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Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised Research Article

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1814-1827 doi: 10.1631/FITEE.2200053

Abstract: As an indispensable part of process monitoring, the performance of relies heavily on the sufficiency of process knowledge. However, data labels are always difficult to acquire because of the limited sampling condition or expensive laboratory analysis, which may lead to deterioration of classification performance. To handle this dilemma, a new strategy is performed in which enhanced is employed to evaluate the value of each unlabeled sample with respect to a specific labeled dataset. Unlabeled samples with large values will serve as supplementary information for the training dataset. In addition, we introduce several reasonable indexes and criteria, and thus human labeling interference is greatly reduced. Finally, the effectiveness of the proposed method is evaluated using a numerical example and the Tennessee Eastman process.

Keywords： Semi-supervised     Active learning     Ensemble learning     Mixture discriminant analysis     Fault classification    

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NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning Research Articles

Jianke HU, Yin ZHANG,yinzh@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3,   Pages 409-421 doi: 10.1631/FITEE.2000657

Abstract: To alleviate oversmoothing, we propose a nested graph network (NGAT), which can work in a semi-supervised

Keywords： Graph learning     Semi-supervised learning     Node classification     Attention    

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Representation learning via a semi-supervised stacked distance autoencoder for image classification Research Articles

Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900116

Abstract: The model is called a semi-supervised distance .In the subsequent supervised training, the optimized parameters are set as the initial values.The proposed semi-supervised distance method is compared with the traditional , sparse , and supervised

Keywords： 自动编码器；图像分类；半监督学习；神经网络    

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Learning to select pseudo labels: a semi-supervised method for named entity recognition Research Articles

Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1800743

Abstract: Our semi-supervised framework includes three steps: constructing an optimal single neural model for a

Keywords： 命名实体识别；无标注数据；深度学习；半监督学习方法    

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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: paper presents a novel interactive image segmentation method via a regression-based ensemble model with semi-supervisedintegrating two complementary spline regressors and strengthening the robustness of each regressor via semi-supervisedThen, a regressor boosting method based on a clustering hypothesis and semi-supervised learning is proposed

Keywords： Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-plate spline regression (TPSR)     Semi-supervised    

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Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1332-1348 doi: 10.1631/FITEE.2200299

Abstract: Interactive medical image segmentation based on human-in-the-loop machine learning is a novel paradigm that draws on human expert knowledge to assist medical image segmentation. However, existing methods often fall into what we call interactive misunderstanding, the essence of which is the dilemma in trading off short- and long-term interaction information. To better use the interaction information at various timescales, we propose an interactive segmentation framework, called interactive MEdical image segmentation with self-adaptive Confidence CAlibration (MECCA), which combines action-based confidence learning and multi-agent reinforcement learning. A novel confidence network is learned by predicting the alignment level of the action with short-term interaction information. A confidence-based reward-shaping mechanism is then proposed to explicitly incorporate confidence in the policy gradient calculation, thus directly correcting the model’s interactive misunderstanding. MECCA also enables user-friendly interactions by reducing the interaction intensity and difficulty via label generation and interaction guidance, respectively. Numerical experiments on different segmentation tasks show that MECCA can significantly improve short- and long-term interaction information utilization efficiency with remarkably fewer labeled samples. The demo video is available at https://bit.ly/mecca-demo-video.

Keywords： image segmentation     Interactive segmentation     Multi-agent reinforcement learning     Confidence learning     Semi-supervised    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Data-based methods of supervised learning have gained popularity because of available Big Data and computingHowever, the common paradigm of the loss function in supervised learning requires large amounts of labeledTherefore, a fault detection method based on self-supervised feature learning was proposed to addressFirst, self-supervised learning was employed to extract features under various working conditions onlyThe self-supervised representation learning uses a sequence-based Triplet Loss.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Micromixing performance of the teethed high shear mixer under semi-batch operation

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 4,   Pages 546-559 doi: 10.1007/s11705-021-2069-3

Abstract: Semi-batch operated reaction processes are necessary for some competitive reaction systems to achieveparameters of the teethed high shear mixers were adjusted to study the micromixing performance in the semi-batchcarried out to disclose the evolution of the flow pattern and turbulent energy dissipation rate of the semi-batchparameters studied in this work, which can provide valuable guidance on the design and optimization of the semi-batch

Keywords： high shear mixer     semi-batch operation     micromixing performance     Villermaux/Dushman system     segregation    

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Bending and rotational behaviour of semi-continuous composite beams

WANG Jingfeng, LI Guoqiang

Frontiers of Structural and Civil Engineering 2008, Volume 2, Issue 2,   Pages 116-122 doi: 10.1007/s11709-008-0015-9

Abstract: Stresses and deflections were measured in various semi-continuous composite beams.composite connections were measured in terms of beam curvatures and deflections by using two full-scale semi-rigidThe effect of semi-rigid connections on the performance of composite beams with various loadings wasThe tests show that the semi-continuous composite beams are more economic and effective than the simpleThe semi-rigid connections affect the bending capacities and beam deflections, so the connection behavior

Keywords： rotational     effective     deflection calculation     semi-continuous composite     full-scale semi-rigid    

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Prediction of the theoretical and semi-empirical model of ambient temperature

Foued CHABANE,Noureddine MOUMMI,Abdelhafid BRIMA,Abdelhafid MOUMMI

Frontiers in Energy 2016, Volume 10, Issue 3,   Pages 268-276 doi: 10.1007/s11708-016-0413-y

Abstract: It is well known that the ambient temperature is a sensitive parameter which has a great effect on biology, technology, geology and even on human behavior. A prediction is a statement about an uncertain event. It is often, but not always, based upon experience or knowledge. Although guaranteed accurate information about the future is in many cases impossible, prediction can be useful to assist in making plans about possible developments. As a result, temperature profiles can be developed which accurately represent the expected ambient temperature exposure that this environment experiences during measurement. The ambient temperature over time is modeled based on the previous and data and using a Lagrange interpolation. To observe the comprehensive variation of ambient temperature the profile must be determined numerically. The model proposed in this paper can provide an acceptable way to measure the change in ambient temperature.

