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.

Physical Parameter Identification Method Based on Modal Analysis for Two-axis On-road Vehicles:Theory and Simulation

Physical parameters are very important for vehicle dynamic modeling and analysis.However,most of physical parameter identification methods are assuming some physical parameters of vehicle are known,and the other unknown parameters can be identified.In order to identify physical parameters of vehicle in the case that all physical parameters are unknown,a methodology based on the State Variable Method（SVM） for physical parameter identification of two-axis on-road vehicle is presented.The modal parameters of the vehicle are identified by the SVM,furthermore,the physical parameters of the vehicle are estimated by least squares method.In numerical simulations,physical parameters of Ford Granada are chosen as parameters of vehicle model,and half-sine bump function is chosen to simulate tire stimulated by impulse excitation.The first numerical simulation shows that the present method can identify all of the physical parameters and the largest absolute value of percentage error of the identified physical parameter is 0.205%;and the effect of the errors of additional mass,structural parameter and measurement noise are discussed in the following simulations,the results shows that when signal contains 30 d B noise,the largest absolute value of percentage error of the identification is 3.78%.These simulations verify that the presented method is effective and accurate for physical parameter identification of two-axis on-road vehicles.The proposed methodology can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.

IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD

An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix, in combination with component energy index （CEI） which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio （SNR）and gives a reliable separation of spurious and physical estimates.

General Situation of Traditional Chinese Medicine Identification Methods

Traditional Chinese medicines are the material basis for the treatment of diseases under theoretical direction, as well as the raw materials of traditional Chinese medicine decoction pieces and Chinese patent medicines. The quality of traditional Chinese medicine directly influences clinical efficacy. Therefore, the identification of traditional Chinese medicine is the responsibility of medicinal workers. The identification method develops from observation, tasting, smelling and listening to firing method and testing with water, and the construction of fingerprints of traditional Chinese medicines and molecular biological techniques. The development and evolution of traditional Chinese medicine identification methods was reviewed in this paper.

A Review of Identity Methods of Internet of Things (IOT)

The Internet of Things (IOT) is a recent technology originating from the field of sensor networks. It has received significant attention because it is involved in most aspects of our daily lives. The IOT vision makes objects of various kinds become part of the Internet by assigning each object a unique identifier, enabling objects to communicate with each other in the same or different environments. IOT can collect, process, and exchange data via a data communication network. There are many methods for identifying objects;some have existed since the beginning of IOT innovation, such as Radio Frequency Identification (RFID), Barcode/2D code, IP address, Electronic Product Codes (EPC), etc. Continuous development in IOT domain and the large number of objects connected to the Internet daily require an improved identification method to cope with the rapid development in this field. Many modern methods have been proposed recently, based on various technologies such as computer vision, fingerprinting, and machine learning. This paper introduces an overview of IOT and discusses its fundamental elements;it mainly focuses on identification of IOT which is considered the main part that the IOT systems rely on. The paper discusses the existing identification methods for IOT. Moreover, it provides a review of the modern identification methods proposed in recent literature.

RECONSTRUCTION OF PART OF AN ACTUAL BLAST-WAVE FLOW FIELD TO AGREE WITH EXPERIMENTAL DATA BY USING NUMERICAL METHOD WITH HIGH IDENTIFICATION

In this paper, on the basis of experimental data of two kinds of chemical explosions, the piston-pushing model of spherical blast-waves and the second-order Godunov-type scheme of finite difference methods with high identification to discontinuity are used to the numerical reconstruction of part of an actual hemispherical blast-wave flow field by properly adjusting the moving bounary conditions of a piston. This method is simple and reliable. It is suitable to the evaluation of effects of the blast-wave flow field away from the explosion center.

A MODEL IDENTIFICATION METHOD OF VIBRATING STRUCTURES FROM INCOMPLETE MODAL INFORMATION

The accurate mathematical models for complicated structures are very difficult to construct.The work presented here provides an identification method for estimating the mass.damping,and stiffness matrices of linear dynamical systems from incomplete experimental data.The mass,stiffness and damping matrices are assumed to be real,symmetric,and positive definite The partial set of experimental complex eigenvalues and corresponding eigenvectors are given.In the proposed method the least squares algorithm is combined with the iteration technique to determine systems identified matrices and corresponding design parameters.Seeveral illustative examples,are presented to demonstrate the reliability of the proposed method .It is emphasized that the mass,damping and stiffness matrices can be identified simultaneously.

Multi-source Data-driven Identification of Urban Functional Areas:A Case of Shenyang,China

Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.

