An Empirical Study of the Allocation Efficiency of Rural Financial Resources in Hubei Province from the Perspective of Agricultural Loans

The incompatibility of China's economy and finance has to some extent inhibited the development of rural economy. Taking Hubei Province for example,we measure the allocation efficiency of rural financial resources from the perspective of agricultural input and output,and use the modern rural financial development theory to set forth some policy recommendations on how to build a new rural financial resource allocation system. Studies have shown that the allocation efficiency of rural financial resources is low in China,and improving the allocation efficiency of rural financial resources is the key to perfecting rural financial environment while increasing financial support for agriculture.

Toward the Energy Efficiency of Resource Allocation Algorithms for OFDMA Downlink MIMO Systems

The problem of the simultaneous multi-user resource allocation algorithm in orthogonal frequency division multiple access(OFDMA)based systems has recently attracted significant interest.However,most studies focus on maximizing the system throughput and spectral efficiency.As the green radio is essential in 5G and future networks,the energy efficiency becomes the major concern.In this paper,we develop four resource allocation schemes in the downlink OFDMA network and the main focus is on analyzing the energy efficiency of these schemes.Specifically,we employ the advanced multi-antenna technology in a multiple input-multiple output(MIMO)system.The first scheme is based on transmit spatial diversity(TSD),in which the vector channel with the highest gain between the base station(BTS)and specific antenna at the remote terminal(RT)is chosen for transmission.The second scheme further employs spatial multiplexing on the MIMO system to enhance the throughput.The space-division multiple-access(SDMA)scheme assigns single subcarrier simultaneously to RTs with pairwise“nearly orthogonal”spatial signatures.In the fourth scheme,we propose to design the transmit beamformers based on the zero-forcing(ZF)criterion such that the multi-user interference(MUI)is completely removed.We analyze the tradeoff between the throughput and power consumption and compare the performance of these schemes in terms of the energy efficiency.

Literature Review on the Impact of Blockchain Technology on Resource Allocation Efficiency

With the rapid development of Internet technology,the importance of blockchain technology has become increasingly prominent.Faced with this situation,extensive research has been carried out at home and abroad.Through the analysis of relevant literature on blockchain in recent years,it is found that there are many research results of blockchain technology in medical care,finance,education,etc.,but its application in the field of resource allocation efficiency is rare.From the existing studies on the influencing factors of resource allocation efficiency in China,it is found that there are significant differences in resource allocation efficiency between China and some developed countries or between various provinces and cities of China.

Joint Optimization of Satisfaction Index and Spectrum Efficiency with Cache Restricted for Resource Allocation in Multi-Beam Satellite Systems

Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.

Photosynthetic Carbon Gain, Allocation and Resources-Use Efficiency in Invasive Eupatorium Adenophorum and Its Native Congener E. Japonicum under Different Light and Nutrient Conditions

Invasion is often facilitated by high resources availabilities and suppressed under low resources habitats. However, a number of invasive plants can successfully establish and dominate in resource-poor and （or） the understory of closed forests, indicating the plant＇s performances are habitats-dependent and species-specific. It is therefore necessary to explore the ecophysiological characteristics associated invasiveness for one invasive species across multiple resources availabilities whilst taking the relatedness into these comparative studies. In this study, invasive Eupitorium adenophorum and its native congener E. japonicum grew under different resource gradients in terms of light levels and soil nitrogen additions to identify the functional significance morphological and physiological traits associated closely with invasion and to examine their comparative responses. Photosynthetic carbon gain, biomass allocation and resource-use efficiency are evaluated in this pot experiment. Across treatments, E. adenophorum exhibited consistently higher values for most of the morphological variables including plant stature, relative growth rate （RGR）, leaf root ratio （LRR）, leaf area ratio （LAR）, total leaf area, and lower root： shoot ratio （RSR）. Significantly higher Pmax corresponded with higher photosynthetic nitrogen use efficiency （PNUE） and photosynthetic energy use efficiency （PEUE） especially in low light and （or） unfertile condition. Higher Gs and Pmax but lower photosynthetic water use efficiency （WUE） indicated the trade-off relationship between WUE and PNUE for E. adenophorum. Final biomasses were higher for E. adenophorum in nutrient and（or） light limited conditions, in which higher leaf construction cost（CC） compared with E. japonicum could be over-compensated by its significantly higher assimilation rates. The effects of light levels on these plant attributes were stronger than soil nutrient contents. The responses of these two congeneric species to light and nitrogen availabilities were similar, but the differences were magnified in resources limited conditions, indicating the better performancer at acquiring and at using limited resources of E. adenophorum over its co-occurring native flora. Our study presented the distinctive advantages of E. adenophorum in resources-poor environments, indicating conventional strategy of managing resources levels to control the invasion and expending of exotic species may not be as effective as expected.

