Recent epidemiological measures in Romania link the level of restrictions to the locality-level infection rate. This shows the number of new cases in the last two weeks, per thousand people (‰). The government has only published locality-level data since early March this year (2021) (but not on the official COVID19 communication site, but in the government’s generic data repository), and there is no official tool where locality -level data could be displayed. Together with other epidemiological and economic indicators, we have already mirrored this data on our COVID-19 – Romanian Economic Impact Monitor.Continue reading “🗺 Harta ratei de incidență pe localități 🌄 Locality-level incidence rate map”
Lately, I was working on developing the visualizations for the COVID-19 – Romanian Economic Impact Monitor. This is a research project led by the Faculty of Economics and Business Administration of the Babes-Bolyai University – Romania’s largest and top-ranked) with specialists from the Babes-Bolyai University, myself from Lancaster University and the Romanian National Bank. This is the first concerted effort in our country to quantify the effects of the pandemic on the economy. Prepare for some Grafana beauty! 👇Continue reading “COVID-19 – Romanian Economic Impact Monitor”
This is a follow-up on my recent post on automatic restoration of old video footage using machine learning.
📽 Source videos
Fining source videos for Bucharest project proved to be more challenging than for Budapest, but eventually I settled on a footage from the 1930s, often considered the golden age of the city – a time when it was also dubbed little Paris (this period is also called perioada interbelică – the period between the wars in Romanian)Continue reading “Bucharest 1930s 📽 old footage restored using machine learning”
Recently, several videos have been popping up on the internet that showed really old video footage restored to modern standards. From a contextual perspective, it is a very fascinating process – i.e. using the knowledge of the past 100 years to create a better image of the even more distant past – but it is also an interesting machine learning application. In a nutshell, the process is the following: you show an algorithm a lot if images of how our world currently looks like, a few images about how our world used to look like in the past – and then it tries to recreate the feel of the modern images on the old images (and a video is just a bunch of images chained after another).
Perhaps the most prominent videos in this category are the ones made by Denis Shiryaev: Arrival of a Train at La Ciotat from 1896 and A Trip Through New York City from 1911. Denis shares the methodology only conceptually, but of course anyone in the know suspects that there are several steps involved. So, I looked for some old footage of Budapest and I had a nice weekend project lined up… But before I delve in, allow me to take off my 👒 in front of Denis – this was a reaaally long and a reaaally difficult process!Continue reading “Budapest 1896 📽 Automatic restoration of old video footage using machine learning”
As coronavirus is threatening to become a global pandemic, I’ve built seven epidemiological models of increasing complexity in order to illustrate how infectious diseases get transmitted over time. Among others, I try to answer the questions of what is the scientific rationale behind a surgical mask or an all-out quarantine. This is a video commentary of a simulation modelling exercise using system dynamics – if you like it, maybe I’ll make some others in the future 😃.Continue reading “Modelling 🦠 Coronavirus – Quarantine?!”