资源类型

期刊论文 73

年份

2023 2

2022 5

2021 3

2020 4

2019 7

2018 6

2017 5

2016 8

2015 7

2014 4

2013 5

2012 6

2011 2

2010 1

2009 6

2008 2

展开 ︾

关键词

最小二乘支持向量机 2

风场反演 2

HHT 1

HY-2卫星 1

SINS/GNSS数据融合 1

交互式图像分割；多元自适应回归样条；集成学习；薄板样条回归；半监督学习；支持向量回归 1

人工神经网络 1

人机识别；随机森林；支持向量机；逻辑回归；多维性能评价指标 1

全极化定标 1

全极化微波辐射计 1

全球定位系统 1

加窗 1

协同向量；任务分配；多智能体系统；联盟形成；人工智能 1

响应预测 1

图像质量评价；全参考方法；特征提取；核空间；支持向量回归 1

地球重力场 1

大地水准面 1

定位；中心对称十字阵；非圆信源；近场；方向矢量分解 1

并网逆变器；模型预测控制；直接功率控制；三矢量；恒定开关频率；功率误差 1

展开 ︾

检索范围：

排序： 展示方式：

Construction and identification of lentiviral RNA interference vector of rat leptin receptor gene

Zhengjuan LIU, Jie BIAN, Yuchuan WANG, Yongli ZHAO, Dong YAN, Xiaoxia WANG

《医学前沿（英文）》 2009年 第3卷 第1期   页码 57-60 doi: 10.1007/s11684-009-0003-z

摘要： Leptin resistance is a main mechanism of acquired childhood obesity, and the suppression of long form of leptin receptor (OBRb) gene expression in diet-induced obese rats indicates that the down-regulation of OBRb gene expression plays a pivotal role in the mechanism of leptin resistance. The aim of the present study was to construct the lentiviral RNA interference (RNAi) vector of rat OBRb gene and evaluate the effects of siRNA on silencing OBRb gene expression. The target sequence of siRNA-OBRb was designed, and the complementary DNA containing both sense and antisense oligonucleotides was synthesized. After phosphorylation and annealing, these double-stranded DNA was cloned to pRNA-lentivector-VGFP to construct pRNA-Lenti-OBRb-VGFP recombinants with U6-containing promoter, target sequence and Poly III terminator. Then, the products were confirmed by electrophoresis and sequencing analysis, and the effects of RNAi on reducing gene expression were further confirmed by real-time polymerase chain reaction in transfected rat glioma cells expressing OBRb. The target sequence of siRNA-OBRb was successfully cloned to pRNA-lentivector-VGFP, and the RNAi protocol specifically reduced the expression of OBRb mRNA by approximately 80% compared with controls in transfected rat glioma cells. The successful construction of rat lentivirus vectors expressing OBRb-specific shRNA may be useful for further investigation .

关键词： receptors     leptin     RNA interference     lentivirus vector    

HTML PDF 收藏

Construction of lentiviral vector carrying Rab9 gene and its expression in mouse brain

Youguo HAO, Min ZHANG, Jinzhi XU, Bitao BU, Jiajun WEI

《医学前沿（英文）》 2009年 第3卷 第2期   页码 141-147 doi: 10.1007/s11684-009-0041-6

摘要： Rab proteins and their effectors facilitate vesicular transport by tethering donor vesicles to their respective target membranes. Rab9 mediates late endosome-to- -Golgi-network trafficking. To explore the possibility of Rab9-related gene therapy for neurodegenerative diseases, we packed Lentivirus encoding Rab9. The expressing plasmid pCDH1-MCF1-Rab9-EF1-copGFP was constructed by using molecular biological techniques. The Lentivirus encoding Rab9 cDNA was packed by Lifectamine-2000 mediated co-transfection of the plasmid pPACKH1- , pPACKH1- and pVSV- into 293T cells. DNA sequencing proved the successful construction of pCDH1-MCF1-Rab9-EF1-copGFP. After 72 hours, the expression of GFP could be detected in BV-2 cells. Western blotting revealed that the Rab9 gene expression in BALB/c mice brain was up-regulated significantly 4 weeks after injection with Lentivirus encoding Rab9, which evidenced a satisfactory increasing effect of this virus. Administration of Lenti-Rab9 to postnatal day 3 Niemann-Pick disease type C (NPC) mice reduced motor defects and prevented the weight loss associated with female NPC mice, as well as modulating the death rate of Purkinje neurons. It is concluded that the packaging of Lentivirus encoding Rab9 was successful. Lentivirus encoding Rab9 can increase the expression of Rab9 gene effectively, which might offer a novel means for the treatment of neurodegenerative diseases.

