This study explores the significance,current research landscape,and conceptualization of sports safety promotion.Safety in sports is fundamental to youth physical activities,and an excessive focus on or neglect of saf...This study explores the significance,current research landscape,and conceptualization of sports safety promotion.Safety in sports is fundamental to youth physical activities,and an excessive focus on or neglect of safety is unwarranted.Globally,numerous countries have extensively researched sports safety promotion and implemented diverse strategies.Drawing from KABP(Knowledge,Attitude,Behavior,Practice)theory and 4M(Man,Machine,Medium,Management)management,this paper presents a conceptual framework for sports safety promotion.It integrates these theories to devise a comprehensive accident prevention model within a sports safety promotion system.The framework prioritizes enhancing students’safety literacy and underscores the practical application of safety knowledge and skills in simulated sports settings following structured safety education.It aims to enhance students’competency and proficiency in averting sports-related injuries.展开更多
In order to improve the energy efficiency of large-scale data centers, a virtual machine(VM) deployment algorithm called three-threshold energy saving algorithm(TESA), which is based on the linear relation between the...In order to improve the energy efficiency of large-scale data centers, a virtual machine(VM) deployment algorithm called three-threshold energy saving algorithm(TESA), which is based on the linear relation between the energy consumption and(processor) resource utilization, is proposed. In TESA, according to load, hosts in data centers are divided into four classes, that is,host with light load, host with proper load, host with middle load and host with heavy load. By defining TESA, VMs on lightly loaded host or VMs on heavily loaded host are migrated to another host with proper load; VMs on properly loaded host or VMs on middling loaded host are kept constant. Then, based on the TESA, five kinds of VM selection policies(minimization of migrations policy based on TESA(MIMT), maximization of migrations policy based on TESA(MAMT), highest potential growth policy based on TESA(HPGT), lowest potential growth policy based on TESA(LPGT) and random choice policy based on TESA(RCT)) are presented, and MIMT is chosen as the representative policy through experimental comparison. Finally, five research directions are put forward on future energy management. The results of simulation indicate that, as compared with single threshold(ST) algorithm and minimization of migrations(MM) algorithm, MIMT significantly improves the energy efficiency in data centers.展开更多
文摘This study explores the significance,current research landscape,and conceptualization of sports safety promotion.Safety in sports is fundamental to youth physical activities,and an excessive focus on or neglect of safety is unwarranted.Globally,numerous countries have extensively researched sports safety promotion and implemented diverse strategies.Drawing from KABP(Knowledge,Attitude,Behavior,Practice)theory and 4M(Man,Machine,Medium,Management)management,this paper presents a conceptual framework for sports safety promotion.It integrates these theories to devise a comprehensive accident prevention model within a sports safety promotion system.The framework prioritizes enhancing students’safety literacy and underscores the practical application of safety knowledge and skills in simulated sports settings following structured safety education.It aims to enhance students’competency and proficiency in averting sports-related injuries.
基金Project(61272148) supported by the National Natural Science Foundation of ChinaProject(20120162110061) supported by the Doctoral Programs of Ministry of Education of China+1 种基金Project(CX2014B066) supported by the Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(2014zzts044) supported by the Fundamental Research Funds for the Central Universities,China
文摘In order to improve the energy efficiency of large-scale data centers, a virtual machine(VM) deployment algorithm called three-threshold energy saving algorithm(TESA), which is based on the linear relation between the energy consumption and(processor) resource utilization, is proposed. In TESA, according to load, hosts in data centers are divided into four classes, that is,host with light load, host with proper load, host with middle load and host with heavy load. By defining TESA, VMs on lightly loaded host or VMs on heavily loaded host are migrated to another host with proper load; VMs on properly loaded host or VMs on middling loaded host are kept constant. Then, based on the TESA, five kinds of VM selection policies(minimization of migrations policy based on TESA(MIMT), maximization of migrations policy based on TESA(MAMT), highest potential growth policy based on TESA(HPGT), lowest potential growth policy based on TESA(LPGT) and random choice policy based on TESA(RCT)) are presented, and MIMT is chosen as the representative policy through experimental comparison. Finally, five research directions are put forward on future energy management. The results of simulation indicate that, as compared with single threshold(ST) algorithm and minimization of migrations(MM) algorithm, MIMT significantly improves the energy efficiency in data centers.
