Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from l...Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from limited time of flight.Conventional techniques suffer from high delay,low throughput,and early node death due to aerial topology of UAV networks.To deal with these issues,this paper proposes a UAV parameter vector which considers node energy,channel state information and mobility of UAVs.By intelligently estimating the proposed parameter,the state of UAV can be predicted closely.Accordingly,efficient clustering may be achieved by using suitable metaheuristic techniques.In the current work,Elbow method has been used to determine optimal cluster count in the deployed FANET.The proposed UAV parameter vector is then integrated into two popular hybrid metaheuristic algorithms,namely,water cycle-moth flame optimization(WCMFO)and Grey Wolf-Particle Swarm optimization(GWPSO),thereby enhancing the lifespan of the system.A methodology based on the holistic approach of parameter and signal formulation,estimation model for intelligent clustering,and statistical parameters for performance analysis is carried out by the energy consumption of the network and the alive node analysis.Rigorous simulations are run to demonstrate node density variations to validate the theoretical developments for various proportions of network system sizes.The proposed method presents significant improvement over conventional stateof-the-art methods.展开更多
Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant ...Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant challenge, as the need for robust security measures becomes increasingly imperative. This paper presented an innovative method based on differential analyses to detect abrupt changes in network traffic characteristics. The core concept revolves around identifying abrupt alterations in certain characteristics such as input/output volume, the number of TCP connections, or DNS queries—within the analyzed traffic. Initially, the traffic is segmented into distinct sequences of slices, followed by quantifying specific characteristics for each slice. Subsequently, the distance between successive values of these measured characteristics is computed and clustered to detect sudden changes. To accomplish its objectives, the approach combined several techniques, including propositional logic, distance metrics (e.g., Kullback-Leibler Divergence), and clustering algorithms (e.g., K-means). When applied to two distinct datasets, the proposed approach demonstrates exceptional performance, achieving detection rates of up to 100%.展开更多
目的评估手术治疗肘关节恐怖三联征的临床疗效。方法连续收集本院2020年1月-2022年1月收住并接受手术治疗28例肘关节恐怖三联征患者的临床资料,动态随访1年,观察患者的VAS疼痛评分、肘关节屈伸、前臂旋转范围、肘关节功能恢复情况和并...目的评估手术治疗肘关节恐怖三联征的临床疗效。方法连续收集本院2020年1月-2022年1月收住并接受手术治疗28例肘关节恐怖三联征患者的临床资料,动态随访1年,观察患者的VAS疼痛评分、肘关节屈伸、前臂旋转范围、肘关节功能恢复情况和并发症发生情况。结果28例患者中男性19例、女性9例,平均年龄(31.28±11.52)岁。尺骨冠状突骨折Regan-Morrey I型5例、II型18例、III型5例;桡骨头骨折Mason I型9例、II型13例、III型6例。分别采用不同麻醉方式、手术入路和术式完成骨折内固定和韧带修复,随访结束时28例骨折均骨性愈合(100%),发生1例异位骨化(3.57%)被成功纠治(100%)。与术前比较,患者术后1年的肘关节疼痛(VAS评分:7.21±2.18 VS 2.01±0.21,P<0.001)、肘关节屈伸度(29.68±16.13 VS 130.81±18.95,P<0.001)、前臂旋前范围(10.63±8.25 VS 76.35±2.45,P<0.001)、旋后范围(10.21±8.89 VS 75.32±3.85,P<0.001)、肘关节功能(Mayo评分:38.36±18.63 VS 87.45±12.38,P<0.001)均显著改善。结论手术治疗肘关节恐怖三联征疗效显著,选择合适手术入路及手术模式重建肘关节的稳定性、术后早期康复锻炼,是获得满意疗效的关键。展开更多
文摘Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from limited time of flight.Conventional techniques suffer from high delay,low throughput,and early node death due to aerial topology of UAV networks.To deal with these issues,this paper proposes a UAV parameter vector which considers node energy,channel state information and mobility of UAVs.By intelligently estimating the proposed parameter,the state of UAV can be predicted closely.Accordingly,efficient clustering may be achieved by using suitable metaheuristic techniques.In the current work,Elbow method has been used to determine optimal cluster count in the deployed FANET.The proposed UAV parameter vector is then integrated into two popular hybrid metaheuristic algorithms,namely,water cycle-moth flame optimization(WCMFO)and Grey Wolf-Particle Swarm optimization(GWPSO),thereby enhancing the lifespan of the system.A methodology based on the holistic approach of parameter and signal formulation,estimation model for intelligent clustering,and statistical parameters for performance analysis is carried out by the energy consumption of the network and the alive node analysis.Rigorous simulations are run to demonstrate node density variations to validate the theoretical developments for various proportions of network system sizes.The proposed method presents significant improvement over conventional stateof-the-art methods.
文摘Internet services and web-based applications play pivotal roles in various sensitive domains, encompassing e-commerce, e-learning, e-healthcare, and e-payment. However, safeguarding these services poses a significant challenge, as the need for robust security measures becomes increasingly imperative. This paper presented an innovative method based on differential analyses to detect abrupt changes in network traffic characteristics. The core concept revolves around identifying abrupt alterations in certain characteristics such as input/output volume, the number of TCP connections, or DNS queries—within the analyzed traffic. Initially, the traffic is segmented into distinct sequences of slices, followed by quantifying specific characteristics for each slice. Subsequently, the distance between successive values of these measured characteristics is computed and clustered to detect sudden changes. To accomplish its objectives, the approach combined several techniques, including propositional logic, distance metrics (e.g., Kullback-Leibler Divergence), and clustering algorithms (e.g., K-means). When applied to two distinct datasets, the proposed approach demonstrates exceptional performance, achieving detection rates of up to 100%.
文摘目的评估手术治疗肘关节恐怖三联征的临床疗效。方法连续收集本院2020年1月-2022年1月收住并接受手术治疗28例肘关节恐怖三联征患者的临床资料,动态随访1年,观察患者的VAS疼痛评分、肘关节屈伸、前臂旋转范围、肘关节功能恢复情况和并发症发生情况。结果28例患者中男性19例、女性9例,平均年龄(31.28±11.52)岁。尺骨冠状突骨折Regan-Morrey I型5例、II型18例、III型5例;桡骨头骨折Mason I型9例、II型13例、III型6例。分别采用不同麻醉方式、手术入路和术式完成骨折内固定和韧带修复,随访结束时28例骨折均骨性愈合(100%),发生1例异位骨化(3.57%)被成功纠治(100%)。与术前比较,患者术后1年的肘关节疼痛(VAS评分:7.21±2.18 VS 2.01±0.21,P<0.001)、肘关节屈伸度(29.68±16.13 VS 130.81±18.95,P<0.001)、前臂旋前范围(10.63±8.25 VS 76.35±2.45,P<0.001)、旋后范围(10.21±8.89 VS 75.32±3.85,P<0.001)、肘关节功能(Mayo评分:38.36±18.63 VS 87.45±12.38,P<0.001)均显著改善。结论手术治疗肘关节恐怖三联征疗效显著,选择合适手术入路及手术模式重建肘关节的稳定性、术后早期康复锻炼,是获得满意疗效的关键。
