scholarly journals Forecasting Model for the Value of Areca Nut’s Export of Thailand

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 1241-1253
Author(s):  
Phanita Phakdi
Keyword(s):  
Exponential Growth ◽  
International Market ◽  
Agricultural Product ◽  
Forecasting Model ◽  
Accurate Information ◽  
Areca Nut ◽  
Export Volume ◽  
Efficiency And Effectiveness ◽  
Exponential Growth Model ◽  
Nut Production

Having accurate information about the agricultural situation is very important. The predicting trends of agricultural product will allow to make right decision in economy nowadays. The aims of the paper are to demonstrate the trend in areca nut export in Thailand and import in India to specific period and to plan our strategy and policies accordingly to promote areca nut production and export. With this meaning, a study on areca nut export in Thailand and import and production in India from 2013 to 2020 was conducted. The result found that Exponential Growth Model is the most effective for forecasting in the export and import volume of areca nut. The data also was illustrated the trends in 5 years from 2021- 2025. The result revealed that the forecasting trend of export volume of areca nut in Thailand for 2021 – 2025 is linearly decreasing from 3.47610MTs in 2020 to 0.450858MTs in 2025. While, the forecasting trend of import volume of areca nut in India for 2021 – 2025 is linear increasing gradually, from35.5783 MTs in 2020 to 37.2886 MTs in 2025. Areca nut should be considered as an economics crop significantly of Thailand in future for export of Thailand because there are needs in the international market and price still be reasonable. Driving and implementing sustainable agriculture should focus on efficiency and effectiveness truly.

An Estimation of Endogenous Formaldehyde Exposure due to Consumption of Indonesian Opah Fish (Lampris guttatus) in Three Major Export Destination Countries

2019 ◽  
Vol 14 (1) ◽  
pp. 1 ◽  
Author(s):  
Umi Anissah ◽  
Ajeng Kurniasari Putri ◽  
Giri Rohmad Barokah
Keyword(s):  
Risk Assessment ◽  
Health Risks ◽  
Health Problem ◽  
International Market ◽  
Formaldehyde Content ◽  
Export Volume ◽  
Formaldehyde Exposure ◽  
Export Destination ◽  
Export Product ◽  
Over Time

The demand for Indonesian opah fish as an export product is increasing in the international market. Three countries (Malaysia, Mauritius, and Taiwan) recorded as the leading export destination of Indonesian opah fish. However, as the fish kept in a frozen state during export transportation, the endogenous formaldehyde may increase over time. This research presented the health risk assessment of population in the leading export destination countries that consumed opah fish from Indonesia. The study aimed to reveal the most potential export destination country that may accept an increasing volume of opah fish supply from Indonesia. The potency was determined from current export volume, the amount of endogenous formaldehyde content, and fish consumption at each country. The data were calculated with @Risk®7.0 software. The results showed opah fish consumed by Malaysian can be categorized as safe. Increasing the number of opah fish imported by Malaysian as much as six times, 12 times, 18 times, 27 and 36 times relatively does not cause health risks related to the presence of its endogenous formaldehyde. Moreover, opah fish consumed by Taiwanese is also safe, but with increasing the number of consumptions by more than 26 times is suspected to be potentially causing a health problem. However, opah fish consumed in Mauritius was categorized as unsafe and potentially caused health risks. Based on these results, Indonesia may consider to increase the opah fish export to Malaysia and Taiwan in the future.

scholarly journals Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hiroaki Murayama ◽  
Taishi Kayano ◽  
Hiroshi Nishiura
Keyword(s):  
Confidence Interval ◽  
Growth Model ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Hypergeometric Distribution ◽  
Actual Number ◽  
Growth Data ◽  
Exponential Growth Model

Abstract Background In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. Methods The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. Results The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. Conclusions The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

scholarly journals Estimated Effect of COVID-19 Lockdown on Skin Tumor Size and Survival: An Exponential Growth Model

2020 ◽  
Vol 111 (8) ◽  
pp. 629-638
Author(s):  
A. Tejera-Vaquerizo ◽  
J. Cañueto ◽  
A. Toll ◽  
J. Santos-Juanes ◽  
A. Jaka ◽  
...  
Keyword(s):  
Growth Model ◽  
Exponential Growth ◽  
Tumor Size ◽  
Skin Tumor ◽  
Exponential Growth Model

scholarly journals Determinants for Contribution of Pineapple Growers for Export Volume in Gampaha District in Sri Lanka

