A User-Transformer Relation Identification Method Based on QPSO and Kernel Fuzzy Clustering

User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization(QPSO)and Fuzzy C-Means Clustering.The main idea is:as energymeters at different transformer areas exhibit different zero-crossing shift features,we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations.The proposed method contributes in three main ways.First,based on the fuzzy C-means clustering algorithm(FCM),the quantum particle swarm optimization(PSO)is introduced to optimize the FCM clustering center and kernel parameters.The optimized FCM algorithm can improve clustering accuracy and efficiency.Since easily falls into a local optimum,an improved PSO optimization algorithm(IQPSO)is proposed.Secondly,considering that traditional FCM cannot solve the linear inseparability problem,this article uses a FCM(KFCM)that introduces kernel functions.Combinedwith the IQPSOoptimization algorithm used in the previous step,the IQPSO-KFCM algorithm is proposed.Simulation experiments verify the superiority of the proposed method.Finally,the proposed method is applied to transformer detection.The proposed method determines the class members of transformers and meters in the actual transformer area,and obtains results consistent with actual user-transformer relations.This fully shows that the proposed method has practical application value.

Interpersonal Perception in Virtual Groups: Examining Homophily, Identification and Individual Attraction Using Social Relations Model in Network

With the penetration of the Internet, virtual groups have become more and more popular. The reliability and accuracy of interpersonal perception in the virtual environment is an intriguing issue. Using the Social relations model (SRM) [1], this paper investigates interpersonal perception in virtual groups from a multilevel perspective. In particular, it examines the following three areas: homophily, identification, and individual attraction, and explores how much of these directional and dyadic relational evaluations can be attributed to the effect of the actor, the partner, and the relationship.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

A fast automatic identification method for seismic belts based on distance correlation and its earthquake case

Earthquake prediction practice and a large number of earthquake cases show that anomalous images of small earthquake belts may appear near the epicenter before strong earthquakes.Through the research of earthquake cases,researchers have a relatively consistent method to determine the clarity of an identified seismic belt,but there is still a lack of method on seismic belt identification from the distribution of scattered points.Due to the complexity of exhaustive algorithm,the rapid automatic identification technique of seismic belts has been progressing slowly.Visual recognition is still the basic method of seismic belt identification.Based on the algorithm of distance correlation,this paper presents a fast automatic identification method of seismic belts.The effectiveness of this method was proved by 100 random earthquakes and an example of seismic belts of magnitude 4.0 before the 2005 Jiujiang M5.7 earthquake.The results show that:①the automatic identification of seismic belts should first identify the"relational earthquake",then identify the"suspected seismic belt",and finally use the criterion of seismic belt clarity to determine;②random earthquakes and real earthquakes identification results show that the distance correlation method can realize the fast automatic identification of seismic belts by computer.

A Study On the Structural Dimension of Middle Class Relational Identification in Chinese Context

Through in-depth interviews,this study makes an exploratory study on the dimension of the middle class relational identification in Chinese context by using the grounded theory.It is mainly composed of 4 dimensions:relational orientation,relational adaptation,relational evaluation and relational development.According to the four dimension model of middle class relational identification,the middle class relational identification in China is the cognitive and behavioral orientation that in the action of achieving a certain purpose,because of the perception of consistence with each other in role cognition and personal cognition,the middle class is willing to unite and trust,respect and understand and coordinate the conflict to adapt to this relationship,and then to form a positive evaluation of the relationship and a sense of belonging and commitment to this relationship.The construction of the structural dimension of middle class relational identification in China is conducive to explaining the endemic phenomena of Chinese middle class.

