Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate des...Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.展开更多
目的为评价CEREC椅旁CAD/CAM系统制作的IPS e.max CAD玻璃陶瓷高嵌体应用于根管治疗后牙缺损病例的临床效果。方法选择42例根管治疗后牙,应用高嵌体的牙体预备方式,采用CEREC椅旁CAD/CAM修复系统和IPS e.max CAD玻璃陶瓷,即刻完成修复...目的为评价CEREC椅旁CAD/CAM系统制作的IPS e.max CAD玻璃陶瓷高嵌体应用于根管治疗后牙缺损病例的临床效果。方法选择42例根管治疗后牙,应用高嵌体的牙体预备方式,采用CEREC椅旁CAD/CAM修复系统和IPS e.max CAD玻璃陶瓷,即刻完成修复体并粘接;修复1年后复查,参照改良修正后的美国公众健康服务标准(US Public Health Service Criteria,USPHS),在修复体边缘染色、边缘继发龋、修复体边缘适合性、修复体崩瓷折裂或脱落、修复体颜色、牙龈健康状况、修复体邻接关系、患者满意度8个方面进行评价。结果修复体边缘染色C级病例1例,成功率97.6%;边缘继发龋C级病例1例,成功率97.6%;修复体邻接关系欠佳C级病例1例,成功率97.6%;在边缘适合性、修复体崩瓷折裂或脱落、修复体颜色、牙龈健康状况、患者满意方面表现优秀,成功率均为100%。结论椅旁CAD/CAM系统制作的IPS e.maxCAD高嵌体修复体在短期内可取得良好的修复效果。展开更多
基金This work was supported in part by the Natural Science Foundation of the Education Department of Henan Province(Grant 22A520025)the National Natural Science Foundation of China(Grant 61975053)the National Key Research and Development of Quality Information Control Technology for Multi-Modal Grain Transportation Efficient Connection(2022YFD2100202).
文摘Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.
文摘目的为评价CEREC椅旁CAD/CAM系统制作的IPS e.max CAD玻璃陶瓷高嵌体应用于根管治疗后牙缺损病例的临床效果。方法选择42例根管治疗后牙,应用高嵌体的牙体预备方式,采用CEREC椅旁CAD/CAM修复系统和IPS e.max CAD玻璃陶瓷,即刻完成修复体并粘接;修复1年后复查,参照改良修正后的美国公众健康服务标准(US Public Health Service Criteria,USPHS),在修复体边缘染色、边缘继发龋、修复体边缘适合性、修复体崩瓷折裂或脱落、修复体颜色、牙龈健康状况、修复体邻接关系、患者满意度8个方面进行评价。结果修复体边缘染色C级病例1例,成功率97.6%;边缘继发龋C级病例1例,成功率97.6%;修复体邻接关系欠佳C级病例1例,成功率97.6%;在边缘适合性、修复体崩瓷折裂或脱落、修复体颜色、牙龈健康状况、患者满意方面表现优秀,成功率均为100%。结论椅旁CAD/CAM系统制作的IPS e.maxCAD高嵌体修复体在短期内可取得良好的修复效果。
