Software-defined satellite networks(SDSNs)play an essential role in future networks.Due to the diverse service scenarios,SDSN faces the demand of packet processing for heterogeneous protocols.Existing packet switching...Software-defined satellite networks(SDSNs)play an essential role in future networks.Due to the diverse service scenarios,SDSN faces the demand of packet processing for heterogeneous protocols.Existing packet switching typically works on one single protocol.For protocol-heterogeneous users,existing packet switch architectures have to construct multiple protocol-specific switching instances,resulting in severe resource waste.In this article,we propose the heterogeneous protocol-independent packet switch architecture(HISA).HISA employs a fast parsing structure to achieve efficient heterogeneous packet parsing and a novel match-action pipeline to achieve shared packet processing among heterogeneous users.HISA can also support the online configuration of switching behaviors.Use cases illustrate the effectiveness of applying HISA in SDSN.Numerical results show that compared to existing packet switching,HISA can significantly improve the resource utilization of SDSN.展开更多
Precise experimental control and characterization of electron wave packet dynamics driven by external optical fields remain a fundamental challenge,particularly at ultrafast temporal and sub-microscopic spatial scales...Precise experimental control and characterization of electron wave packet dynamics driven by external optical fields remain a fundamental challenge,particularly at ultrafast temporal and sub-microscopic spatial scales.To overcome these challenges,we introduce a photon-based simulation platform employing a traveling-wave electrooptic phase-modulated waveguide.In our setup,the incident electromagnetic pulse serves as an analog to the electron wave packet,while the traveling-wave modulation simulates the external optical driving field.Our experimental study systematically explores pulse evolution under three distinct regimes defined by the relation between the pulse duration(Δt)and the modulation period(T).When the pulse duration is significantly shorter than the modulation period,we observe a uniform spectral shift analogous to electron acceleration in dielectric laser accelerators,where spectral phase gradients represent electron momentum accumulation.Conversely,when the pulse duration greatly exceeds the modulation period,discrete diffraction patterns emerge,closely resembling the discrete sideband features of electron-photon coupling observed in photon-induced near-field electron microscopy.Notably,in the intermediate regime(T/4<Δt<T/2),the pulse spectrum exhibits Airy-function-type characteristics with self-healing effects.These experimental results provide critical insights into electron-wave interactions under external optical fields and establish a robust,programmable framework for further investigation.展开更多
Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP s...Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP spoofing attacks.Attackers can exploit this weakness to impersonate legitimate pods,enabling unauthorized access,lateral movement,and large-scale Distributed Denial of Service(DDoS)attacks.Existing security mechanisms such as network policies and intrusion detection systems introduce latency and performance overhead,making them less effective in dynamic Kubernetes environments.This research presents PodCA,an eBPF-based security framework designed to detect and prevent IP spoofing in real time while minimizing performance impact.PodCA integrates with Kubernetes’Container Network Interface(CNI)and uses eBPF to monitor and validate packet metadata at the kernel level.It maintains a container network mapping table that tracks pod IP assignments,validates packet legitimacy before forwarding,and ensures network integrity.If an attack is detected,PodCA automatically blocks spoofed packets and,in cases of repeated attempts,terminates compromised pods to prevent further exploitation.Experimental evaluation on an AWS Kubernetes cluster demonstrates that PodCA detects and prevents spoofed packets with 100%accuracy.Additionally,resource consumption analysis reveals minimal overhead,with a CPU increase of only 2–3%per node and memory usage rising by 40–60 MB.These results highlight the effectiveness of eBPF in securing Kubernetes environments with low overhead,making it a scalable and efficient security solution for containerized applications.展开更多
