Composite water samples taken from Owena Multi-purpose Dam in six sampling campaigns covering the wet and dry seasons were analyzed for physico-chemical and microbial characteristics using standard methods for the exa...Composite water samples taken from Owena Multi-purpose Dam in six sampling campaigns covering the wet and dry seasons were analyzed for physico-chemical and microbial characteristics using standard methods for the examination of water and wastewater jointly published by the American Public Health Association, American Water Works Association and Water Pollution Control Federation. Results showed significant (p < 0.05) seasonal variations in most measured parameters with few showing significant spatial variation. The characteristics of the water from the dam lake revealed an acceptable quality for most measured parameters with low chemical pollutants burden when compared with drinking water standards and water quality for aquaculture. However, high values of turbidity, colour, iron, manganese and microbial load were recorded compared with drinking water standards, which call for proper treatment of the water before distribution for public consumption.展开更多
Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze mul...Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze multi-purpose plants. A simple approach is proposed to determine the utilization of shared resources and to reduce the equipment’s idle times. Three scenarios are presented to describe the proposed model. Generally, according to desire of a decision maker, different scenarios can be considered in the model to achieve to the expected design or plant configuration. The main characteristics of the proposed model are flexibility, the easiness of practical application and the simulation of the model in an easy way.展开更多
The effect of the positive bias on Reynolds stress （RS） and its effect on the radial turbulent transport at the edge plasma （r/a =0.9） and scrape-off layer （SOL） region of plasma in tokamak are investigated. The...The effect of the positive bias on Reynolds stress （RS） and its effect on the radial turbulent transport at the edge plasma （r/a =0.9） and scrape-off layer （SOL） region of plasma in tokamak are investigated. The radial and poloidal electric fields （Sr, Ep） and ion saturation current （Is） are measured by multi-purpose probe （MPP）. This probe is fabricated and constructed for the first time in the IR-T1 tokamak. The most advantage of this probe is that the variations of Er and Ep can be measured in different radii at the single shot. Thus the information of different radii can be compared with high precision. The bias voltage is fixed at Vbias = 200 V and it has been applied with the limiter bias that is fixed in r/a = 0.9. Moreover, the phase difference between radial and poloidal electric fields, and temporal evolution of the RS .spectrum detected by MPP are calculated. RS magnitude on the edge （r/a = 0.9） is more than its value in the SOL （r/a = 1.02）. With the applied bias 200 V, ItS and the magnitude of the phase difference between Er and Ep are increased, while the radial turbulent transport is decreased simultaneously. Thus it can be concluded that RS affects radial turbulence. Temporal evolution of the RS spectrum shows that the frequency of RS is increased and reaches its highest value at r/a=0.9 in the presence of bias.展开更多
Aimed at current deficiencies of multi-purpose guided missile kill probability model against gunship, the concept of the important coefficient of vulnerability blade unit is proposed in this paper. Laser fuze actuatio...Aimed at current deficiencies of multi-purpose guided missile kill probability model against gunship, the concept of the important coefficient of vulnerability blade unit is proposed in this paper. Laser fuze actuation model and warhead condition kill probability model of rotor blades are established by Monte Carlo method and kinetics theory with new ideas. Based on limited data, armor thickness of gunship is estimated, and a complete multi-purpose guided missile kill probability mathematical model is established, which provides necessary mathematical tool for the accurate and objective analysis of multi-purpose guided missile kill probability against gunship. Based on the establishment of the model, sensitivity analysis and optimal design of the main factors of multi-purpose guided missile kill probability are conducted, and the results show that the single multi-purpose guided missile lethality performance can be improved significantly by sensitivity analysis and optimization.展开更多