Application of Blockchain Technology in Optimizing Resource Allocation Efficiency

Based on the existing literature,this paper analyzed and explored the factors that affect the efficiency of resource allocation,and evaluated the current situation of resource allocation in various fields.It is found that with the emergence of the new pattern of China’s economic development,the economic growth rate has slowed down,and the method of large-scale production driving economic growth is no longer applicable to the current economic situation.Nowadays,when structural transformation and upgrading have entered a new stage,to achieve the optimization of resource allocation efficiency,it is necessary to start from three aspects:improving information transparency,upgrading industrial structure,and planning government intervention.Through the adaptation analysis of blockchain technology and the existing problems in optimizing resource allocation efficiency,it explored the feasibility of blockchain technology to optimize resource allocation efficiency,and promote economical,efficient and high-quality development.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Spatial Disparity and Efficiency of Science and Technology Resources in China

In the knowledge economy era,science and technology(S&T) resources are getting more and more important in shaping regional competiveness and building regional innovation capacity.As such,the spatial distribution of S&T resources is a key to understanding regional development and disparities.By designing an input-output indicator system,this paper develops an evaluation model to examine the spatial distribution of S&T resources in China and assess their spatial efficiency.Moreover,the paper tries to explain spatial differences in the efficiency of S&T resources in China.Major findings are:1) the input and output of S&T resources in China shows a clear T-shaped spatial structure,i.e.,concentrated mainly in the coastal region and along the Changjiang(Yangtze) River;2) the efficiency of S&T resources in China displays strong spatial disparities,with the level of efficiency descending from the east to the west while high efficiency appearing in only several clusters;3) the utilization rates of S&T resources in most provinces are quite low,resulting in low efficiency of S&T resources allocation.The paper suggests that the utilization rate of S&T resources should be raised and the commercialization of S&T outputs should be enhanced to improve the efficiency of S&T resources in China.

Efficient and fair resource allocation in downlink OFDMA systems

A resource allocation problem considering both efficiency and fairness in orthogonal frequency division multiple access （OFDMA） systems is studied. According to the optimality conditions, a downlink resource allocation algorithm consisting of subcarrier assignment and power alloca- tion is proposed. By adjusting the tradeoff coefficient, the proposed algorithm can achieve different levels of compromise between efficiency and fairness. The well-known classic resource allocation policies such as sum-rate maximization algorithm, proportional fairness algorithm and max-rain algorithm are all special cases of the proposed algorithm. Simulation results show that the compromise between efficiency and fairness can be continuously adjusted according to system requirements.

Optimal Energy Efficiency Resource Allocation Strategy for Cognitive Clustering Network under PUEA Attack

5G has pushed the use of radio spectrum to a new level,and cognitive clustering network can effectively improve the utilization of radio spectrum,which is a feasible way to solve the growing demand for wireless communications.However,cognitive clustering network is vulnerable to PUEA attack,which will lead to the degradation of system detection performance,thereby reducing the energy efficiency.Aiming at these problems,this paper investigates the optimal energy efficiency resource allocation scheme for cognitive clustering network under PUEA attack.A cooperative user selection algorithm based on selection factor is proposed to effectively resist PUEA user attack and improve detection performance.We construct the energy efficiency optimization problem under multi-constraint conditions and transform the nonlinear programming problem into parametric programming problem,which is solved by Lagrangian function and Karush-Kuhn-Tucker condition.Then the sub-gradient iterative algorithm based on optimal energy efficiency under PUEA attack is proposed and its complexity is analyzed.Simulation results indicate that proposed method is effective when subjected to PUEA attacks,and the impact of different parameters on energy efficiency is analyzed.