When a 3D model is transmitted over a lossy network,some model information may inevitably be missing.Under such situation,one may not be able to visualize the receiving model unless the lost model information has been...When a 3D model is transmitted over a lossy network,some model information may inevitably be missing.Under such situation,one may not be able to visualize the receiving model unless the lost model information has been retransmitted.Progressive model transmission offers an alternative to avoid the"all or nothing situation"by allowing a model to be visualized with a degraded quality when only part of the model data has been received.Unfortunately,in case some model refinement information is missing,one may still need to wait for such information to be retransmitted before the model can be rendered with a desired visual quality.To address this problem,we have developed a novel error resilient packetization scheme.We first construct a Non-Redundant Directed Acyclic Graph to encode the dependencies among the vertex splits of a progressive mesh.A special Global Graph Equipartition Packing Algorithm is then applied to partitioning this graph into several equal size sub-graphs,which is packed as packets.The packing algorithm comprises two main phases:initial partition phase and global refinement phase.Experimental results demonstrate that the proposed scheme can minimize the dependencies between packets.Hence,it reduces the delay in rendering 3D models with proper quality at the clients.展开更多
High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support s...High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.展开更多
Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier ap...Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier approaches such as Port Knocking(PK)and Single Packet Authorization(SPA)introduced pre-authentication concepts,they suffer from limitations including plaintext communication,protocol dependency,reliance on dedicated clients,and inefficiency under modern network conditions.These constraints hinder their applicability in emerging distributed and resource-constrained environments such as AIoT and browser-based systems.To address these challenges,this study proposes a novel port-sequence-based PAPC scheme structured as a modular model comprising a client,server,and ephemeral Key Management System(KMS).The system employs the Advanced Encryption Standard(AES-128)to protect message confidentiality and uses a Hash-Based Message Authentication Code(HMAC-SHA256)to ensure integrity.Authentication messages are securely fragmented and mapped to destination port numbers using a signature-based avoidance algorithm,which prevents collisions with unsafe or reserved port ranges.The server observes incoming port sequences,retrieves the necessary keys from the KMS,reconstructs and verifies the encrypted data,and conditionally updates firewall policies.Unlike SPA,which requires decrypting all incoming payloads and imposes server-side overhead,the proposed system verifies only port-derived fragments,significantly reducing computational burden.Furthermore,it eliminates the need for raw socket access or custom clients,supporting browser-based operation and enabling protocol-independent deployment.Through a functional web-based prototype and emulated testing,the system achieved an F1-score exceeding 95%in detecting unauthorized access while maintaining low resource overhead.Although port sequence generation introduces some client-side cost,it remains lightweight and scalable.By tightly integrating lightweight cryptographic algorithms with a transport-layer communication model,this work presents a conceptually validated architecture that contributes a novel direction for interoperable and scalable Zero Trust enforcement in future network ecosystems.展开更多
The hydration state of amphiphilic block copolymers during the self-assembly transition is closely related to the structure and properties of copolymers. In this study, the temperature-induced self-assembly of copolym...The hydration state of amphiphilic block copolymers during the self-assembly transition is closely related to the structure and properties of copolymers. In this study, the temperature-induced self-assembly of copolymer poly(N,N-dimethylacrylamide)-poly(diacetone acrylamide)(PDMAA_(30)-PDAAM_(60))_(2)in aqueous solution was monitored by near-infrared spectroscopy with water as a probe. The wavelet packet transform was employed to improve the spectral resolution. The spectral information of hydrated water surrounding the hydrophilic PDMAA and hydrophobic PDAAM blocks was then extracted, revealing the significant roles of water in morphological transition of the copolymer from spherical to worm-like micelles. Specifically, water molecules interacting with N atoms and C=O groups of the hydrophilic block gradually decrease during the morphological transition, while hydrogen-bond structures NH–CO of the hydrophobic block gradually break, bringing more water molecules into contact with the hydrophobic block. This work provides a foundation for exploring the role of water molecules during the self-assembly transition of complex block copolymers.展开更多
To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(...To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(WPD)and enhanced deep learning techniques.In the proposed method,an agent at the receiver processes the received signal using WPD to generate an initial Spectrogram Waterfall(SW),which is subsequently segmented using a sliding window to serve as the input for the jamming recognition network.The network employs a bilateral filter to preprocess the input SW,thereby enhancing the edge features of the jamming signals.To extract abstract features,depthwise separable convolution is utilized instead of traditional convolution,thereby reducing the network’s parameter count and enhancing real-time performance.A pyramid pooling layer is integrated before the fully connected layer to enable the network to process input SW of varying sizes,thus enhancing scalability.During network training,adaptive moment estimation is employed as the optimizer,allowing the network to dynamically adjust the learning rate and accelerate convergence.A comprehensive comparison between the proposed jamming recognition network and six other models is conducted,along with Ablation Experiments(AE)based on numerical simulations.Simulation results demonstrate that the proposed method based on WPD and enhanced deep learning achieves high-precision recognition of various jamming patterns while maintaining a favorable balance among prediction accuracy,network complexity,and prediction time.展开更多
