Network efficiency analysis of Chinese inter-bank market

The inter-bank market network models are constructed based on the inter-bank credit lending relationships, and the network efficiency characters of the Chinese inter-bank market are studied. Since it is impossible to obtain the specific credit data among banks, this paper estimates the inter-bank lending matrix based on the partial information of banks. Thus, directed network models of the Chinese inter-bank market are constructed by using the threshold method. The network efficiency measures and the effects of random attacks and selective attacks on the global efficiency of the inter-bank network are analyzed based on the network models of the inter-bank market. Empirical results suggest that the efficiency measures are sensitive to the threshold, and that the global efficiency is little affected by random attacks, while it is highly sensitive to selective attacks. Properties such as inter-bank market network efficiency would be useful for risk management and stability of the inter-bank market.

Network-level optimization method for road network maintenance programming based on network efficiency

To maintain their capacity,transportation infrastructures are in need of regular maintenance and rehabilitation.The major challenge facing transportation engineers is the network-level policies to maintain the deteriorating roads at an acceptable level of serviceability.In this work,a quantitative transportation network efficiency measure is presented and then how to determine optimally network-level road maintenance policy depending on the road importance to the network performance has been demonstrated.The examples show that the different roads should be set different maintenance time points in terms of the retention capacities of the roads,because the different roads play different roles in network and have different important degrees to the network performance.This network-level road maintenance optimization method could not only save lots of infrastructure investments,but also ensure the service level of the existing transportation system.

Study on the Interior Market Network Structure and Its Efficiency in a Knowledge Based Company

A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expounds an interior market network structure which is fit for the company intellectual capital operation, and analyses this organization pattern about the reasons of existence, the effectiveness of growing up in scale, the economies of knowledge distribution and the efficiency of operation, and it will provide some beneficial theoretical guidance about how can a company improve its competition competence in the knowledge environment through organization innovation.

Monitoring Efficiency Evaluation of the Well-water-level Observation Network in China

In order to understand the monitoring efficiency status of the well-water-level observation network in China after the completion of the 10 th "Five-year Plan " digital network project,and to provide a basis for the future network optimization and equipment updating, the monitoring efficiency of the well-water-level observation network was evaluated. On the whole,61. 8% observing stations have good monitoring effectiveness,the observation environment of 73. 5% of observing stations meets the monitoring requirements of well-water-level. The operation status of the network is as a whole getting better,operation rates of 75% observing instruments are above 95%. Most well water levels can monitor crustal stress changes and seismic activities. However,some observation stations,due to inherent deficiency in wells,environmental disturbance,instrument aging,and low-level operation and maintenance,need to improve the monitoring efficiency level by taking measures such as observation environment improvement,equipment updating,and management training. About 6. 5% of the stations need to stop observation due to the unqualified observational environment.

Analysis of identification methods of key nodes in transportation network

The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

A random walk evolution model of wireless sensor networks and virus spreading

In this paper, considering both cluster heads and sensor nodes, we propose a novel evolving a network model based on a random walk to study the fault tolerance decrease of wireless sensor networks （WSNs） due to node failure, and discuss the spreading dynamic behavior of viruses in the evolution model. A theoretical analysis shows that the WSN generated by such an evolution model not only has a strong fault tolerance, but also can dynamically balance the energy loss of the entire network. It is also found that although the increase of the density of cluster heads in the network reduces the network efficiency, it can effectively inhibit the spread of viruses. In addition, the heterogeneity of the network improves the network efficiency and enhances the virus prevalence. We confirm all the theoretical results with sufficient numerical simulations.

An energy efficiency clustering routing protocol for WSNs in confined area

Wireless sensor networks (WSNs) are important application for safety monitoring in underground coal mines, which are difficult to monitor due to natural conditions. Based on the characteristic of limited energy for WSNs in confined underground area such as coal face and laneway, we presents an energy- efficient clustering routing protocol based on weight (ECRPW) to prolong the lifetime of networks. ECRPW takes into consideration the nodes' residual energy during the election process of cluster heads. The constraint of distance threshold is used to optimize cluster scheme. Furthermore, the protocol also sets up a routing tree based on cluster heads' weight. The results show that ECRPW had better perfor- mance in energy consumption, death ratio of node and network lifetime.