关键词： Rab9     lentivirus     gene therapy     gene transfer    

HTML PDF 收藏

Cotransfecting norepinephrine transporter and vesicular monoamine transporter 2 genes for increased retention of metaiodobenzylguanidine labeled with iodine 131 in malignant hepatocarcinoma cells

null

《医学前沿（英文）》 2017年 第11卷 第1期   页码 120-128 doi: 10.1007/s11684-017-0501-3

摘要：

Norepinephrine transporter (NET) transfection leads to significant uptake of iodine-131-labeled metaiodobenzylguanidine (131I-MIBG) in non-neuroendocrine tumors. However, the use of 131I-MIBG is limited by its short retention time in target cells. To prolong the retention of 131I-MIBG in target cells, we infected hepatocarcinoma (HepG2) cells with Lentivirus-encoding human NET and vesicular monoamine transporter 2 (VMAT2) genes to obtain NET-expressing, NET-VMAT2-coexpressing, and negative-control cell lines. We evaluated the uptake and efflux of 131I-MIBG both in vitro and in vivo in mice bearing transfected tumors. NET-expressing and NET-VMAT2-coexpressing cells respectively showed 2.24 and 2.22 times higher 131I-MIBG uptake than controls. Two hours after removal of 131I-MIBG-containing medium, 25.4% efflux was observed in NET-VMAT2-coexpressing cells and 38.6% in NET-expressing cells. In vivo experiments were performed in nude mice bearing transfected tumors; results revealed that NET-VMAT2-coexpressing tumors had longer 131I-MIBG retention time than NET-expressing tumors. Meanwhile, NET-VMAT2-coexpressing and NET-expressing tumors displayed 0.54% and 0.19%, respectively, of the injected dose per gram of tissue 24 h after 131I-MIBG administration. Cotransfection of HepG2 cells with NET and VMAT2resulted in increased 131I-MIBG uptake and retention. However, the degree of increase was insufficient to be therapeutically effective in target cells.

关键词： norepinephrine transporter     vesicular monoamine transporter 2     -MIBG     gene therapy     lentivirus vector    

HTML PDF 收藏

Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

《结构与土木工程前沿（英文）》 2013年 第7卷 第1期   页码 72-82 doi: 10.1007/s11709-013-0185-y

摘要： A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibility as a classification problem, which is an imperative task in earthquake engineering. This paper examines the potential of SVM model in prediction of liquefaction using actual field cone penetration test (CPT) data from the 1999 Chi-Chi, Taiwan earthquake. The SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRM) induction principle to minimize the error. Using cone resistance ( ) and cyclic stress ratio ( ), model has been developed for prediction of liquefaction using SVM. Further an attempt has been made to simplify the model, requiring only two parameters ( and maximum horizontal acceleration ), for prediction of liquefaction. Further, developed SVM model has been applied to different case histories available globally and the results obtained confirm the capability of SVM model. For Chi-Chi earthquake, the model predicts with accuracy of 100%, and in the case of global data, SVM model predicts with accuracy of 89%. The effect of capacity factor ( ) on number of support vector and model accuracy has also been investigated. The study shows that SVM can be used as a practical tool for prediction of liquefaction potential, based on field CPT data.

关键词： earthquake     cone penetration test     liquefaction     support vector machine (SVM)     prediction    

HTML PDF 收藏

A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction

A. CHITRA,S. HIMAVATHI

《能源前沿（英文）》 2015年 第9卷 第1期   页码 22-30 doi: 10.1007/s11708-014-0339-1

摘要： Online estimation of rotor resistance is essential for high performance vector controlled drives. In this paper, a novel modified neural algorithm has been identified for the online estimation of rotor resistance. Neural based estimators are now receiving active consideration as they have a number of advantages over conventional techniques. The training algorithm of the neural network determines its learning speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. In this paper, the neural estimator has been studied with conventional and proposed learning algorithms. The sensitivity of the rotor resistance change has been tested for a wide range of variation from -50% to+50% on the stability of the drive system with and without estimator. It is quiet appealing to settle with optimal estimation time and error for the viable realization. The study is conducted extensively for estimation and tracking. The proposed learning algorithm is found to exhibit good estimation and tracking capabilities. Besides, it reduces computational complexity and, hence, more feasible for practical digital implementation.

