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作者： Chen, Hui-Ling Liu, Da-You Yang, Bo Liu, Jie Wang, Gang Wang, Su-Jing Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783642208409

This study proposes an efficient non-parametric classifier for bankruptcy prediction using an adaptive fuzzy k-nearest neighbor (FKNN) method, where the nearest neighbor k and the fuzzy strength parameter m are adaptively specified by the particle swarm optimization (PSO) approach. In addition to performing the parameter optimization for FKNN, PSO is utilized to choose the most discriminative subset of features for prediction as well. Time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search ability of PSO. Moreover, both the continuous and binary PSO are implemented in parallel on a multi-core platform. The resultant bankruptcy prediction model, named PTVPSO-FKNN, is compared with three classification methods on a real-world case. The obtained results clearly confirm the superiority of the developed model as compared to the other three methods in terms of Classification accuracy, Type I error, Type II error and AUC (area under the receiver operating characteristic (ROC) curve) criterion. It is also observed that the PTVPSO-FKNN is a powerful feature selection tool which has indentified a subset of best discriminative features. Additionally, the proposed model has gained a great deal of efficiency in terms of CPU time owing to the parallel implementation. © 2011 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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A novel method to measure graph similarity 12

A novel method to measure graph similarity

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12th IEEE International Conference on E-Business engineering, ICEBE 2015

作者： Wang, Xu Ouyang, Jihong College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781467380027

A novel method to measure the graph similarity is proposed, where the labels, in-degrees, and out-degrees of the vertices in the graph are comprehensively considered in order to conquer the high complexity and information loss in the measurement process. In this proposal, the graph is decomposed into a generalized tree and its similarity can be measured by computing the cost of the node sequence triples in the generalized tree. The proposed method decreases the computational complexity to O(n2) in comparison with the other available graph similarity methods. An example is provided to illustrate that the method is feasible and effective. © 2015 IEEE.

关键词： Forestry

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An approach to accelerate diagnosis by isomorphic determining

An approach to accelerate diagnosis by isomorphic determinin...

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2009 International Conference on Information engineering and Computer Science, ICIECS 2009

作者： Wang, Xiaoyu Ouyang, Dantong Feng, Yuxuan Zhao, Jian College of Computer Science and Technology Jilin University Key Laboratory Symbolic Computation and Knowledge Engineering Ministry of Educaion Changchun China

ISBN: (纸本)9781424449941

When diagnosing dynamic system represented as discrete-event systems, it needs to find what happened to the systems from observations. The behavior of system could be represented by automaton model. The diagnostic task consists in determining the models compatible with the observations, but the global computation which is needed in synchronization costs exponential time. In this paper we propose a new method to simplify the automaton by isomorphic determining. The cost of computation will be significantly cut down by merging the automatons with the same structure, and the time-complexity of the diagnosis process could be reduced by the method. ©2009 IEEE.

关键词： Discrete event simulation

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Simulating the Folding Pathway of RNA Secondary Structure Using the Modified Ant Colony Algorithm

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Journal of Bionic engineering 2010年第4期7卷 382-389页

作者： Jun Yu~(1,2),Changhai Zhang~(1,2),Yuanning Liu~(1,2),Xin Li~(1,2) 1.College of Computer Science and Technology,Jilin University,Changchun 130012,P.R.China 2.key laboratory of symbolic Computation and knowledge engineering (Ministry of Education,China) Jilin University,Changchun 130012,P.R.China [a] College of Computer Science Technology Jilin University Changchun 130012 P. R. China [b] Key Laboratory of Symbolic Computation Knowledge Engineering (Ministry of Education China) Jilin University Changchun 130012 P. R. China

A new method for simulating the folding pathway of RNA secondary structure using the modified ant colony algorithmis *** a given RNA sequence,the set of all possible stems is obtained and the energy of each stem iscalculated and stored at the initial ***,a more realistic formula is used to compute the energy ofmulti-branch loop in the following *** a folding pathway is simulated,including such processes as constructionof the heuristic information,the rule of initializing the pheromone,the mechanism of choosing the initial andnext stem and the strategy of updating the pheromone between two different *** by testing RNA sequences withknown secondary structures from the public databases,we analyze the experimental data to select appropriate values *** measure indexes show that our procedure is more consistent with phylogenetically proven structures thansoftware RNAstructure sometimes and more effective than the standard Genetic Algorithm.

关键词： RNA secondary structure folding pathway ant colony algorithm

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A conditioned secure access control model based on multi-weighted roles in workflow system

A conditioned secure access control model based on multi-wei...

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5th International Conference on Control and Automation, ICCA'05

作者： Zhang, Jian Sun, Jigui Li, Niya Hu, Chengquan College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China

ISBN: (纸本)0780391381

The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on the basis of multi-weighted roles. A conditioned RBAC strategy is discussed on the basis of dynamic role assignment. A new concept of workflow access authorization is defined on the basis of roles with multi-weights, including the hierarchy weight, the degree weight and the sequence weight. Furthermore, in order to solve the problems of the sequence constraint of cooperative activating task by multi-roles and multi-users, a sort algorithm based on token and a sort algorithm based on weighted roles synthesis are presented respectively. Finally, an example is given to show the work processes of these algorithms. This model can express complicated workflow secure access control constraint. © 2005 IEEE.

