scholarly journals Modeling the flow of the COVID-19 in Germany: The efficacy of lockdowns and social behavior

2020 ◽  
Author(s):  
Muhamad Khairul Bahri
Keyword(s):  
Computer Simulation ◽  
Social Behavior ◽  
Young People ◽  
System Dynamics ◽  
Computer Model ◽  
Health Workers ◽  
Uncertain Parameters ◽  
Seir Model ◽  
The Given ◽  
Death Cases

AbstractThis study develops a computer simulation in understanding the flow of the COVID-19 in Germany between January 2020 and July 2020. This aims to analyze not only the flow of the COVID-19 but also the efficacy of taken measures during the given period. The computer model is based on the SEIR concept and it is based on the system dynamics approach in which some uncertain parameters are estimated through the calibration process. Moreover, the SEIR computer model is developed by considering different flows of COVID-19 cases in older and young people in Germany. This study successfully reproduces similar patterns of infected, recovered, and death cases. Moreover, as the SEIR model can successfully reproduce similar patterns, the SEIR model can be a basis to estimate other resources such as health workers, and bed capacities.

scholarly journals Understanding the First and the Second Waves of the COVID-19 in Germany: Is our Social Behavior Enough to Protect us from the Pandemic?

2021 ◽  
Vol 18 (15) ◽  
Author(s):  
Muhamad KHAIRULBAHRI
Keyword(s):  
Young People ◽  
Computer Model ◽  
Health Workers ◽  
Public Spaces ◽  
Unknown Parameters ◽  
Behavioral Measures ◽  
Seir Model ◽  
Resource Needs ◽  
Second Wave ◽  
Death Cases

Like other European countries, Germany has experienced the 2nd wave of the COVID-19 amid obligations of social distancing and wearing of face masks in public spaces. Although Germany successfully contained the virus during the 1st wave, it has faced difficulties in controlling the COVID-19 during the 2nd wave. This study develops a computer model representing the COVID-19 flow in Germany by comparing the effects of the measures taken during the 1st and the 2nd waves. The computer model is based on the SEIR concept and the system dynamics (SD) approach in which some unknown parameters are estimated through the calibration process. Moreover, the SEIR computer model is developed by considering different cases in older and young people and the SEIR model successfully reproduces similar patterns of infected, recovered, and death cases in the 1st and the 2nd waves in Germany. The SEIR model also shows that the measures taken in the 1st wave have different efficacies than those in the 2nd wave, leading to higher infected cases during the 2nd wave. Since the SEIR model can successfully reproduce similar patterns, the SEIR model can be a basis for further studies in estimating other resource needs such as health workers, and bed capacities. HIGHLIGHTS The SEIR model estimates the efficacies of behavioral measures and lockdowns Behavioral measures are less effective than lockdowns Germany experienced higher infected cases in the first wave than in the second wave Relaxed lockdowns lead to higher infected cases in the second wave Lockdowns are the key to curb COVID-19 flow GRAPHICAL ABSTRACT

Submerged upflow biotower operation and computer simulation

1994 ◽  
Vol 30 (11) ◽  
pp. 143-146
Author(s):  
Ronald D. Neufeld ◽  
Christopher A. Badali ◽  
Dennis Powers ◽  
Christopher Carson
Keyword(s):  
Computer Simulation ◽  
Benzoic Acid ◽  
Computer Model ◽  
Rate Constants ◽  
Batch Mode ◽  
Operational Conditions ◽  
First Order ◽  
Low Concentrations ◽  
Biological Transformation ◽  
Kinetics Of

A two step operation is proposed for the biodegradation of low concentrations (< 10 mg/L) of BETX substances in an up flow submerged biotower configuration. Step 1 involves growth of a lush biofilm using benzoic acid in a batch mode. Step 2 involves a longer term biological transformation of BETX. Kinetics of biotransformations are modeled using first order assumptions, with rate constants being a function of benzoic acid dosages used in Step 1. A calibrated computer model is developed and presented to predict the degree of transformation and biomass level throughout the tower under a variety of inlet and design operational conditions.

Machine Learning Approach for Confirmation of COVID-19 Cases: Positive, Negative, Death and Release (Preprint)

2020 ◽  
Author(s):  
Samir Bandyopadhyay Sr ◽  
SHAWNI DUTTA ◽  
SHAWNI DUTTA ◽  
SHAWNI DUTTA
Keyword(s):  
Machine Learning ◽  
Short Term Memory ◽  
Health Workers ◽  
Original Data ◽  
High Rate ◽  
Learning Approach ◽  
Good Decision ◽  
Number Of Patients ◽  
Machine Learning Approach ◽  
Death Cases

BACKGROUND In recent days, Covid-19 coronavirus has been an immense impact on social, economic fields in the world. The objective of this study determines if it is feasible to use machine learning method to evaluate how much prediction results are close to original data related to Confirmed-Negative-Released-Death cases of Covid-19. For this purpose, a verification method is proposed in this paper that uses the concept of Deep-learning Neural Network. In this framework, Long short-term memory (LSTM) and Gated Recurrent Unit (GRU) are also assimilated finally for training the dataset and the prediction results are tally with the results predicted by clinical doctors. The prediction results are validated against the original data based on some predefined metric. The experimental results showcase that the proposed approach is useful in generating suitable results based on the critical disease outbreak. It also helps doctors to recheck further verification of virus by the proposed method. The outbreak of Coronavirus has the nature of exponential growth and so it is difficult to control with limited clinical persons for handling a huge number of patients with in a reasonable time. So it is necessary to build an automated model, based on machine learning approach, for corrective measure after the decision of clinical doctors. It could be a promising supplementary confirmation method for frontline clinical doctors. The proposed method has a high prediction rate and works fast for probable accurate identification of the disease. The performance analysis shows that a high rate of accuracy is obtained by the proposed method. OBJECTIVE Validation of COVID-19 disease METHODS Machine Learning RESULTS 90% CONCLUSIONS The combined LSTM-GRU based RNN model provides a comparatively better results in terms of prediction of confirmed, released, negative, death cases on the data. This paper presented a novel method that could recheck occurred cases of COVID-19 automatically. The data driven RNN based model is capable of providing automated tool for confirming, estimating the current position of this pandemic, assessing the severity, and assisting government and health workers to act for good decision making policy. It could be a promising supplementary rechecking method for frontline clinical doctors. It is now essential for improving the accuracy of detection process. CLINICALTRIAL 2020-04-03 3:22:36 PM