关键词： neural networks     back propagation (BP)     rotor resistance estimators     vector control     induction motor    

HTML PDF 收藏

Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support vector

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

《结构与土木工程前沿（英文）》 2021年 第15卷 第2期   页码 520-536 doi: 10.1007/s11709-021-0689-9

摘要： This study aims to improve the unconfined compressive strength of soils using additives as well as by predicting the strength behavior of stabilized soils using two artificial-intelligence-based models. The soils used in this study are stabilized using various combinations of cement, lime, and rice husk ash. To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratory dataset comprising 137 soil specimens treated with different combinations of cement, lime, and rice husk ash is used. Two artificial-intelligence-based models including artificial neural networks and support vector machines are used comparatively to predict the strength characteristics of soils treated with cement, lime, and rice husk ash under different conditions. The suggested models predicted the unconfined compressive strength of soils accurately and can be introduced as reliable predictive models in geotechnical engineering. This study demonstrates the better performance of support vector machines in predicting the strength of the investigated soils compared with artificial neural networks. The type of kernel function used in support vector machine models contributed positively to the performance of the proposed models. Moreover, based on sensitivity analysis results, it is discovered that cement and lime contents impose more prominent effects on the unconfined compressive strength values of the investigated soils compared with the other parameters.

关键词： unconfined compressive strength     artificial neural network     support vector machine     predictive models     regression    

HTML PDF 收藏

Efficiency of scalar and vector intensity measures for seismic slope displacements

Gang WANG

《结构与土木工程前沿（英文）》 2012年 第6卷 第1期   页码 44-52 doi: 10.1007/s11709-012-0138-x

摘要： Ground motion intensity measures are usually used to predict the earthquake-induced displacements in earth dams, soil slopes and soil structures. In this study, the efficiency of various single ground motion intensity measures (scalar ) or a combination of them (vector ) are investigated using the PEER-NGA strong motion database and an equivalent-linear sliding-mass model. Although no single intensity measure is efficient enough for all slope conditions, the spectral acceleration at 1.5 times of the initial slope period and Arias intensity of the input motion are found to be the most efficient scalar for flexible slopes and stiff slopes respectively. Vector can incorporate different characteristics of the ground motion and thus significantly improve the efficiency over a wide range of slope conditions. Among various vector considered, the spectral accelerations at multiple spectral periods achieve high efficiency for a wide range of slope conditions. This study provides useful guidance to the development of more efficient empirical prediction models as well as the ground motion selection criteria for time domain analysis of seismic slope displacements.

关键词： seismic slope displacements     intensity measures     empirical prediction    

HTML PDF 收藏

Construction of a universal recombinant expression vector that regulates the expression of human lysozyme

Shen LIU, Shengzhe SHANG, Xuezhen YANG, Huihua ZHANG, Dan LU, Ning LI

《农业科学与工程前沿（英文）》 2018年 第5卷 第3期   页码 382-389 doi: 10.15302/J-FASE-2018211

摘要：

The mammary gland provides a novel method for producing recombinant proteins in milk of transgenic animals. A key component in the technology is the construction of an efficient milk expression vector. Here, we established a simple method to construct a milk expression vector, by a combination of homologous recombination and digestion-ligation. Our methodology is expected to have the advantages of both plasmid and bacterial artificial chromosome (BAC) vectors. The BAC of mouse whey acidic protein gene (mWAP) was modified twice by homologous recombination to produce a universal expression vector, and the human lysozyme gene (hLZ) was then inserted into the vector by a digestion-ligation method. The final vector containing the 8.5 kb mWAP 5′ promoter, 4.8 kb hLZ genomic DNA, and 8.0 kb mWAP 3′ genomic DNA was microinjected into pronuclei of fertilized mouse embryos, to successfully generate two transgenic mouse lines that expressed recombinant human lysozyme (rhLZ) in milk. The highest expression level of rhLZ was 0.45 g·L−1, and rhLZ exhibited the same antibacterial activity as native hLZ. Our results have provided a simple approach to construct a universal milk expression vector, and demonstrated that the resulting vector regulates the expression of hLZ in milk.

