Official monthly unemployment data is unavailable in China, while intense public interest in unemployment requires timely and accurate information. Using data on web queries from lead search engines in China, Baidu an...Official monthly unemployment data is unavailable in China, while intense public interest in unemployment requires timely and accurate information. Using data on web queries from lead search engines in China, Baidu and Google, I build two indices measuring intensity of online unemployment-related searches. The unemployment-related search indices identify a structural break in the time series between October and November 2008, which corresponds to a turning point indicated by some macroeconomic indicators. The unemployment- related search indices are proven to have significant correlation with Purchasing Managers＇ Employment Indices and a set of macroeconomic indicators that are closely related to changes in unemployment in China. The results of Granger causality analysis show that the unemployment-related search indices can improve predictions of the c indicators. It suggests that unemploy- ment-related searches can potentially provide valuable, timely, and low-cost information for macroeconomic monitoring.展开更多
Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice ...Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice felds using traditional ground surveys is impractical when high cost,time and labour requirements are considered,and the availability of such detailed records is limited.Although satellite remote sensing appears to be a viable solution,conventional segmentation and classification methods with spectral bands are often unable to contrast the distinct characteristics between rice fields and other vegetation classes.To this end,we explored a novel,Google Earth Engine(GEE)based multiindex random forest(RF)classification approach to map rice fields over two decades.Landsat images from 2000 to 2020 of two Sri Lankan rice cultivation districts were extracted from GEE and a multi-index RF classification algorithm was applied to distinguish the rice fields.The results showed above 80%accuracy for both training and validation,when compared against high spatial resolution Google Earth imagery.In essence,multi-index sampling and RF together synergised the compelling classifcation accuracy by effectively capturing vegetation,water(ponding)and soil characteristics unique to the rice felds using a single-click approach.The maps developed in this study were further compared against the MODIS land cover type product(MCD12Q1)and the corresponding superior statistics on rice fields demonstrated the robustness of the proposed approach.Future work seeking effective index combinations is recommended,and this approach can potentially be extended to other crop analyses elsewhere.展开更多
This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers.For decades,information available for the patients and allergologists consisted of pollen counts,whic...This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers.For decades,information available for the patients and allergologists consisted of pollen counts,which are vital but insufficient.New technology paves the way to substantial increase in amount and diversity of the data.This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept,which combines the pollen and pollution information and transforms it into a qualitative risk index.This new index is available in an app(Mobile Airways Sentinel NetworK-air)that was developed in the frame of the European Union grant Impact of Air POLLution on sleep,Asthma and Rhinitis(a project of European Institute of Innovation and Technology-Health).On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions.The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.展开更多
Background:The 2014 Ebola epidemic in West Africa has attracted public interest worldwide,leading to millions of Ebola-related Internet searches being performed during the period of the epidemic.This study aimed to ev...Background:The 2014 Ebola epidemic in West Africa has attracted public interest worldwide,leading to millions of Ebola-related Internet searches being performed during the period of the epidemic.This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred.The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola.Methods:Google Trends(GT)was used to explore Internet activity related to Ebola.The study period was from 29 December 2013 to 14 June 2015.Pearson’s correlation was performed to correlate Ebola-related relative search volumes(RSVs)with the number of weekly and overall Ebola cases.Multivariate regression was performed using Ebola-related RSV as a dependent variable,and the overall number of Ebola cases and the Human Development Index were used as predictor variables.Results:The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic.The queries varied in the different countries.Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted,in relation to the different flux volumes and different time courses.In the affected African countries,web query search volumes were mostly concentrated in the capital areas.However,in Western countries,web queries were uniformly distributed over the national territory.In terms of the three countries mainly affected by the Ebola epidemic,the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate.The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high.Conclusion:Google Trends showed a coarse-grained nature,strongly correlating with global epidemiological data,but was weaker at country展开更多
The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factor...The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factors or sentiments and use out-of-date data sources.In this study,a robust cryptocurrency valuation method is developed using up-to-date datasets.Using various panel regression models and moving-window regression tests,the impacts of fundamental factors and sentiments in the valuation of cryptocurrencies are explored with data covering from January 1,2009 to April 30,2023.The research shows the importance of sentiments and suggests that the fear and greed index can indicate when to make a cryptocurrency investment,while Google search interest in cryptocurrency is crucial when choosing the appropriate type of cryptocurrency.Moreover,consensus mechanism and initial coin offering have significant effects on cryptocurrencies without stablecoins,while their impacts on cryptocurrencies with stablecoins are insignificant.Other fundamental factors,such as the type of supply and the presence of smart contracts,do not have a significant influence on cryptocurrency.Findings from this study can enhance cryptocurrency marketisation and provide insightful guidance for investors,portfolio managers,and policymakers in assessing the utility level of each cryptocurrency.展开更多
基金The Project is sponsored by the Scientific Research Foundation for the Retttmed Overseas Chinese Scholars, Ministry of Education of PRC, and supported by Beijing Natural Science Foundation （No. 9144025）. I would like to thank the reviewers who provide insightful comments and suggestions for improving this paper. I also would like to thank the editors who proofread and edit the paper. Without the supportive work of the reviewers and editors, this paper would not have been possible.
