Google has been successfully able to demonstrate the effective use of real-time data in its apps. They have been adding new content and capabilities. In a recent blog post, Google has introduced a yet another capability in Google Maps which will be showing location-specific Covid-19 data.
In the past, google has been adding new and innovative data-centric mechanisms to its suite of apps. These have included features such as:
So, now Google Maps is adding an additional layer inside it which will use color-coding.
It is not hard to use. Simply speaking, you need to tap on the layers button (Typically showing up at the top right corner) and then click on the Covid-19 info.
What you will see next is the data of new cases per 100,000 people in the area – averaged over a seven day period for normalization purposes. This data is available for 220 countries and regions supported by Google Maps. It can even allow for drilling down to a particular region or city.
What is new?
Arguably, country and region-wide data on Covid-19 cases has already been available for a considerable time. However, what is new here is the integration of Google maps with the data. This opens up new avenues for conducting research, for health authorities to explore regions visually, or simply if you just want to be the smart-citizen by understanding how the spread is occurring. It adds on to existing google apps such as those helping to get around safely.
What is Missing?
While interesting, the data is just one aspect of the big picture. For one, the data presented seems to be instantaneous (i.e. non-temporal). In other words, we cannot explore trends and gradients by simply looking at the map. It also does not show recoveries, or information about local facilities such as hospitals. While there may be existing, localized apps for that, to my knowledge, there is no direct, public integration of any of these apps with Google maps.
JOURNAL OF SIMULATION (JoS) SPECIAL ISSUE ON “Modeling and Simulation in the Cloud Computing era”
Cloud computing has received considerable interest by the scientific and industrial community because, thanks to advances in Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), it allows the implementation of solutions to exploit computing and data storage capacity, network resources, and scalability rapidly. In this context, Cloud, Edge and Fog computing can offer suitable services to share and collaborate on M&S and perform complex simulation experiments faster and more efficiently using Modelling and Simulation as a Service (MSAAS). While MSAAS offers an ever-expanding number of possibilities, it also entails a considerable number of challenges. One of the key challenges is related to the fact that cloud infrastructures are massive at all scales, therefore developing MSAAS solutions is difficult without an adequate knowledge of the involved platforms and technologies.
The aim of this special issue is to provide a comprehensive guide on current ideas and results in M&S for Cloud computing and vice versa. Specifically, the issue aims at: (i) presenting the current state-of-the-art about M&S environments and frameworks based on open standards, recent extensions, and innovations related to Cloud computing technologies; and, (ii) identifying potential research directions and technologies that will drive innovations in M&S on Cloud Computing Infrastructures. Additionally, the special issue will also look for submissions employing Complex Systems related methodologies, toolkits, and frameworks such as involving Complex Social Networks, and Agent-based Modelling, among others.
Nowadays, there is research aiming at investigating the impact of Cloud computing on M&S techniques and methodologies. We believe that a journal special issue on “Modeling and Simulation in the Cloud Computing era” will be a timely contribution to a field that is gaining considerable research interest and is expected to be of increasing interest to commercial developers in a wide range of application domains. Moreover, we believe that the methodological and technological trends in the convergence of Cloud Computing and M&S disciplines need to be explored more in order to provide an exclusive research roadmap to both Cloud Computing and M&S communities. Furthermore, this special issue involves strongly scientific programming aspects related to mathematical models and quantitative analysis techniques that use heavily cloud computing solutions.
Manuscripts for the Special Issue must provide a novel contribution and must be carefully placed in relation to the relevant scientific literature. Authors clearly address research issues of M&S in the Cloud and show the use of existing methodologies, techniques, and tools for the development of future-generation of simulators based on Cloud computing services.
Topics of interest include, but are not limited to:
– High-performance simulation in the Cloud;
– Cloud-based parallel and distributed simulation;
– Simulation optimization approaches that leverage Cloud Computing;
– Dependability and performance analyses through Big data in the Cloud;
– Hybrid modelling research that combines the application of Cloud-based solution to one or more stages of a simulation study;
– Real-time simulations in the Cloud;
– Application-focused papers that also contribute to methodology;
– Literature review (invited; please contact the Guest Editors with a proposal);
– Invited viewpoint papers (invited; please contact the Guest Editors with a proposal).
