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Error Formulas for Lagrange Projectors Determined by Cartesian Sets

Journal of Systems Science & Complexity 2018年第4期31卷 1090-1102页

作者： LI Zhe ZHANG Shugong DONG Tian GONG Yihe School of Science Changchun University of Science and Technology Changchun 130022 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University Changchun 130012 China Northeast Electric Power University Jilin 132012 China School of Mathematics Jilin University Changchun 130012 China

This paper studies error formulas for Lagrange projectors determined by Cartesian sets. Cartesian sets are properly subgrids of tensor product grids. Given interpolated functions with all order continuous partial derivatives, the authors directly construct the good error formulas for Lagrange projectors determined by Cartesian sets. Owing to the special algebraic structure, such a good error formula is useful for error estimate.

关键词： Cartesian sets error formulas ideal interpolation multivariate polynomial interpolation

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Deriving all minimal consistency-based diagnosis sets using SAT solvers

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Progress in Natural Science:Materials International 2009年第4期19卷 489-494页

作者： Xiangfu Zhao a,b, Liming Zhang a,b, Dantong Ouyang a,b, Yu Jiao a,b a key laboratory of symbolic computation and knowledge engineering of ministry of education, Jilin University, Changchun 130012, China b School of Computer Science and Technology, Jilin University, Changchun 130012, China [a]Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China [b]School of Computer Science and Technology Jilin University Changchun 130012 China

In this paper, a novel method is proposed for judging whether a component set is a consistency-based diagnostic set, using SAT solv- ers. Firstly, the model of the system to be diagnosed and all the observations are described with conjunctive normal forms (CNF). Then, all the related clauses in the CNF files to the components other than the considered ones are extracted, to be used for satisfiability checking by SAT solvers. Next, all the minimal consistency-based diagnostic sets are derived by the CSSE-tree or by other similar algorithms. We have implemented four related algorithms, by calling the gold medal SAT solver in SAT07 competition – RSAT. Experimental results show that all the minimal consistency-based diagnostic sets can be quickly computed. Especially our CSSE-tree has the best effciency for the singleor double-fault diagnosis.

关键词： Conjunctive normal form Consistency-based diagnosis Model-based diagnosis SAT solver

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An Automatic Solution in Security Inspection 7

An Automatic Solution in Security Inspection

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7th International Conference on Machine Vision and Information Technology, CMVIT 2023

作者： Zhang, Hui Zhang, Xiaoli Ministry of Education Key Laboratory of Symbolic Computation and Knowledge Engineer Changchun China

ISBN: (纸本)9781665464857

In this paper, we present a brand new dataset named cellphone buttery defects in X-ray(CBDx). CBDx consists of 300 X-ray images and 250 of them are anomaly free. We name them 'good'. Others have some defects in the area of buttery. We name them 'anomaly', as Fig. 1. It raises a new task of detecting anomaly defects of cellphone butteries. But the challenge is how to distinguish the anomaly in the case of only training the 'good' cellphone. We define this task as an anomaly detection task. We propose an approach to deal with the task from the perspective of unbalanced classification. Specifically, we propose a data augmentation strategy that creates an anomaly sample mimic to the real defects. It helps the classifier to learn self-supervised deep representations and then make it an one-class classifier based on the representations. The classifier is well designed to discriminate the defect samples from the good ones. We evaluate different data augmentation strategies on CBDx. Our approach is more significant in this scenario with no defect training samples, which can be applied in real-world security inspection someday. Also, it can be used on the industrial texture anomaly detection, such as MVTec_AD. © 2023 IEEE.

关键词： Anomaly detection

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Local feature aggregation algorithm based on graph convolutional network

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Frontiers of Computer Science 2022年第3期16卷 203-205页

作者： Hao WANG Liyan DONG Minghui SUN College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China

1Introduction and main contributions In the field of social networks and knowledge graphs,semi-supervised learning models based on graph convolutional networks have achieved great success in node classification[1],inductive node embedding[2],link prediction[3],and *** semi-supervised models based on graph convolutional network(GCN)[4]expect to obtain more feature information of a graph or accelerate the training.

关键词： convolution aggregation semi

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DeciLS-PBO: an effective local search method for pseudo-Boolean optimization

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Frontiers of Computer Science 2024年第5期18卷 239-241页

作者： Luyu JIANG Dantong OUYANG Qi ZHANG Liming ZHANG College of Computer Science and Technology Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education) Jilin UniversityChangchun 130012China

1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromi... 详细信息

关键词： Max optimization local

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Boosting few-shot point cloud segmentation with intra-class correlation and iterative prototype fusion

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Computer Vision and Image Understanding 2025年 258卷

作者： Zhang, Xindan Li, Ying Zhang, Xinnian College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China of Information and Communication Technology Ajou University Korea Republic of

Semantic segmentation of 3D point clouds is often limited by the challenge of obtaining labeled data. Few-shot point cloud segmentation methods, which can learn previously unseen categories, help reduce reliance on labeled datasets. However, existing methods are susceptible to correlation noise and suffer from significant discrepancies between support prototypes and query features. To address these issues, we first introduce an intra-class correlation enhancement module for filtering correlation noise driven by inter-class similarity and intra-class diversity. Second, to better represent the target classes, we propose an iterative prototype fusion module that adapts the query point cloud feature space, mitigating the problem of object variations in the support set and query set. Extensive experiments on S3DIS and ScanNet benchmark datasets demonstrate that our approach achieves competitive performance with state-of-the-art methods. © 2025 Elsevier Inc.

