Limitations and Implications of Doubling Time Approach in COVID-19 Infection Spreading Study

Author(s):  
Apurbalal Senapati ◽  
Soumen Maji ◽  
Arunendu Mondal

To control the spread of COVID-19, around the world, many countries imposed lockdowns. Numerous studies were reported on COVID-19 in different disciplines with various aspects. The doubling time is a mathematical technique to estimate the current rate of spread of the disease. Researchers used the doubling technique to address the COVID-19 pandemic situation. The larger doubling period represents a low spreading rate, whereas the smaller doubling period represents a high spreading rate. In other words, high infection implies the low doubling period and low infection implies the high doubling period. So, there is an inverse relationship between doubling time and the infection rate. But the real-life data does not follow such a rule properly in various domains. The data shows that after a certain time when the infection is high, the doubling period is also high, which misleads our general concept of doubling time. This chapter addressed this issue by investigating the real-time COVID-19 data. To overcome this limitation, a gradient smoothing technique has been proposed.

Lung Cancer ◽  
2018 ◽  
Vol 126 ◽  
pp. 217-223 ◽  
Author(s):  
Elizabeth Dudnik ◽  
Mor Moskovitz ◽  
Sameh Daher ◽  
Sivan Shamai ◽  
Ekaterina Hanovich ◽  
...  

Beekeepers are faced with quite a number of challenges such as selection of fields and enhancement of honey production. In this paper crisp deterministic honey bee production model was formulated in an attempt to optimize the distribution of beehives in the apiary in order to maximize production of honey and minimize unhealthy competition among foraging bees which often arises as a result of overcrowding. The model was characterized using Weighted sum model (WSM) and Analytic Hierarchical Model (AHM). Finally the validity of the model was tested with the real life data and the results obtained shows that proper distribution of the bee hives in the apiary is important to maximize production and minimize unpleasant fields.


2017 ◽  
Vol 12 (1) ◽  
pp. S417-S418
Author(s):  
Elizabeth Dudnik ◽  
Mor Moskovitz ◽  
Sameh Daher ◽  
Sivan Shamai ◽  
Ekaterina Hanovich ◽  
...  

Author(s):  
Kumar Ashish ◽  
Subhagata Chattopadhyay ◽  
Xiao-Zhi Gao ◽  
Nirmal Baran Hui

The paper aims at establishing the output-to-input relationship of the real-life adult depression data using a neural network (NN) model. The said model has been developed to diagnose and detect the associated severity (grade) of the illness. An intelligent NN-based reverse model has been trained through batch mode and put to test on another set of real-life data. Reverse mapping of this model has been developed to isolate significantly contributing input components (factors) for any given case to expedite the preventive procedure for further deterioration as well as the start of treatment.


Author(s):  
Wen-Chien Cheng ◽  
Chih-Yen Tu ◽  
Biing-Ru Wu ◽  
Chih-Yu Chen ◽  
Wei-Chun Chen ◽  
...  

Author(s):  
Ismail Beypinar ◽  
Hacer Demir ◽  
Abdullah Sakin ◽  
Burcu Yapar Taskoylu ◽  
Teoman Sakalar ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Meral Bayraktar ◽  
Rahmi Guclu ◽  
Necati Tahrali

The effect of vibration on the axle has been considered. Vibration measurements at different speeds have been performed on the axle of a running rail vehicle to figure out displacement, acceleration, time, and frequency response. Based on the experimental works, equivalent stress has been used to find out life of the axles for 90% and 10% reliability. Calculated life values of the rail vehicle axle have been compared with the real life data and it is found that the life of a vehicle axle taking into account the vibration effects is in good agreement with the real life of the axle.


Sign in / Sign up

Export Citation Format

Share Document