Man-machine Function Allocation Based on Uncertain Linguistic Multiple Attribute Decision Making

Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective, reliable and inexpensive. Therefore, our research mainly focuses on the problems of function allocation between man and machine in man-machine systems, analyses each capability advantage of man and machine according to their respective inherent characteristics and makes a comparison between them. In view of highly uncertain characteristics of decision attribute value in the practical process, we introduce the uncertain linguistic multiple attribute decision making （ULMADM） method in the function allocation process. Meanwhile, we also use the uncertain extended weighted arithmetic averaging （UEWAA） method to determine the automation level range of the operator functions. Then, we eventually estab- lish the automation level of man-machine function allocation by using the multi-attribute decision making algorithm, which is combined by UEWAA and uncertain linguistic hybrid aggregation （ULHA） operators. Finally, an example about function allocation is given, that is, fault diagnosis in the cockpit of civil aircraft. The final result of the example demonstrates that the proposed method about function allocation is feasible and effective.

An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both localand global allocation of resources in data centers.Hence,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in datacenters.Our approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant resources.With the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.

Differences in functional traits and reproductive allocations between native and invasive plants

Because co-occurring native and invasive plants are subjected to similar environmental selection pressures,the differences in functional traits and reproductive allocation strategies between native and invasive plants may be closely related to the success of the latter.Accordingly,this study examines differences in functional traits and reproductive allocation strategies between native and invasive plants in Eastern China.Plant height,branch number,reproductive branch number,the belowground-to-aboveground biomass ratio,and the reproductive allocation coefficient of invasive plants were all notably higher than those of native species.Additionally,the specific leaf area(SLA)values of invasive plants were remarkably lower than those of native species.Plasticity indexes of SLA,maximum branch angle,and branch number of invasive plants were each notably lower than those of native species.The reproductive allocation coefficient was positively correlated with reproductive branch number and the belowground-to-aboveground biomass ratio but exhibited negative correlations with SLA and aboveground biomass.Plant height,branch number,reproductive branch number,the belowground-to-aboveground biomass ratio,and the reproductive allocation coefficient of invasive plants may strongly influence the success of their invasions.

Comprehensive Reliability Allocation Method for CNC Lathes Based on Cubic Transformed Functions of Failure Mode and Effects Analysis

Reliability allocation of computerized numerical controlled（CNC）lathes is very important in industry.Traditional allocation methods only focus on high-failure rate components rather than moderate failure rate components,which is not applicable in some conditions.Aiming at solving the problem of CNC lathes reliability allocating,a comprehensive reliability allocation method based on cubic transformed functions of failure modes and effects analysis（FMEA）is presented.Firstly,conventional reliability allocation methods are introduced.Then the limitations of direct combination of comprehensive allocation method with the exponential transformed FMEA method are investigated.Subsequently,a cubic transformed function is established in order to overcome these limitations.Properties of the new transformed functions are discussed by considering the failure severity and the failure occurrence.Designers can choose appropriate transform amplitudes according to their requirements.Finally,a CNC lathe and a spindle system are used as an example to verify the new allocation method.Seven criteria are considered to compare the results of the new method with traditional methods.The allocation results indicate that the new method is more flexible than traditional methods.By employing the new cubic transformed function,the method covers a wider range of problems in CNC reliability allocation without losing the advantages of traditional methods.

Adaptive Resource Allocation Algorithm for 5G Vehicular Cloud Communication

The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.

Study on functions and rational allocation of Shule River Basin groundwater resources

Based on Investigation and Assessment on Rational Exploitation and Utilization of Groundwater Resources in Typical Areas of the Hexi Corridor, the thesis studies on groundwater and environmental problems arising from the large-scale agricultural development projects in Shule River Basin. The thesis analyzes problems in exploiting and utilizing water resources, defines the function zoning of groundwater resources in key areas and evaluates them. Finally, the thesis uses three-dimensional unsteady flow simulation and regional social and economic development plan to study on the allocation of groundwater in Shule River Basin. A proposal for rational allocation of Shule River Basin water resources has been put forward.

Resource Allocation Using SPA Based on Different Cost Functions in Elastic Optical Networks

Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.

Comprehensive Utility Function for Resource Allocation in Mobile Edge Computing

In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.