Damage Identification in Beam-Type Structures Using Pseudo Strain Energy Density and Grey Relation Coefficient

Based on pseudo strain energy density (PSED) and grey relation coefficient (GRC), an index is proposed to locate the damage of beam-type structures in time-domain. The genetic algorithm (GA) is utilized to identify the structural damage severity of confirmed damaged locations. Furthermore, a systematic damage identification program based on GA is developed on MATLAB platform. ANSYS is employed to conduct the finite element analysis of complicated civil engineering structures, which is embedded with interface technique. The two-step damage identification is verified by a finite element model of Xinxingtang Highway Bridge and a laboratory beam model based on polyvinylidens fluoride (PVDF). The bridge model was constructed with 57 girder segments, and simulated with 58 measurement points. The damaged segments were located accurately by GRC index regardless of damage extents and noise levels. With stiffness reduction factors of detected segments as variables, the GA program evolved for 150 generations in 6 h and identified the damage extent with the maximum errors of 1% and 3% corresponding to the noise to signal ratios of 0 and 5%, respectively. In contrast, the common GA-based method without using GRC index evolved for 600 generations in 24 h, but failed to obtain satisfactory results. In the laboratory test, PVDF patches were used as dynamic strain sensors, and the damage locations were identified due to the fact that GRC indexes of points near damaged elements were smaller than 0.6 while those of others were larger than 0.6. The GA-based damage quantification was also consistent with the value of crack depth in the beam model.

Identification of a LMNA (c.646C>T) variant by whole-exome sequencing in combination with a dilated cardiomyopathy (DCM) related gene filter in a family with familiar DCM

Dilated cardiomyopathy（DCM）is characterized by the dilated heart chambers and reduced systolic function in the absence of specific aetiology[1].Approximately one third of DCM cases are hereditary.In recent years,DCM concomitant with arrhythmias and sudden death resulting from gene mutation has been widely

ISOLATION AND IDENTIFICATION OF THE RELATED GENE MEDIATING γ-RADIATION-INDUCED APOPTOSIS IN HUMAN HL- 60 CELLS

To identify the member of the caspase family proteases involved in γ radiation induced apoptosis in HL 60 cells, using degenerated oligonucleotide primers encoding the highly conserved peptides, which were present in all known caspases, RT PCR was performed on poly (A) RNA from the γ radiation induced apoptotic HL 60 cells. Then, cloned and sequenced to identify the amplified DNA fragments. The results showed that the amplified DNA fragments were identified with a part of caspase 3 cDNA. It indicated that caspase 3 was involved in γ radiation induced apoptosis in HL 60 cells and may be the pivotal element of radiation induced apoptosis.

Inversion of focal mechanism and events identification using an improved relative amplitude method

The relative amplitude method （RAM） is more suitable for source inversion of low magnitude earthquakes because it avoids the modeling of short-period waveforms. We introduced an improved relative amplitude method （IRAM） which is more robust in practical cases. The IRAM uses a certain function to quantify the fitness between the observed and the predicted relative amplitudes among direct P wave, surface reflected pP and sP waves for a given focal mechanism. Using the IRAM, we got the fault-plane solutions of two earthquakes of mb4.9 and mb3.8, occurred in Issyk-Kul lake, Kyrgyzstan. For the larger event, its fault-plane solutions are consistent with the Harvard＇s CMT solutions. As to the smaller one, the strikes of the solution are consistent with those of the main faults near the epicenter. The synthetic long period waveforms and the predicted P wave first motions of the solutions are consistent with observations at some of regional stations. Finally, we demonstrated that fault-solutions cannot interpret the characteristics of teleseismic P waveforms of the underground nuclear explosion detonated in Democratic People＇s Republic of Korea （DPRK） on October 9, 2006.

IMMUNOCHEMICAL IDENTIFICATION AND LOCALIZATION OF CYTOCHROME P-450HSjISOZYME, AN ENZYME RELATED TO NITROSAMINE METABOLISM, IN HUMAN GASTRIC MUCOSA AND GASTRIC CARCINOMA