关键词： BAC recombinant methods     gene expression     human lysozyme     transgenic mice     milk expression vector    

HTML PDF 收藏

bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector

Ali Reza GHANIZADEH, Hakime ABBASLOU, Amir Tavana AMLASHI, Pourya ALIDOUST

《结构与土木工程前沿（英文）》 2019年 第13卷 第1期   页码 215-239 doi: 10.1007/s11709-018-0489-z

摘要： Plastic concrete is an engineering material, which is commonly used for construction of cut-off walls to prevent water seepage under the dam. This paper aims to explore two machine learning algorithms including artificial neural network (ANN) and support vector machine (SVM) to predict the compressive strength of bentonite/sepiolite plastic concretes. For this purpose, two unique sets of 72 data for compressive strength of bentonite and sepiolite plastic concrete samples (totally 144 data) were prepared by conducting an experimental study. The results confirm the ability of ANN and SVM models in prediction processes. Also, Sensitivity analysis of the best obtained model indicated that cement and silty clay have the maximum and minimum influences on the compressive strength, respectively. In addition, investigation of the effect of measurement error of input variables showed that change in the sand content (amount) and curing time will have the maximum and minimum effects on the output mean absolute percent error (MAPE) of model, respectively. Finally, the influence of different variables on the plastic concrete compressive strength values was evaluated by conducting parametric studies.

关键词： bentonite/sepiolite plastic concrete     compressive strength     artificial neural network     support vector machine     parametric analysis    

HTML PDF 收藏

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

《环境科学与工程前沿（英文）》 2019年 第13卷 第2期 doi: 10.1007/s11783-019-1102-y

摘要：

An image-recognition-based diagnosis system of pipe defect types was established.

1043 practical pipe images were gathered by CCTV robot in a southern Chinese city.

The overall accuracy of the system is 84% and the highest accuracy is 99.3%.

The accuracy shows positive correlation to the number of training samples.

关键词： Sewer pipe defects     Defect diagnosing     Image recognition     Multi-features extraction     Support vector machine    

HTML PDF 收藏

A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector

Venkadesan ARUNACHALAM,Himavathi SRINIVASAN,A. MUTHURAMALINGAM

《能源前沿（英文）》 2016年 第10卷 第4期   页码 382-392 doi: 10.1007/s11708-016-0421-y

摘要： This paper presents a new neural network based model reference adaptive system (MRAS) to solve low speed problems for estimating rotor resistance in vector control of induction motor (IM). The MRAS using rotor flux as the state variable with a two layer online trained neural network rotor flux estimator as the adaptive model (FLUX-MRAS) for rotor resistance estimation is popularly used in vector control. In this scheme, the reference model used is the flux estimator using voltage model equations. The voltage model encounters major drawbacks at low speeds, namely, integrator drift and stator resistance variation problems. These lead to a significant error in the estimation of rotor resistance at low speed. To address these problems, an offline trained NN with data incorporating stator resistance variation is proposed to estimate flux, and used instead of the voltage model. The offline trained NN, modeled using the cascade neural network, is used as a reference model instead of the voltage model to form a new scheme named as “NN-FLUX-MRAS.” The NN-FLUX-MRAS uses two neural networks, namely, offline trained NN as the reference model and online trained NN as the adaptive model. The performance of the novel NN-FLUX-MRAS is compared with the FLUX-MRAS for low speed problems in terms of integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The proposed NN-FLUX-MRAS is shown to overcome the low speed problems in Matlab simulation.
HTML PDF 收藏

向量量化综述 Regular Papers

Ze-bin WU, Jun-qing YU

《信息与电子工程前沿（英文）》 2019年 第20卷 第4期   页码 507-524 doi: 10.1631/FITEE.1700833

摘要： 向量量化用于语音与图像编码可有效减小带宽和存储开销。根据码书生成过程，可将传统向量量化方法分为7类：树形向量量化、直和向量量化、迪卡尔积向量量化、格子向量量化、基于分类的向量量化、反馈向量量化以及模糊向量量化。在过去10年中，基于向量量化的近似近邻搜索发展迅速，涌现大量在大规模数据集内存中搜索图像的编码方法。这些方法的一个显著特征是使用多个码书，形成两种新的码书结构：线性组合码书和联合码书，这将成为未来发展趋势。这些方法用于近似近邻搜索的本质是在速度、准确率和空间开销之间权衡，有时其中一个会受损。因此，找到一个在速度、准确率和空间开销中平衡的向量量化方法依然是一个值得研究的问题。

关键词： 近似近邻搜索；图像编码；向量量化    

HTML PDF 收藏

Damage assessment of laminated composite beam structures using damage locating vector (DLV) method

T. VO-DUY,N. NGUYEN-MINH,H. DANG-TRUNG,A. TRAN-VIET,T. NGUYEN-THOI

《结构与土木工程前沿（英文）》 2015年 第9卷 第4期   页码 457-465 doi: 10.1007/s11709-015-0303-0

摘要： In this paper, the damage locating vector (DLV) method using normalized cumulative energy ( ) is employed to locate multiple damage sites in laminated composite beam structures. Numerical simulations of two laminated composite beams are employed to investigate several damage scenarios in which the degradation of elements is modeled by the reduction in the longitudinal Young’s modulus and transverse Young’s modulus of beam layers. The results show that the DLV method gives good performance for this kind of structure.