关键词： Semantic Segmentation

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Efficient Image Transmission Schemes over Zigbee-Based Image Sensor Networks

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Chinese Journal of Electronics 2016年第2期25卷 284-289页

作者： TAO Dan YANG Guangwei CHEN Houjin WU Hao LIU Pingping School of Electronic and Information Engineering Beijing Jiaotong University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University College of Computer Science and Technology Jilin University

Image transmission is one of the biggest challenges in wireless sensor networks because of the limited resource on sensor nodes. We proposed two image transmission schemes driven by reliability and real time considerations in order to transfer JPEG images over Zigbee-based sensor networks. By adding two bytes counter in the header of data packet, we can easily solve the repeated data reception problem caused by retransmission mechanism in traditional Zigbees network layer. We proposed an efficient retransmission and acknowledgment mechanism in Zigbees application layer. By classifying different data reception response events, we can provide data packets with differential responses and ensure that image packets can be transferred quickly even with large maximum number of retransmission. Practical results show the effectiveness of our solutions to make image transmission over Zigbee-based sensor networks efficient.

关键词： Image sensor networks Image transmission Retransmission and acknowledgment mechanism Zigbee

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Applying model-transformation techniques to ontology evolution

Applying model-transformation techniques to ontology evoluti...

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2nd International Conference on Grid Service engineering and Management, GSEM 2005 - Co-located with the 6th International Conference on Net.ObjectDays 2005, NODe 2005

作者： Jin, Longfei Liu, Lei Guo, Degui Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education of China Jilin University Changchun China

ISBN: (纸本)3885793989

Ontology evolution in the Model Driven Semantic Web can be looked as a process of model transformations. A model-transformation based conceptual framework for ontology evolution is presented in the paper. Applications of model transformations in every phase of ontology evolution process are described. The framework combines technologies of ontology evolution, Ontology Definition Metamodel and model transformations, and it can be looked as a method for ontology evolution in the Model Driven Semantic Web.

关键词： Ontology

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SEOE:an option graph based semantically embedding method for prenatal depression detection

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Frontiers of Computer Science 2024年第6期18卷 245-258页

作者： Xiaosong HAN Mengchen CAO Dong XU Xiaoyue FENG Yanchun LIANG Xiaoduo LANG Renchu GUAN College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012China Department of Electrical Engineering and Computer Science and Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA Department of Computer Science and Technology Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationZhuhai College of Science and TechnologyZhuhai 519041China Jilin Provincial Institute of Population Science and Technology Changchun 130000China

Prenatal depression,which can affect pregnant women’s physical and psychological health and cause postpartum depression,is increasing ***,it is essential to detect prenatal depression early and conduct an attribution *** studies have used questionnaires to screen for prenatal depression,but the existing methods lack *** diagnose the early signs of prenatal depression and identify the key factors that may lead to prenatal depression from questionnaires,we present the semantically enhanced option embedding(SEOE)model to represent questionnaire *** can quantitatively determine the relationship and patterns between options and *** first quantifies options and resorts them,gathering options with little difference,since Word2Vec is highly dependent on *** resort task is transformed into an optimization problem involving the traveling salesman ***,all questionnaire samples are used to train the options’vector using ***,an LSTM and GRU fused model incorporating the cycle learning rate is constructed to detect whether a pregnant woman is suffering from *** verify the model,we compare it with other deep learning and traditional machine learning *** experiment results show that our proposed model can accurately identify pregnant women with depression and reach an F1 score of *** most relevant factors of depression found by SEOE are also verified in the *** addition,our model is of low computational complexity and strong generalization,which can be widely applied to other questionnaire analyses of psychiatric disorders.

关键词： questionnaire analyses text classification graph representation learning traveling salesman problem prenatal depression

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A Simplified Rational Representation for Positive-Dimensional Polynomial Systems and SHEPWM Equations Solving

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Journal of Systems Science & Complexity 2017年第6期30卷 1470-1482页

作者： SHANG Baoxin ZHANG Shugong TAN Chang XIA Peng School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University College of Science Northeast Electric Power University College of Science Northeast Forestry University School of Mathematics Liaoning University

The paper is concerned with the improvement of the rational representation theory for solving positive-dimensional polynomial systems. The authors simplify the expression of rational representation set proposed by Tan and Zhang(2010), obtain the simplified rational representation with less rational representation sets, and hence reduce the complexity for representing the variety of a positive-dimensional ideal. As an application, the authors compute a "nearly" parametric solution for the SHEPWM problem with a fixed number of switching angles.

关键词： Positive-dimensional polynomial system solving rational univariate representation SHEPWM simplified rational representation

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