scholarly journals Modelling and forecasting the spread tendency of the COVID-19 in China

2020 ◽  
Author(s):  
Deshun Sun ◽  
Li Duan ◽  
Jianyi Xiong ◽  
Daping Wang
Keyword(s):  
Mathematical Model ◽  
Removal Rate ◽  
High Accuracy ◽  
Error Rates ◽  
Peak Time ◽  
Model Data ◽  
Key Factors ◽  
Effective Strategies ◽  
Forecasting Error ◽  
Modelling And Forecasting

Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. Parameters of our model were estimated based on collected data that issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed is 99.8%. The average forecasting error rates of the infected and the removed are 0.78% and 0.75%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.

scholarly journals Modeling and forecasting the spread tendency of the COVID-19 in China

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Deshun Sun ◽  
Li Duan ◽  
Jianyi Xiong ◽  
Daping Wang
Keyword(s):  
Mathematical Model ◽  
Removal Rate ◽  
High Accuracy ◽  
Error Rates ◽  
Peak Time ◽  
Model Data ◽  
Key Factors ◽  
Effective Strategies ◽  
Forecasting Error ◽  
Modeling And Forecasting

Abstract To forecast the spread tendency of the COVID-19 in China and provide effective strategies to prevent the disease, an improved SEIR model was established. The parameters of our model were estimated based on collected data that were issued by the National Health Commission of China (NHCC) from January 10 to March 3. The model was used to forecast the spread tendency of the disease. The key factors influencing the epidemic were explored through modulation of the parameters, including the removal rate, the average number of the infected contacting the susceptible per day and the average number of the exposed contacting the susceptible per day. The correlation of the infected is 99.9% between established model data in this study and issued data by NHCC from January 10 to February 15. The correlation of the removed, the death and the cured are 99.8%, 99.8% and 99.6%, respectively. The average forecasting error rates of the infected, the removed, the death and the cured are 0.78%, 0.75%, 0.35% and 0.83%, respectively, from February 16 to March 3. The peak time of the epidemic forecast by our established model coincided with the issued data by NHCC. Therefore, our study established a mathematical model with high accuracy. The aforementioned parameters significantly affected the trend of the epidemic, suggesting that the exposed and the infected population should be strictly isolated. If the removal rate increases to 0.12, the epidemic will come to an end on May 25. In conclusion, the proposed mathematical model accurately forecast the spread tendency of COVID-19 in China and the model can be applied for other countries with appropriate modifications.

scholarly journals Simulation of the laser-material interaction of ultrashort pulse laser processing of silicon nitride workpieces and the key factors in the ablation process

2021 ◽  
Author(s):  
Babak Soltani ◽  
Faramarz Hojati ◽  
Amir Daneshi ◽  
Bahman Azarhoushang
Keyword(s):  
Mathematical Model ◽  
Laser Ablation ◽  
Pulse Laser ◽  
Ultrashort Pulse ◽  
Laser Processing ◽  
Laser Power ◽  
Removal Rate ◽  
Ultrashort Pulse Laser ◽  
Laser Material ◽  
Material Interaction

AbstractUnderstanding the laser ablation mechanism is highly essential to find the effect of different laser parameters on the quality of the laser ablation. A mathematical model was developed in the current investigation to calculate the material removal rate and ablation depth. Laser cuts were created on the workpiece with different laser scan speeds from 1 to 10 mm s−1 by an ultrashort pulse laser with a wavelength of about 1000 nm. The calculated depths of laser cuts were validated via practical experiments. The variation of the laser power intensity on the workpiece’s surface during laser radiation was also calculated. The mathematical model has determined the laser-material interaction mechanism for different laser intensities. The practical sublimation temperature and ablated material temperature during laser processing are other data that the model calculates. The results show that in laser power intensities (IL) higher than 1.5 × 109 W cm−2, the laser-material interaction is multiphoton ionisation with no effects of thermal reaction, while in lower values of IL, there are effects of thermal damages and HAZ adjacent to the laser cut. The angle of incidence is an essential factor in altering incident IL on the surface of the workpiece during laser processing, which changes with increasing depth of the laser cut.

scholarly journals Generation of Alternative Battery Allocation Proposals in Distribution Systems by the Optimization of Different Economic Metrics within a Mathematical Model

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1726
Author(s):  
Norberto Martinez ◽  
Alejandra Tabares ◽  
John F. Franco
Keyword(s):  
Mathematical Model ◽  
Distribution Systems ◽  
Net Present Value ◽  
Test System ◽  
Peak Time ◽  
Voltage Profile ◽  
Peak Reduction ◽  
Stochastic Variation ◽  
Peak Shaving ◽  
Technical Operation

Battery systems bring technical and economic advantages to electrical distribution systems (EDSs), as they conveniently store the surplus of cheap renewable generation for use at a more convenient time and contribute to peak shaving. Due to the high cost of batteries, technical and economic studies are needed to evaluate their correct allocation within the EDS. To contribute to this analysis, this paper proposes a stochastic mathematical model for the optimal battery allocation (OBA), which can be guided by the optimization of two different economic metrics: net present value (NPV) and internal rate of return (IRR). The effects of the OBA in the EDS are evaluated considering the stochastic variation of photovoltaic generation and load. Tests with the 33-node IEEE test system indicate that OBA results in voltage profile improvement (~1% at peak time), peak reduction (31.17%), increased photovoltaic hosting capacity (18.8%), and cost reduction (3.06%). Furthermore, it was found that the IRR metric leads to a different solution compared to the traditional NPV optimization due to its inherent consideration of the relation between cash flow and investment. Thus, both NPV and IRR-based allocation alternatives can be used by the decision maker to improve economic and technical operation of the EDS.