The New Architecture with Time-Spatial Consistency for 5G Networks

While operators have started deploying fourth generation(4G) wireless communication systems,which could provide up to1 Gbps downlink peak data rate,the improved system capacity is still insufficient to meet the drastically increasing demand of mobile users over the next decade.The main causes of the above-mentioned phenomenon include the following two aspects:1) the growth rate of the network capacity is far below that of user's demand,and 2) the relatively deterministic wireless access network(WAN) architecture in the existing systems cannot accommodate the prominent increase of mobile traffic with space-time domain dynamics.In order to address the above-mentioned challenges,we investigate the time-spatial consistency architecture for the future WAN,whilst emphasizing the critical roles of some spectral-efficient techniques such as Massive multiple-input multiple-output(MIMO),full-duplex(FD)operation and heterogeneous networks(HetNets).Furthermore,the energy efficiency(EE)of the HetNets under the proposed architecture is also evaluated,showing that the proposed user-selected uplink power control algorithm outperforms the traditional stochastic-scheduling strategy in terms of both capacity and EE in a two-tier HetNet.The other critical issues,including the tidal effect,the temporal failure owing to the instantaneously increased traffic,and the network wide load-balancing problem,etc.,are also anticipated to be addressed in the proposed architecture.(Abstract)

Efficient Broadcast Retransmission Based on Network Coding for InterPlaNetary Internet

In traditional wireless broadcast networks,a corrupted packet must be retransmitted even if it has been lost by only one receiver.Obviously,this is not bandwidth-efficient for the receivers that already hold the retransmitted packet.Therefore,it is important to develop a method to realise efficient broadcast transmission.Network coding is a promising technique in this scenario.However,none of the proposed schemes achieves both high transmission efficiency and low computational complexity simultaneously so far.To address this problem,a novel Efficient Opportunistic Network Coding Retransmission(EONCR)scheme is proposed in this paper.This scheme employs a new packet scheduling algorithm which uses a Packet Distribution Matrix(PDM)directly to select the coded packets.The analysis and simulation results indicate that transmission efficiency of EONCR is over 0.1,more than the schemes proposed previously in some simulation conditions,and the computational overhead is reduced substantially.Hence,it has great application prospects in wireless broadcast networks,especially energyand bandwidth-limited systems such as satellite broadcast systems and Planetary Networks(PNs).

Continuous Weight Attack on Complex Network

We introduce a continuous weight attack strategy and numerically investigate the effect of continuous weight attack strategy on the Barabasi-Albert （BA） scale-free network and the Erdos-Rdnyi （ER） random network. We use a weight coefficient ω to define the attack intensity. The weight coefficient ω increases continuously from 1 to infinity, where 1 represents no attack and infinity represents complete destructive attack. Our results show that the continuous weight attack on two selected nodes with small ω （ω≈ 3） could achieve the same damage of complete elimination of a single selected node on both BA and ER networks. It is found that the continuous weight attack on a single selected edge with small ω （ω≈ 2） can reach the same effect of complete elimination of a single edge on BA network, but on ER network the damage of the continuous weight attack on a single edge is c/ose to but always smaller than that of complete elimination of edge even if ω is very large.

An effective method to improve the robustness of small-world networks under attack

In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario.

Detection Situation and Improvement of Lightning Monitoring Network in Guizhou Province

Based on lightning location data of lightning monitoring network in Guizhou Province in recent eight years,the effective detection radius of a station and the effective detection range of lightning monitoring network in Guizhou Province were analyzed. The results show that the effective detection radius of a lightning monitoring sub-station in Guizhou Province is 160 km; some counties in the southwest,northwest and northeast of Guizhou were not detected. To improve the detector efficiency of lightning monitoring network in Guizhou Province,it is suggested that nine sub-stations should be built in Weining,Shuicheng,Qinglong,Pingtang,Rongjiang,Yuping,Songtao,Tongren and Renhuai,so that the effective detection efficiency will reach more than 95%.

