IMPLEMENTING SECURITY FOR ACTIVE NETWORKS IN INTERNET

Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

GPS Rapid Static and Kinematic Positioning Based on GPS Active Network

This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrections to user measurements,based on the location of the user.Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24_hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.

A Cluster-Based Secure Active Network Environment

We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallely processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

A Novel Active Network Architecture Based on Extensible Services Router

Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.

HSCP:a hardware and software combined platform to improve precision in active network measurement

In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy to program,which retains software flexibility at the same time.By improving the precision of packet timestamp programmable hardware equipment,it provides packet sending control more accurately and supports the microsecond packet interval.We have implemented a model on the NetMagic platform,and done some experiments to analyze the accuracy difference of the user,the kernel and hardware timestamp.

An Identified Study on the Active Network of a Thermoacoustic Regenerator

An active thermo-acoustic network model of regenerator which is a key component to accomplish the con-version between thermal-and acoustic power in thermo-acoustic system has been established in this paper. The experiment was carried out to quantify the network. A method called least square is employed in order to identify the H matrix describing the system. The results obtained here show that the active thermo-acoustic network can reliably depict the characteristics of a thermo-acoustic system.

EFFICIENT SIMULATION AND OPTIMIZATION OF LINEAR ACTIVE NETWORKS

An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to solve a high dimension linear algebra equation.Animportant characteristic in circuit optimization is that the number of independently tunableparameters is small.In terms of the property of linear networks,the circuit is described by amultiport network in the presented method,and the hybrid matrix is established.The dimensionof the equation to be solved is the same as the number of optimization parameters in objectivefunction evaluations,which provides a fast simulation tool for optimization.

Vibration Suppression for Active Magnetic Bearings Using Adaptive Filter with Iterative Search Algorithm

Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.

A Statistical Study of Magnetic Flux Emergence in Solar Active Regions Prior to Strongest Flares

Using the data on magnetic field maps and continuum intensity for Solar Cycles 23 and 24,we explored 100 active regions(ARs)that produced M5.0 or stronger flares.We focus on the presence/absence of the emergence of magnetic flux in these ARs 2-3 days before the strong flare onset.We found that 29 ARs in the sample emerged monotonically amidst quiet-Sun.A major emergence of a new magnetic flux within a pre-existing AR yielding the formation of a complex flare-productive configuration was observed in another 24 cases.For 30 ARs,an insignificant(in terms of the total magnetic flux of pre-existing AR)emergence of a new magnetic flux within the pre-existing magnetic configuration was observed;for some of them the emergence resulted in a formation of a configuration with a small δ-sunspot;11 out of 100 ARs exhibited no signatures of magnetic flux emergence during the entire interval of observation.In six cases the emergence was in progress when the AR appeared on the Eastern limb,so that the classification and timing of emergence were not possible.We conclude that the recent flux emergence is not a necessary and/or sufficient condition for strong flaring of an AR.The flux emergence rate of flare-productive ARs analyzed here was compared with that of flare-quiet ARs analyzed in our previous studies.We revealed that the flare-productive ARs tend to display faster emergence than the flare-quiet ones do.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

“ACTIVE”英语学科育人模式构建与应用

本研究以“立德树人”为核心理念,构建“ACTIVE”英语学科育人模式。该模式通过六个关键维度--学科育人(AIM)、文化浸润(Culture)、思维可见(Thinking)、技术融合(Integration)、美德根植(Virtue)和情感共鸣(Empathy)--全面激发学生英语学习的热情,培养他们的语言能力,同时注重道德品质的熏陶和文化素养的提升,促进英语学科素养落地。本研究不仅为英语教学实践提供了新的视角,也为其他学科育人模式的构建提供了有益的参考和借鉴。

Liquid crystal-integrated metasurfaces for an active photonic platform

Metasurfaces have opened the door to next-generation optical devices due to their ability to dramatically modulate electromagnetic waves at will using periodically arranged nanostructures.However,metasurfaces typically have static optical responses with fixed geometries of nanostructures,which poses challenges for implementing transition to technology by replacing conventional optical components.To solve this problem,liquid crystals(LCs)have been actively employed for designing tunable metasurfaces using their adjustable birefringent in real time.Here,we review recent studies on LCpowered tunable metasurfaces,which are categorized as wavefront tuning and spectral tuning.Compared to numerous reviews on tunable metasurfaces,this review intensively explores recent development of LC-integrated metasurfaces.At the end of this review,we briefly introduce the latest research trends on LC-powered metasurfaces and suggest further directions for improving LCs.We hope that this review will accelerate the development of new and innovative LC-powered devices.

Variation in the permafrost active layer over the Tibetan Plateau during 1980–2020

The active layer,acting as an intermediary of water and heat exchange between permafrost and atmosphere,greatly influences biogeochemical cycles in permafrost areas and is notably sensitive to climate fluctuations.Utilizing the Chinese Meteorological Forcing Dataset to drive the Community Land Model,version 5.0,this study simulates the spatial and temporal characteristics of active layer thickness(ALT)on the Tibetan Plateau(TP)from 1980 to 2020.Results show that the ALT,primarily observed in the central and western parts of the TP where there are insufficient station observations,exhibits significant interdecadal changes after 2000.The average thickness on the TP decreases from 2.54 m during 1980–1999 to 2.28 m during 2000–2020.This change is mainly observed in the western permafrost region,displaying a sharp regional inconsistency compared to the eastern region.A persistent increasing trend of ALT is found in the eastern permafrost region,rather than an interdecadal change.The aforementioned changes in ALT are closely tied to the variations in the surrounding atmospheric environment,particularly air temperature.Additionally,the area of the active layer on the TP displays a profound interdecadal change around 2000,arising from the permafrost thawing and forming.It consistently decreases before 2000 but barely changes after 2000.The regional variation in the permafrost active layer over the TP revealed in this study indicates a complex response of the contemporary climate under global warming.

