There is something wrong with how smart cities are built all-around the world. A few problems that we might have are unable scale pilot programs due to short term goals, public interest or lack of financial incentives, sparse participation from people [Mancebo], citizen participation has no decision making power, or we are over-engineering it, or trying to build smart cities like an algorithm — trying to find one size fits all approach. Cities such as Barcelona, Paris, and Amsterdam tried to approach smart cities in different ways in terms of public-private relations, citizen participation, etc. but none were widely successful…

Townsend talks about the emergence of technologies such as cable technology, microcontrollers, apps like dodgeball, and free public wifi and how they shaped the modern cities. In the case of cable television, regulations by local governments helped to strike deals with municipalities with the investment from industry players. He calls his “Bankrolled by industry and backed by local governments.” Thus both the governments and private industry have to play their role. Citizens can shape technology and empower the cities. Thus involving citizens and providing them different platforms as in the case of graduate programs at NYU for media and communication…

Technology is at the forefront in defining smart cities. Smart cities and governments use IT to foster the learning required to keep pace with IT development within government and across society. A smart city has emerged to describe a set of ideas that has invaded the domains of urban management and planning. Different companies have different definitions of smart city development based on their interests and ideologies. The common goals are effective city services and efficient city systems. The cities are the site for innovation, production, distribution, and consumption of products and services. The scale of smart city markets ranges…

No one seems to agree with what a smart actually is. Defining smart cities is not an easy task. Different people have different perspectives on smart cities. Smart cities are a difficult concept to define as a lot of factors govern it from technology to social policies like infrastructure. They are also a reason for uneven development. The issue is identifying the problem is more difficult than it is thought to be. …

Niagara Falls is a group of three waterfalls at the southern end of Niagara Gorge, between the Canadian province of Ontario and the US state of New York. The smaller American Falls and Bridal Veil Falls lie entirely within the United States. The largest one is the Horseshoe Falls by Goat Island.

The Niagara Discovery USA Pass, includes

• Maid of the Mist (the boat ride);
• Cave of the Winds Trip (amazing for everyone. An elevator will take you 53 meters deep into the Niagara Gorge. …

Activation functions are really important for an Artificial Neural Network to learn and make sense of something really complicated and Non-linear complex functional mappings between the inputs and response/output variable. They introduce non-linear properties to the network. Their main purpose is to convert an input signal of a node in an Artificial Neural Network to an output signal. That output signal is used as an input in the next layer in the stack. It is also known as Transfer Function.

An activation function decides whether a neuron should be “fired” or not. …

Types of Data:

Why shouldn’t you initialize the weights with zeroes or randomly (without knowing the distribution):

• If the weights in a network start too small, then the signal shrinks as it passes through each layer until it’s too tiny to be useful.
• If the weights in a network start too large, then the signal grows as it passes through each layer until it’s too massive to be useful.

Types of Initializations:

Xavier/Glorot Initialization

Xavier Initialization initializes the weights in your network by drawing them from a distribution with zero mean and a specific variance,

where fan_in is the number of incoming neurons.

It draws…