Recognition of LPI radar signal based on dual efficient network

Addressing the issue of low pulse identification rates for low probability of intercept(LPI)radar signals under low signal-to-noise ratio(SNR)conditions,this paper aims to investigate a new method in the field of deep learning to recognize modulation types of LPI radar signals efficiently.A novel algorithm combining dual efficient network(DEN)and non-local means(NLM)denoising was proposed for the identification and selection of LPI radar signals.Time-domain signals for 12 radar modulation types were simulated,adding Gaussian white noise at various SNRs to replicate complex electronic countermeasure scenarios.On this basis,the noisy radar signals undergo Choi-Williams distribution(CWD)time-frequency transformation,converting the signals into two-dimensional(2D)time-frequency images(TFIs).The TFIs are then denoised using the NLM algorithm.Finally,the denoised data is fed into the designed DEN for training and testing,with the selection results output through a softmax classifier.Simulation results demonstrate that at an SNR of-8 dB,the algorithm can achieve a recognition accuracy of 97.22%for LPI radar signals,exhibiting excellent performance under low SNR conditions.Comparative demonstrations prove that the DEN has good robustness and generalization performance under conditions of small sample sizes.This research provides a novel and effective solution for further improving the accuracy of identification and selection of LPI radar signals.

An Efficient Method for Identifying Lower Limb Behavior Intentions Based on Surface Electromyography

Surface electromyography(sEMG)is widely used for analyzing and controlling lower limb assisted exoskeleton robots.Behavior intention recognition based on sEMG is of great significance for achieving intelligent prosthetic and exoskeleton control.Achieving highly efficient recognition while improving performance has always been a significant challenge.To address this,we propose an sEMG-based method called Enhanced Residual Gate Network(ERGN)for lower-limb behavioral intention recognition.The proposed network combines an attention mechanism and a hard threshold function,while combining the advantages of residual structure,which maps sEMG of multiple acquisition channels to the lower limb motion states.Firstly,continuous wavelet transform(CWT)is used to extract signals features from the collected sEMG data.Then,a hard threshold function serves as the gate function to enhance signals quality,with an attention mechanism incorporated to improve the ERGN’s performance further.Experimental results demonstrate that the proposed ERGN achieves extremely high accuracy and efficiency,with an average recognition accuracy of 98.41%and an average recognition time of only 20 ms-outperforming the state-of-the-art research significantly.Our research provides support for the application of lower limb assisted exoskeleton robots.

Energy-Performance Tradeoffs in laaS Cloud with Virtual Machine Scheduling

In the cloud data centers,how to map virtual machines(VMs) on physical machines(PMs) to reduce the energy consumption is becoming one of the major issues,and the existing VM scheduling schemes are mostly to reduce energy consumption by optimizing the utilization of physical servers or network elements.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,this paper proposes a two-stage VM scheduling scheme:(1) We propose a static VM placement scheme to minimize the number of activating PMs and network elements to reduce the energy consumption;(2) In the premise of minimizing the migration costs,we propose a dynamic VM migration scheme to minimize the maximum link utilization to improve the network performance.This scheme makes a tradeoff between energy efficiency and network performance.We design a new twostage heuristic algorithm for a solution,and the simulations show that our solution achieves good results.

Applying systematic conservation planning to constitute a protection strategy for broad-leaved Korean pine forests in Changbai Mountains, China

The broad-leaved Korean pine(Pinus koraiensis) forest is one of the most biodiverse zonal communities in the North Temperate Zone and an important habitat for many endangered species.Broad-leaved Korean pine forests(BKPFs) are shrinking quickly due to deforestation and rapid urbanization. Thus, scientific protection strategies are urgently needed to change this status. Changbai Mountains contains one of the largest BKPFs and is considered a priority biodiversity conservation area in China. Guided by systematic conservation planning(SCP) methods and procedures, we chose representative species and communities in BKPFs ecosystem as priority conservation objects, and set quantitative conservation target, which is in the light of the biodiversity characteristic of BKPFs. The watershed area is used as planning unit. We used CPlan software to calculate the irreplaceability(Ir)value of each planning unit and the contribution value(Ti) of each conservation object to(1) assess the conservation efficiency;(2) identify the conservation gap of the existing conservation network. Then wecalculated a human disturbance index(HDI) for planning units in the conservation gaps and combine this with the Ir value to design three conservation scenarios to optimize the conservation network.Results show that planning units with high conservation value 14.16% of the total area, with3084.36 km2 were covered by the existing conservation network. 79.28% of planning units with high conservation value have not been protected which were concentrated mainly in the eight gap areas.Only 25.3% of protection objects achieved their conservation target with the existing conservation network. Conservation efficiency is low. Three conservation scenarios are constituted, each prioritizing a different aim:(1) ecological value;(2)species rescue; and(3) economical avoidance. The three conservation schemes potentially enable 93%,88% and 51% of conservation objects, respectively, to achieve identified conservation targets, thereby improving conservation efficiency significantly.