1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods s...Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods such as acupuncture and tuina.Even though TCM is used daily by more than 70,000 healthcare facilities and over 700,000 clinical practitioners in China,there is a poor understanding of the extent to which TCM diagnostic methods are used,how different treatment modalities are deployed in general,and what major factors may affect the integration of TCM and Western medicine.This study aimed to fill this void in the literature.Methods In the 2021 National Healthcare Improvement Evaluation Survey,we included three questions gauging the perception and practices of TCM amongst physicians working in TCM-related facilities,investigating the frequency of their deployment of TCM diagnostic methods,and predominant TCM treatment methods.Our empirical analysis included descriptive statistics,intergroup chi-square analysis,and binary logistic regression to examine the association between different types of facilities and individual characteristics and TCM utilization patterns.Results A total of 7618 clinical physicians comprised our study sample.Among them,84.27%have integrated TCM and Western medicine in their clinical practice,and 80.77%of TCM practitioners used the 4 diagnostic methods as a tool in their clinical practice.Chinese herbal medicine was the most widely utilized modality by Chinese TCM physicians(used by 88.49%of respondents),compared with the Chinese patent medicine and non-pharmacological TCM methods,which were used by 73.14%,and 69.39%,respectively.Herbal tea as an out-of-pocket health-maintenance intervention is also a notable practice,recommended by 29.43%of physicians.Significant variations exist across certain institutions,departments,and individual practitioners.Conclusion Given that most of the surveyed physicians integrated TCM with Western medicine in their clinical practices,the practice of“pure TCM”appears to be obsolete in China’s tertiary healthcare institutions.Notably,remarkable variation exists in the use of different TCM modalities across institutions and among individuals,which might be related to and thus limited by the practitioners’experience.Future research focusing on the efficacy and safety of TCM interventions for specific diseases,the development of standardized clinical guidelines,and the enhancement of TCM education and training are called for to optimize TCM-Western medicine integration.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
Progressing beyond the stowage and deployment of reflectors and designing for multiple deployed states result in reflector shape reconfiguration,thus allowing for new functions including radiation pattern reconfigurat...Progressing beyond the stowage and deployment of reflectors and designing for multiple deployed states result in reflector shape reconfiguration,thus allowing for new functions including radiation pattern reconfiguration,and is valuable for space applications such as satellite-based radar and communications.This paper introduces a concept for achieving the deployment and shape reconfiguration of a paraboloid reflector using a 7R-8R(revolute joint)truss network.By realizing reconfigurability mechanically,complex electronic systems such as phased arrays can be avoided,and adopting a single-degree-of-freedom(DOF)design further reduces the number of required actuators.The proposed reflector is axisymmetric and can be doubly curved.It comprises a flexible mesh surface supported by a rigid truss network constructed from 7R and 8R linkages.Approximation of multiple target surfaces is achieved by synthesizing the truss network dimensions using a multiobjective optimization approach.The non-dominated sorting genetic algorithm is used in conjunction with analytical dimension parameterization and forward kinematics computation to determine the optimal dimensions for the truss network.In the resulting designs,the reflector follows a single-DOF trajectory,on which it unfolds from a compact stowed bundle toward a deployed state approximating a doubly curved target surface,then onwards to additional deployed states approximating different target surfaces.Design studies are conducted to demonstrate the reflector’s ability to approximate different target surfaces and continuously transform between such surfaces.This study proposes a new method for reconfiguring reflector shape mechanically,thus uniquely reconfiguring the shape of a doubly curved surface and achieving both deployment and shape reconfiguration under a unified single-DOF motion.展开更多
The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove vario...The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove various space debris. For this purpose, this paper presents a tendon-actuated flexible deployable manipulator. The flexible manipulator consists of several deployable units connected by Cardan joints and actuated by tendons. Compared with the present technologies for capturing space debris such as rigid robotic arm or flying net, this flexible manipulator is deployable, reusable, lightweight and applicable to the capture of large space debris. In order to investigate its deployment dynamics, an accurate dynamic model of the flexible manipulator is established based on the natural coordinate formulation (NCF) and the absolute nodal coordinate formulation (ANCF). Subsequently, numerical simulations are carried out to study the effects of system parameters and the base satellite on its deployment dynamics. Finally, ground experiments for both deployment and bending of the flexible manipulator are conducted to verify its effectiveness and feasibility.展开更多
Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployab...Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployable mechanism with synchronization constraints.However,each deployable unit’s drive distribution and resistance load are uneven,and the forced synchronization constraints lead to the flexible deformation of rods and difficulties in the deployment scheme design.This paper introduces an asynchronous deployment scheme with a multi-DOF closed-chain deployable truss.The DOF of the truss is calculated,and the kinematic and dynamic models are established,considering the truss’s and cable net’s real-time coupling.An integrated solving algorithm for implicit differential-algebraic equations is proposed to solve the dynamic models.A prototype of a six-unit antenna was fabricated,and the experiment was carried out.The dynamic performances in synchronous and asynchronous deployment schemes are analyzed,and the results show that the cable resistance and truss kinetic energy impact under the asynchronous deployment scheme are minor,and the antenna is more straightforward to deploy.The work provides a new asynchronous deployment scheme and a universal antenna modeling method for dynamic design and performance improvement.展开更多
The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,wi...The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.展开更多
Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has b...Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.展开更多
In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployme...In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm(VFBA)using the classical four-node regular distribution as an entry point.The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity,reduce the premature maturity problem caused by population convergence,avoid the over aggregation of individuals in the local optimal region,and enhance the superiority in global search;the virtual force algorithm simulates the attraction and repulsion between individuals,which enables individual bats to precisely locate the optimal solution within the search space.At the same time,the fusion effect of virtual force prompts the bat individuals to move faster to the potential optimal solution.To validate the effectiveness of the fusion algorithm,the benchmark test function is selected for simulation testing.Finally,the simulation result verifies that the VFBA achieves superior coverage and effectively reduces node redundancy compared to the other three regular layout methods.The VFBA also shows better coverage results when compared to other optimization algorithms.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic ...Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic cell to design a family of inflatable origami tubular structures with the targeted configuration.First,the classification of rigid foldable degree-4 vertices is studied thoroughly.Since the proposed GMTC is comprised of forming units(FU)and linking units(LU),types of FUs and LUs are investigated based on the classification of degree-4 vertices,respectively.The rigid foldability of the GMTC is presented by studying the kinematics of the FUs and LUs.Volume of the GMTC is analyzed to investigate multistable configurations of the basic cell.The variations in volume of the GMTC offer great potential for developing the inflatable tubular structure.Design method and parametric optimization of the tubular structure with targeted configuration are proposed.The feasibility of the approach is validated by the approximation of four different cases,namely parabolic,semicircular,trapezoidal,and straight-arc hybrid tubular structures.展开更多
The exploitation of oil resources has now extended to ultra-deep formations,with depths even exceeding 10,000 m.During drilling operations,the bottomhole temperature(BHT)can surpass 240℃.Under such high-temperature c...The exploitation of oil resources has now extended to ultra-deep formations,with depths even exceeding 10,000 m.During drilling operations,the bottomhole temperature(BHT)can surpass 240℃.Under such high-temperature conditions,measurement while drilling(MWD)instruments are highly likely to malfunction due to the inadequate temperature resistance of their electronic components.As a wellbore temperature control approach,the application of thermal insulated drill pipe(TIDP)has been proposed to manage the wellbore temperature in ultra-deep wells.This paper developed a temperature field model for ultra-deep wells by coupling the interactions of multiple factors on the wellbore temperature.For the first time,five distinct TIDP deployment methods were proposed,and their corresponding wellbo re temperature variation characte ristics were investigated,and the heat transfer laws of the ultra-deep wellbore-formation system were quantitatively elucidated.The results revealed that TIDP can effectively restrain the rapid rise in the temperature of the drilling fluid inside the drill string by reducing the heat flux of the drill string.Among the five deployment methods,the method of deploying TIDP from the bottomhole upwards exhibits the best performance.For a 12,000 m simulated well,when6000 m of TIDP are deployed from the bottomhole upwards,the BHT decreases by 52℃,while the outlet temperature increases by merely 1℃.This not only achieves the objective of wellbore temperature control but also keeps the temperature of the drilling fluid at the outlet of annulus at a relatively low level,thereby reducing the requirements for the heat exchange equipment on the ground.The novel findings of this study provide significant guidance for wellbore temperature control in ultra-deep and ultra-high-temperature wells.展开更多
