Demand response transactions between electric con-sumers,load aggregators,and the distribution network manag-er based on the"combination of price and incentive"are feasi-ble and efficient.However,the incenti...Demand response transactions between electric con-sumers,load aggregators,and the distribution network manag-er based on the"combination of price and incentive"are feasi-ble and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggrega-tors from taking illegitimate interests through deceptive behav-iors in the demand response transactions.Firstly,a demand re-sponse transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and val-idate the proposed method.展开更多
Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production,increasing network hashrates and electricity consumption.Growth in network hashrates has furth...Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production,increasing network hashrates and electricity consumption.Growth in network hashrates has further crowded out small cryptocurrency investors owing to the heightened costs of mining hardware and electricity.These changes prompt cryptocurrency miners to become new investors,leading to cryptocurrency price increases.The potential bidirectional relationship between cryptocurrency price and electricity consumption remains unidentified.Hence,this research thus utilizes July 312015–July 122019 data from 13 cryptocurrencies to investigate the short-and long-run causal effects between cryptocurrency transaction and electricity consumption.Particularly,we consider structural breaks induced by external shocks through stationary analysis and comovement relationships.Over the examined time period,we found that the series of cryptocurrency transaction and electricity consumption gradually returns to mean convergence after undergoing daily shocks,with prices trending together with hashrates.Transaction fluctuations exert both a temporary effect and permanent influence on electricity consumption.Therefore,owing to the computational power deployed to wherever high profit is found,transactions are vital determinants of electricity consumption.展开更多
Back Ground: Risky sexual behavior among orphans and vulnerable children and its associated physical, psychological and social consequences is becoming a major public health concern globally. Objectives: To assess the...Back Ground: Risky sexual behavior among orphans and vulnerable children and its associated physical, psychological and social consequences is becoming a major public health concern globally. Objectives: To assess the prevalence of risky sexual behavior and its determinants among orphan and vulnerable children in Addis Ababa. Methodology: A community based cross sectional study was conducted on three support and care giving organizations for orphans and vulnerable children in Addis Ababa, Ethiopia from March to June 2014. A total of 422 orphan and vulnerable children were selected using systematic sampling. Data were collected using pre tested self-administered questionnaire. Logistic regression was used to analyze the data. Result: A total of 407 (96.4%) respondents participated in this study. Among them 112 (27.5%) had sexual intercourse in their life time, of these 50 (44.6%) started sex before the age of 15, 94 (83.9%) had forced sex, 84 (75.0%) had multiple sexual partners, only 16 (14.3%) used condom the first time they had sex and 96 (85.7%) participated in transactional sex. Females were about 3.25 (2.67 - 7.3) times more likely to engage in risky sexual behavior than male respondents, double orphans had 4.32 (2.45 - 9.54) odds of risky sexual behavior compared to their counterparts. Those respondents who had knowledge of HIV transmission and prevention were less likely to be involved in risky sexual behavior 0.58 (0.41 - 0.93). Conclusion: Orphan and vulnerable children are at a higher likelihood of risky sexual behavior. Intervention targeted at multilevel such as orphan survival training, assertive communication skills, sexuality education and education about HIV risk perception, physical, psychological and human right protection, social support, and economic access for basic needs need to be given consideration.展开更多
Taking Luochuan County of Shaanxi Province as an example,the factors that affect farmers' behaviors on participating in insurance is analyzed and evaluated according to the questionnaires and by selecting the inde...Taking Luochuan County of Shaanxi Province as an example,the factors that affect farmers' behaviors on participating in insurance is analyzed and evaluated according to the questionnaires and by selecting the indexes covering household features,agricultural production risks,the attitudes of rural households towards risks and the transaction cost of participating insurance and by using Logistic regression model.The results show that comparing with insurance company,the government has larger influence on farmers' behaviors on participating insurance;the premium of agricultural insurance does not obstruct farmers' participation in insurance;the bad-handled relations between the government and insurance company have bad effects on the development of local agricultural insurance.In order to promote farmers to participate in agricultural insurance,the relevant countermeasures are put forward:firstly,increasing the investment on rural education and improving cultural level of farmers;secondly,intensifying the promotion on agricultural insurance;thirdly,reasonably planning the duties and rights of the government and the insurance company;fourthly,vigorously encouraging the farmers to conduct scale production of apple and form the scale economy.展开更多
With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considere...With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considered,namely the anonymous transaction scenario and real-name transaction scenario.First,starting from the interaction network of transactional groups,the degree distribution,density,and modularity of normal and money laundering transactions in two transaction scenarios are compared and analyzed,so as to clarify the characteristics and paths of money laundering transactions.Then,according to the two typical application scenarios,different transaction datasets are selected,and different models are used to train the models on the recognition of money laundering behaviors in the two datasets.Among them,in the anonymous transaction scenario,the graph convolutional neural network is used to identify the spatial structure,the recurrent neural network is fused to obtain the dynamic pattern,and the model ChebNet-GRU is constructed.The constructed ChebNet-GRU model has the best effect in the recognition of money laundering behavior,with a precision of 94.3%,a recall of 59.5%,an F1 score of 72.9%,and a microaverage F1 score of 97.1%.While in the real-name transaction scenario,the traditional machine learning method is far better than the deep learning method,and the micro-average F1 score of the random forest and XGBoost models both reach 99.9%,which can effectively identify money laundering in currency transactions.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.B230201048).