Comparison of methods for identification of cold tolerance of rice

Under low temperature stress,theplasmamembrane and chloroplast of plant cellsare impaired,resulting in electrolyte leakage and al-teration of chlorophyll fluorescence which can bemeasured with conductometer and fluoremeter.The cold tolerance of excised leaves of several ricevarieties were determined with these two instru-ments at seedling and heading stages to compare

An Overview of Calibration Technology of Industrial Robots

With the continuous improvement of automation,industrial robots have become an indispensable part of automated production lines.They widely used in a number of industrial production activities,such as spraying,welding,handling,etc.,and have a great role in these sectors.Recently,the robotic technology is developing towards high precision,high intelligence.Robot calibration technology has a great significance to improve the accuracy of robot.However,it has much work to be done in the identification of robot parameters.The parameter identification work of existing serial and parallel robots is introduced.On the one hand,it summarizes the methods for parameter calibration and discusses their advantages and disadvantages.On the other hand,the application of parameter identification is introduced.This overview has a great reference value for robot manufacturers to choose proper identification method,points further research areas for researchers.Finally,this paper analyzes the existing problems in robot calibration,which may be worth researching in the future.

Rapid identification of landslide,collapse and crack based on low-altitude remote sensing image of UAV

Landslides,collapses and cracks are the main types of geological hazards,which threaten the safety of human life and property at all times.In emergency surveying and mapping,it is timeconsuming and laborious to use the method of field artificial investigation and recognition and using satellite image to identify ground hazards,there are some problems,such as time lag,low resolution,and difficult to select the map on demand.In this paper,a10 cm per pixel resolution photogrammetry of a geological hazard-prone area of Taohuagou,Shanxi Province,China is carried out by DJ 4 UAV.The digital orthophoto model(DOM),digital surface model(DSM) and three-dimensional point cloud model(3 DPCM) are generated in this region.The method of visual interpretation of cracks based on DOM(as main)-3 DPCM(as auxiliary) and landslide and collapse based on 3 DPCM(as main)-DOM and DSM(as auxiliary) are proposed.Based on the low altitude remote sensing image of UAV,the shape characteristics,geological characteristics and distribution of the identified hazards are analyzed.The results show that using UAV low altitude remote sensing image,the method of combination of main and auxiliary data can quickly and accurately identify landslide,collapse and crack,the accuracy of crack identification is 93%,and the accuracy of landslide and collapse identification is 100%.It mainly occurs in silty clay and mudstone geology and is greatly affected by slope foot excavation.This study can play a great role in the recognition of sudden hazards by low altitude remote sensing images of UAV.

Objective identification research on cold vortex and mid-summer rainy periods in Northeast China

Considering the differences between the Northeast China Cold Vortex （CV） and the Mid-Summer （MS） rainy period and their corresponding atmospheric circulations are comprehensively analyzed, and the objective identification methods of defining the annual beginning and ending dates of Northeast China CV and MS rainy periods are developed respectively. The annual beginning date of the CV （MS） rainy period is as follows. In a period from April to August, if daily regional mean precipitation ryi is larger than yearly regional mean precipitation R （or 2R） on a certain day, the station precipitation rs is larger than the station yearly mean precipitation （r/ （or 2（r）） in at least 50% of stations in Northeast China, and this condition is satisfied in the following 2 （7） days, then this date is defined as the beginning date of the CV （MS） rainy period. While the definition of the ending date of the MS rainy period shows the opposite process to its beginning date. With this objective identification method, the multi-year average （1981-2010） beginning date of the CV rainy period is May 3, the beginning date of the MS rainy period is June 27, the ending day of the CV rainy period is defined as the day before the beginning date of the MS rainy period, and the ending date of the MS rainy period is August 29. Meanwhile, corresponding anomaly analysis at a 500-hPa geopotential height, 850-hPa wind, Omega and relative humidity fields all show that the definitions of the average beginning and ending dates of the CV and MS rainy periods have a certain circulation meaning. Furthermore, the daily evolution of the CV index, meridional and zonal wind index, etc. all show that these objectively defined beginning and ending dates of the CV and MS rainy periods have climate significance.

VIBRATION CONTROL OF FLUID-FILLED PRISMATIC SHELL WITH ACTIVE CONSTRAINED LAYER DAMPING TREATMENTS

Active constrained layer damping （ACLD） combines the simplicity and reliability of passive damping with the light weight and high efficiency of active actuators to obtain high damping over a wide frequency band. A fluid-filled prismatic shell is set up to investigate the validity and efficiency of ACLD treatments in the case of fluid-structure interaction. By using state subspace identification method, modal parameters of the ACLD system are identified and a state space model is established subsequently for the design of active control laws. Experiments are conducted to the fluid-filled prismatic shell subjected to random and impulse excitation, respectively, For comparison, the shell model without fluid interaction is experimented as well. Experimental results have shown that the ACLD treatments can suppress vibration of the fluid-free and fluid-filled prismatic shell effectively. Under the same control gain, vibration attenuation is almost the same in both cases.

Identification Method for Single-line-to-ground Faults with Line Break Based on Phasor Measurement in Distribution Networks

The single-line-to-ground faults with line breaks(SLGFs-LBs)occur more and more frequently in distribution networks and can cause major safety accidents.It is difficult to distinguish the single-line-to-ground faults(SLGFs)in resonant grounding systems and ungrounding systems due to the same electrical characteristics on the source side and uncertain operation conditions of distribution networks.This paper proposes a method for distinguishing SLGFs-LBs and SLGFs.First,the source-side and load-side voltage characteristics of SLGFs and SLGFs-LBs are analyzed,and the phase difference between the voltages of the fault phase and non-fault phase on the load side is selected as the identification criterion.Phasor measurement units(PMUs)are selected as measuring devices.Then,the effects of operation conditions and external devices in distribution networks on the proposed method are discussed,and the phase errors caused by them are calculated to correct the identification method.Finally,the field testing and simulation experiments are conducted to verify the effectiveness and robustness of the proposed method.