New Key Factors Discovery to Enhance Dengue Fever Forecasting Model

2014 ◽  
Vol 931-932 ◽  
pp. 1457-1461 ◽  
Author(s):  
Phatsavee Ongruk ◽  
Padet Siriyasatien ◽  
Kraisak Kesorn
Keyword(s):  
Wind Speed ◽  
Dengue Fever ◽  
Forecast Model ◽  
Key Factors ◽  
Dengue Virus Infection ◽  
Conventional Model ◽  
Forecasting Error ◽  
Proposed Model ◽  
Basic Set ◽  
Almost All

There are several factors that can be used to predict a dengue fever outbreak. Almost all existing research approaches, however, usually exploit the use of a basic set of core attributes to forecast an outbreak, e.g. temperature, humidity, wind speed, and rainfall. In contrast, this research identifies new attributes to improve the prediction accuracy of the outbreak. The experimental results are analyzed using a correlation analysis and demonstrate that the density of dengue virus infection rate in female mosquitoes and seasons have strong correlation with a dengue fever outbreak. In addition, the research constructs a forecast model using Poisson regression analysis. The result shows the proposed model obtains significantly low forecasting error rate when compared it against the conventional model using only temperature, humidity, wind speed, and rainfall parameters.

Marketing Fraud: An Approach for Differentiating Multilevel Marketing from Pyramid Schemes

2002 ◽  
Vol 21 (1) ◽  
pp. 139-151 ◽  
Author(s):  
Peter J. Vander Nat ◽  
William W. Keep
Keyword(s):  
Mathematical Model ◽  
Distribution Channel ◽  
Specific Form ◽  
The Internet ◽  
Key Factors ◽  
Direct Selling ◽  
Multilevel Marketing ◽  
International Growth ◽  
Pyramid Scheme ◽  
Pyramid Schemes

A specific form of direct selling, multilevel marketing (MLM), experienced significant international growth during the 1990s, facilitated in part by the development of the Internet. A corresponding increase in the investigation and prosecution of illegal pyramid schemes occurred during the same period. These parallel activities led to increased uncertainty among marketing managers who used or wished to use the MLM approach. The authors examine similarities between the multilevel approach to marketing and activities associated with illegal pyramid schemes. A mathematical model is used to differentiate between the two on the basis of previous pyramid scheme cases and current U.S. law. The results of the model suggest key factors that marketers interested in MLM will need to consider when developing this type of distribution channel.

Design of Temperature Monitoring System Based on MSP430

2011 ◽  
Vol 301-303 ◽  
pp. 1162-1165
Author(s):  
Fei Hu ◽  
Wen Qing Yin ◽  
Cai Rong Chen
Keyword(s):  
Monitoring System ◽  
Simple Structure ◽  
High Accuracy ◽  
Temperature Monitoring ◽  
Low Power Consumption ◽  
Key Factors ◽  
Process Data ◽  
Long Distance ◽  
Fast Acquisition ◽  
Digital Temperature Sensor

The Greenhouse Temperature Is one of the Key Factors for Controlling the Growth of Crops. Traditional Methods of Temperature Monitoring Can Not Meet the Modern Greenhouse Requirements of High Accuracy, Fast Acquisition and Response. a Greenhouse Temperature Monitoring System Based on MSP430 Was Designed. this System Uses Digital Temperature Sensor DS18B20 to Measure Temperature, MSP430 to Process Data and Transmit Data to the Host Computer through RS485 Bus, Realizing the Real-Time Detection and Long-Distance Transmission of Greenhouse Temperature. this System Has the Features of Simple Structure, Low Power Consumption, Stability and Strong Portability Etc.

Robotic chemotherapy compounding: A multicenter productivity approach

2021 ◽  
pp. 107815522199284
Author(s):  
Ana C Riestra ◽  
Carmen López-Cabezas ◽  
Marion Jobard ◽  
Mertxe Campo ◽  
María J Tamés ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Correlation Analysis ◽  
Hospital Pharmacy ◽  
Multiple Regression Model ◽  
Key Factors ◽  
Independent Variables ◽  
Specific Factors ◽  
Automated Process ◽  
Productivity Indicators ◽  
The Mathematical Model