In the big data era,the surge in network traffic volume poses challenges for network management and cybersecurity.Network Traffic Classification(NTC)employs deep learning to categorize traffic data,aiding security and...In the big data era,the surge in network traffic volume poses challenges for network management and cybersecurity.Network Traffic Classification(NTC)employs deep learning to categorize traffic data,aiding security and analysis systems as Intrusion Detection Systems(IDS)and Intrusion Prevention Systems(IPS).However,current NTC methods,based on isolated network simulations,usually fail to adapt to new protocols and applications and ignore the effects of network conditions and user behavior on traffic patterns.To improve network traffic management insights,federated learning frameworks have been proposed to aggregate diverse traffic data for collaborative model training.This approach faces challenges like data integrity,label noise,packet loss,and skewed data distributions.While label noise can be mitigated through the use of sophisticated traffic labeling tools,other issues such as packet loss and skewed data distributions encountered in Network Packet Brokers(NPB)can severely impede the efficacy of federated learning algorithms.In this paper,we introduced the Robust Traffic Classifier with Federated Contrastive Learning(FC-RTC),combining federated and contrastive learning methods.Using the Supcon-Loss function from contrastive learning,FC-RTC distinguishes between similar and dissimilar samples.Training by sample pairs,FC-RTC effectively updates when receiving corrupted traffic data with packet loss or disorder.In cases of sample imbalance,contrastive loss functions for similar samples reduce model bias towards higher proportion data.By addressing uneven data distribution and packet loss,our system enhances its capability to adapt and perform accurately in real-world network traffic analysis,meeting the specific demands of this complex field.展开更多
Rotational dynamics simulations of neutral O_(2)molecules driven by linearly,elliptically and circularly polarized femtosecond pulsed lasers are carried out using a full quantum time-dependent wave packet evolution me...Rotational dynamics simulations of neutral O_(2)molecules driven by linearly,elliptically and circularly polarized femtosecond pulsed lasers are carried out using a full quantum time-dependent wave packet evolution method.Here,the direction of laser propagation is set along the z axis,and the polarization plane is restricted to the xy plane.The results indicate that the alignment of O_(2)molecules in the z direction is weakly affected by varying the ellipticity when the total laser intensity is held constant.For rotation within the xy plane,the linearly polarized laser significantly excites rotational motion,with the degree of excitation increasing as the ellipticity increases.In contrast,under the influence of a circularly polarized laser,the angular distribution of O_(2)molecules in the xy plane remains isotropic.Additionally,the effects of the initial rotational quantum number,the temperature of the O_(2)molecules and the nuclear spin on laser-induced alignment are discussed.展开更多
Light-induced conical intersections(LICIs)present a distinctive mechanism for nonadiabatic coupling,thereby facilitating ultrafast chemical reactions,including the indirect photodissociation of diatomic molecules.In c...Light-induced conical intersections(LICIs)present a distinctive mechanism for nonadiabatic coupling,thereby facilitating ultrafast chemical reactions,including the indirect photodissociation of diatomic molecules.In contrast to static conical intersections,LICIs are dynamically tunable,providing a pathway for precise control of molecular dissociation.In this study,we employ the time-dependent quantum wave packet method to investigate the dissociation dynamics of the OH molecule,focusing on its ground state X^(2)Πand repulsive state 1^(2)Σ~-.By varying laser field parameters(intensity,full width at half maximum(FWHM),and wavelength),we elucidate how nonadiabatic coupling governs selective dissociation channel control.Our findings reveal that the choice of initial vibrational states and the tailoring of laser conditions significantly influence dissociation pathways,providing theoretical insights into manipulating molecular dynamics via LICIs.These results provide a foundation for future experimental studies and the development of advanced molecular control techniques.展开更多
Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitor...Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitoring.Frequent topology changes,high mobility,and limited energy availability pose significant challenges to maintaining stable and high-performance routing.Traditional routing protocols,such as Ad hoc On-Demand Distance Vector(AODV),Load-Balanced Optimized Predictive Ad hoc Routing(LB-OPAR),and Destination-Sequenced Distance Vector(DSDV),often experience performance degradation under such conditions.To address these limitations,this study evaluates the effectiveness of Dynamic Adaptive Routing(DAR),a protocol designed to adapt routing decisions in real time based on network dynamics and resource constraints.The research utilizes the Network Simulator 3(NS-3)platform to conduct controlled simulations,measuring key performance indicators such as latency,Packet Delivery Ratio(PDR),energy consumption,and throughput.Comparative analysis reveals that DAR consistently outperforms conventional protocols,achieving a 20%-30% reduction in latency,a 25% decrease in energy consumption,and marked improvements in throughput and PDR.These results highlight DAR’s ability to maintain high communication reliability while optimizing resource usage in challenging operational scenarios.By providing empirical evidence of DAR’s advantages in highly dynamic UAV network environments,this study contributes to advancing adaptive routing strategies.The findings not only validate DAR’s robustness and scalability but also lay the groundwork for integrating artificial intelligence-driven decision-making and real-world UAV deployment.Future work will explore cross-layer optimization,multi-UAV coordination,and experimental validation in field trials,aiming to further enhance communication resilience and energy efficiency in next-generation aerial networks.展开更多
基金supported by the National Natural Science Foundation of China(62101300,62341130)the Youth Fund Program of the Beijing National Research Center for Information Science and Technology under Grant BNR2021RC01012the Open Research Fund Program of the Beijing National Research Center for Information Science and Technology under Grant BNR2021KF02001.
文摘Software-defined satellite networks(SDSNs)play an essential role in future networks.Due to the diverse service scenarios,SDSN faces the demand of packet processing for heterogeneous protocols.Existing packet switching typically works on one single protocol.For protocol-heterogeneous users,existing packet switch architectures have to construct multiple protocol-specific switching instances,resulting in severe resource waste.In this article,we propose the heterogeneous protocol-independent packet switch architecture(HISA).HISA employs a fast parsing structure to achieve efficient heterogeneous packet parsing and a novel match-action pipeline to achieve shared packet processing among heterogeneous users.HISA can also support the online configuration of switching behaviors.Use cases illustrate the effectiveness of applying HISA in SDSN.Numerical results show that compared to existing packet switching,HISA can significantly improve the resource utilization of SDSN.
基金supported by the National Natural Science Foundation of China(Grant No.12174260)the Shanghai Rising-Star Program(Grant No.21QA1406400)+1 种基金the Shanghai Science and Technology Development Fund(Grant Nos.21ZR1443500 and 21ZR1443600)supported by Research Grants Council,University Grants Committee(Grant Nos.STG3/E-704/23-N,CityU 11212721,and CityU 11204523).
文摘Precise experimental control and characterization of electron wave packet dynamics driven by external optical fields remain a fundamental challenge,particularly at ultrafast temporal and sub-microscopic spatial scales.To overcome these challenges,we introduce a photon-based simulation platform employing a traveling-wave electrooptic phase-modulated waveguide.In our setup,the incident electromagnetic pulse serves as an analog to the electron wave packet,while the traveling-wave modulation simulates the external optical driving field.Our experimental study systematically explores pulse evolution under three distinct regimes defined by the relation between the pulse duration(Δt)and the modulation period(T).When the pulse duration is significantly shorter than the modulation period,we observe a uniform spectral shift analogous to electron acceleration in dielectric laser accelerators,where spectral phase gradients represent electron momentum accumulation.Conversely,when the pulse duration greatly exceeds the modulation period,discrete diffraction patterns emerge,closely resembling the discrete sideband features of electron-photon coupling observed in photon-induced near-field electron microscopy.Notably,in the intermediate regime(T/4<Δt<T/2),the pulse spectrum exhibits Airy-function-type characteristics with self-healing effects.These experimental results provide critical insights into electron-wave interactions under external optical fields and establish a robust,programmable framework for further investigation.
基金partially supported by Asia Pacific University of Technology&Innovation(APU)Bukit Jalil,Kuala Lumpur,MalaysiaThe funding body had no role in the study design,data collection,analysis,interpretation,or writing of the manuscript.
