COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learni...COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and deaths.Many researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic actions.Furthermore,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting model.Other research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various countries.Thus,we proposed a prediction and analysis model to predict COVID-19 in Saudi Arabia.The time series dependent face book prophet model is used to t the data and provide future predictions.This study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or weekly.We found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 dataset.In contrast,the proposed model of death cases has a high ability to forecast the COVID-19 dataset.Finally,obtaining more data could empower the model for further validation.展开更多
Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we recons...Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.展开更多
In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in sto...In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in stock returns.Wefind that the three-factor model can explain the common variation in stock returns well.However, it is mis-specifiedfor the Chinese stock market.We demonstrate that the size effect and the book-to-market effect are significant andpersistent over our sample period.Interestingly, the book-to-market effect for China is much stronger than the averageones in mature markets and other emerging markets documented by Fama and French (1998).Moreover, we find noevidence to support the argument that seasonal effects can explain the results of the multifactor model.Last, our mixedobservations on firm-specific fundamentals suggest that the risk-based explanation proposed by Fama and French(1995) cannot shed light on the size and BM effect for China.In view of the features of the Chinese stock market, weinstead argue that China’s size and book-to-market effect may be attributed to syndicate speculators’ manipulation andmispricing caused by irrational investor behavior.展开更多
文摘COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and deaths.Many researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic actions.Furthermore,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting model.Other research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various countries.Thus,we proposed a prediction and analysis model to predict COVID-19 in Saudi Arabia.The time series dependent face book prophet model is used to t the data and provide future predictions.This study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or weekly.We found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 dataset.In contrast,the proposed model of death cases has a high ability to forecast the COVID-19 dataset.Finally,obtaining more data could empower the model for further validation.
基金supported by the DIALOG Program[grant name“Research into Excellence Patterns in Science and Art”]financed by the Ministry of Science and Higher Education in Poland
文摘Purpose: This study aims to present the key systemic changes in the Polish book evaluation model to focus on the publisher list, as inspired by the Norwegian Model. Design/methodology/approach: In this study we reconstruct the framework of the 2010 and 2018 models of book evaluation in Poland within the performance-based research funding system. Findings: For almost 20 years the book evaluation system in Poland has been based on the verification of various technical criteria(e.g. length of the book). The new 2018 model is based on the principle of prestige inheritance(a book is worth as much as its publisher is) and is inspired by the publisher list used in the Norwegian Model. In this paper, we argue that this solution may be a more balanced policy instrument than the previous 2010 model in which neither the quality of the publisher nor the quality of the book played any role in the evaluation.Research limitations: We work from the framework of the 2018 model of book evaluation specified in the law on higher education and science from 20 July 2018, as implementation acts are not available yet. Practical implications: This study may provide a valuable point of reference on how structural reforms in the research evaluation model were implemented on a country level. The results of this study may be interesting to policy makers, stakeholders and researchers focused on science policy. Originality/value: This is the very first study that presents the new framework of the Polish research evaluation model and policy instruments for scholarly book evaluation. We describe what motivated policy makers to change the book evaluation model, and what arguments were explicitly raised to argue for the new solution.
文摘In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in stock returns.Wefind that the three-factor model can explain the common variation in stock returns well.However, it is mis-specifiedfor the Chinese stock market.We demonstrate that the size effect and the book-to-market effect are significant andpersistent over our sample period.Interestingly, the book-to-market effect for China is much stronger than the averageones in mature markets and other emerging markets documented by Fama and French (1998).Moreover, we find noevidence to support the argument that seasonal effects can explain the results of the multifactor model.Last, our mixedobservations on firm-specific fundamentals suggest that the risk-based explanation proposed by Fama and French(1995) cannot shed light on the size and BM effect for China.In view of the features of the Chinese stock market, weinstead argue that China’s size and book-to-market effect may be attributed to syndicate speculators’ manipulation andmispricing caused by irrational investor behavior.
