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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

Frontiers in Energy 2012, Volume 6, Issue 2,   Pages 129-137 doi: 10.1007/s11708-012-0183-0

Abstract: 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.

Keywords： induction motor     direct filed oriented control     Luenberger observer     estimation     space vector modulation    

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Fault tolerant control strategy for modular PWM current source inverter

Frontiers in Energy 2023, Volume 17, Issue 2,   Pages 228-238 doi: 10.1007/s11708-022-0852-6

Abstract: , a fault-tolerant control method for an input-series output-parallel modular grid-tied pulse-width modulationThis method actively offsets the neutral point of the current space vector to ensure a sinusoidal outputthe proposed method effectively suppresses the resonance caused by the transformer and the modified modulation

Keywords： current source converter (CSC)     fault-tolerant control     space vector modulation     active damping     resonance    

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Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

Abdelkarim AMMAR,Amor BOUREK,Abdelhamid BENAKCHA

Frontiers in Energy 2020, Volume 14, Issue 4,   Pages 836-849 doi: 10.1007/s11708-017-0444-z

Abstract: used to generate reference voltages in stationary frame and give them to the controlled motor after modulationby a space vector modulation (SVM) inverter.

Keywords： induction motor     direct torque control (DTC)     space vector modulation (SVM)     sliding mode control (SMC)    

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Aneffective approach for low-complexity maximumlikelihood based automatic modulation classification of Article

Maqsood H. SHAH, Xiao-yu DANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 465-475 doi: 10.1631/FITEE.1800306

Abstract: A low-complexity likelihood methodology is proposed for automatic modulation classification of orthogonalspace-time block code (STBC) based multiple-input multiple-output (MIMO) systems.Alamouti-STBC systems with 2 ×2 and 2 ×1 and space-time transmit diversity with a 4 ×4 transmit and receiveSome popular modulation schemes are used as the modulation test pool.

Keywords： Multiple-input multiple-output     Space-time block code     Maximum likelihood     Automatic modulation classification    

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High efficiency spreading spectrum modulation based on double orthogonal complex sequences

Shi Xiaohong

Strategic Study of CAE 2012, Volume 14, Issue 3,   Pages 108-112

Abstract:

This paper presents a kind of high efficiency spreading spectrum modulation

Keywords： modulation and demodulation     high efficiency spreading spectrum modulation     forward phase correction    

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A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1088-1098 doi: 10.1631/FITEE.1500111

Abstract: This paper describes a new technique of driving pulse edge modulation for insulated gate bipolar transistors

Keywords： Driving pulse edge modulation     Switching voltage spike     Complex programmable logic device (CPLD)     Active    

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Image quality assessmentmethod based on nonlinear feature extraction in kernel space Article

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10,   Pages 1008-1017 doi: 10.1631/FITEE.1500439

Abstract: To match human perception, extracting perceptual features effectively plays an important role in image quality assessment. In contrast to most existing methods that use linear transformations or models to represent images, we employ a complex mathematical expression of high dimensionality to reveal the statistical characteristics of the images. Furthermore, by introducing kernel methods to transform the linear problem into a nonlinear one, a full-reference image quality assessment method is proposed based on high-dimensional nonlinear feature extraction. Experiments on the LIVE, TID2008, and CSIQ databases demonstrate that nonlinear features offer competitive performance for image inherent quality representation and the proposed method achieves a promising performance that is consistent with human subjective evaluation.

Keywords： Image quality assessment     Full-reference method     Feature extraction     Kernel space     Support vector regression    

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Cannabidiol prevents depressive-like behaviors through the modulation of neural stem cell differentiation

Frontiers of Medicine 2022, Volume 16, Issue 2,   Pages 227-239 doi: 10.1007/s11684-021-0896-8

Abstract: prevented rNSCs overactivation and differentiation into astrocyte, which was partly mediated by the modulation

Keywords： cannabidiol     depression     radial neural stem cells     neurogenesis    

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

Pijush SAMUI

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 1,   Pages 72-82 doi: 10.1007/s11709-013-0185-y

Abstract: A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibilityThe effect of capacity factor ( ) on number of support vector and model accuracy has also been investigated

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

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

A. CHITRA,S. HIMAVATHI

Frontiers in Energy 2015, Volume 9, Issue 1,   Pages 22-30 doi: 10.1007/s11708-014-0339-1

Abstract: Online estimation of rotor resistance is essential for high performance vector controlled drives.