Keywords： ambient temperature     environment     correlation     theoretical model     semi-empirical    

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Cavitation in semi-open centrifugal impellers for a miniature pump

LUO Xianwu, LIU Shuhong, ZHANG Yao, XU Hongyuan

Frontiers in Energy 2008, Volume 2, Issue 1,   Pages 31-35 doi: 10.1007/s11708-008-0011-8

Abstract: Cavitation in miniature pumps was investigated experimentally for two semi-open centrifugal impellershave similar cavitation performances as an ordinary-size pump, with the cavitation performance of the semi-openAlso, both the hydraulic and cavitation performance of the semi-open impeller were improved by the leaned

Keywords： cavitation performance     semi-open impeller     increased     two-dimensional     efficiency    

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Removal of dyes from wastewater by growing fungal pellets in a semi-continuous mode

Tao Lu, Qilei Zhang, Shanjing Yao

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 338-345 doi: 10.1007/s11705-017-1644-0

Abstract: This semi-continuous mode, which consists of commutative processes of dye-removal and re-culture, has

Keywords： dye     mycelial pellets     marine fungus     bubble column reactor     semi-continuous biosorption    

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Utilization of waste vanadium-bearing resources in the preparation of rare-earth vanadate catalysts for semi-hydrogenation

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 12,   Pages 1793-1806 doi: 10.1007/s11705-022-2191-x

Abstract: Importantly, we found that rare-earth vanadate catalysts exhibited good activities toward the semi-hydrogenation

Keywords： petrochemical solid wastes     vanadium recovery     resource utilization     nanomaterials     semi-hydrogenation    

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Probe into semi dryland agriculture limited supplemental irrigation model in the water deficit areas

Li Yingneng

Strategic Study of CAE 2012, Volume 14, Issue 3,   Pages 41-45

Abstract: style="text-align: justify;">According to precipitation use and irrigation degree, the research to the semi-drylandThe paper emphatically discussed the questions of implication related with the semi-dryland agriculture, expounded the significance of the water deficit areas of North China, and gave the semi-dryland agriculturalthe characteristics of the water deficit areas in North China, the model and tactics of developing semi-dryland

Keywords： semi-dryland     agriculture     limited supplemental irrigation     mode    

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Uncertainty propagation in dynamics of composite plates: A semi-analytical non-sampling-based approach

Mahdi FAKOOR, Hadi PARVIZ

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1359-1371 doi: 10.1007/s11709-020-0658-8

Abstract: were investigated via development of a new approach named the deterministic-stochastic Galerkin-based semi-analytical

Keywords： composite plate     spatially varying stochastic properties     Galerkin method     polynomial chaos approach     semi-analytical    

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Title Author Date Type Operation

Ensemble enhanced active learning mixture discriminant analysis model and its application for semi-supervised

Weijun WANG, Yun WANG, Jun WANG, Xinyun FANG, Yuchen HE

Journal Article

NGAT: attention in breadth and depth exploration for semi-supervised graph representation learning

Jianke HU, Yin ZHANG,yinzh@zju.edu.cn

Journal Article

Representation learning via a semi-supervised stacked distance autoencoder for image classification

Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn

Journal Article

Learning to select pseudo labels: a semi-supervised method for named entity recognition

Zhen-zhen Li, Da-wei Feng, Dong-sheng Li, Xi-cheng Lu,lizhenzhen14@nudt.edu.cn,davyfeng.c@gmail.com,dsli@nudt.edu.cn,xclu@nudt.edu.cn

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

Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and

Journal Article

Micromixing performance of the teethed high shear mixer under semi-batch operation

Journal Article

Bending and rotational behaviour of semi-continuous composite beams

WANG Jingfeng, LI Guoqiang

Journal Article

Prediction of the theoretical and semi-empirical model of ambient temperature

Foued CHABANE,Noureddine MOUMMI,Abdelhafid BRIMA,Abdelhafid MOUMMI

Journal Article

Cavitation in semi-open centrifugal impellers for a miniature pump

LUO Xianwu, LIU Shuhong, ZHANG Yao, XU Hongyuan

Journal Article

Removal of dyes from wastewater by growing fungal pellets in a semi-continuous mode

Tao Lu, Qilei Zhang, Shanjing Yao

Journal Article

Utilization of waste vanadium-bearing resources in the preparation of rare-earth vanadate catalysts for semi-hydrogenation

Journal Article

Probe into semi dryland agriculture limited supplemental irrigation model in the water deficit areas

Li Yingneng

Journal Article

Uncertainty propagation in dynamics of composite plates: A semi-analytical non-sampling-based approach

Mahdi FAKOOR, Hadi PARVIZ

Journal Article