Resource allocation based on fairness and QoS provisioning for OFDMA-WLAN system

To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm based on fairness and quality of service QoS provisioning is proposed. Different QoS requirements are converted into different rate requirements to calculate the QoSs atisfaction level.The optimization object is revised as a fairness-driven resource optimization function to provide fairness. The complex resource allocation problem is divided into channel allocation and power assignment sub-problems. The sub-problems are solved by the bipartite graph matching and water-filling based method.Compared with other algorithms the proposed algorithm sacrifices less data rate for higher fairnes and QoS satisfaction.The sim ulation results show that the proposed algorithm is capableo fp rovi ding QoS and fairness and performs better in a tradeoff among QoS fairness and data rate.

Non-dominated sorting quantum particle swarm optimization and its application in cognitive radio spectrum allocation

In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.

Two-Stage Resource Allocation Scheme for Three-Tier Ultra-Dense Network

In 5 G Ultra-dense Network(UDN), resource allocation is an efficient method to manage inter-small-cell interference. In this paper, a two-stage resource allocation scheme is proposed to supervise interference and resource allocation while establishing a realistic scenario of three-tier heterogeneous network architecture. The scheme consists of two stages: in stage I, a two-level sub-channel allocation algorithm and a power control method based on the logarithmic function are applied to allocate resource for Macrocell and Picocells, guaranteeing the minimum system capacity by considering the power limitation and interference coordination; in stage II, an interference management approach based on K-means clustering is introduced to divide Femtocells into different clusters. Then, a prior sub-channel allocation algorithm is employed for Femtocells in diverse clusters to mitigate the interference and promote system performance. Simulation results show that the proposed scheme contributes to the enhancement of system throughput and spectrum efficiency while ensuring the system energy efficiency.

Fast Convergence Resource Allocation in IEEE 802.16 OFDMA Systems with Minimum Rate Guarantee

Resource allocation in the context of OFDMA-based systems is challenging, given a combinatorial nature of the problem. In the context of IEEE 802.16 systems this problem is further exacerbated by additional constraints that are faced with its two dimensional frame nature. The main challenges associated with resource allocation in these systems are: mapping the allocated bandwidth resources to users in this two dimensional frame, power and frequency allocation, and Qo S guarantee. This optimization problem can usually be solved by an iterative algorithm. The solutions proposed have a constant step size in iterations which causes a long convergence time. For this reason, the solutions proposed are not applicable in IEEE 802.16 systems. In this paper we propose a novel resource allocation algorithm in IEEE 802.16 systems which has an adaptive step size in iterations while taking into account the minimum rate guarantee for users.

Utility-based and fairness-aware radio resource allocation in OFDMA cellular relay networks with traffic prioritization

The combination of orthogonal frequency division multiple access(OFDMA) with relaying techniques provides plentiful opportunities for high-performance and cost-effective networks.It requires intelligent radio resource management schemes to harness these opportunities.This paper investigates the utility-based resource allocation problem in a real-time and non-real-time traffics mixed OFDMA cellular relay network to exploit the potentiality of relay.In order to apply utility theory to obtain an efficient tradeoff between throughput and fairness as well as satisfy the delay requirements of real-time traffics,a joint routing and scheduling scheme is proposed to resolve the resource allocation problem.Additionally,a low-complexity iterative algorithm is introduced to realize the scheme.The numerical results indicate that besides meeting the delay requirements of real-time traffic,the scheme can achieve the tradeoff between throughput and fairness effectively.

Multi-QoS Guaranteed Resource Allocation for Multi-Services Based on Opportunity Costs

To meet the booming development of diversified services and new applications in the future, the fifth-generation mobile conmmnication system （5G） has arisen. Resources are increasingly scarce in the @namic time-varying of 5G networks. Allocating resources effectively and ensuring quality of service （QoS） requirements of multi-seiwices come to be a research focus. In this paper, we utilize effective capacity to build a utility function with multi-QoS metrics, including rate, delay bound and packet loss ratio. Taking advantage of opportunity cost （OC）, we also propose a multi-QoS guaranteed resource allocation algm＇ithm for multi-services to consider the future condition of system. In the algorithm, according to different business characteristics and the theory of OC, we propose different selection conditions for QoS users and best effort （BE） users to choose more reasonable resources. Finally, simulation results show that our proposed algorithm achieves superior system utility and relatively better fairness in multi-service scenarios.