Anisotropy of the upper mantle in Chinese mainland and its vicinity

In order to deepen the understanding of the spatial change images of upper mantle media for strain strength and polarization direction, anisotropy and shear wave splitting, anisotropy and strain, strain and the tectonic process, based on the theory on the characteristics of shear wave splitting parameters in the presence of two weak azimuthal anisotropic layers and observations concerned, and using signal identification methods with high precision, the results for 136 earthquakes are obtained. The pictures of anisotropy strength and polarization direction beneath twenty stations are got. Combining the results existed previously, the characteristics and origin of the upper mantle anisotropy are discussed.

Analysis of the Volatile Constituents of PinusTabulaeformis Carr. Pine Cones

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Advances in Research on Drought Resistance in Rice

Rice is the main grain crop in China. With global warming, drought and water shortage have become one of the important factors limiting rice production. Improving the drought resistance of rice can effectively alleviate the loss of rice yield caused by drought. In this paper, the research progress on rice drought resistance and its evaluation methods, mapping of QTLs for drought resistance-related traits, and mining for drought resistance genes were reviewed, and molecular breeding for drought resistance in rice was prospected.

Non-probabilistic information fusion technique for structural damage identification based on measured dynamic data with uncertainty

Based on measured natural frequencies and acceleration responses,a non-probabilistic information fusion technique is proposed for the structural damage detection by adopting the set-membership identification（SMI） and twostep model updating procedure.Due to the insufficiency and uncertainty of information obtained from measurements,the uncertain problem of damage identification is addressed with interval variables in this paper.Based on the first-order Taylor series expansion,the interval bounds of the elemental stiffness parameters in undamaged and damaged models are estimated,respectively.The possibility of damage existence（PoDE） in elements is proposed as the quantitative measure of structural damage probability,which is more reasonable in the condition of insufficient measurement data.In comparison with the identification method based on a single kind of information,the SMI method will improve the accuracy in damage identification,which reflects the information fusion concept based on the non-probabilistic set.A numerical example is performed to demonstrate the feasibility and effectiveness of the proposed technique.

Vortex analysis of water flow through gates by different vortex identification methods

The pre-gate suction vortex,gate-bottom-edge transverse vortex,gate-slot vertical vortex,and downstream-of-gate return vortex are important factors affecting the flow instability of flat gates,which may lead to fatigue failure in severe cases.This study used the volume of fluid(VOF)model and large eddy simulation(LES)method to accurately capture the transient turbulence characteristics of flow under different water flow conditions and reveal the flow field and vortex structure.The Q—criterion,Omega(Ω)method,and latest third-generation Liutex vortex identification method were used to analyze and compare the pre-gate suction vortex,gate-slot vertical vortex,and downstream-of-gate return vortex,focusing on the ability of each vortex identification method to capture the flow field information and vortex characteristics.The results reveal that theΩmethod and Liutex method are less dependent on the threshold value,and the Liutex method captures a wide range of pre-gate vortices.Different flow conditions cause changes in the vortex structure of over-gate flow.When the relative opening of the gate is smaller,the intensity of the vortices in the flow field around the gate is greater,the return vortices downstream of the gate are more disordered,and the vortex changes are more violent,which in turn affects the efficient and stable operation of the gate.

Film identification method based on improved deeplabv3+ for full-film double-ditch corn seedbed

This study aimed to investigate the task demand of intelligent unmanned fertilizer application in seedling stage of corn planted in full-film double-ditch seedbed,a film identification method based on improved DeepLabv3+ identification method for full-film double-ditch corn seedbed was proposed.The differences in performance indicators of the original Deeplabv3+ network taking Xception as the backbone network and the network model that replaced three lightweight backbone networks,MobileNetV2,MobileNetV3 and GhostNet were tested.At the same time,the network models,classical semantic segmentation was introduced to PSPNet and UNet for comparative test.The MIoU of DeepLabv3+ network model that replaced its backbone network increased by 5.01%,and FPS improved by 206%compared with original network,and the model size reduced by 90.3%.The three DeepLabv3+ models after replacing the backbone network were further compressed,and the two-layer expansion convolution with low expansion rate in ASPP was deleted,and the common convolution after feature fusion was replaced by the depthwise separable convolution to obtain a lightweight network model.After testing the improved network model,it was found that the average decline of precision indicators was only 0.17%,FPS raised to 66.5,with an average increase of 25.5%,and the size of the model was compressed to 10.53 MB.Test results showed that,the improved model showed excellent performance,and could provide important technology and method support for the research and development of intelligent topdressing and field management on full-film double-ditch corn seedbed during seedling stage.