This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity a...This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity and those where PV installation would maximize global decarbonization benefits.This mismatch is discussed based on three key factors influencing decarbonization via PV technology:per capita gross domestic product;carbon intensity of the energy system;and solar resource availability.Current PV deployment is predominantly concentrated in economically advanced countries,and does not coincide with regions where the environmental and economic impact of such installations would be most significant.Through a series of thought experiments,it is demonstrated how alternative prioritization strategies could significantly reduce global carbon emissions.Argument is put forward for a globally coordinated approach to PV deployment,particularly targeting high-impact sunbelt regions,to enhance the efficacy of decarbonization efforts and promote equitable energy access.The study underscores the need for international policies that support sustainable energy transitions in economically less developed regions through workforce development and assistance with the activation of capital.展开更多
Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic...Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic sensing model that is more in line with the actual situation.First,the Voronoi diagram is constructed in the monitoring area to determine the Thiessen polygon of each node.Then,the virtual force on each node is calculated,and the node update its position according to the direction and size of the total force,so as to achieve the purpose of improving the network coverage rate.The simulation results show that the proposed algorithm can effectively improve the coverage rate of the network,and also has a good effect on the coverage uniformity.展开更多
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.展开更多
文摘Composite water samples taken from Owena Multi-purpose Dam in six sampling campaigns covering the wet and dry seasons were analyzed for physico-chemical and microbial characteristics using standard methods for the examination of water and wastewater jointly published by the American Public Health Association, American Water Works Association and Water Pollution Control Federation. Results showed significant (p < 0.05) seasonal variations in most measured parameters with few showing significant spatial variation. The characteristics of the water from the dam lake revealed an acceptable quality for most measured parameters with low chemical pollutants burden when compared with drinking water standards and water quality for aquaculture. However, high values of turbidity, colour, iron, manganese and microbial load were recorded compared with drinking water standards, which call for proper treatment of the water before distribution for public consumption.
文摘Designing of a multi-purpose plant as one of the well-known manufacturing systems is more challenging than other manufacturing systems. This paper applies a stochastic colored Petri net (CPN) to design and analyze multi-purpose plants. A simple approach is proposed to determine the utilization of shared resources and to reduce the equipment’s idle times. Three scenarios are presented to describe the proposed model. Generally, according to desire of a decision maker, different scenarios can be considered in the model to achieve to the expected design or plant configuration. The main characteristics of the proposed model are flexibility, the easiness of practical application and the simulation of the model in an easy way.
文摘The effect of the positive bias on Reynolds stress （RS） and its effect on the radial turbulent transport at the edge plasma （r/a =0.9） and scrape-off layer （SOL） region of plasma in tokamak are investigated. The radial and poloidal electric fields （Sr, Ep） and ion saturation current （Is） are measured by multi-purpose probe （MPP）. This probe is fabricated and constructed for the first time in the IR-T1 tokamak. The most advantage of this probe is that the variations of Er and Ep can be measured in different radii at the single shot. Thus the information of different radii can be compared with high precision. The bias voltage is fixed at Vbias = 200 V and it has been applied with the limiter bias that is fixed in r/a = 0.9. Moreover, the phase difference between radial and poloidal electric fields, and temporal evolution of the RS .spectrum detected by MPP are calculated. RS magnitude on the edge （r/a = 0.9） is more than its value in the SOL （r/a = 1.02）. With the applied bias 200 V, ItS and the magnitude of the phase difference between Er and Ep are increased, while the radial turbulent transport is decreased simultaneously. Thus it can be concluded that RS affects radial turbulence. Temporal evolution of the RS spectrum shows that the frequency of RS is increased and reaches its highest value at r/a=0.9 in the presence of bias.