An RVT-based power allocation method for dynamic LEO-MEO links

Optimizing the power resources allocation method of low earth orbit(LEO)satellites to medium earth orbit(MEO)satellite'links is a significant way to construct efficient satellite constellations for satellite communication.A game theory power allocation method based on remaining visible time(RVT)of LEO-MEO satellites is proposed.Firstly,one LEO-MEO satellite network is classified as a cluster in which the RVT of LEO satellites is modeled.Secondly,the cost function of RVT concerning the character of orbit and throughput in each LEO satellite is mainly designed,which gives greater punishment of utility value to LEO satellites with less RVT and is an essential part of the reasonable utility function applied in diverse motion scenes.Meanwhile,the existence of Nash equilibrium for the proposed utility function in game theory area is proved.Thirdly,an off-cluster scheme for LEO satellites through the proposed threshold is raised to ensure the overall utility value of the whole LEO satellites in cluster.Finally,the performance improvement of the proposed algorithm to the baseline algorithm is verified through simulations in different scenarios.

Utility-optimization dynamic subcarrier allocation algorithm for SC-FDMA systems

Two utility-optimization dynamic subcarrier allocation(DSA) algorithms are designed for single carrier frequency division multiple access system(SC-FDMA).The two proposed algorithms aim to support diverse transmission capacity requirements in wireless networks,which consider both the channel state information(CSI) and the capacity requirements of each user by setting appropriate utility functions.Simulation results show that with considerable lower computational complexity,the first utility-optimization algorithm can meet the system capacity requirements of each user effectively.However,the rate-sum capacity performance is poor.Furthermore,the second proposed utility-optimization algorithm can contribute a better trade-off between system rate-sum capacity requirement and the capacity requirements of each user by introducing the signal to noise ratio(SNR) information to the utility function based on the first utility-optimization algorithm,which can improve the user requirements processing capability as well as achieve a better sum-rate capacity.

Service Function Chain Migration in LEO Satellite Networks

With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.

The Effects of Electroacupuncture at the Heart Meridian on Myocardial Contractile Function in Rabbits with Myocardial Ischemia

Acute myocardial ischemia was induced by intravenous injection of pituitrin, and electroacupuncture (EA) was applied at the Heart and Lung Meridians (HM and LM), 3 points on each meridian. The changes in the left intraventricular pressure (LVP), the maximum rise rate of intraventricular pressure (LVP dp/dtmax), the area of cardiac force loop (ACFL), and the maximum shortening velocity of myocardial contractile element (Vmax) were observed. As a result, there were significant differences in the improvement of LVP, LVP dp/dtmax, ACFL and Vmax between EA at HM and LM. The regulatory action of EA at HM on the myocardial contractile function was significantly better than that of EA at LM, indicating that HM has a close relationship with the myocardial contractile function.……

Research on Service Function Chain Orchestrating Algorithm Based on SDN and NFV

Software defined network(SDN)and network function virtualization(NFV)have become a new paradigm of a new generation of network architecture.SDN and NFV can effectively improve the flexibility of deploying and managing service function chains(SFCs).By combining SDN and NFV and applying them to the resource orchestration problem of SFC deployment,the three-tier architecture consisting of SDN controller,network function virtualization and physical underlying computing resource layer in the process of heterogeneous network resource mapping is considered.And an optimization algorithm for active control resources based on SDN and NFV is proposed.Firstly,the user’s utility is modeled by the multistandard aggregated multi-criteria utility algorithm,and the optimization goal is transformed into the problem of maximizing the user’s utility.Then the controller,based on the algorithm’s prediction of the future state and realtime monitoring of the network utilization,makes decisions and issues control commands for the arriving SFC requests,based on which it occupies the underlying resources held by the virtualized network function(VNF).The simulation results show that,compared with the static timing resource allocation algorithm,the active control resource deployment algorithm proposed in the article has better performance in terms of resource utilization,acceptance rate,and user creation utility.

技术进步偏向与要素配置对我国林业全要素生产率的影响

技术进步是促进林业全要素生产率增长的重要动力,聚焦林业技术进步偏向、要素配置与全要素生产率之间关系进行研究,为充分发挥林业技术进步的带动力提供量化支持,助力我国林业经济高质量发展。采用2005—2021年我国31个省(自治区、直辖市)面板数据,分别构建全样本及四大区域的超越对数生产函数进行实证分析。结果发现:技术进步偏向、要素配置状态是我国林业全要素生产率增长的重要引擎;林业全要素生产率增长存在地区差异,各区域全要素生产率增长率均有所下降,但下降程度不同;技术进步偏向并不总是促进林业全要素生产率增长,四大区域的林业技术进步在多数年份偏向于资本与林地;部分地区的林业全要素投入与要素效率状态未完全相适应,要素配置有待改善;技术进步、技术效率变化存在区域差异。在此基础上,从促进区域间交流合作、调整生产技术进步方向、改善要素配置、提高科技创新能力等方面提出促进我国林业全要素生产率增长的建议。