it (start from changing input then go down the line ?) any idea on how to do it would be nice ! if needed I am using c++.

Simplified Smart Rockets using Genetic Algorithm

This is a very bare bones program where a population of blocks learn to reach a target on a 2d screen (My attempt at making a smart rockets program)

I’ve only used python for 2 weeks so i’m positive certain aspects of the program have extraneous lines of code and unnecessary junk, so what are some ways I can optimize the program/algorithm and make it more readable?

import random import math import pygame import time  WINDOW_SIZE = (600, 600) COLOR_KEY = {"RED": [255, 0, 0, 10],              "GREEN": [0, 255, 0, 128],              "BLUE": [0, 0, 255, 128],              "WHITE": [255, 255, 255],              "BLACK": [0, 0, 0]}  target = [500, 500] pop_size = 20 max_moves = 1500 mutation_rate = 30   class Block:     def __init__(self):         self.color = COLOR_KEY["GREEN"]         self.size = (40, 40)         self.move_set = []         self.position = [0, 0] = -1         self.target_reached = False      def evaluate(self):         dx = target[0] - self.position[0]         dy = target[1] - self.position[1]         if dx == 0 and dy == 0:    = 1.0         else:    = 1 / math.sqrt((dx * dx) + (dy * dy))      def move(self, frame_count):         if not self.target_reached:             self.position[0] += self.move_set[frame_count][0]             self.position[1] += self.move_set[frame_count][1]              if self.position[0] == target[0] and self.position[1] == target[1]:                 self.target_reached = True                 self.color = COLOR_KEY["BLUE"]   def create_pop():     pop = []     for block in range(pop_size):         pop.append(Block())      return pop   def generate_moves(population):     for block in population:         for _ in range(max_moves+1):             rand_x = random.randint(-1, 1)             rand_y = random.randint(-1, 1)             block.move_set.append([rand_x, rand_y])      return population   def fitness(population):     for block in population:         block.evaluate()   def selection(population):     population = sorted(population, key=lambda block:, reverse=True)     best_fit = round(0.1 * len(population))     population = population[:best_fit]     return population   def cross_over(population):     offspring = []      for _ in range(int(pop_size/2)):         parents = random.sample(population, 2)         child1 = Block()         child2 = Block()          split = random.randint(0, max_moves)         child1.move_set = parents[0].move_set[0:split] + parents[1].move_set[split:max_moves]         child2.move_set = parents[1].move_set[0:split] + parents[0].move_set[split:max_moves]          offspring.append(child1)         offspring.append(child2)      return offspring   def mutation(population):     chance = random.randint(0, 100)     num_mutated = random.randint(0, pop_size)      if chance >= 100 - mutation_rate:         for _ in range(num_mutated):             mutated_block = population[random.randint(0, len(population) - 1)]             for _ in range(50):                 if chance >= 100 - mutation_rate/2:                     rand_x = random.randint(0, 1)                     rand_y = random.randint(0, 1)                 else:                     rand_x = random.randint(-1, 1)                     rand_y = random.randint(-1, 1)                  mutated_block.move_set[random.randint(0, max_moves - 1)] = [rand_x, rand_y]      return population   def calc_avg_fit(population):     avg_sum = sum( for block in population)     return avg_sum/pop_size   def ga(population):     fitness(population)     avg_fit = calc_avg_fit(population)     population = selection(population)     population = cross_over(population)     population = mutation(population)      returning = (avg_fit, population)     return returning   def main():     pygame.init()     window = pygame.display.set_mode(WINDOW_SIZE)     pygame.display.set_caption("AI Algorithm")     population = create_pop()     population = generate_moves(population)      my_font = pygame.font.SysFont("Arial", 16)     frame_count = 0     frame_rate = 0     t0 = time.process_time()     gen = 0     avg_fit = 0      while True:         event = pygame.event.poll()         if event.type == pygame.QUIT:             break          frame_count += 1         if frame_count % max_moves == 0:             t1 = time.process_time()             frame_rate = 500 / (t1-t0)             t0 = t1             frame_count = 0             data = ga(population)             avg_fit = data[0]             population = data[1]             gen += 1          window.fill(COLOR_KEY["BLACK"], (0, 0, WINDOW_SIZE[0], WINDOW_SIZE[1]))          for block in population:             block.move(frame_count)          for block in population:             window.fill(block.color, (block.position[0], block.position[1], block.size[0], block.size[1]))          window.fill(COLOR_KEY["RED"], (target[0] + 10, target[1] + 10, 20, 20), 1)          frame_rate_text = my_font.render("Frame = {0} rate = {1:.2f} fps Generation: {2}"                                          .format(frame_count, frame_rate, gen), True, COLOR_KEY["WHITE"])          fitness_text = my_font.render("Average Fitness: {0}".format(avg_fit), True, COLOR_KEY["WHITE"])          window.blit(fitness_text, (WINDOW_SIZE[0] - 300, 40))         window.blit(frame_rate_text, (WINDOW_SIZE[0] - 300, 10))          pygame.display.flip()      pygame.quit()   main() 