文摘Aimed at current deficiencies of multi-purpose guided missile kill probability model against gunship, the concept of the important coefficient of vulnerability blade unit is proposed in this paper. Laser fuze actuation model and warhead condition kill probability model of rotor blades are established by Monte Carlo method and kinetics theory with new ideas. Based on limited data, armor thickness of gunship is estimated, and a complete multi-purpose guided missile kill probability mathematical model is established, which provides necessary mathematical tool for the accurate and objective analysis of multi-purpose guided missile kill probability against gunship. Based on the establishment of the model, sensitivity analysis and optimal design of the main factors of multi-purpose guided missile kill probability are conducted, and the results show that the single multi-purpose guided missile lethality performance can be improved significantly by sensitivity analysis and optimization.
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金The Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences——A Strategic Study on Healthy China Development and Health System Reform(2021-I2M-1-046).
文摘Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods such as acupuncture and tuina.Even though TCM is used daily by more than 70,000 healthcare facilities and over 700,000 clinical practitioners in China,there is a poor understanding of the extent to which TCM diagnostic methods are used,how different treatment modalities are deployed in general,and what major factors may affect the integration of TCM and Western medicine.This study aimed to fill this void in the literature.Methods In the 2021 National Healthcare Improvement Evaluation Survey,we included three questions gauging the perception and practices of TCM amongst physicians working in TCM-related facilities,investigating the frequency of their deployment of TCM diagnostic methods,and predominant TCM treatment methods.Our empirical analysis included descriptive statistics,intergroup chi-square analysis,and binary logistic regression to examine the association between different types of facilities and individual characteristics and TCM utilization patterns.Results A total of 7618 clinical physicians comprised our study sample.Among them,84.27%have integrated TCM and Western medicine in their clinical practice,and 80.77%of TCM practitioners used the 4 diagnostic methods as a tool in their clinical practice.Chinese herbal medicine was the most widely utilized modality by Chinese TCM physicians(used by 88.49%of respondents),compared with the Chinese patent medicine and non-pharmacological TCM methods,which were used by 73.14%,and 69.39%,respectively.Herbal tea as an out-of-pocket health-maintenance intervention is also a notable practice,recommended by 29.43%of physicians.Significant variations exist across certain institutions,departments,and individual practitioners.Conclusion Given that most of the surveyed physicians integrated TCM with Western medicine in their clinical practices,the practice of“pure TCM”appears to be obsolete in China’s tertiary healthcare institutions.Notably,remarkable variation exists in the use of different TCM modalities across institutions and among individuals,which might be related to and thus limited by the practitioners’experience.Future research focusing on the efficacy and safety of TCM interventions for specific diseases,the development of standardized clinical guidelines,and the enhancement of TCM education and training are called for to optimize TCM-Western medicine integration.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
基金Supported by National Natural Science Foundation of China(Grant Nos.52320105005,52035008)the New Cornerstone Science Foundation through the Xplorer Prize(Grant No.XPLORER-2020-1035).
文摘Progressing beyond the stowage and deployment of reflectors and designing for multiple deployed states result in reflector shape reconfiguration,thus allowing for new functions including radiation pattern reconfiguration,and is valuable for space applications such as satellite-based radar and communications.This paper introduces a concept for achieving the deployment and shape reconfiguration of a paraboloid reflector using a 7R-8R(revolute joint)truss network.By realizing reconfigurability mechanically,complex electronic systems such as phased arrays can be avoided,and adopting a single-degree-of-freedom(DOF)design further reduces the number of required actuators.The proposed reflector is axisymmetric and can be doubly curved.It comprises a flexible mesh surface supported by a rigid truss network constructed from 7R and 8R linkages.Approximation of multiple target surfaces is achieved by synthesizing the truss network dimensions using a multiobjective optimization approach.The non-dominated sorting genetic algorithm is used in conjunction with analytical dimension parameterization and forward kinematics computation to determine the optimal dimensions for the truss network.In the resulting designs,the reflector follows a single-DOF trajectory,on which it unfolds from a compact stowed bundle toward a deployed state approximating a doubly curved target surface,then onwards to additional deployed states approximating different target surfaces.Design studies are conducted to demonstrate the reflector’s ability to approximate different target surfaces and continuously transform between such surfaces.This study proposes a new method for reconfiguring reflector shape mechanically,thus uniquely reconfiguring the shape of a doubly curved surface and achieving both deployment and shape reconfiguration under a unified single-DOF motion.
