The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensur...The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.展开更多
目的探讨血清CA12-5水平对肝硬化腹腔积液程度的诊断价值。方法收集2011年1月-2015年12月在首都医科大学附属北京天坛医院住院并且符合纳入标准的肝硬化患者142例。根据是否出现腹腔积液将所有患者分为腹腔积液组（n=81）和无腹腔积液组...目的探讨血清CA12-5水平对肝硬化腹腔积液程度的诊断价值。方法收集2011年1月-2015年12月在首都医科大学附属北京天坛医院住院并且符合纳入标准的肝硬化患者142例。根据是否出现腹腔积液将所有患者分为腹腔积液组（n=81）和无腹腔积液组（n=61）,符合正态分布的计量资料组间比较采用两独立样本t检验,不符合正态分布的采用Mann-Whitney U非参数检验,计数资料组间比较采用χ2检验。采用Spearman相关分析评估血清CA12-5水平与腹腔积液程度的相关性。结果腹腔积液组血清CA12-5水平显著高于无腹腔积液组[290.00（50.82-618.40）U/ml vs 15.39（9.77-23.04）U/ml,Z=-8.531,P〈0.01]。血清CA12-5水平与腹腔积液程度呈正相关（r=0.812,P〈0.01）,且对腹腔积液具有较高的诊断价值（受试者工作特征曲线下面积为0.92）。当血清CA12-5取值为35.00 U/ml时具有最佳的敏感度和特异度,分别为81.5%和88.5%。结论血清CA12-5有助于肝硬化腹腔积液的诊断及监测腹腔积液的消长。展开更多
文摘The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.
文摘目的探讨血清CA12-5水平对肝硬化腹腔积液程度的诊断价值。方法收集2011年1月-2015年12月在首都医科大学附属北京天坛医院住院并且符合纳入标准的肝硬化患者142例。根据是否出现腹腔积液将所有患者分为腹腔积液组（n=81）和无腹腔积液组（n=61）,符合正态分布的计量资料组间比较采用两独立样本t检验,不符合正态分布的采用Mann-Whitney U非参数检验,计数资料组间比较采用χ2检验。采用Spearman相关分析评估血清CA12-5水平与腹腔积液程度的相关性。结果腹腔积液组血清CA12-5水平显著高于无腹腔积液组[290.00（50.82-618.40）U/ml vs 15.39（9.77-23.04）U/ml,Z=-8.531,P〈0.01]。血清CA12-5水平与腹腔积液程度呈正相关（r=0.812,P〈0.01）,且对腹腔积液具有较高的诊断价值（受试者工作特征曲线下面积为0.92）。当血清CA12-5取值为35.00 U/ml时具有最佳的敏感度和特异度,分别为81.5%和88.5%。结论血清CA12-5有助于肝硬化腹腔积液的诊断及监测腹腔积液的消长。