Research on High Altitude Remote Sensing Building Segmentation Based on Improved U-Net Algorithm

Building extraction from high resolution remote sensing image is a key technology of digital city construction[14].In order to solve the problems of low efficiency and low precision of traditional remote sensing image segmentation,an improved U-Net network structure is adopted in this paper.Firstly,in order to extract efficient building characteristic information,FPN structure was introduced to improve the ability of integrating multi-scale information in U-Net model;Secondly,to solve the problem that feature information weakens with the deepening of network depth,an efficient residual block network is introduced;Finally,In order to better distinguish the target area and background area in the image and improve the precision of building target edge detection,the cross entropy loss and Dice loss were linearly combined and weighted.Experimental results show that the algorithm can improve the image segmentation effect and improve the image accuracy by 18%.

QoS-TEOS:QoS Guaranteed Throughput-Efficiency Optimal Distributed Scheduling in WiMAX Mesh Networks

WiMAX distributed scheduling can be modeled as two procedures：three-way handshaking procedure and data subframe scheduling procedure.Due to manipulating data transmission directly,data subframe scheduling has a closer relationship with user Quality of Service（QoS） satisfaction,and has more severe impact on network performance,compared with handshaking procedure.A QoS guaranteed Throughput-Efficiency Optimal distributed data subframe Scheduling scheme,named as QoS-TEOS,is proposed.QoS-TEOS achieves QoS guarantee through modeling services into different ranks and assigning them with corresponding priorities.A service with higher priority is scheduled ahead of that with lower priority and offered with high QoS quality.Same kinds of services that request similar QoS quality are classified into one service set.Different service sets are scheduled with different strategies.QoS-TEOS promotes network performance through improving network throughput and efficiency.Theoretical analysis shows that the scheduled data transmission should balance data generation rate from upper layer and transmission rate of physical layer,to avoid network throughput and efficiency declining.Simulation results show that QoS-TEOS works excellently to achieve throughput-efficiency optimization and guarantee a high QoS.

Cross Layer QoS Aware Scheduling based on Loss-Based Proportional Fairness with Multihop CRN

As huge users are involved,there is a difficulty in spectrum allocation and scheduling in Cognitive Radio Networks(CRNs).Collision increases when there is no allocation of spectrum and these results in huge drop rate and network performance degradation.To solve these problems and allocate appropriate spectrum,a novel method is introduced termed as Quality of Service(QoS)Improvement Proper Scheduling(QIPS).The major contribution of the work is to design a new cross layer QoS Aware Scheduling based on Loss-based Proportional Fairness with Multihop(QoSAS-LBPFM).In Medium Access Control(MAC)multi-channel network environment mobile nodes practice concurrent broadcast between several channels.Acquiring the advantage of introduced cross layer design,the real-time channel conditions offered by Cognitive Radio(CR)function allows adaptive sub channel choice for every broadcast.To optimize the resources of network,the LBPFM adaptively plans the radio resources for allocating to diverse services without lessening the quality of service.Results obtained from simulation proved that QoSAS-LBPFM provides enhanced QoS guaranteed performance against other existing QIPS algorithm.

Weighted graph convolutional networks based on network node degree and efficiency

In the study of graph convolutional networks,the information aggregation of nodes is important for downstream tasks.However,current graph convolutional networks do not differentiate the importance of different neighboring nodes from the perspective of network topology when ag-gregating messages from neighboring nodes.Therefore,based on network topology,this paper proposes a weighted graph convolutional network based on network node degree and efficiency(W-GCN)model for semi-supervised node classification.To distinguish the importance of nodes,this paper uses the degree and the efficiency of nodes in the network to construct the impor-tance matrix of nodes,rather than the adjacency matrix,which usually is a normalized symmetry Laplacian matrix in graph convolutional network.So that weights of neighbor nodes can be as-signed respectively in the process of graph convolution operation.The proposed method is ex-amined through several real benchmark datasets(Cora,CiteSeer and PubMed)in the experimen-tal part.And compared with the graph convolutional network method.The experimental results show that the W-GCN model proposed in this paper is better than the graph convolutional net-work model in prediction accuracy and achieves better results.