关键词： normalized cumulative energy     structural health monitoring (SHM)     damage locating vector method (DLV)     laminated composite beam structure    

HTML PDF 收藏

Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor

F. BENCHABANE, A. TITAOUINE, O. BENNIS, K. YAHIA, D. TAIBI

《能源前沿（英文）》 2012年 第6卷 第2期   页码 129-137 doi: 10.1007/s11708-012-0183-0

摘要： This paper investigates a Luenberger flux observer with speed adaptation for a direct field oriented control of an induction motor. An improved method of speed estimation that operates on the principle of speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltage and current. Simulation results show that the proposed direct field oriented control with the proposed observer provides good performance dynamic characteristics. The induction motor is fed by an indirect power electronics converter. This indirect converter is controlled by a sliding mode technique that enables minimization of harmonics introduced by the line converter, as well as the control of the power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

关键词： induction motor     direct filed oriented control     Luenberger observer     estimation     space vector modulation (SVM)     sliding mode control     boost-rectifier    

HTML PDF 收藏

最小二乘支持向量机的扩展及其在时间序列预测中的应用

向小东

《中国工程科学》 2008年 第10卷 第11期   页码 89-92

摘要：

根据时间序列近期数据较远期数据包含有更多未来信息的思想，对最小二乘支持向量机预测方法进行了扩展，得到了更具一般性的最小二乘支持向量机预测模型，给出了扩展后的预测模型具体算法。两个时间序列的预测实例表明，扩展后的预测方法获得了更好的预测效果，提升了最小二乘支持向量机预测方法的价值。

关键词： 最小二乘支持向量机     扩展     时间序列     预测    

HTML PDF 收藏

标题 作者 时间 类型 操作

Construction and identification of lentiviral RNA interference vector of rat leptin receptor gene

Zhengjuan LIU, Jie BIAN, Yuchuan WANG, Yongli ZHAO, Dong YAN, Xiaoxia WANG

期刊论文

Construction of lentiviral vector carrying Rab9 gene and its expression in mouse brain

Youguo HAO, Min ZHANG, Jinzhi XU, Bitao BU, Jiajun WEI

期刊论文

Cotransfecting norepinephrine transporter and vesicular monoamine transporter 2 genes for increased retention of metaiodobenzylguanidine labeled with iodine 131 in malignant hepatocarcinoma cells

null

期刊论文

Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

期刊论文

A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction

A. CHITRA,S. HIMAVATHI

期刊论文

Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support vector

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

期刊论文

Efficiency of scalar and vector intensity measures for seismic slope displacements

Gang WANG

期刊论文

Construction of a universal recombinant expression vector that regulates the expression of human lysozyme

Shen LIU, Shengzhe SHANG, Xuezhen YANG, Huihua ZHANG, Dan LU, Ning LI

期刊论文

bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector

Ali Reza GHANIZADEH, Hakime ABBASLOU, Amir Tavana AMLASHI, Pourya ALIDOUST

期刊论文

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in

Xiangyang Ye, Jian’e Zuo, Ruohan Li, Yajiao Wang, Lili Gan, Zhonghan Yu, Xiaoqing Hu

期刊论文

A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector

Venkadesan ARUNACHALAM,Himavathi SRINIVASAN,A. MUTHURAMALINGAM

期刊论文

向量量化综述

Ze-bin WU, Jun-qing YU

期刊论文

Damage assessment of laminated composite beam structures using damage locating vector (DLV) method

T. VO-DUY,N. NGUYEN-MINH,H. DANG-TRUNG,A. TRAN-VIET,T. NGUYEN-THOI

期刊论文

Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor

F. BENCHABANE, A. TITAOUINE, O. BENNIS, K. YAHIA, D. TAIBI

期刊论文

最小二乘支持向量机的扩展及其在时间序列预测中的应用

向小东

期刊论文