Peer review of manuscripts submitted to the special issue is conducted according to agreed and ethical peer review standards (http://journalauthors.tandf.co.uk/preparation/ethics.asp) for the publication of articles, so as to ensure the integrity of peer review and assure the quality of published articles.
All authors, peer reviewers, and referees comply with the Publisher’s guidelines on the ethics of journal publishing (http://journalauthors.tandf.co.uk/preparation/ethics.asp) and respect the confidentiality of the review process, and that material under review shall be held to be the contributing author’s intellectual property unless and until otherwise assigned.
Please indicate that your article is for a special issue during the submission process; both in your cover letter and when asked by the ScholarOne system. You should be able to select the special issue title from a drop-down menu, which will help the Editorial Office and the Editors to correctly allocate your paper for peer review.
Please do not hesitate to contact the Guest Editors for any questions.
Manuscript submission deadline: January 15th, 2021
Notification of Acceptance/Rejection: March 06th, 2021
Submission of Revised Manuscripts: April 06th, 2021
Final notification of acceptance: June 21th, 2021
Journal Special Issue Publication Date: September 2021
SPECIAL ISSUE EDITORS:
Lead Guest Editor:
Alberto Falcone (firstname.lastname@example.org), Department of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, Italy.
Alfredo Garro (email@example.com), Department of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, Italy.
Navonil Mustafee (firstname.lastname@example.org), Centre for Simulation, Analytics and Modelling (CSAM), University of Exeter Business School, Exeter, United Kingdom.
Muaz A. Niazi (email@example.com), Computer Science Department, University, Islamabad, Pakistan.
Gabriel Wainer (firstname.lastname@example.org), Department of Systems and Computer Engineering, Carleton University, Canada.
Oddly enough, odd numbers can be not only interesting but also quite satisfying – perhaps simply because they are so odd. 🙂
So, here we have our second odd-numbered post (Post number 3) on Github and Unity.
In the third part of the series, I try to present some suggestions on using #Github with #Unity3D in Team Projects. I also briefly take a look on how I worked with my students/team members in handling #internet connectivity issues.
Additionally, I present a possible workflow for using Github and Unity (2019.3 or later) together in remote teams/student project scenarios.
One of the key machines used in the “Theory of Computation” subject is the “Turing Machine”. Turing machine is currently, possibly, the most advanced model capable of being able to connect with a large number of possible languages. This is besides its ability to simulate modern computer systems and algorithms.
If you missed the first part to get the #Unity#DarkMode for Free , please check out my previous post. In the second part of the tutorial, we cover: A demo of using #Github with #Unity3D. An overview of #Git terms A possible workflow for using Github and Unity (2019.3 or later)
Beginning Git and GitHub: A Comprehensive Guide to Version Control, Project Management, and Teamwork for the New Developer https://amzn.to/2YERRXI
Hill-climbing search is one of the key search algorithms used in Artificial Intelligence.
The idea behind this search is to look for points based on the current location. So, if we have a data point D with a certain number of values V, the way it works is to somehow look for better points based on small variations in the different values.
Github is an amazing resource. Interestingly Unity and Github can be used in conjunction with each other. This has especially been useful for my students in the current times (Covid-19 era) where teachers often have to work with students on a remote basis. I have developed a set of videos explaining the basics of using Github and Unity for remote teams such as those that are with remote students.
In the first video, I discuss benefits of using Github in conjunction with Unity. Please take a look and let me know if I need to add anything in my future posts.
Life, as we know it, has an inherent complexity associated with it. It is made up of numerous intertwined and hierarchical complex adaptive systems (cas). These systems evolve and adapt at a massive scale. Ranging from the current outbreaks of various virii such as variants of Influenza, SARS, SARS-Covid-19 and others are inherently connected with a large number of life forms and species.
Recent advances in Artificial Intelligence have demonstrated the use of techniques and algorithms which are similar, even if in a very very light manner, to the complexities in the natural world. One of these very popular so-called evolutionary algorithms is the “Genetic algorithm” presented originally by the likes of Prof. John Holland (RIP). Here we present a brief overview of Genetic Algorithms.