ULTRA HIGH-SPEED AND LOW-POWER FLEXIBLE ARCHITECTURE USING STATE TRANSITION MATRIX MODEL FOR EPC GEN-2 COMMUNICATION PROTOCOL PROCESSOR

2012 ◽  
Vol 32 (3) ◽  
Author(s):  
Ajay Ogirala ◽  
Vyasa Sai ◽  
Akram Kamrani ◽  
Jayant Rajgopal ◽  
Bryan A. Norman ◽  
...  
Keyword(s):  
Low Power ◽  
Matrix Model ◽  
Transition Matrix ◽  
High Speed ◽  
State Transition ◽  
Communication Protocol ◽  
State Transition Matrix ◽  
Ultra High Speed ◽  
Flexible Architecture

scholarly journals The prediction for development of COVID-19 in global major epidemic areas through empirical trends in China by utilizing state transition matrix model

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhong Zheng ◽  
Ke Wu ◽  
Zhixian Yao ◽  
Xinyi Zheng ◽  
Junhua Zheng ◽  
...  
Keyword(s):  
South Korea ◽  
Matrix Model ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
World Health ◽  
Daily Increment ◽  
The World ◽  
Increment Rate ◽  
Health Organization

Abstract Background Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model. Results The optimistic scenario (non-Hubei model, daily increment rate of − 3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of − 2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of − 1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20 k in South Korea, 209 k in Italy, and 226 k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

scholarly journals The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

2020 ◽  
Author(s):  
Zhong Zheng ◽  
Ke Wu ◽  
Zhixian Yao ◽  
Xinyi Zheng ◽  
Junhua Zheng ◽  
...  
Keyword(s):  
South Korea ◽  
Matrix Model ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
World Health ◽  
Daily Increment ◽  
The World ◽  
Increment Rate ◽  
Health Organization

Abstract Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model. Results: The optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

scholarly journals The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

2020 ◽  
Author(s):  
Zhong Zheng ◽  
Ke Wu ◽  
Zhixian Yao ◽  
Xinyi Zheng ◽  
Junhua Zheng ◽  
...  
Keyword(s):  
South Korea ◽  
Matrix Model ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
World Health ◽  
Daily Increment ◽  
The World ◽  
Increment Rate ◽  
Health Organization

Abstract Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. All data were analyzed through the State Transition Matrix model. Results: the optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

scholarly journals The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

2020 ◽  
Author(s):  
Zhong Zheng ◽  
Ke Wu ◽  
Zhixian Yao ◽  
Junhua Zheng ◽  
Jian Chen
Keyword(s):  
South Korea ◽  
Matrix Model ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
Medical Resources ◽  
Daily Increment ◽  
The World ◽  
Pessimistic Scenario ◽  
Increment Rate

AbstractBackgroundSince pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from Hubei and non-Hubei in China.MethodsWe extracted data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) as the training set to deduce the arrival of the IFP of new cases in Hubei and non-Hubei on subsequent days and the data from Mar 6 to Mar 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death data were collected and analyzed. Using this state transition matrix model, the horizon of the IFP of time (the rate of new increment reaches zero) could be predicted in South Korean, Italy, and Iran. Also, through this model, the global trend of the epidemic will be decoded to allocate international medical resources better and instruct the strategy for quarantine.Resultsthe optimistic scenario (non-Hubei model, daily increment rate of −3.87%), the relative pessimistic scenario (Hubei model, daily increment rate of −2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of −1.50%) were inferred and modeling from data in China. Matching and fitting with these scenarios, the IFP of time in South Korea would be Mar 6-Mar 12, Italy Mar 10-Mar 24, and Iran is Mar 10-Mar 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. There should be room for improvement if these metrics continue to improve. In that case, the IFP will arrive earlier than our estimation. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be higher than predicted above.ConclusionWe can affirm that the end of the burst of the epidemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to manipulate the development of COVID-19.

scholarly journals The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

2020 ◽  
Author(s):  
Zhong Zheng ◽  
Ke Wu ◽  
Zhixian Yao ◽  
Junhua Zheng ◽  
Jian Chen
Keyword(s):  
South Korea ◽  
Matrix Model ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
World Health ◽  
Daily Increment ◽  
The World ◽  
Increment Rate ◽  
Health Organization

Abstract Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to Mar 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. All data were analyzed through the State Transition Matrix model. Results: the optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6-Mar 12, Italy Mar 10-Mar 24, and Iran is Mar 10-Mar 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. There should be room for improvement if these metrics continue to improve. In that case, the IFP will arrive earlier than our estimation. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be higher than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

Electromagnetic characterization of strong-coupled Omega-type bianisotropic metamaterials using the state transition matrix method

2021 ◽  
pp. 1-19
Author(s):  
Ugur Cem Hasar ◽  
Gokhan Ozturk ◽  
Mehmet Ertugul ◽  
Joaquim José Barroso ◽  
Omar M. Ramahi
Keyword(s):  
Matrix Method ◽  
Transition Matrix ◽  
State Transition ◽  
The State ◽  
State Transition Matrix

Numerical Algebra Solution: A New Algorithm for the State Transition Matrix

2017 ◽  
Vol 60 (12) ◽  
pp. 2620-2629 ◽  
Author(s):  
Wenfeng Nie ◽  
Tianhe Xu ◽  
Yujun Du ◽  
Fan Gao ◽  
Guochang Xu
Keyword(s):  
Transition Matrix ◽  
State Transition ◽  
The State ◽  
State Transition Matrix ◽  
Numerical Algebra
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