In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted ...In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted distances between new facilities and existing facilities is minimized. We present a linear programming model for this problem with block norms, then we use it for problems with fuzzy data. We also do this for rectilinear and infinity norms as special cases of block norms.展开更多
Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on...Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on these types.The recent situation of tectonic movement of main structural belts and seismicity in this area are expounded.From the above,it is concluded that across-fault measurement can reflect not only the conditions of fault movement nearby but also the change of regional stress fields; not only is this a method to obtain regional seismogenic information and to conduct short-term prediction but it is also involved with large scale space-time prediction of moderate and strong earthquakes on the basis of the macro characteristics of fractures.展开更多
Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time...Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time of big data. This work proposes a performance and availability evaluation of big data environments in the private cloud through a methodology and stochastic and combinatorial models considering performance metrics such as execution times, processor utilization, memory utilization, and availability. The proposed methodology considers objective activities, performance, and availability modeling to evaluate the private cloud environment. A performance model based on stochastic Petrinets is adopted to evaluate the big data environment on the private cloud. Reliability block diagram models are adopted to evaluate the availability of big environment data in the private cloud. Two case studies based on the CloudStack platform and Hadoop cluster are adopted to demonstrate the viability of the proposed methodologies and models. Case Study 1 evaluated the performance metrics of the Hadoop cluster in the private cloud, considering different service offerings, workloads, and the number of data sets. The sentiment analysis technique is used in tweets from users with symptoms of depression to generate the analyzed datasets. Case Study 2 evaluated the availability of big data environments in the private cloud.展开更多
文摘In this paper we study the problem of locating multiple facilities in convex sets with fuzzy parameters. This problem asks to find the location of new facilities in the given convex sets such that the sum of weighted distances between new facilities and existing facilities is minimized. We present a linear programming model for this problem with block norms, then we use it for problems with fuzzy data. We also do this for rectilinear and infinity norms as special cases of block norms.
文摘Based on the arrangement of the across-fault measurement data along the northern edge of the Qinghai-Xizang block,we divide the deformation into different types and probe the nature of various fault movements based on these types.The recent situation of tectonic movement of main structural belts and seismicity in this area are expounded.From the above,it is concluded that across-fault measurement can reflect not only the conditions of fault movement nearby but also the change of regional stress fields; not only is this a method to obtain regional seismogenic information and to conduct short-term prediction but it is also involved with large scale space-time prediction of moderate and strong earthquakes on the basis of the macro characteristics of fractures.
基金浙江省“尖兵”“领雁”研发攻关计划(2024C01058)浙江省“十四五”第二批本科省级教学改革备案项目(JGBA2024014)+2 种基金2025年01月批次教育部产学合作协同育人项目(2501270945)2024年度浙江大学本科“AI赋能”示范课程建设项目(24)浙江大学第一批AI For Education系列实证教学研究项目(202402)。
文摘Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time of big data. This work proposes a performance and availability evaluation of big data environments in the private cloud through a methodology and stochastic and combinatorial models considering performance metrics such as execution times, processor utilization, memory utilization, and availability. The proposed methodology considers objective activities, performance, and availability modeling to evaluate the private cloud environment. A performance model based on stochastic Petrinets is adopted to evaluate the big data environment on the private cloud. Reliability block diagram models are adopted to evaluate the availability of big environment data in the private cloud. Two case studies based on the CloudStack platform and Hadoop cluster are adopted to demonstrate the viability of the proposed methodologies and models. Case Study 1 evaluated the performance metrics of the Hadoop cluster in the private cloud, considering different service offerings, workloads, and the number of data sets. The sentiment analysis technique is used in tweets from users with symptoms of depression to generate the analyzed datasets. Case Study 2 evaluated the availability of big data environments in the private cloud.