文摘Official monthly unemployment data is unavailable in China, while intense public interest in unemployment requires timely and accurate information. Using data on web queries from lead search engines in China, Baidu and Google, I build two indices measuring intensity of online unemployment-related searches. The unemployment-related search indices identify a structural break in the time series between October and November 2008, which corresponds to a turning point indicated by some macroeconomic indicators. The unemployment- related search indices are proven to have significant correlation with Purchasing Managers＇ Employment Indices and a set of macroeconomic indicators that are closely related to changes in unemployment in China. The results of Granger causality analysis show that the unemployment-related search indices can improve predictions of the c indicators. It suggests that unemploy- ment-related searches can potentially provide valuable, timely, and low-cost information for macroeconomic monitoring.
文摘Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice felds using traditional ground surveys is impractical when high cost,time and labour requirements are considered,and the availability of such detailed records is limited.Although satellite remote sensing appears to be a viable solution,conventional segmentation and classification methods with spectral bands are often unable to contrast the distinct characteristics between rice fields and other vegetation classes.To this end,we explored a novel,Google Earth Engine(GEE)based multiindex random forest(RF)classification approach to map rice fields over two decades.Landsat images from 2000 to 2020 of two Sri Lankan rice cultivation districts were extracted from GEE and a multi-index RF classification algorithm was applied to distinguish the rice fields.The results showed above 80%accuracy for both training and validation,when compared against high spatial resolution Google Earth imagery.In essence,multi-index sampling and RF together synergised the compelling classifcation accuracy by effectively capturing vegetation,water(ponding)and soil characteristics unique to the rice felds using a single-click approach.The maps developed in this study were further compared against the MODIS land cover type product(MCD12Q1)and the corresponding superior statistics on rice fields demonstrated the robustness of the proposed approach.Future work seeking effective index combinations is recommended,and this approach can potentially be extended to other crop analyses elsewhere.
文摘This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers.For decades,information available for the patients and allergologists consisted of pollen counts,which are vital but insufficient.New technology paves the way to substantial increase in amount and diversity of the data.This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept,which combines the pollen and pollution information and transforms it into a qualitative risk index.This new index is available in an app(Mobile Airways Sentinel NetworK-air)that was developed in the frame of the European Union grant Impact of Air POLLution on sleep,Asthma and Rhinitis(a project of European Institute of Innovation and Technology-Health).On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions.The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.
文摘Background:The 2014 Ebola epidemic in West Africa has attracted public interest worldwide,leading to millions of Ebola-related Internet searches being performed during the period of the epidemic.This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred.The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola.Methods:Google Trends(GT)was used to explore Internet activity related to Ebola.The study period was from 29 December 2013 to 14 June 2015.Pearson’s correlation was performed to correlate Ebola-related relative search volumes(RSVs)with the number of weekly and overall Ebola cases.Multivariate regression was performed using Ebola-related RSV as a dependent variable,and the overall number of Ebola cases and the Human Development Index were used as predictor variables.Results:The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic.The queries varied in the different countries.Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted,in relation to the different flux volumes and different time courses.In the affected African countries,web query search volumes were mostly concentrated in the capital areas.However,in Western countries,web queries were uniformly distributed over the national territory.In terms of the three countries mainly affected by the Ebola epidemic,the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate.The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high.Conclusion:Google Trends showed a coarse-grained nature,strongly correlating with global epidemiological data,but was weaker at country
文摘The valuation of cryptocurrencies is important given the increasing significance of this potential asset class.However,most state-of-the-art cryptocurrency valuation methods only focus on one of the fundamental factors or sentiments and use out-of-date data sources.In this study,a robust cryptocurrency valuation method is developed using up-to-date datasets.Using various panel regression models and moving-window regression tests,the impacts of fundamental factors and sentiments in the valuation of cryptocurrencies are explored with data covering from January 1,2009 to April 30,2023.The research shows the importance of sentiments and suggests that the fear and greed index can indicate when to make a cryptocurrency investment,while Google search interest in cryptocurrency is crucial when choosing the appropriate type of cryptocurrency.Moreover,consensus mechanism and initial coin offering have significant effects on cryptocurrencies without stablecoins,while their impacts on cryptocurrencies with stablecoins are insignificant.Other fundamental factors,such as the type of supply and the presence of smart contracts,do not have a significant influence on cryptocurrency.Findings from this study can enhance cryptocurrency marketisation and provide insightful guidance for investors,portfolio managers,and policymakers in assessing the utility level of each cryptocurrency.
