Being extremely dependent on it’s coal reserves for its economy, Wyoming has seen a decline in use of coal over the past few years. Is there a way to tackle this problem, with also not hurting its environment?

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Image Credits: Casper Star-Tribune


Wyoming is one of the most important states, in context to the coal production as it produces nearly half the coal burnt in USA. However, due to the rise of natural gas energy and renewable sources, the state revenue has been on the decline. This has prompted Mr. …

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Credits: Unsplash (Johannes Plenio, @jplenio)


Peaker Plants are those power plants which run only when the demand for electricity crosses a certain base load[1]. As these power plants are used occasionally, the cost of operating them is much higher than the normal power plants, which are operated continuously. The time of operation of peaker plants depends on the location of the plant. In case the plant is located in a region of lower temperatures, the peak might occur during early hours of the morning. However, if the temperatures are considerable high, the peak could occur in later evenings. …

Spacepy python library serves as a useful tool to store and read complex files, while also storing the description of the data.

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Image from NASA from Unsplash

The most important aspect of any organization is to have a mechanism to read and store data. The most common ways of storing data is through the formats of ‘.csv’, ‘.tsv’ or ‘.txt’. Although these files have the ease of reading information using a standard sparser or a customized separator, it becomes difficult to store multi-dimensional data and its corresponding information (about the units, methodology for data collection, etc.).

A novel way of storing the data and its information is to use the ‘.cdf’ format for files. CDF stands for Common Data Format, and it accepts the most generalized type of data, irrespective of its dimensions and shape. Created by Wolfram Research, CDF enables easy information storage and transmission. …

Basic methodology for Spatial-Temporal Clustering of Data through an example from Radar data

Radars are pretty useful. Measurements from these radars can be used in a number of applications, ranging from NWP (Numerical Weather Prediction), Pollution Analysis, Visibility Analysis amongst others. Radars are widely famous because of their ability to measure a plethora of parameters through wide variation in space and time.

Radar data is not universal. Depending upon the type of radar and the motive of measurements, the time-space resolution varies. …

(Acknowledgments: This algorithm was developed as an extension of the project, ‘Analysis of US Pollution Data’, for 19603, a graduate level course at Carnegie Mellon, the project which was in collaboration with Hariharan Ramasubramanian and Madhulika Dashputre, under the guidance of Professor Alexander Davis, Engineering and Public Policy, CMU.)

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Pollution is an ever-growing issue in the modern world

Pollution has become a word of widespread discussion all over the world, mainly due to its increasing presence in our lives. Be it New Delhi in India, or be it Beijing in China, air pollution has caused rapid disruption in daily activities leading to closure of schools and public places. Apart from harming the social life, pollution has also affected the environment in an adverse manner, which rampant fluctuations in atmospheric parameter. This article considers four major pollutants, Carbon monoxide (CO), Sulphur dioxide (SO2), Nitrogen dioxide (NO2) and Ozone (O3). These pollutants are the key components of any industrial smog or emission which is released into the atmosphere. Moreover, it is easier to measure these concentrations because of readily available techniques. …


Yash Gokhale

Graduate Student at Carnegie Mellon University.

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