Monoclonal antibody (MAb) to rat liver cyto-chrome P-450j isozyme, an activating enzyme specific to nitrosamine metabolism, was used coupled with immunoblotting, densitometer scanning of SDS-PAGE gels and immunohistochemical technique. The trace P-450HSj isozyme (Mr. 51.5 Kd) was found in human gastric mucosa. It was similar to P-450j in molecular weight, catalytic and immunochemical properties. The concentrations of P-450HSj in mucosa of lesser curvature were higher than those in greater curvature. This might be one of the important reasons that lesser curvature is the commonest area for gastric carcinoma. But there was possibly less P-450HSj in gastric mucosa with cancer. Im-munohistochemically, P-450HSj was discovered in the cytoplasm of some glandular epithelial cells, especially in the glands with hyperplastic and intestinal metaplastic changes adjacent to carcinoma. It was also found in some normal glands and in tumor cells of high-differentiated adenocarcinoma, but not in those of low-differentiated ones. Following subjects are discussed: (1) the method of detecting trace P-450HSj, (2) the rule of distribution of P-450HSj, and (3) the relationship between the isozyme and the occurrence of gastric cancer caused by nitrosa-mines.

Identification of a candidate elongation related gene in rice induced by GA_3

We identified a gibberellin-induced gene frag-ment in rice elongation by using differentialdisplay(DD)of mRNA.The rice seedlingscarried the eui(elongated)gene,named Zhen-chang A,were used,which were sensitive toGAand elongated rapidly after application of

Nonlinear Modeling and Identification of Structural Joint by Response Control Vibration Test

Components of mechanical product are assembled by structural joints,such as bolting,riveting,welding,etc.Structural joints introduce nonlinearity to some engineering structures,and the nonlinearity need to be modeled precisely.To meet serious quality requirements,it is necessary to detect and identify nonlinearity of mechanical products for structural optimization.Modal test to acquire a dynamic response has been applied for decades,which provides reliable results for finite element(FE)model updating.Here response control vibration test for identification of nonlinearity is presented.A nonlinear system can be regarded as linearity for particular steady state response,and classical linear analysis tool is applicable to extract modal data for particular response.First,its applicability is illustrated by some numerical simulations.Subsequently,it is implemented on experimental setup with structural joints by shaking table.The stiffness and damping function dependent of relative displacement are fitted to describe its inherent nonlinearity.The spring and damping forces are identified by harmonic balance method(HBM)to predict output response.Based on the identified results,the procedure is recommended that it allows a reliable measurement of nonlinearity with a certain accuracy.

Structural damage identification using test static data based on grey system theory

A new structural damage identification method using limited test static displacement based on grey system theory is proposed in this paper. The grey relation coefficient of displacement curvature is defined and used to locate damage in the structure, and an iterative estimation scheme for solving nonlinear optimization programming problems based on the quadratic programming technique is used to identify the damage magnitude. A numerical example of a cantilever beam with single or multiple damages is used to examine the capability of the proposed grey-theory-based method to localize and identify damages. The factors of meas-urement noise and incomplete test data are also discussed. The numerical results showed that the damage in the structure can be localized correctly through using the grey-related coefficient of displacement curvature, and the damage magnitude can be iden-tified with a high degree of accuracy, regardless of the number of measured displacement nodes. This proposed method only requires limited static test data, which is easily available in practice, and has wide applications in structural damage detection.

On grey relation projection model based on projection pursuit

Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.

基于灰色关联度分析-极限学习机的低阻油层及水淹层测井识别——以渤海P区块馆陶组为例

历经近20的开发,渤海P区块进入高含水期,馆陶组发育的大量低阻油层与水淹层在测井曲线形态上差异不明显。为了精确进行水淹层识别以及水淹层等级划分,采用了机器学习算法。首先采用灰色关联度分析,筛选低阻油层和水淹层识别的敏感参数曲线;其次构建了极限学习机水淹层识别模型,对模型进行训练,获取最优参数。将其应用于实际资料处理,结果表明,基于灰色关联度分析极限学习机的低阻油层及水淹层测井识别方法对低阻油层与水淹层的预测精度较高,符合率达89.3%,远远优于未经过灰色关联度分析筛选的预测结果,具有实际应用价值。