文摘Kubernetes has become the dominant container orchestration platform,withwidespread adoption across industries.However,its default pod-to-pod communicationmechanism introduces security vulnerabilities,particularly IP spoofing attacks.Attackers can exploit this weakness to impersonate legitimate pods,enabling unauthorized access,lateral movement,and large-scale Distributed Denial of Service(DDoS)attacks.Existing security mechanisms such as network policies and intrusion detection systems introduce latency and performance overhead,making them less effective in dynamic Kubernetes environments.This research presents PodCA,an eBPF-based security framework designed to detect and prevent IP spoofing in real time while minimizing performance impact.PodCA integrates with Kubernetes’Container Network Interface(CNI)and uses eBPF to monitor and validate packet metadata at the kernel level.It maintains a container network mapping table that tracks pod IP assignments,validates packet legitimacy before forwarding,and ensures network integrity.If an attack is detected,PodCA automatically blocks spoofed packets and,in cases of repeated attempts,terminates compromised pods to prevent further exploitation.Experimental evaluation on an AWS Kubernetes cluster demonstrates that PodCA detects and prevents spoofed packets with 100%accuracy.Additionally,resource consumption analysis reveals minimal overhead,with a CPU increase of only 2–3%per node and memory usage rising by 40–60 MB.These results highlight the effectiveness of eBPF in securing Kubernetes environments with low overhead,making it a scalable and efficient security solution for containerized applications.
基金Supported by the National Natural Science Foundation of China under Grant No.60533080the National Research Foundation for Doctoral Program of Higher Education of China Under Grant No.20060335111.
文摘When a 3D model is transmitted over a lossy network,some model information may inevitably be missing.Under such situation,one may not be able to visualize the receiving model unless the lost model information has been retransmitted.Progressive model transmission offers an alternative to avoid the"all or nothing situation"by allowing a model to be visualized with a degraded quality when only part of the model data has been received.Unfortunately,in case some model refinement information is missing,one may still need to wait for such information to be retransmitted before the model can be rendered with a desired visual quality.To address this problem,we have developed a novel error resilient packetization scheme.We first construct a Non-Redundant Directed Acyclic Graph to encode the dependencies among the vertex splits of a progressive mesh.A special Global Graph Equipartition Packing Algorithm is then applied to partitioning this graph into several equal size sub-graphs,which is packed as packets.The packing algorithm comprises two main phases:initial partition phase and global refinement phase.Experimental results demonstrate that the proposed scheme can minimize the dependencies between packets.Hence,it reduces the delay in rendering 3D models with proper quality at the clients.
文摘High-quality services in today’s mobile networks require stable delivery of bandwidth-intensive network content.Multipath QUIC(MPQUIC),as a multipath protocol that extends QUIC,can utilize multiple paths to support stable and efficient transmission.The standard coupled congestion control algorithm in MPQUIC synchronizes these paths to manage congestion,meeting fairness requirements and improving transmission efficiency.However,current algorithms’Congestion Window(CWND)reduction approach significantly decreases CWND upon packet loss,which lowers effective throughput,regardless of the congestion origin.Furthermore,the uncoupled Slow-Start(SS)in MPQUIC leads to independent exponential CWND growth on each path,potentially causing buffer overflow.To address these issues,we propose the CC-OLIA,which incorporates Packet Loss Classifcation(PLC)and Coupled Slow-Start(CSS).The PLC distinguishes between congestion-induced and random packet losses,adjusting CWND reduction accordingly to maintain throughput.Concurrently,the CSS module coordinates CWND growth during the SS,preventing abrupt increases.Implementation on MININET shows that CC-OLIA not only maintains fair performance but also enhances transmission efficiency across diverse network conditions.
基金supported by Institute for Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2022-II221200)Convergence Security Core Talent Training Business(Chungnam National University).