Resource Allocation of Agricultural Science and Technology R&D

The status quo of resource allocation of agricultural science and technology R&D(research and development)both at home and abroad,including the amount and function of agricultural science and technology research funds,human resources in the resources of agricultural science and technology R&D,the efficiency of resource allocation of agricultural science and technology R&D,the management system of agricultural scientific innovation and the operation status of scientific funds,is analyzed.The problems in the current resource allocation of agricultural science and technology R&D are put forward,including unreasonable resource allocation;low efficiency,and low efficiency of the transformation of agricultural scientific achievements.The highly effective resource allocation of agricultural science and technology R&D is analyzed from the aspects of resource allocation structure,environment,channel,spatial layout and industrial chain.

Cross-efficiency DEA model-based evaluation of allocative efficiency of rural information resources in Jiangsu Province, China

Purpose: This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province, China as the research sample.Design/methodology/approach: We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings: Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations: We have to give up using some indicators because of limited data availability. There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications: The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value: Little or no research has been published about the allocative efficiency of rural information resources. The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.

Traffic resource allocation for complex networks

In this paper, an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks. The network resources are the total node packet-delivering capacity and the total link bandwidth. An analytical method is developed to estimate the overall network capacity by using the concept of efficient betweenness （ratio of algorithmic betweenness and local processing capacity）. Three network structures （scale-free, small-world, and random networks） and two typical routing protocols （shortest path protocol and efficient routing protocol） are adopted to demonstrate the performance of the proposed strategy. Our results show that the network capacity is reversely proportional to the average path length for a particular routing protocol and the shortest path protocol can achieve the largest network capacity when the proposed resource allocation strategy is adopted.

Clustering and Resource Allocation Strategy for D2D Multicast Networks with Machine Learning Approaches

In this paper,the clustering and resource allocation problem in device-to-device(D2D)multicast transmission underlay cellular networks are investigated.For the sake of classifying D2D users into different D2D multicast clusters,a hybrid intelligent clustering strategy(HICS)based on unsupervised machine learning is proposed first.By maximizing the total energy efficiency of D2D multicast clusters,a joint resource allocation scheme is then presented.More specifically,the energy efficiency optimization problem is constructed under the quality of service(QoS)constraints.Since the joint optimization problem is non-convex,we transform the original problem into a mixed-integer programming problem according to the Dinkelbach algorithm.Furthermore,to avoid the high computational complexity inherent in the traditional resource allocation problem,a Q-Learning based joint resource allocation and power control algorithm is proposed.Numerical results reveal that the proposed algorithm achieves better energy efficiency in terms of throughput per energy consumption.

Collaborative Multiple Access And Energy-Efficient Resource Allocation in Distributed Maritime Wireless Networks

With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource scheduling is not suitable for MWNs due to the special environment. In this paper,we introduce the collaborative relay communication in distributed MWNs to improve the link reliability, and propose an orthogonal time-frequency resource block reservation based multiple access(RRMA) scheme for both one-hop direct link and two-hop collaborative relay link to reduce the interference. To further improve the network performance, we formulate an energy efficiency(EE) maximization resource allocation problem and solve it by an iterative algorithm based on the Dinkelbach method. Finally, numerical results are provided to investigate the proposed RRMA scheme and resource allocation algorithm, showing that the low outage probability and transmission delay can be attained by the proposed RRMA scheme. Moreover,the proposed resource allocation algorithm is capable of achieving high EE in distributed MWNs.

Energy-Efficient Resource Allocation for Heterogeneous Network with Grouping D2D

In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate a resource allocation problem,which aims at maximizing the energy efficiency(EE)of the system while guaranteeing the quality-of-service(Qos)of users.To efficiently solve this problem,the non-convex optimization problem is first transformed into a convex optimization problem.By transforming the fractional-form problem into an equivalent subtractive-form problem,an iterative power allocation algorithm is proposed to maximize the system EE.Moreover,the optimal closedform power allocation expressions are derived by the Lagrangian approach.Simulation results show that our algorithm achieves higher EE performance than the traditional D2D communication scheme.