2016 ◽  
Vol 4 (1) ◽  
pp. 69-73
Author(s):  
R. A. D. S. Rupasinghe ◽  
H. A. S. L Jayasinghe ◽  
R. M. P. S Rathnayake ◽  
T. A. P Silva
Keyword(s):  
Sri Lanka ◽  
Export Performance ◽  
Export Price ◽  
Export Market ◽  
Agricultural Product ◽  
Local Market ◽  
Domestic Price ◽  
Generalized Model ◽  
Wide Range ◽  
Export Volume

Pineapple is the third largest agricultural product after tea and coconut, which has a demand in export market. Although the nature has blessed with an ideal climate for growing wide range of delicious fruits including pineapple, Sri Lanka is not in a position to meet the growing demand. Therefore, that is very important to study about the export performance of fresh pineapple in Sri Lankan context. The general objective of this study was to identify the determinants of contribution of pineapple growers for export volume in Gampaha district. A structured questionnaire based survey was carried out to collect the data from random sample of 130 pineapple growers in Dompe and Diulapitiya DS divisions in Gampaha district. The result of Tobit model revealed that the contribution of pineapple growers for exports of pineapple was significantly determined by the age of grower, experience of grower, pineapple cultivated land extent, amount supply for local market, domestic price and export price. In the study of specific objectives, there was an upward trend from 1990 to 2004 and trend was declined from 2004 to 2012 with some fluctuations. The reason was that the export of preserved pineapple has shown a significant improvement within last few years and in developing the forecasting model for future forecast and the generalized model for current situation analysis for fresh pineapple exports in Sri Lanka. Vector Autoregressive Model (VAR) was used to develop the forecast model and the generalized model was developed without considering the time factor. The result revealed that the export of fresh pineapple was significantly determined by the average exchange rate and the domestic price.

scholarly journals Models for Predicting Global Plastic Waste

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Yuexing Hao ◽  
Glenn Shafer
Keyword(s):  
Growth Model ◽  
Real World ◽  
Exponential Growth ◽  
Plastic Waste ◽  
The Self ◽  
Scientific Models ◽  
Adaptive Model ◽  
The Real ◽  
Exponential Growth Model ◽  
Self Adaptive

For more than half a century, plastic prod-ucts have been a part of people’s lives. When plastic waste is thrown into nature, it can cause a sequence of dangerous effects. Previous researchers esti-mated that global plastic waste in 2020 will be more than 400 million tons. To reduce plastic waste, they built scientific models to analyze the sources of plas-tic and provided solutions for regenerating these plastic wastes. However, their models are static and inaccurate, which may cause some false predictions.In this paper, we first observe the distribution of the real-world plastic waste data. Then, we build simple exponential growth model and logistics model to match these data. By testing different models on our plots, we discover that the SELF-ADAPTIVE MODEL is the best to describe and correctly predict our future plastic waste production, as this model combines the benefits of SIMPLE EXPONENTIAL GROWTH MODEL and the LOGISTIC MODEL. The self-Adaptive model has the potential to minimize the error rate and make the predictions more accurate. Based on this model, we can develop more accurate and informative solu-tions for the real-world plastic problems.

scholarly journals COVID-19 Misinformation Spread in Eight Countries: Exponential Growth Modeling Study

10.2196/24425 ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. e24425
Author(s):  
Elaine Okanyene Nsoesie ◽  
Nina Cesare ◽  
Martin Müller ◽  
Al Ozonoff
Keyword(s):  
Infectious Disease ◽  
Exponential Growth ◽  
Doubling Time ◽  
Growth Models ◽  
Application Programming Interface ◽  
Public Understanding ◽  
World Health ◽  
Exponential Growth Model ◽  
Health Organization ◽  
Disease Epidemics

