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Side-channel attacks and learning-vector quantization Article

Ehsan SAEEDI, Yinan KONG, Md. Selim HOSSAIN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 511-518 doi: 10.1631/FITEE.1500460

Abstract: Several approaches have been proposed to analyze side-channel information, among which machine learningMachine learning in terms of neural networks learns the signature (power consumption and electromagneticcryptography (ECC), to explore the efficiency of side-channel information characterization based on a learningvector quantization (LVQ) neural network.

Keywords： Side-channel attacks     Elliptic curve cryptography     Multi-class classification     Learning vector quantization    

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Vector quantization: a review Regular Papers

Ze-bin WU, Jun-qing YU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 4,   Pages 507-524 doi: 10.1631/FITEE.1700833

Abstract:

Vector quantization (VQ) is a very effective way to save bandwidth and storage for speech coding andTraditional vector quantization methods can be divided into mainly seven types, tree-structured VQ, directOver the past decade, quantization-based approximate nearest neighbor (ANN) search has been developingSo, finding a vector quantization method that can strike a balance between speed and accuracy and consume

Keywords： Approximate nearest neighbor search     Image coding     Vector quantization    

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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.The training algorithm of the neural network determines its learning speed, stability, weight convergenceIn this paper, the neural estimator has been studied with conventional and proposed learning algorithmsThe proposed learning algorithm is found to exhibit good estimation and tracking capabilities.

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

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Training time minimization for federated edge learning with optimized gradient quantization and bandwidth Research Article

Peixi LIU, Jiamo JIANG, Guangxu ZHU, Lei CHENG, Wei JIANG, Wu LUO, Ying DU, Zhiqin WANG,jiangjiamo@caict.ac.cn,gxzhu@sribd.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8,   Pages 1247-1263 doi: 10.1631/FITEE.2100538

Abstract: Training a machine learning model with (FEEL) is typically time consuming due to the constrained computationIn particular, a stochastic quantization scheme is adopted for compression of uploaded gradients, whichConstrained by the total bandwidth, the problem is formulated as a joint quantization level and bandwidthWith different learning tasks and models, the validation of our analysis and the near-optimal performance

Keywords： Federated edge learning     Quantization optimization     Bandwith allocation     Training time minimization    

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Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Amit SHIULY; Debabrata DUTTA; Achintya MONDAL

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 3,   Pages 347-358 doi: 10.1007/s11709-022-0819-z

Abstract: In the present study, a new image-based machine learning method is used to predict concrete compressiveThese include support-vector machine model and various deep convolutional neural network models, namelyThe images and corresponding compressive strength were then used to train machine learning models toOverall, the present findings validated the use of machine learning models as an efficient means of estimating

Keywords： support vector machine     deep convolutional neural network     microscope     digital image     curing period    

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A robust intelligent audio watermarking scheme using support vector machine Article

Mohammad MOSLEH,Hadi LATIFPOUR,Mohammad KHEYRANDISH,Mahdi MOSLEH,Najmeh HOSSEINPOUR

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 12,   Pages 1320-1330 doi: 10.1631/FITEE.1500297

Abstract: water-marking scheme using a synergistic combination of singular value decomposition (SVD) and support vectorBy learning the destructive effects of noise, the detector in question can effectively retrieve the watermark

Keywords： Audio watermarking     Copyright protection     Singular value decomposition (SVD)     Machine learning     Supportvector machine (SVM)    

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Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging

Baiwan Zhou, Dongmei An, Fenglai Xiao, Running Niu, Wenbin Li, Wei Li, Xin Tong, Graham J Kemp, Dong Zhou, Qiyong Gong, Du Lei

Frontiers of Medicine 2020, Volume 14, Issue 5,   Pages 630-641 doi: 10.1007/s11684-019-0718-4

Abstract: Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controlspatients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vector

Keywords： temporal lobe epilepsy     functional magnetic resonance imaging     structural magnetic resonance imaging     machine learning     support vector machine    

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Interactive image segmentation with a regression based ensemble learning paradigm Article

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 1002-1020 doi: 10.1631/FITEE.1601401