Energy Efficient Constrained Shortest Path First-Based Joint Resource Allocation and Route Selection for Multi-Hop CRNs

Cognitive radio networks(CRNs) are expected to improve spectrum utilization efficiently by allowing secondary users(SUs) to opportunistically access the licensed spectrum of primary users(PUs).In CRNs,source and destination SUs may achieve information interaction in an ad hoc manner.In the case that no direct transmission link between the SU transmission pairs is available,multi-hop relay SUs can be applied to forward information for the source and destination SUs,resulting in multi-hop CRNs.In this paper,we consider a multi-hop CRN consisting of multiple PUs,SU transmission pairs and relay SUs.Stressing the importance of transmission hops and the tradeoff between data rate and power consumption,we propose an energy efficient constrained shortest path first(CSPF)-based joint resource allocation and route selection algorithm,which consists of two sub-algorithms,i.e.,CSPF-based route selection sub-algorithm and energy efficient resource allocation sub-algorithm.More specifically,we first apply CSPF-based route selection sub-algorithm to obtain the shortest candidate routes(SCRs) between the SU pair under the transmission constraints.Then,an energy efficient resource allocation problem of the SCRs is formulated and solved by applying iterative algorithm and Lagrange dual method.Simu-lation results demonstrate the effectiveness of the proposed algorithm.

Energy efficient resource allocation for D2D multicast communications

The resource allocation for device-to-device(D2D)multicast communications is investigated.To achieve fair energy efficiency(EE)among different multicast groups,the max-min fairness criterion is used as the optimization criterion and the EE of D2D multicast groups are taken as the optimization objective function.The aim is to maximize the minimum EE for different D2D multicast groups under the constraints of the maximum transmit power and minimum transmit rate,which is modeled as a non-convex and mixed-integer fractional programming problem.Here,suboptimal resource allocation algorithms are proposed to solve this problem.First,channel assignment scheme is performed to assign channel to D2D multicast groups.Second,for a given channel assignment,iterative power allocation schemes with and without loss of cellular users’rate are completed,respectively.Simulation results corroborate the convergence performance of the proposed algorithms.In addition,compared with the traditional throughput maximization algorithm,the proposed algorithms can improve the energy efficiency of the system and the fairness achieved among different multicast groups.

Enhanced PSO Based Energy-Efficient Resource Allocation and CQI Based MCS Selection in LTE-A Heterogeneous System

In order to maximize system energy efficiency(EE) under user quality of service(Qo S) restraints in Long Term Evolution-Advanced(LTE-A) networks,a constrained joint resource optimization allocation scheme is presented,which is NP-hard. Hence,we divide it into three sub-problems to reduce computation complexity,i.e.,the resource block(RB) allocation,the power distribution,and the modulation and coding scheme(MCS) assignment for user codewords. Then an enhanced heuristic approach GAPSO is proposed and is adopted in the RB and power allocation respectively to reduce computational complexity further on. Moreover,a novel MCS allocation scheme is put forward,which could make a good balance between the system reliability and availability under different channel conditions. Simulation results show that the proposed GAPSO could achieve better performance in convergence speed and global optimum searching,and that the joint resource allocation scheme could improve energy efficiency effectively under user Qo S requirements.

Energy Efficient Resource Allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

In this paper,maximizing energy efficiency(EE)through radio resource allocation for renewable energy powered heterogeneous cellular networks(HetNet)with energy sharing,is investigated.Our goal is to maximize the network EE,conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources.We define the objective function as a sum weighted EE of all links in the HetNet.We formulate the resource allocation problem in terms of subcarrier assignment,power allocation and energy sharing,as a mixed combinatorial and non-convex optimization problem.We propose an energy efficient resource allocation scheme,including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker(KKT)conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning(RL).Our numerical results show that both centralized and distributed algorithms converge with a few times of iterations.The numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.