文摘Pre-Authentication and Post-Connection(PAPC)plays a crucial role in realizing the Zero Trust security model by ensuring that access to network resources is granted only after successful authentication.While earlier approaches such as Port Knocking(PK)and Single Packet Authorization(SPA)introduced pre-authentication concepts,they suffer from limitations including plaintext communication,protocol dependency,reliance on dedicated clients,and inefficiency under modern network conditions.These constraints hinder their applicability in emerging distributed and resource-constrained environments such as AIoT and browser-based systems.To address these challenges,this study proposes a novel port-sequence-based PAPC scheme structured as a modular model comprising a client,server,and ephemeral Key Management System(KMS).The system employs the Advanced Encryption Standard(AES-128)to protect message confidentiality and uses a Hash-Based Message Authentication Code(HMAC-SHA256)to ensure integrity.Authentication messages are securely fragmented and mapped to destination port numbers using a signature-based avoidance algorithm,which prevents collisions with unsafe or reserved port ranges.The server observes incoming port sequences,retrieves the necessary keys from the KMS,reconstructs and verifies the encrypted data,and conditionally updates firewall policies.Unlike SPA,which requires decrypting all incoming payloads and imposes server-side overhead,the proposed system verifies only port-derived fragments,significantly reducing computational burden.Furthermore,it eliminates the need for raw socket access or custom clients,supporting browser-based operation and enabling protocol-independent deployment.Through a functional web-based prototype and emulated testing,the system achieved an F1-score exceeding 95%in detecting unauthorized access while maintaining low resource overhead.Although port sequence generation introduces some client-side cost,it remains lightweight and scalable.By tightly integrating lightweight cryptographic algorithms with a transport-layer communication model,this work presents a conceptually validated architecture that contributes a novel direction for interoperable and scalable Zero Trust enforcement in future network ecosystems.
基金supported by the National Natural Science Foundation of China (Nos. 22174075 and 22374082)the Haihe Laboratory of Sustainable Chemical Transformations。
文摘The hydration state of amphiphilic block copolymers during the self-assembly transition is closely related to the structure and properties of copolymers. In this study, the temperature-induced self-assembly of copolymer poly(N,N-dimethylacrylamide)-poly(diacetone acrylamide)(PDMAA_(30)-PDAAM_(60))_(2)in aqueous solution was monitored by near-infrared spectroscopy with water as a probe. The wavelet packet transform was employed to improve the spectral resolution. The spectral information of hydrated water surrounding the hydrophilic PDMAA and hydrophobic PDAAM blocks was then extracted, revealing the significant roles of water in morphological transition of the copolymer from spherical to worm-like micelles. Specifically, water molecules interacting with N atoms and C=O groups of the hydrophilic block gradually decrease during the morphological transition, while hydrogen-bond structures NH–CO of the hydrophobic block gradually break, bringing more water molecules into contact with the hydrophobic block. This work provides a foundation for exploring the role of water molecules during the self-assembly transition of complex block copolymers.
基金supported by National Natural Science Foundation of China under Grant U23A20279China Electronics Tian’ao Innovation Theory and Technology Group Fund under Grand 20221193-04-04.
文摘To overcome the challenges of poor real-time performance,limited scalability,and low intelligence in conventional jamming pattern recognition methods,this paper proposes a method based on Wavelet Packet Decomposition(WPD)and enhanced deep learning techniques.In the proposed method,an agent at the receiver processes the received signal using WPD to generate an initial Spectrogram Waterfall(SW),which is subsequently segmented using a sliding window to serve as the input for the jamming recognition network.The network employs a bilateral filter to preprocess the input SW,thereby enhancing the edge features of the jamming signals.To extract abstract features,depthwise separable convolution is utilized instead of traditional convolution,thereby reducing the network’s parameter count and enhancing real-time performance.A pyramid pooling layer is integrated before the fully connected layer to enable the network to process input SW of varying sizes,thus enhancing scalability.During network training,adaptive moment estimation is employed as the optimizer,allowing the network to dynamically adjust the learning rate and accelerate convergence.A comprehensive comparison between the proposed jamming recognition network and six other models is conducted,along with Ablation Experiments(AE)based on numerical simulations.Simulation results demonstrate that the proposed method based on WPD and enhanced deep learning achieves high-precision recognition of various jamming patterns while maintaining a favorable balance among prediction accuracy,network complexity,and prediction time.
基金supported by the Joint Funds of the National Natural Science Foundation of China under grant No.U22B2025.