Introduction The aim of this study is to compare productivity of the KIRO Oncology compounding robot in three hospital pharmacy departments and identify the key factors to predict and optimize automatic compounding time. Methods The study was conducted in three hospitals. Each hospital compounding workload and workflow were analyzed. Data from the robotic compounding cycles from August 2017 to July 2018 were retrospectively obtained. Nine cycle specific parameters and five productivity indicators were analysed in each site. One-to-one differences between hospitals were evaluated. Next, a correlation analysis between cycle specific factors and productivity indicators was conducted; the factors presenting a highest correlation to automatic compounding time were used to develop a multiple regression model (afterwards validated) to predict the automatic compounding time. Results A total of 2795 cycles (16367 preparations) were analysed. Automatic compounding time showed a relevant positive correlation (ǀrs|>0.40) with the number of preparations, number of vials and total volume per cycle. Therefore, these cycle specific parameters were chosen as independent variables for the mathematical model. Considering cycles lasting 40 minutes or less, predictability of the model was high for all three hospitals (R2:0.81; 0.79; 0.72). Conclusion Workflow differences have a remarkable incidence in the global productivity of the automated process. Total volume dosed for all preparations in a cycle is one of the variables with greater influence in automatic compounding time. Algorithms to predict automatic compounding time can be useful to help users in order to plan the cycles launched in KIRO Oncology.

KEY FACTORS FOR REDUCING LIVE POULTRY LOSSES DURING TRANSPORTATION

2021 ◽  
Vol 113 ◽  
pp. 115-131
Author(s):  
Valery KURGANOV ◽  
Mikhail GRYAZNOV ◽  
Egor TIMOFEEV ◽  
Liliya POLYAKOVA
Keyword(s):  
Mathematical Model ◽  
Factor Analysis ◽  
Economic Impact ◽  
Processing Plant ◽  
Poultry Farm ◽  
Key Factors ◽  
Live Poultry

The results of this study on the loss of live poultry at various stages of delivery from the farm to the processing plant by road are given. A factor analysis of the reasons for the loss of livestock delivered from the farm to the processing plant was carried out. The dependencies of livestock losses on loading delays and the duration of the movement of the loaded poultry farm to the processing plant were established. Methodological recommendations for rationing the number of injuries observed during delivery were developed. The study of losses of live birds during delivery to the processing plant from the density of stocking in shipping boxes was carried out; the economic and mathematical model for optimizing the landing of live birds in shipping boxes was proposed. The calculation of the economic impact of the implementation of the results of the study is given.

Multi-Object Multi-Discipline Probabilistic Design of High-Pressure Turbine Blade-Tip Radial Running Clearance

2013 ◽  
Vol 572 ◽  
pp. 551-554
Author(s):  
Wen Zhong Tang ◽  
Cheng Wei Fei ◽  
Guang Chen Bai
Keyword(s):  
Mathematical Model ◽  
High Pressure ◽  
Optimal Design ◽  
Mechanical System ◽  
High Accuracy ◽  
Probabilistic Design ◽  
High Pressure Turbine ◽  
Surface Method ◽  
Blade Tip ◽  
The Mathematical Model

For the probabilistic design of high-pressure turbine (HPT) blade-tip radial running clearance (BTRRC), a distributed collaborative response surface method (DCRSM) was proposed, and the mathematical model of DCRSM was established. From the BTRRC probabilistic design based on DCRSM, the static clearance δ=1.865 mm is demonstrated to be optimal for the BTRRC design considering aeroengine reliability and efficiency. Meanwhile, DCRSM is proved to be of high accuracy and efficiency in the BTRRC probabilistic design. The present study offers an effective way for HPT BTRRC dynamic probabilistic design and provides also a promising method for the further probabilistic optimal design of complex mechanical system.

A Mathematical Model for Root Canal Preparation Using Endodontic File: Part B

2019 ◽  
Vol 43 ◽  
pp. 20-27
Author(s):  
Pravin R. Lokhande ◽  
S. Balaguru
Keyword(s):  
Mathematical Model ◽  
Root Canal ◽  
Removal Rate ◽  
Plastic Zone Size ◽  
Necessary Condition ◽  
Plastic Behavior ◽  
Root Canal Preparation ◽  
Crack Tip Opening Displacement ◽  
Opening Displacement ◽  
The Mathematical Model

The aim of this article is to develop the mathematical model to describe response of endodontic file in curved root canal during the preparation of root canal using fracture mechanics approach. Any obturation process involves the filling of prepared root canal using bio-compatible materials like gutta-percha. During preparation of infected root canal, substrate, dead tissue and pulp is removed and tapered shape is formed so that any practitioner can fill it effectively. During preparation process of root canal, the canal wall applies locking action and causes resistance to motion of endodontic file, finally resulting into fatigue failure. This article described plastic behavior of endodontic file in curved root canal, mathematical model describing the necessary condition for crack growth in endodontic file, a mathematical model describing plastic zone size for crack on surface of endodontic file, a mathematical model describing crack tip opening displacement for crack on surface of endodontic file and mathematical model for pure-combined torsion and bending consideration for design of endodontic file. The mathematical model described is helpful for the Endodontic experts, researchers, design engineers. However the applicability of the described mathematical model limited to assumption of study. The gap between root canal to be prepared and endodontic file is zero while preparation. The endodontic file weight, speed of rotation and substrate removal rate is assumed to be constant. The mathematical model for endodontic file discussed above proved to be efficient tool for studying the root canal preparation.

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