关键词： Security systems

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A pseudo label based dataless naive bayes algorithm for text classification with seed words 27

A pseudo label based dataless naive bayes algorithm for text...

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27th International Conference on Computational Linguistics, COLING 2018

作者： Li, Ximing Yang, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

ISBN: (纸本)9781948087506

Traditional supervised text classifiers require a large number of manually labeled documents, which are often expensive to obtain. Recently, dataless text classification has attracted more attention, since it only requires very few seed words of categories that are much cheaper. In this paper, we develop a pseudo-label based dataless Naive Bayes (PL-DNB) classifier with seed words. We initialize pseudo-labels for each document using seed word occurrences, and employ the expectation maximization algorithm to train PL-DNB in a semi-supervised manner. The pseudo-labels are iteratively updated using a mixture of seed word occurrences and estimations of label posteriors. To avoid noisy pseudo-labels, we also consider the information of nearest neighboring documents in the pseudo-label update step, i.e., preserving local neighborhood structure of documents. We empirically show that PL-DNB outperforms traditional dataless text classification algorithms with seed words. Especially, PL-DNB performs well on the imbalanced dataset. © 2018 COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings. All rights reserved.

关键词： Iterative methods

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Solving SAT problem with Boolean algebra

Solving SAT problem with Boolean algebra

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International Conference on Frontier of Computer Science and Technology

作者： Xu, Youjun Ouyang, Dantong Ye, Yuxin He, Jialiang College of Computer Science and Technology China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769541396

The satisfiability(SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on extension rule. Based on the study of extension rule, we And that the SAT problem can be solved with hitting set algorithms. If we can find a hitting set of a clause set, and if there is not any pair of complementary literals in the hitting set, the clause set is satisfiable. Algorithm BHS based on Boolean algebra proposed by Jiang is an efficient hitting set algorithm. SSBF proposed in this paper is a revised algorithm of BHS that can be used to judge the satisfiability of a clause set. The test result shows that SSBF is an efficient algorithm. © 2010 IEEE.

关键词： Boolean algebra

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Few-Shot Fine-Grained Classification of Histological Images 1

Few-Shot Fine-Grained Classification of Histological Images

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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023

作者： Jiang, Yingdong Huang, Jing Jin, Zihe Shen, Leqi Zhang, Ziyi College of Software Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education ChangChun China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education ChangChun China College of Computer Science and Technology Jilin University ChangChun China

ISBN: (纸本)9798350358780

Histological image classification plays a crucial role in cancer diagnosis. However, the acquisition of well-labeled histological images is prohibitively expensive, and obtaining rare abnormal samples is challenging. Therefore, applying few-shot learning methods to histological image classification tasks holds significant clinical value. Nevertheless, existing research predom-inantly relies on coarse-grained image classification approaches based on natural image datasets, which struggle to address the fine-grained challenges encountered in histological image classification, such as intra-class diversity and inter-class similarity. To tackle this issue, this study proposes a novel few-shot fine-grained classification method for histological images, named 'Category-Aware Feature Map Reconstruction Network.' This method employs channel weights to localize the differences between inter-class and intra-class regions, composed of intra-class channel weights and inter-class channel weights, collectively referred to as category-aware weights. Specifically, intra-class channel weights indicate the matching degree of salient regions within the support set of a particular class, while inter-class channel weights represent the degree of containing distinct information between classes. The category-aware weights are utilized to transform the support feature maps and query feature maps, generating feature maps that capture differentiating details between categories. Finally, the distance between the transformed query feature map and support feature map is calculated to achieve probabilistic predictions for the categories. On a histological few-shot dataset, this method achieves an accuracy of 90.23% using ResNet-12 as the feature extractor, surpassing the baseline model by 5.24% and outperforming other few-shot methods by at least 10% in the 5-way 10-shot experimental setting. The proposed method exhibits exceptional performance on histological image few-shot datasets, playing a

关键词： Computer aided diagnosis

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A globally optimal approach for surveillance video cropping

A globally optimal approach for surveillance video cropping

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作者： Liu, Jin Shi, Xiaohu Zhang, Yu College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education 130012 Changchun China

In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the video for display on a smaller monitor. In this framework, the video content is firstly modeled by whether image frames change at each pixel. Then a shortest path algorithm is used to find the globally optimal trajectory for a cropping window. After that a second shortest path formulation is employed to find good cuts from one trajectory to another, improving the coverage of interesting events in the video content. Finally, additional techniques are demonstrated to improve the quality and efficiency of the algorithm, and results are shown on surveillance videos from PETS 2006.

关键词： Trajectories

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Interval-valued fuzzy description logic IFALCN - Preliminary results

Interval-valued fuzzy description logic IFALCN - Preliminary...

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2010 IEEE International Conference on Intelligent computing and Intelligent Systems, ICIS 2010

作者： Huo, Linlin Ouyang, Jihong Liu, Dayou Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)9781424465835

To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical des cription logic ALCN is extended to the fuzzy description logic IFALCN. Its' syntax, semantics and fuzzy tableau algorithm are presented in detail. Our work enhances the expressiveness and reasoning ability of ALCN. IFALCN is the generalization of fuzzy ALCN based on single value and more expressive than the latter and can conform to human cognition better. ©2010 IEEE.

关键词： Fuzzy sets

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