基金the National Natural Science Foundation of China(Nos.11832005,12372042,12232011)Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)+1 种基金the Fundamental Research Funds for the Central Universities(No.NS2023002)State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics)(No.MCAS-S-0223K04).
文摘The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove various space debris. For this purpose, this paper presents a tendon-actuated flexible deployable manipulator. The flexible manipulator consists of several deployable units connected by Cardan joints and actuated by tendons. Compared with the present technologies for capturing space debris such as rigid robotic arm or flying net, this flexible manipulator is deployable, reusable, lightweight and applicable to the capture of large space debris. In order to investigate its deployment dynamics, an accurate dynamic model of the flexible manipulator is established based on the natural coordinate formulation (NCF) and the absolute nodal coordinate formulation (ANCF). Subsequently, numerical simulations are carried out to study the effects of system parameters and the base satellite on its deployment dynamics. Finally, ground experiments for both deployment and bending of the flexible manipulator are conducted to verify its effectiveness and feasibility.
基金supported by the National Key R&D Program of China(Grant No.2023YFB3407103)the National Natural Science Foundation of China(Grant Nos.52175242 and 52175027)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(Grant No.2022QNRC001).
文摘Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployable mechanism with synchronization constraints.However,each deployable unit’s drive distribution and resistance load are uneven,and the forced synchronization constraints lead to the flexible deformation of rods and difficulties in the deployment scheme design.This paper introduces an asynchronous deployment scheme with a multi-DOF closed-chain deployable truss.The DOF of the truss is calculated,and the kinematic and dynamic models are established,considering the truss’s and cable net’s real-time coupling.An integrated solving algorithm for implicit differential-algebraic equations is proposed to solve the dynamic models.A prototype of a six-unit antenna was fabricated,and the experiment was carried out.The dynamic performances in synchronous and asynchronous deployment schemes are analyzed,and the results show that the cable resistance and truss kinetic energy impact under the asynchronous deployment scheme are minor,and the antenna is more straightforward to deploy.The work provides a new asynchronous deployment scheme and a universal antenna modeling method for dynamic design and performance improvement.
基金co-supported by the Natural Science Basic Research Program of Shaanxi,China(No.2023-JC-QN-0043)the ND Basic Research Funds,China(No.G2022WD).
文摘The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.
基金support of the Natural Science Foundation of Jiangsu Province,China(BK20240977)the China Scholarship Council(201606850024)+1 种基金the National High Technology Research and Development Program of China(2016YFD0701003)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1488)。
文摘Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.
基金supported in part by the National Natural Science Foundation of China under Grant No.62271453in part by the National Natural Science Foundation of China No.62101512+2 种基金in part by the Central Support for Local Projects under Grant No.YDZJSX2024D031in part by Project supported by the Shanxi Provincial Foundation for Leaders of Disciplines in Science,China under Grant No.2024Q022in part by Shanxi Province Patent Conversion Special Plan Funding Projects under Grant No.202405004。
文摘In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm(VFBA)using the classical four-node regular distribution as an entry point.The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity,reduce the premature maturity problem caused by population convergence,avoid the over aggregation of individuals in the local optimal region,and enhance the superiority in global search;the virtual force algorithm simulates the attraction and repulsion between individuals,which enables individual bats to precisely locate the optimal solution within the search space.At the same time,the fusion effect of virtual force prompts the bat individuals to move faster to the potential optimal solution.To validate the effectiveness of the fusion algorithm,the benchmark test function is selected for simulation testing.Finally,the simulation result verifies that the VFBA achieves superior coverage and effectively reduces node redundancy compared to the other three regular layout methods.The VFBA also shows better coverage results when compared to other optimization algorithms.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
基金supported by the National Natural Science Foundation of China(No.52222501,52075016,52192632)the Fundamental Research Funds for the Central Universities(Grant No.YWF-23-L-904).
