In the United States, emission regulations are enacted at a state level;individual states are allowed to define what methods they will use to mitigate their carbon emissions. The consequence of this is especially inte...In the United States, emission regulations are enacted at a state level;individual states are allowed to define what methods they will use to mitigate their carbon emissions. The consequence of this is especially interesting in the state of Texas where new legislation has created a “deregulated” electricity market in which end-users are capable of choosing their electricity provider and subsequently the type of electricity they wish to consume (generated by fossil fuels or renewable sources). In this paper we analyze the effects of carbon tax on the development of renewable generation capacity at the utility level while taking into account expected adoption of rooftop PV systems by individual consumers using agent based modeling techniques. Monte Carlo simulations show carbon abatement trends and proffer updated renewable portfolio standards at various levels of likelihood.展开更多
Objective: To compare the haemodynamic effects of the induction agents ketamine, etomidate and sevoflurane using the model of electrical velocimetry based cardiac output monitoring in paediatric cardiac surgical patie...Objective: To compare the haemodynamic effects of the induction agents ketamine, etomidate and sevoflurane using the model of electrical velocimetry based cardiac output monitoring in paediatric cardiac surgical patients. Design: Prospective randomized study. Setting: Tertiary care hospital. Participants: 60 children < 2 years age undergoing cardiac surgery. Interventions: The patients were randomized into 3 equal groups to receive 1.5-2.5 mg/kg iv ketamine (group K), 0.2-0.3 mg/kg iv etomidate (group E) or upto 8% sevoflurane (group S) as the induction agent. Hemodynamic parameters were noted before and after induction of anaesthesia utilizing a noninvasive cardiac monitor based on the model of electrical velocimetry. Measurements and Main Results: The demographic characteristics of the patients were similar in the three groups. The HR decreased in all groups, least in group E (P ≤ 0.01) but the MAP decreased only in group S (P ≤ 0.001). In group S, the stroke volume improved from 9 ± 3.2 ml to 10 ± 3.2 ml (P ≤ 0.05) and the stroke volume variation decreased from 25% ± 6.4% to 13% ± 6.2% (P ≤ 0.001). The stroke index and systemic arterial saturation improved in all groups (P ≤ 0.01). The cardiac index and index of contractility were unchanged. The transthoracic fluid content reduced in groups E and S, but did not change in group K (P ≤ 0.05). Conclusions: Etomidate appeared to provide the most stable conditions for induction of anesthesia in children undergoing cardiac surgery, followed by ketamine and sevoflurane.展开更多
Forecasting orders accurately plays a crucial role for household electric appliance (HEA) enterprises keeping low inventory level. In order to reduce the influence of bullwhip effect, sales data are applied to forecas...Forecasting orders accurately plays a crucial role for household electric appliance (HEA) enterprises keeping low inventory level. In order to reduce the influence of bullwhip effect, sales data are applied to forecast orders of the next period instead of ordering data. Mobile agent is applied to achieve the sales data from retailers in the data preparation. And the converting approach from sales data of retailers to prediction data is proposed. Autoregressive and moving average (ARMA) model is introduced to forecast orders and a comparison amongst final prediction error (FPE), Akaike information criterion(AIC), Bayes information criterion(BIC) and Akaike's corrected information criterion(AICC) criterion is shown. The sample test verifies the superiority of AICC; therefore it is applied to identify ARMA order. Forecasting architecture is established and then the prototype system is tested, at last a case shows the orders prediction of the next quarter and verifies the effectiveness of the proposed method.展开更多
This paper presents the use of proposed Smart Grid Distribution Management System (SGDMS) for Singapore contestable and non-contestable consumers. The SGDMS is a distributed management system proposed using Multi-Agen...This paper presents the use of proposed Smart Grid Distribution Management System (SGDMS) for Singapore contestable and non-contestable consumers. The SGDMS is a distributed management system proposed using Multi-Agent System (MAS) technology. This system can optimise the distribution of renewable energy while minimizing electricity bills for consumers. The entire system was developed using Java with the extension of JADE which is an IEEE FIPA compliant multi-agent system platform. This decentralised platform allows agents to interact and communicate using energy sources from different sectors and control them intelligently to minimise the cost of electricity for the consumers. Simulation studies were carried out on the proposed system to show its potential for providing solutions through intelligent distribution techniques and how it influences the cost of electricity.展开更多
文摘In the United States, emission regulations are enacted at a state level;individual states are allowed to define what methods they will use to mitigate their carbon emissions. The consequence of this is especially interesting in the state of Texas where new legislation has created a “deregulated” electricity market in which end-users are capable of choosing their electricity provider and subsequently the type of electricity they wish to consume (generated by fossil fuels or renewable sources). In this paper we analyze the effects of carbon tax on the development of renewable generation capacity at the utility level while taking into account expected adoption of rooftop PV systems by individual consumers using agent based modeling techniques. Monte Carlo simulations show carbon abatement trends and proffer updated renewable portfolio standards at various levels of likelihood.