Abstract: novel interactive image segmentation method via a regression-based ensemble model with semi-supervised learningcomplementary spline regressors and strengthening the robustness of each regressor via semi-supervised learningThen, a regressor boosting method based on a clustering hypothesis and semi-supervised learning is proposedNext, a support vector regression (SVR) based decision fusion model is adopted to integrate the results

Keywords： Interactive image segmentation     Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-platespline regression (TPSR)     Semi-supervised learning     Support vector regression (SVR)    

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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 SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRMThe 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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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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Performance analysis of new word weighting procedures for opinion mining Article

G. R. BRINDHA,P. SWAMINATHAN,B. SANTHI

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 11,   Pages 1186-1198 doi: 10.1631/FITEE.1500283

Abstract: The proliferation of forums and blogs leads to challenges and opportunities for processing large amounts of information. The information shared on various topics often contains opinionated words which are qualitative in nature. These qualitative words need statistical computations to convert them into useful quantitative data. This data should be processed properly since it expresses opinions. Each of these opinion bearing words differs based on the significant meaning it conveys. To process the linguistic meaning of words into data and to enhance opinion mining analysis, we propose a novel weighting scheme, referred to as inferred word weighting (IWW). IWW is computed based on the significance of the word in the document (SWD) and the significance of the word in the expression (SWE) to enhance their performance. The proposed weighting methods give an analytic view and provide appropriate weights to the words compared to existing methods. In addition to the new weighting methods, another type of checking is done on the performance of text classification by including stop-words. Generally, stop-words are removed in text processing. When this new concept of including stop-words is applied to the proposed and existing weighting methods, two facts are observed: (1) Classification performance is enhanced; (2) The outcome difference between inclusion and exclusion of stop-words is smaller in the proposed methods, and larger in existing methods. The inferences provided by these observations are discussed. Experimental results of the benchmark data sets show the potential enhancement in terms of classification accuracy.

Keywords： Inferred word weight     Opinion mining     Supervised classification     Support vector machine (SVM)     Machinelearning    

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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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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

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 3,   Pages 382-389 doi: 10.15302/J-FASE-2018211

Abstract: 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, and the human lysozyme gene (hLZ) was then inserted into the vector by a digestion-ligationThe final vector containing the 8.5 kb mWAP 5′ promoter, 4.8 kb hLZ genomic DNA, and 8.0that the resulting vector regulates the expression of hLZ in milk.

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

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

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

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 1,   Pages 215-239 doi: 10.1007/s11709-018-0489-z

Abstract: 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

Keywords： bentonite/sepiolite plastic concrete     compressive strength     artificial neural network     support vector machine    

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Title Author Date Type Operation

Side-channel attacks and learning-vector quantization

Ehsan SAEEDI, Yinan KONG, Md. Selim HOSSAIN

Journal Article

Vector quantization: a review

Ze-bin WU, Jun-qing YU

Journal Article

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

A. CHITRA,S. HIMAVATHI

Journal Article

Training time minimization for federated edge learning with optimized gradient quantization and bandwidth

Peixi LIU, Jiamo JIANG, Guangxu ZHU, Lei CHENG, Wei JIANG, Wu LUO, Ying DU, Zhiqin WANG,jiangjiamo@caict.ac.cn,gxzhu@sribd.cn

Journal Article

Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Amit SHIULY; Debabrata DUTTA; Achintya MONDAL

Journal Article

A robust intelligent audio watermarking scheme using support vector machine

Mohammad MOSLEH,Hadi LATIFPOUR,Mohammad KHEYRANDISH,Mahdi MOSLEH,Najmeh HOSSEINPOUR

Journal Article

Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging

Baiwan Zhou, Dongmei An, Fenglai Xiao, Running Niu, Wenbin Li, Wei Li, Xin Tong, Graham J Kemp, Dong Zhou, Qiyong Gong, Du Lei

Journal Article

Interactive image segmentation with a regression based ensemble learning paradigm

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Journal Article

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

Pijush SAMUI

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

Performance analysis of new word weighting procedures for opinion mining

G. R. BRINDHA,P. SWAMINATHAN,B. SANTHI

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

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

Journal Article

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

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

Journal Article