Background The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available. Objective We aim to characterize and compare the start, peak, and doubling time of COVID-19 misinformation topics across 8 countries using an exponential growth model usually employed to study infectious disease epidemics. Methods COVID-19 misinformation topics were selected from the World Health Organization Mythbusters website. Data representing exposure was obtained from the Google Trends application programming interface for 8 English-speaking countries. Exponential growth models were used in modeling trends for each country. Results Searches for “coronavirus AND 5G” started at different times but peaked in the same week for 6 countries. Searches for 5G also had the shortest doubling time across all misinformation topics, with the shortest time in Nigeria and South Africa (approximately 4-5 days). Searches for “coronavirus AND ginger” started at the same time (the week of January 19, 2020) for several countries, but peaks were incongruent, and searches did not always grow exponentially after the initial week. Searches for “coronavirus AND sun” had different start times across countries but peaked at the same time for multiple countries. Conclusions Patterns in the start, peak, and doubling time for “coronavirus AND 5G” were different from the other misinformation topics and were mostly consistent across countries assessed, which might be attributable to a lack of public understanding of 5G technology. Understanding the spread of misinformation, similarities and differences across different contexts can help in the development of appropriate interventions for limiting its impact similar to how we address infectious disease epidemics. Furthermore, the rapid proliferation of misinformation that discourages adherence to public health interventions could be predictive of future increases in disease cases.

scholarly journals COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth

2020 ◽  
Author(s):  
Yi Li ◽  
Meng Liang ◽  
Xianhong Yin ◽  
Xiaoyu Liu ◽  
Meng Hao ◽  
...  
Keyword(s):  
Exponential Growth ◽  
Added Value ◽  
China National Knowledge Infrastructure ◽  
Real Situation ◽  
Knowledge Infrastructure ◽  
Global Trend ◽  
Simple Regression Model ◽  
Exponential Growth Model ◽  
Data Points ◽  
Novel Coronavirus

SummaryBackgroundIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. We aimed to build a mathematical model to capture the global trend of epidemics outside China.MethodsIn this retrospective, outside-China diagnosis number reported from Jan 21 to Feb 28, 2020 was downloaded from WHO website. We develop a simple regression model on these numbers: where Nt is the total diagnosed patient till the ith day, t=1 at Feb 1.FindingsBased on this model, we estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.Research in contextEvidence before this studyIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. Now there are 4,691 patients across 51 countries and territories outside China. We searched PubMed and the China National Knowledge Infrastructure database for articles published up to Feb 28, 2020, using the keywords “COVID”, “novel coronavirus”, “2019-nCoV” or “2019 novel coronavirus”. No published work about the global trend of epidemics outside China could be identified.Added value of this studyWe built a simple “log-plus” linear model to capture the global trend of epidemics outside China. We estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.Implications of all the available evidenceWith the limited number of data points and the complexity of the real situation, a straightforward model is expected to work better. Our model suggests that the COVID-19 disease follows an approximate exponential growth model stably at the very beginning. We predict that the number of confirmed patients outside China will increase ten folds in every 19 days without strong intervention by applying our model. Powerful actions on public health should be taken to combat this epidemic all over the world.

scholarly journals Predicting the COVID-19 positive cases in India with concern to Lockdown by using Mathematical and Machine Learning based Models

2020 ◽  
Author(s):  
Ajit Kumar Pasayat ◽  
Satya Narayan Pati ◽  
Aashirbad Maharana
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Regression Model ◽  
Growth Model ◽  
Linear Regression Model ◽  
Exponential Growth ◽  
Time Window ◽  
Epidemic Curve ◽  
First Case ◽  
Exponential Growth Model

In this study, we analyze the number of infected positive cases of COVID-19 outbreak with concern to lockdown in India in the time window of February 11th 2020 to Jun 30th 2020. The first case in India was reported in Kerala on January 30th 2020. To break the chain of spreading, Government announced a nationwide lockdown on March 24th 2020, which is increased two times. The Ongoing lockdown 3.0 is over on May 18th, 2020. We derived how the lockdown relaxation is going to impact on containment of the outbreak. Here the Exponential Growth Model has been used to derive the epidemic curve based on the data collected from February 11th 2020, to May 11th 2020, and the Machine Learning based Linear Regression model that gives the epidemic curve to predict the cases with the continuous flow of the lockdown. We estimate that if the lockdown is continuing with more relaxation, then the estimated infected cases reach up to 1.16 crores by June 30th 2020, and the lockdown would persist with current restriction, then the expected predicted infected cases are 5.69 lacs. The Exponential Growth Model and the Linear Regression Model are advantageous to predict the number of affected cases of COVID-19. These models can be used for forecasting in long term intervals. It shows from our result that lockdown with certain restriction has a vital role in preventing the spreading of this epidemic in this current situation.

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