投桃报李:临时员工助人行为对正式员工隐性知识分享的影响机制

多元雇佣触发的员工内部关系矛盾问题日趋复杂,如何促进多元雇佣聚力发展,已成为零工经济情境下理论和实践领域着力探讨的核心议题。文章基于社会交换理论,引入关系认同和感知义务作为中介变量,将任务相依性作为边界条件,构建临时员工助人行为对正式员工隐性知识分享的双路径机理模型,旨在分析临时员工助人行为对正式员工隐性知识分享的作用效果及潜在机制。通过对三阶段收集的237份纵向数据分析表明:关系认同和感知义务在临时员工助人行为与正式员工隐性知识分享之间起中介作用;任务相依性会强化临时员工助人行为对关系认同和感知义务的影响效应,并且任务相依性能够调节关系认同和感知义务的中介路径,即任务相依性程度越强,临时员工通过关系认同和感知义务对正式员工隐性知识分享的正向影响越强。

基于循证构建血液透析导管相关性血流感染早期识别及护理流程管理方案

目的:基于循证构建血液透析导管相关性血流感染早期识别及护理流程管理方案,以期提高临床护理质量,降低血液透析病人导管相关性血流感染发生率。方法:基于循证护理的方法,检索、评价、汇总国内外关于预防血液透析导管相关性感染护理管理的最佳证据,构建导管相关性血流感染早期识别及护理流程管理方案基本框架,采用德尔菲专家咨询法对17名专家开展两轮函询,确定方案各级条目,通过层次分析法确定条目权重。结果:两轮函询专家权威系数依次为0.862,0.860;Kendall′s W值分别为0.546(χ^(2)=76.804,P<0.001)、0.614(χ^(2)=93.371,P=0.005),最终筛选并确定包括2个一级条目、10个二级条目、35个三级条目的早期识别及护理流程管理方案。结论:基于循证构建的血液透析导管相关性血流感染早期识别及护理流程管理方案科学、可靠,能够为血液透析病人导管相关性血流感染的早期识别和管理提供依据。

基于GA-LSTM自适应卡尔曼滤波的路面不平度识别

准确、快速地识别出车辆当前行驶的路面激励信息,是实现智能底盘控制进而保证车辆平顺性的关键。针对传统路面不平度识别算法准确率低、自适应性差等问题,提出了基于遗传算法(genetic algorithm,GA)优化长短期记忆神经网络(long short-term memory networks,LSTM)自适应卡尔曼滤波的路面不平度识别算法。基于2自由度车辆悬架模型,通过灰色关联法选择LSTM神经网络的特征输入变量,并采用GA优化LSTM神经网络的模型参数以准确识别路面等级,并据此实时更新卡尔曼滤波器算法中的噪声矩阵,实现了在复杂路况下对路面不平度的自适应识别。仿真和试验研究表明,所提出的基于GA-LSTM自适应卡尔曼滤波算法能够快速准确的识别路面不平度与路面等级,与传统卡尔曼滤波算法相比,相关系数、均方根误差和最大绝对误差分别提高3.11%、37.5%和51.2%,表明所提算法对复杂工况具有很好的自适应能力。

ZL114A铝合金本构关系与失效准则参数的确定

针对航空发动机机匣材料ZL114A铝合金,构建描述该材料在较大温度范围下大变形及失效行为的材料模型。通过万能试验机及分离式霍普金森压杆试验装置测试ZL114A铝合金在常温准静态、高温和高应变率下的力学性能,分析温度和应变率对材料流动应力的影响。采用有限元程序和优化算法反求25~375℃内材料的硬化参数,结合高应变率(1310~5964 s^(-1))下材料的动态行为关系,构建包含塑性应变、温度及应变率的经验型本构模型。开展缺口拉伸、缺口压缩等试验并建立相对应的有限元模型,获取材料在不同应力三轴度下的失效应变,标定分段形式的Johnson-Cook(J-C)失效准则参数。通过不同温度下的平板侵彻试验和数值模拟验证失效准则及其参数的有效性。结果表明,ZL114A铝合金具有明显的应变硬化、温度软化及高应变率强化特性;具有应力饱和特征的Hockett-Sherby(HS)硬化模型较为准确地描述材料大变形下的力学行为;构建的材料本构关系可以描述ZL114A铝合金在大应变、宽温度、高应变率下的力学行为;分段形式的失效准则具有预测不同温度下材料失效行为的能力。