Surface integral – can it be simplified?

Compute the integral $ $ \int\int_S \sin{y} dS$ $ where S is the part of the surface $ x^2 + z^2 = \cos^2 y $ lying between the planes $ y = 0$ and $ y = \pi/2$ .

The only way I can see of doing this is to parametrize the surface, using $ x$ and $ z$ as the parameters, and solving this as a normal surface integral. However, that results in a pretty convoluted integral:

$ $ \int\int_D\frac{1-x^2-z^2}{1+x^2+z^2}dxdz$ $

Either I’m doing something wrong, or there’s some sort of simplification that I’m not recognizing. Any hints?

How can create a simplified tool from this complex combination for data collection?

I am trying to create a tool on excel to collect data from different municipality to know their slum level. The values for the variables inside the first box (piped water…Bottled water) household data collected from surveys and are a percentage added up to form the Improved water(please have in mind that not all households/ area will have all the variables. e.g an area may have piped water but not public tap but a different area may have both. This will be the same for the improved sanitation, durable structure and sufficient living.

An area is considered a slum if it misses atleast one of the four main variables (improved water, improved sanitation, durable structure and sufficient living).

My calculation has been done on SPSS and thus the shelter deprevations figures. Basically, this table means that one shelter deprivation is a combination of all possible combinations with one variable missing. The same happens for two, three upto four where all are missing.

Finally all these combinations are brought together to get a non-slum area which is the value 44.5 in the yellow box. Taking from 100 we get 55.5% which is the slum percentage.

I am trying to see how best I can do the shelter deprivation part with excel to make a tool. The part in red shows what I got from multiplying the average (72.8) by the shelter deprivation values from spss. I got the value 54.10% as my slum which is not far off the real figure 55.5%.

Anyone know how I can tackle this. Below is the link with the image of my calculations

dynamic pseudo-code for simplified coin changing algorithm

As a homework exercise our professor presented to us a simplified version of the coin-changing problem in which we do not need to minimize the number of coins used or track the number of possible combinations. Instead we need only to determine if a certain subset of coins of same or varying denomination, equal exactly to, some amount M.

My recursion equation of the problem is as follows:

let k = 0  If ∑ (v1 + v2 + … + vn) = M        return true  If ∑ (v1 + v2 + … + vn) < M     return false  Else      Increment k by 1     make recursive call on coin subset {v1, v2, … v(n-k)} 

The next question is to convert this into pseudo-code that represents a dynamic programming solution to this problem.

I’m a bit stuck. If you were to make a table of every possible sum {v1 + v2}, {v1 + v2 + v3}, {v1 + v2 + v3 + v4}, etc. You could eventually find a solution but wouldn’t that be a much less efficient brute force approach?

I assume the solution would include some implementation of memoization or some way to store and retrieve sums already encountered, but being that the problem is not an optimization problem, I’m having a hard time envisioning a dynamic solution.

Much of the dynamic programming examples that I see suggest iteratively subtracting elements, one item at a time, which is similar to the composition of my recursion equation but I don’t see a modification that would make this pseudo code dynamic in nature.

If anyone could please enlighten me, I’d be very grateful