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

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

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 520-536 doi: 10.1007/s11709-021-0689-9

Abstract: Two artificial-intelligence-based models including artificial neural networks and support vector machinesThis study demonstrates the better performance of support vector machines in predicting the strengthThe type of kernel function used in support vector machine models contributed positively to the performance

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

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Efficiency of scalar and vector intensity measures for seismic slope displacements

Gang WANG

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 1,   Pages 44-52 doi: 10.1007/s11709-012-0138-x

Abstract: efficiency of various single ground motion intensity measures (scalar ) or a combination of them (vectorVector can incorporate different characteristics of the ground motion and thus significantly improveAmong various vector considered, the spectral accelerations at multiple spectral periods achieve high

Keywords： seismic slope displacements     intensity measures     empirical prediction    

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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

Frontiers of Medicine 2009, Volume 3, Issue 1,   Pages 57-60 doi: 10.1007/s11684-009-0003-z

Abstract: The aim of the present study was to construct the lentiviral RNA interference (RNAi) vector of rat OBRb

Keywords： receptors     leptin     RNA interference     lentivirus vector    

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The “Tiangong” Chinese Space Station project

Yang HONG

Frontiers of Engineering Management 2018, Volume 5, Issue 2,   Pages 278-283 doi: 10.15302/J-FEM-2018202

Keywords： manned space station     space station project     basic design    

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Modulation of Gut Microbiota in Pathological States

Yulan Wang, Baohong Wang, Junfang Wu, Xiangyang Jiang, Huiru Tang, Ole H. Nielsen

Engineering 2017, Volume 3, Issue 1,   Pages 83-89 doi: 10.1016/J.ENG.2017.01.013

Abstract:

The human microbiota is an aggregate of microorganisms residing in the human body, mostly in the gastrointestinal tract (GIT). Our gut microbiota evolves with us and plays a pivotal role in human health and disease. In recent years, the microbiota has gained increasing attention due to its impact on host metabolism, physiology, and immune system development, but also because the perturbation of the microbiota may result in a number of diseases. The gut microbiota may be linked to malignancies such as gastric cancer and colorectal cancer. It may also be linked to disorders such as nonalcoholic fatty liver disease (NAFLD); obesity and diabetes, which are characterized as “lifestyle diseases” of the industrialized world; coronary heart disease; and neurological disorders. Although the revolution in molecular technologies has provided us with the necessary tools to study the gut microbiota more accurately, we need to elucidate the relationships between the gut microbiota and several human pathologies more precisely, as understanding the impact that the microbiota plays in various diseases is fundamental for the development of novel therapeutic strategies. Therefore, the aim of this review is to provide the reader with an updated overview of the importance of the gut microbiota for human health and the potential to manipulate gut microbial composition for purposes such as the treatment of antibiotic-resistant Clostridium difficile (C. difficile) infections. The concept of altering the gut community by microbial intervention in an effort to improve health is currently in its infancy. However, the therapeutic implications appear to be very great. Thus, the removal of harmful organisms and the enrichment of beneficial microbes may protect our health, and such efforts will pave the way for the development of more rational treatment options in the future.

Keywords： Gut microbes     Diseases     Microbial modulation    

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Title Author Date Type Operation

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

Journal Article

Fault tolerant control strategy for modular PWM current source inverter

Journal Article

Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

Abdelkarim AMMAR,Amor BOUREK,Abdelhamid BENAKCHA

Journal Article

Aneffective approach for low-complexity maximumlikelihood based automatic modulation classification of

Maqsood H. SHAH, Xiao-yu DANG

Journal Article

High efficiency spreading spectrum modulation based on double orthogonal complex sequences

Shi Xiaohong

Journal Article

A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

Journal Article

Image quality assessmentmethod based on nonlinear feature extraction in kernel space

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Journal Article

Cannabidiol prevents depressive-like behaviors through the modulation of neural stem cell differentiation

Journal Article

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

Pijush SAMUI

Journal Article

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

A. CHITRA,S. HIMAVATHI

Journal Article

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

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

Journal Article

Efficiency of scalar and vector intensity measures for seismic slope displacements

Gang WANG

Journal Article

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

Journal Article

The “Tiangong” Chinese Space Station project

Yang HONG

Journal Article

Modulation of Gut Microbiota in Pathological States

Yulan Wang, Baohong Wang, Junfang Wu, Xiangyang Jiang, Huiru Tang, Ole H. Nielsen

Journal Article