An active high-static-low-dynamic-stiffness vibration isolator with adjustable buckling beams:theory and experiment

High-static-low-dynamic-stiffness(HSLDS)vibration isolators with buckling beams have been widely used to isolate external vibrations.An active adjustable device composed of proportion integration(PI)active controllers and piezoelectric actuators is proposed for improving the negative stiffness stroke of buckling beams.A nonlinear output frequency response function is used to analyze the effect of the vibration reduction.The prototype of the active HSLDS device is built,and the verification experiment is conducted.The results show that compared with the traditional HSLDS vibration isolator,the active HSLDS device can broaden the isolation frequency bandwidth,and effectively reduce the resonant amplitude by adjusting the active control parameters.The maximum vibration reduction rate of the active HSLDS vibration isolator can attain 89.9%,and the resonant frequency can be reduced from 31.08 Hz to 13.28 Hz.Therefore,this paper devotes to providing a new design scheme for enhanced HSLDS vibration isolators.

Artificial Intelligence and Internet of Things Enabled Intelligent Framework for Active and Healthy Living

Obesity poses several challenges to healthcare and the well-being of individuals.It can be linked to several life-threatening diseases.Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss.State-of-the-art technologies have the potential for long-term benefits in post-surgery living.In this work,an Internet of Things(IoT)framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight.The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the patients.It also attempts to automate the data analysis and represent the facts about a patient.The IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the system.The proposed IoT framework also benefits from machine learning based activity classification systems,with relatively high accuracy,which allow the communicated data to be translated into meaningful information.

Synchronization coexistence in a Rulkov neural network based on locally active discrete memristor

At present, many neuron models have been proposed, which can be divided into discrete neuron models and continuous neuron models. Discrete neuron models have the advantage of faster simulation speed and the ease of understanding complex dynamic phenomena. Due to the properties of memorability, nonvolatility, and local activity, locally active discrete memristors(LADMs) are also suitable for simulating synapses. In this paper, we use an LADM to mimic synapses and establish a Rulkov neural network model. It is found that the change of coupling strength and the initial state of the LADM leads to multiple firing patterns of the neural network. In addition, considering the influence of neural network parameters and the initial state of the LADM, numerical analysis methods such as phase diagram and timing diagram are used to study the phase synchronization. As the system parameters and the initial states of the LADM change, the LADM coupled Rulkov neural network exhibits synchronization transition and synchronization coexistence.

Active components of Bupleuri Radix in the treatment of schizophrenia analyzed by network pharmacology and clinical verification

Background:Bupleuri Radix is a common Chinese medicinal material in traditional Chinese medicine.Currently,the therapeutic effect of treating schizophrenia is relatively well understood.However,there are fewer studies examining the underlying mechanisms of its treatment.The objective of the study was to investigate the primary mechanisms of Bupleuri Radix in treating schizophrenia through network pharmacology and clinical validation.Method:Network pharmacology revealed possible molecular mechanisms,followed by clinical verification.Sixty-seven schizophrenia patients undergoing treatment at the Hunan Brain Hospital between October and November 2022 were recruited and randomly divided into the olanzapine group and the olanzapine+Bupleuri Radix group.Additionally,32 healthy people undergoing physical examinations during the same period were included as the control group.The patient’s positive and negative symptom scale scores were compared.qPCR was used to detect the mRNA expression levels of ESR1,mTOR,EIF4E,and SMAD4 in peripheral blood.Results:Through network pharmacological analysis,it was concluded in this study that Bupleuri Radix might regulate the mTOR,PI3K-Akt,and HIF-1 signaling pathways.Clinical experiments indicated that compared with before treatment,the positive and negative symptom scale scores and total scores of the two treatment groups were significantly decreased after treatment(P<0.01).In addition,the positive and negative symptom scale scores and total scores in the olanzapine+Bupleuri Radix group were significantly decreased(P<0.01)compared to the olanzapine group after treatment.Before treatment,ESR1 mRNA expression levels in peripheral blood were significantly higher in the two treatment groups than in the control group,whereas the mRNA expression levels of mTOR,EIF4E,and SMAD4 in peripheral blood were significantly lower(P<0.01).The mRNA expression levels of mTOR,EIF4E,and SMAD4 in peripheral blood were significantly higher after therapy than before treatment,whereas the mRNA expression levels of ESR1 in peripheral blood were significantly lower(P<0.01).After therapy,the olanzapine+Bupleuri Radix group’s mRNA expression levels of mTOR,EIF4E,and SMAD4 were significantly higher than those of the olanzapine group,whereas the mRNA expression levels of ESR1 were significantly lower(P<0.01).Conclusion:The mechanism of Bupleuri Radix’s therapeutic efficacy in schizophrenia may involve the up-regulation of mTOR,EIF4E,and SMAD4 mRNA expression and the down-regulation of ESR1 mRNA expression in peripheral blood.

Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.

Blockchain-Based Power Transaction Method for Active Distribution Network

A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.