文摘Inflatable deployable structures inspired by origami have significant applications in space missions such as solar arrays and antennas.In this paper,a generalized Miura-ori tubular cell(GMTC)is presented as the basic cell to design a family of inflatable origami tubular structures with the targeted configuration.First,the classification of rigid foldable degree-4 vertices is studied thoroughly.Since the proposed GMTC is comprised of forming units(FU)and linking units(LU),types of FUs and LUs are investigated based on the classification of degree-4 vertices,respectively.The rigid foldability of the GMTC is presented by studying the kinematics of the FUs and LUs.Volume of the GMTC is analyzed to investigate multistable configurations of the basic cell.The variations in volume of the GMTC offer great potential for developing the inflatable tubular structure.Design method and parametric optimization of the tubular structure with targeted configuration are proposed.The feasibility of the approach is validated by the approximation of four different cases,namely parabolic,semicircular,trapezoidal,and straight-arc hybrid tubular structures.
基金supported by the National Natural Science Foundation of China(Grant No.U22B2072)Research Project of China Petroleum Science and Technology Innovation Fund(Grant No.2025DQ02-0144)。
文摘The exploitation of oil resources has now extended to ultra-deep formations,with depths even exceeding 10,000 m.During drilling operations,the bottomhole temperature(BHT)can surpass 240℃.Under such high-temperature conditions,measurement while drilling(MWD)instruments are highly likely to malfunction due to the inadequate temperature resistance of their electronic components.As a wellbore temperature control approach,the application of thermal insulated drill pipe(TIDP)has been proposed to manage the wellbore temperature in ultra-deep wells.This paper developed a temperature field model for ultra-deep wells by coupling the interactions of multiple factors on the wellbore temperature.For the first time,five distinct TIDP deployment methods were proposed,and their corresponding wellbo re temperature variation characte ristics were investigated,and the heat transfer laws of the ultra-deep wellbore-formation system were quantitatively elucidated.The results revealed that TIDP can effectively restrain the rapid rise in the temperature of the drilling fluid inside the drill string by reducing the heat flux of the drill string.Among the five deployment methods,the method of deploying TIDP from the bottomhole upwards exhibits the best performance.For a 12,000 m simulated well,when6000 m of TIDP are deployed from the bottomhole upwards,the BHT decreases by 52℃,while the outlet temperature increases by merely 1℃.This not only achieves the objective of wellbore temperature control but also keeps the temperature of the drilling fluid at the outlet of annulus at a relatively low level,thereby reducing the requirements for the heat exchange equipment on the ground.The novel findings of this study provide significant guidance for wellbore temperature control in ultra-deep and ultra-high-temperature wells.
基金supported by the Helmholtz Association within the framework of the innovation platform“Solar TAP”[Az:714-62150-3/1(2023)]co-funded by the European Union(ERC,C2C-PV,project number 101088359)。
文摘This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity and those where PV installation would maximize global decarbonization benefits.This mismatch is discussed based on three key factors influencing decarbonization via PV technology:per capita gross domestic product;carbon intensity of the energy system;and solar resource availability.Current PV deployment is predominantly concentrated in economically advanced countries,and does not coincide with regions where the environmental and economic impact of such installations would be most significant.Through a series of thought experiments,it is demonstrated how alternative prioritization strategies could significantly reduce global carbon emissions.Argument is put forward for a globally coordinated approach to PV deployment,particularly targeting high-impact sunbelt regions,to enhance the efficacy of decarbonization efforts and promote equitable energy access.The study underscores the need for international policies that support sustainable energy transitions in economically less developed regions through workforce development and assistance with the activation of capital.
基金supported by National Natural Science Foundation of China(No.61862038)Lanzhou Talent Innovation and Entrepreneurship Technology Plan Project(No.2019-RC-14).
文摘Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic sensing model that is more in line with the actual situation.First,the Voronoi diagram is constructed in the monitoring area to determine the Thiessen polygon of each node.Then,the virtual force on each node is calculated,and the node update its position according to the direction and size of the total force,so as to achieve the purpose of improving the network coverage rate.The simulation results show that the proposed algorithm can effectively improve the coverage rate of the network,and also has a good effect on the coverage uniformity.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
