The genetic base that cotton breeders commonly use to improve Upland cultivars is very narrow.The AD-genome species Gossypium barbadense,G.tomentosum,and G.mustelinum are part of
China is lack of bromine and potassium seriously.Oilfield brines is the headline goal of bromine and potassium resources exploration.Applicants grab 24oilfield brines samples from various wells of Ordovician
How to allocate a resource efficiently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis（DEA） has been brought to bear on its solution. The existing literature applie...How to allocate a resource efficiently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis（DEA） has been brought to bear on its solution. The existing literature applies Gini coefficient to measure the fairness in the resource allocation process. However, the Gini coefficient is inapplicable in many applications. This paper proposes a novel centralized resource allocation model based on DEA that considers both the efficiency and the fairness. This paper adopts a notion of fairness, namely α-fairness that is well studied in welfare economics and is of practical significance. The new model integratesα-fairness with DEA to support resource allocation decisions. It aids decision makers in making a trade-off between the efficiency and the fairness. An illustrative application is used to validate the proposed approach.展开更多
1.The overall development of new energy vehicles was good in 2017.In early 2017,the new energy vehicle market was greatly affected by major policy adjustments such as drastic decline in new energy vehicle subsidies an...1.The overall development of new energy vehicles was good in 2017.In early 2017,the new energy vehicle market was greatly affected by major policy adjustments such as drastic decline in new energy vehicle subsidies and re-examination of the model catalogue.But China’s determination to vigorously promote the healthy development of the new energy vehicle industry has not changed.In March and April。展开更多
Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructure...Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructures consider virtual machines （VMs） as independent entities with their own characteristics. However, these approaches suffer from scalability issues due to the increasing number of VMs in modern cloud data centers. We claim that scalability issues can bc addressed by leveraging the similarity among VMs behavior in terms of resource usage patterns. In this paper we propose an automated methodology to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. The innovative contribution of the proposed methodology is the use of the statistical technique known as principal component analysis （PCA） to automatically select the most relevant information to cluster similar VMs. We apply the methodology to two case studies, a virtualized testbed and a real enterprise data center. In both case studies, the automatic data selection based on PCA allows us to achieve high performance, with a percentage of correctly clustered VMs between 80% and 100% even for short time series （1 day） of monitored data. Furthermore, we estimate the potential reduction in the amount of collected data to demonstrate how our proposal may address the scalability issues related to monitoring and management in cloud computing data centers.展开更多
文摘The genetic base that cotton breeders commonly use to improve Upland cultivars is very narrow.The AD-genome species Gossypium barbadense,G.tomentosum,and G.mustelinum are part of
基金supported by Geological survey project (Project Number: 12120113078500)
文摘China is lack of bromine and potassium seriously.Oilfield brines is the headline goal of bromine and potassium resources exploration.Applicants grab 24oilfield brines samples from various wells of Ordovician
基金supported by the National Natural Science Foundation of China(7117118171301155)+1 种基金the Fundamental Research Fundsfor the Central Universities(WK2040160008J2014HGBZ0172)
文摘How to allocate a resource efficiently and fairly attracts the attention of both researchers and practitioners. Data envelopment analysis（DEA） has been brought to bear on its solution. The existing literature applies Gini coefficient to measure the fairness in the resource allocation process. However, the Gini coefficient is inapplicable in many applications. This paper proposes a novel centralized resource allocation model based on DEA that considers both the efficiency and the fairness. This paper adopts a notion of fairness, namely α-fairness that is well studied in welfare economics and is of practical significance. The new model integratesα-fairness with DEA to support resource allocation decisions. It aids decision makers in making a trade-off between the efficiency and the fairness. An illustrative application is used to validate the proposed approach.
文摘1.The overall development of new energy vehicles was good in 2017.In early 2017,the new energy vehicle market was greatly affected by major policy adjustments such as drastic decline in new energy vehicle subsidies and re-examination of the model catalogue.But China’s determination to vigorously promote the healthy development of the new energy vehicle industry has not changed.In March and April。
文摘Cloud computing has recently emerged as a leading paradigm to allow customers to run their applications in virtualized large-scale data centers. Existing solutions for monitoring and management of these infrastructures consider virtual machines （VMs） as independent entities with their own characteristics. However, these approaches suffer from scalability issues due to the increasing number of VMs in modern cloud data centers. We claim that scalability issues can bc addressed by leveraging the similarity among VMs behavior in terms of resource usage patterns. In this paper we propose an automated methodology to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. The innovative contribution of the proposed methodology is the use of the statistical technique known as principal component analysis （PCA） to automatically select the most relevant information to cluster similar VMs. We apply the methodology to two case studies, a virtualized testbed and a real enterprise data center. In both case studies, the automatic data selection based on PCA allows us to achieve high performance, with a percentage of correctly clustered VMs between 80% and 100% even for short time series （1 day） of monitored data. Furthermore, we estimate the potential reduction in the amount of collected data to demonstrate how our proposal may address the scalability issues related to monitoring and management in cloud computing data centers.