文摘Demand response transactions between electric con-sumers,load aggregators,and the distribution network manag-er based on the"combination of price and incentive"are feasi-ble and efficient.However,the incentive payment of demand re-sponse is quantified based on private information,which gives the electric consumers and load aggregators the possibility of defrauding illegitimate interests by declaring false information.This paper proposes a method based on Vickrey-Clark-Groves(VCG)theory to prevent electric consumers and load aggrega-tors from taking illegitimate interests through deceptive behav-iors in the demand response transactions.Firstly,a demand re-sponse transaction framework with the price-and-incentive com-bined mode is established to illustrate the deceptive behaviors in the demand response transactions.Then,the idea for eradi-cating deceptive behaviors based on VCG theory is given,and a detailed VCG-based mathematical model is constructed follow-ing the demand response transaction framework.Further,the proofs of incentive compatibility,individual rationality,cost minimization,and budget balance of the proposed VCG-based method are given.Finally,a modified IEEE 33-node system and a modified IEEE 123-node system are used to illustrate and val-idate the proposed method.
基金funding agencies in the public,commercial,or notfor-profit sectors.
文摘Rapidly increasing cryptocurrency prices have encouraged cryptocurrency miners to participate in cryptocurrency production,increasing network hashrates and electricity consumption.Growth in network hashrates has further crowded out small cryptocurrency investors owing to the heightened costs of mining hardware and electricity.These changes prompt cryptocurrency miners to become new investors,leading to cryptocurrency price increases.The potential bidirectional relationship between cryptocurrency price and electricity consumption remains unidentified.Hence,this research thus utilizes July 312015–July 122019 data from 13 cryptocurrencies to investigate the short-and long-run causal effects between cryptocurrency transaction and electricity consumption.Particularly,we consider structural breaks induced by external shocks through stationary analysis and comovement relationships.Over the examined time period,we found that the series of cryptocurrency transaction and electricity consumption gradually returns to mean convergence after undergoing daily shocks,with prices trending together with hashrates.Transaction fluctuations exert both a temporary effect and permanent influence on electricity consumption.Therefore,owing to the computational power deployed to wherever high profit is found,transactions are vital determinants of electricity consumption.
文摘Back Ground: Risky sexual behavior among orphans and vulnerable children and its associated physical, psychological and social consequences is becoming a major public health concern globally. Objectives: To assess the prevalence of risky sexual behavior and its determinants among orphan and vulnerable children in Addis Ababa. Methodology: A community based cross sectional study was conducted on three support and care giving organizations for orphans and vulnerable children in Addis Ababa, Ethiopia from March to June 2014. A total of 422 orphan and vulnerable children were selected using systematic sampling. Data were collected using pre tested self-administered questionnaire. Logistic regression was used to analyze the data. Result: A total of 407 (96.4%) respondents participated in this study. Among them 112 (27.5%) had sexual intercourse in their life time, of these 50 (44.6%) started sex before the age of 15, 94 (83.9%) had forced sex, 84 (75.0%) had multiple sexual partners, only 16 (14.3%) used condom the first time they had sex and 96 (85.7%) participated in transactional sex. Females were about 3.25 (2.67 - 7.3) times more likely to engage in risky sexual behavior than male respondents, double orphans had 4.32 (2.45 - 9.54) odds of risky sexual behavior compared to their counterparts. Those respondents who had knowledge of HIV transmission and prevention were less likely to be involved in risky sexual behavior 0.58 (0.41 - 0.93). Conclusion: Orphan and vulnerable children are at a higher likelihood of risky sexual behavior. Intervention targeted at multilevel such as orphan survival training, assertive communication skills, sexuality education and education about HIV risk perception, physical, psychological and human right protection, social support, and economic access for basic needs need to be given consideration.
基金Supported by Shaanxi Social Science Fund(09E045)
文摘Taking Luochuan County of Shaanxi Province as an example,the factors that affect farmers' behaviors on participating in insurance is analyzed and evaluated according to the questionnaires and by selecting the indexes covering household features,agricultural production risks,the attitudes of rural households towards risks and the transaction cost of participating insurance and by using Logistic regression model.The results show that comparing with insurance company,the government has larger influence on farmers' behaviors on participating insurance;the premium of agricultural insurance does not obstruct farmers' participation in insurance;the bad-handled relations between the government and insurance company have bad effects on the development of local agricultural insurance.In order to promote farmers to participate in agricultural insurance,the relevant countermeasures are put forward:firstly,increasing the investment on rural education and improving cultural level of farmers;secondly,intensifying the promotion on agricultural insurance;thirdly,reasonably planning the duties and rights of the government and the insurance company;fourthly,vigorously encouraging the farmers to conduct scale production of apple and form the scale economy.
基金supported by the National Science Foundation of China(No.61602536)the Emerging Interdisciplinary Project of Central University of Finance and Economics(CUFE),and Financial Sustainable Development Research Team.
文摘With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considered,namely the anonymous transaction scenario and real-name transaction scenario.First,starting from the interaction network of transactional groups,the degree distribution,density,and modularity of normal and money laundering transactions in two transaction scenarios are compared and analyzed,so as to clarify the characteristics and paths of money laundering transactions.Then,according to the two typical application scenarios,different transaction datasets are selected,and different models are used to train the models on the recognition of money laundering behaviors in the two datasets.Among them,in the anonymous transaction scenario,the graph convolutional neural network is used to identify the spatial structure,the recurrent neural network is fused to obtain the dynamic pattern,and the model ChebNet-GRU is constructed.The constructed ChebNet-GRU model has the best effect in the recognition of money laundering behavior,with a precision of 94.3%,a recall of 59.5%,an F1 score of 72.9%,and a microaverage F1 score of 97.1%.While in the real-name transaction scenario,the traditional machine learning method is far better than the deep learning method,and the micro-average F1 score of the random forest and XGBoost models both reach 99.9%,which can effectively identify money laundering in currency transactions.