文摘In the big data era,the surge in network traffic volume poses challenges for network management and cybersecurity.Network Traffic Classification(NTC)employs deep learning to categorize traffic data,aiding security and analysis systems as Intrusion Detection Systems(IDS)and Intrusion Prevention Systems(IPS).However,current NTC methods,based on isolated network simulations,usually fail to adapt to new protocols and applications and ignore the effects of network conditions and user behavior on traffic patterns.To improve network traffic management insights,federated learning frameworks have been proposed to aggregate diverse traffic data for collaborative model training.This approach faces challenges like data integrity,label noise,packet loss,and skewed data distributions.While label noise can be mitigated through the use of sophisticated traffic labeling tools,other issues such as packet loss and skewed data distributions encountered in Network Packet Brokers(NPB)can severely impede the efficacy of federated learning algorithms.In this paper,we introduced the Robust Traffic Classifier with Federated Contrastive Learning(FC-RTC),combining federated and contrastive learning methods.Using the Supcon-Loss function from contrastive learning,FC-RTC distinguishes between similar and dissimilar samples.Training by sample pairs,FC-RTC effectively updates when receiving corrupted traffic data with packet loss or disorder.In cases of sample imbalance,contrastive loss functions for similar samples reduce model bias towards higher proportion data.By addressing uneven data distribution and packet loss,our system enhances its capability to adapt and perform accurately in real-world network traffic analysis,meeting the specific demands of this complex field.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1602502)the National Natural Science Foundation of China(Grant No.12450404).
文摘Rotational dynamics simulations of neutral O_(2)molecules driven by linearly,elliptically and circularly polarized femtosecond pulsed lasers are carried out using a full quantum time-dependent wave packet evolution method.Here,the direction of laser propagation is set along the z axis,and the polarization plane is restricted to the xy plane.The results indicate that the alignment of O_(2)molecules in the z direction is weakly affected by varying the ellipticity when the total laser intensity is held constant.For rotation within the xy plane,the linearly polarized laser significantly excites rotational motion,with the degree of excitation increasing as the ellipticity increases.In contrast,under the influence of a circularly polarized laser,the angular distribution of O_(2)molecules in the xy plane remains isotropic.Additionally,the effects of the initial rotational quantum number,the temperature of the O_(2)molecules and the nuclear spin on laser-induced alignment are discussed.
基金supported by the National Natural Science Foundation of China(Grant Nos.12134005 and 12334011)the Major Research Plan of the National Natural Science Foundation of China(Grant No.92461301)。
文摘Light-induced conical intersections(LICIs)present a distinctive mechanism for nonadiabatic coupling,thereby facilitating ultrafast chemical reactions,including the indirect photodissociation of diatomic molecules.In contrast to static conical intersections,LICIs are dynamically tunable,providing a pathway for precise control of molecular dissociation.In this study,we employ the time-dependent quantum wave packet method to investigate the dissociation dynamics of the OH molecule,focusing on its ground state X^(2)Πand repulsive state 1^(2)Σ~-.By varying laser field parameters(intensity,full width at half maximum(FWHM),and wavelength),we elucidate how nonadiabatic coupling governs selective dissociation channel control.Our findings reveal that the choice of initial vibrational states and the tailoring of laser conditions significantly influence dissociation pathways,providing theoretical insights into manipulating molecular dynamics via LICIs.These results provide a foundation for future experimental studies and the development of advanced molecular control techniques.
文摘Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitoring.Frequent topology changes,high mobility,and limited energy availability pose significant challenges to maintaining stable and high-performance routing.Traditional routing protocols,such as Ad hoc On-Demand Distance Vector(AODV),Load-Balanced Optimized Predictive Ad hoc Routing(LB-OPAR),and Destination-Sequenced Distance Vector(DSDV),often experience performance degradation under such conditions.To address these limitations,this study evaluates the effectiveness of Dynamic Adaptive Routing(DAR),a protocol designed to adapt routing decisions in real time based on network dynamics and resource constraints.The research utilizes the Network Simulator 3(NS-3)platform to conduct controlled simulations,measuring key performance indicators such as latency,Packet Delivery Ratio(PDR),energy consumption,and throughput.Comparative analysis reveals that DAR consistently outperforms conventional protocols,achieving a 20%-30% reduction in latency,a 25% decrease in energy consumption,and marked improvements in throughput and PDR.These results highlight DAR’s ability to maintain high communication reliability while optimizing resource usage in challenging operational scenarios.By providing empirical evidence of DAR’s advantages in highly dynamic UAV network environments,this study contributes to advancing adaptive routing strategies.The findings not only validate DAR’s robustness and scalability but also lay the groundwork for integrating artificial intelligence-driven decision-making and real-world UAV deployment.Future work will explore cross-layer optimization,multi-UAV coordination,and experimental validation in field trials,aiming to further enhance communication resilience and energy efficiency in next-generation aerial networks.