文摘Objective: To compare the haemodynamic effects of the induction agents ketamine, etomidate and sevoflurane using the model of electrical velocimetry based cardiac output monitoring in paediatric cardiac surgical patients. Design: Prospective randomized study. Setting: Tertiary care hospital. Participants: 60 children < 2 years age undergoing cardiac surgery. Interventions: The patients were randomized into 3 equal groups to receive 1.5-2.5 mg/kg iv ketamine (group K), 0.2-0.3 mg/kg iv etomidate (group E) or upto 8% sevoflurane (group S) as the induction agent. Hemodynamic parameters were noted before and after induction of anaesthesia utilizing a noninvasive cardiac monitor based on the model of electrical velocimetry. Measurements and Main Results: The demographic characteristics of the patients were similar in the three groups. The HR decreased in all groups, least in group E (P ≤ 0.01) but the MAP decreased only in group S (P ≤ 0.001). In group S, the stroke volume improved from 9 ± 3.2 ml to 10 ± 3.2 ml (P ≤ 0.05) and the stroke volume variation decreased from 25% ± 6.4% to 13% ± 6.2% (P ≤ 0.001). The stroke index and systemic arterial saturation improved in all groups (P ≤ 0.01). The cardiac index and index of contractility were unchanged. The transthoracic fluid content reduced in groups E and S, but did not change in group K (P ≤ 0.05). Conclusions: Etomidate appeared to provide the most stable conditions for induction of anesthesia in children undergoing cardiac surgery, followed by ketamine and sevoflurane.
基金Supported by National Natural Science Foundation of China (61164013, U1334211, 51174091), the Key Program of China Ministry of Railway (2011Z002-D), and Natural Science Foundation of Jiangxi Province (20122BAB201021)
基金Hubei International Cooperation Projects,China(No.2007CA008)
文摘Forecasting orders accurately plays a crucial role for household electric appliance (HEA) enterprises keeping low inventory level. In order to reduce the influence of bullwhip effect, sales data are applied to forecast orders of the next period instead of ordering data. Mobile agent is applied to achieve the sales data from retailers in the data preparation. And the converting approach from sales data of retailers to prediction data is proposed. Autoregressive and moving average (ARMA) model is introduced to forecast orders and a comparison amongst final prediction error (FPE), Akaike information criterion(AIC), Bayes information criterion(BIC) and Akaike's corrected information criterion(AICC) criterion is shown. The sample test verifies the superiority of AICC; therefore it is applied to identify ARMA order. Forecasting architecture is established and then the prototype system is tested, at last a case shows the orders prediction of the next quarter and verifies the effectiveness of the proposed method.
文摘This paper presents the use of proposed Smart Grid Distribution Management System (SGDMS) for Singapore contestable and non-contestable consumers. The SGDMS is a distributed management system proposed using Multi-Agent System (MAS) technology. This system can optimise the distribution of renewable energy while minimizing electricity bills for consumers. The entire system was developed using Java with the extension of JADE which is an IEEE FIPA compliant multi-agent system platform. This decentralised platform allows agents to interact and communicate using energy sources from different sectors and control them intelligently to minimise the cost of electricity for the consumers. Simulation studies were carried out on the proposed system to show its potential for providing solutions through intelligent distribution techniques and how it influences the cost of electricity.