Spinning Plates

I found a question on Mathstodon the other day, posed by David Radcliffe. Using the numbers 4, 4, 4, 4, 1, 1 and only the basic arithmetic operators, obtain the number 42. It seemed deceptively simple, and so I attempted to solve it. Spoiler alert: it wasn't. So either I misunderstood what tools were available to me (as in, could I have used other operators) or I'm being incredibly myopic and just looking past an obvious answer. I work out a couple of approaches in this talk before giving up.

@online{kilaru2023a,
title = {A Variation of the Four Fours Problem},
organization = {YouTube},
author = {Yasaswi Sri Chandra Gandhi Kilaru},
year = 2023,
month = {Sep},
url = {https://www.youtube.com/watch?v=Um3M8S3i8hI},
}

Reading and implementing the Seam Carving paper. In this video, I write the energy function and test it on a bunch of diverse images. I also explain the energy function and the formal definition of a seam. A seam is a path of pixels that is removed from the image. The energy function is a function that assigns a value to each pixel in the image. The value is a measure of how important the pixel is to the image. The seam is the path of pixels with the lowest energy. The seam is removed from the image and the image is resized. This video is also a code walkthrough of how to read the paper and translate it into code.

@online{kilaru2022b,
title = {Seam Carving. Part 2: Energy Function},
organization = {YouTube},
author = {Yasaswi Sri Chandra Gandhi Kilaru},
year = 2022,
month = {Oct},
url = {https://www.youtube.com/watch?v=kGIflDM9Q78},
}

Reading and implementing the Seam Carving paper. In this video, I go through the seam carving paper while explaining what I'm taking away. I try to understand the contributions of the paper and what we need to implement. I also talk about the ideas I have for implementing the algorithm based on directions from the paper.

@online{kilaru2022a,
title = {Seam Carving. Part 1: Intuition and Ideas},
organization = {YouTube},
author = {Yasaswi Sri Chandra Gandhi Kilaru},
year = 2022,
month = {Oct},
url = {https://www.youtube.com/watch?v=fvvEGFGRQzo},
}

Non-recurrent and unpredictable traffic events directly influence road traffic conditions. There is a need for dynamic monitoring and prediction of these unpredictable events to improve road network management. The problem with the existing traditional methods (flow or speed studies) is that the coverage of many Indian roads is very sparse and reproducible methods to identify and describe the events are not available. Addition of some other form of data is essential to help with this problem. This could be real-time speed monitoring data like Google Maps, Waze, etc. or social data like Twitter, Facebook, etc. In this paper, an unsupervised learning model is used to perform effective tweet classification for enhancing Indian traffic data. The model uses word-embeddings to calculate semantic similarity and achieves a test score of 94.7%.

@misc{kilaru2020,
title = {Traffic event description based on Twitter data using Unsupervised Learning Methods for Indian road conditions},
author = {Yasaswi Sri Chandra Gandhi Kilaru, Indrajit Ghosh},
year = 2020,
month = {Dec},
url = {https://www.civil.iitb.ac.in/~tse/tpmdc_web/index.phtml},
}

Lecture notes for a lecture I gave at IIT Roorkee on Binary Search Trees. After motivating the need for the data structure using a runway reservation system problem, I introduce tree terminology and the basic operations on a binary search tree. Also discussed are the ordering invariant and rounding-up with minor algorithms and runtime technicalities.

@misc{kilaru2019,
title = {Lecture: Binary Search Trees},
author = {Yasaswi Sri Chandra Gandhi Kilaru},
year = 2019,
month = {Nov},
url = {https://kyscg.github.io/assets/pdfs/Binary_Search_Trees_Lecture.pdf},
}