scholarly journals Improvement of Transverse-Flux Machine Characteristics by Finding an Optimal Air-Gap Diameter and Coil Cross-Section at the Given Magneto-Motive Force of the PMs

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 755
Author(s):  
Grebenikov Viktor ◽  
Oleksandr Dobzhanskyi ◽  
Gamaliia Rostislav ◽  
Rupert Gouws
Keyword(s):  
Cross Section ◽  
Computer Model ◽  
Single Phase ◽  
Air Gap ◽  
Laboratory Measurements ◽  
The Finite Element Method ◽  
Power Characteristics ◽  
Transverse Flux ◽  
Output Characteristics ◽  
The Given

This paper presents analysis and study of the single-phase transverse-flux machine. The finite element method results of the machine are compared with the laboratory measurements to confirm the accuracy of the computer model. This computer model is then used to investigate the effect of the machine’s geometry on its output characteristics. Parametric analysis of the machine is carried out to find the optimal air-gap diameter at which the cogging torque of the machine is minimal. In addition, the influence of the coil cross-section on the torque and output power characteristics of the machine is investigated and discussed.

COMPUTER SIMULATION OF PROCESSES IN A DAMPED CURRENT GENERATOR

2020 ◽  
Author(s):  
A.P Sinegubov ◽  
◽  
V.A. Shelest ◽  
D.A. Kopeikin
Keyword(s):  
Computer Simulation ◽  
Computer Model ◽  
Current Generator ◽  
Mos Transistor

The article considers a damped current generator based on a MOS transistor. In the LTspice IV package, a computer model of the generator is being developed, which allows to study its operation and refine the circuit parameters.

scholarly journals Facial pressure zones of an oronasal interface for noninvasive ventilation: a computer model analysis

2014 ◽  
Vol 40 (6) ◽  
pp. 652-657 ◽  
Author(s):  
Luana Souto Barros ◽  
Pedro Talaia ◽  
Marta Drummond ◽  
Renato Natal-Jorge
Keyword(s):  
Computer Simulation ◽  
Skin Lesion ◽  
Computer Model ◽  
Noninvasive Ventilation ◽  
Laser Scanning ◽  
Soft Tissues ◽  
Geometric Model ◽  
Human Face ◽  
Nasal Bridge ◽  
Nasal Cartilage

OBJECTIVE: To study the effects of an oronasal interface (OI) for noninvasive ventilation, using a three-dimensional (3D) computational model with the ability to simulate and evaluate the main pressure zones (PZs) of the OI on the human face. METHODS: We used a 3D digital model of the human face, based on a pre-established geometric model. The model simulated soft tissues, skull, and nasal cartilage. The geometric model was obtained by 3D laser scanning and post-processed for use in the model created, with the objective of separating the cushion from the frame. A computer simulation was performed to determine the pressure required in order to create the facial PZs. We obtained descriptive graphical images of the PZs and their intensity. RESULTS: For the graphical analyses of each face-OI model pair and their respective evaluations, we ran 21 simulations. The computer model identified several high-impact PZs in the nasal bridge and paranasal regions. The variation in soft tissue depth had a direct impact on the amount of pressure applied (438-724 cmH2O). CONCLUSIONS: The computer simulation results indicate that, in patients submitted to noninvasive ventilation with an OI, the probability of skin lesion is higher in the nasal bridge and paranasal regions. This methodology could increase the applicability of biomechanical research on noninvasive ventilation interfaces, providing the information needed in order to choose the interface that best minimizes the risk of skin lesion.

scholarly journals MODEL OF TWO-MASS ELECTROMECHANICAL SYSTEM

2010 ◽  
Vol 2 (1) ◽  
pp. 85-89
Author(s):  
Sigitas Juraitis
Keyword(s):  
System Dynamics ◽  
Induction Motor ◽  
Reference Frame ◽  
Computer Model ◽  
Electromechanical System ◽  
Stationary Reference Frame

The computer model of electromechanical system with elasticity and clearance is elaborated. Model of induction motor is developed in stationary reference frame. Results of simulation are presented and discussed. Conclusions about influence of finite stiffness and clearance on the system dynamics are made.

Uzņemšanas noteikumi augstākās mācību iestādēs: starptautiskā pieredze (19. gs. otrā puse – 20. gs. sākums)

2021 ◽  
pp. 26-30
Author(s):  
Tatjana Bartele
Keyword(s):  
Higher Education ◽  
Young People ◽  
Secondary School ◽  
University Students ◽  
20Th Century ◽  
Russian Empire ◽  
Student Enrolment ◽  
The Russian Empire ◽  
The Given

The article looks at the enrolment requirements of Universities in Europe and the Russian Empire in the given period of time. The state’s attitude is tracked towards different categories of secondary school graduates who wanted to become University students. In this context, the opportunities of getting higher education for young people of Latvia are analysed. The article describes the changes in student enrolment in universities of Latvia and other countries in the 20th century.

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