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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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Strengthened Initialization of Adaptive Cross-Generation Differential Evolution

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Computer Modeling in engineering & Sciences 2022年第3期130卷 1495-1516页

作者： Wei Wan Gaige Wang Junyu Dong Department of Computer Science of Technology Ocean University of ChinaQingdao266100China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun130012China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for NationalitiesNanning530006China

Adaptive Cross-Generation Differential Evolution(ACGDE)is a recently-introduced algorithm for solving multiobjective problems with remarkable performance compared to other evolutionary algorithms(EAs).However,its convergence and diversity are not satisfactory compared with the latest *** order to adapt to the current environment,ACGDE requires improvements in many aspects,such as its initialization and mutant *** this paper,an enhanced version is proposed,namely *** incorporates a strengthened initialization strategy and optimized parameters in contrast to its *** improvements make the direction of crossgeneration mutation more clearly and the ability of searching more *** experiments show that the new algorithm has better diversity and improves convergence to a certain *** the same time,SIACGDE outperforms other state-of-the-art algorithms on four metrics of 24 test problems.

关键词： Differential Evolution(DE) multi-objective optimization(MO) opposition-based learning parameter adaptation

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A new epistasis detecting algorithm based on ant colony optimization 14

A new epistasis detecting algorithm based on ant colony opti...

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6th International Conference on Internet Multimedia computing and Service, ICIMCS 2014

作者： Zhou, Zhihui Liu, Guixia Su, Lingtao Han, Liang Yan, Lun College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9781450328104

The rapid developments of chip-based technology have greatly improved human genetics and made routine the access of thousands of single nucleotide polymorphisms (SNPs) contributing to an informatics challenge. The characterization and interpretation of genes and gene-gene interactions that affect the susceptibility of common, complex multifactorial diseases is a computational and statistical challenge in genome-wide association studies (GWAS). Various methods have been proposed, but they have dificulty to be directly applied to GWAS caused by excessive search space and intensive computational burden. In this paper, we propose an ant colony optimization (ACO) based algorithm by combining the pheromone updating rule with the heuristic information. We tested power performance of our algorithm by conducting suficient experiments including a wide range of simulated datasets experiments and a real genome-wide dataset experiment. Experimental results demonstrate that our algorithm is time efficient and gain good performance in the term of the power of prediction accuracy. Copyright 2014 ACM.

关键词： Ant colony optimization

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Research and implementation of improved real-time crawler modeling

Research and implementation of improved real-time crawler mo...

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International Conference on Electrical Information and Mechatronics, ICEIM 2012

作者： Zuo, Xianglin Wang, Wenbo Wang, Ying Zuo, Wanli College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9783037856901

The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they may instead pay more attention to fresh information. This demand poses challenges to traditional search engines, which concern more about relevance and importance of web pages. A search engine compresses three modules: crawler, indexer and searcher. Changes are needed for all these three parts to improve search engine's freshness. This paper investigates the first part of search engine - crawler, we analyze the requirements for real-time crawler, and propose a novel real-time crawler based on more accurate estimation of refresh time. Experimental results demonstrate that the proposed real-time crawler can help search engine improve its freshness. © (2013) Trans Tech Publications, Switzerland.

关键词： Search engines

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computing PUR of Zero-Dimensional Ideals of Breadth at Most One

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Journal of Systems Science & Complexity 2021年第6期34卷 2396-2409页

作者： PAN Jian SHANG Baoxin LI Zhe ZHANG Shugong School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education)Jilin UniversityChangchun 130012China College of Science Northeast Electric Power UniversityJilin 132012China School of Science Changchun University of Science and TechnologyChangchun 130022China

In this paper,for a zero-dimensional polynomial ideal I,the authors prove that k[x_(1),x_(2),…,x_(n)]/I is cyclic if and only if the breadth of I is 0 or ***,the authors present a new algorithm to compute polynomial ... 详细信息

关键词： Cyclic basis Grobner basis polynomial univariate representation separating element

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Learning the structure of dynamic bayesian network with domain knowledge

Learning the structure of dynamic bayesian network with doma...

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Chen, Juan Jia, Haiyang Huang, Yuxiao Liu, Dayou College of Computer Science and Technology Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9781467314855

Dynamic Bayesian Network (DBN) is a graphical model for representing temporal stochastic processes. Learning the structure of DBN is a fundamental step for parameter learning, inference and application. For large scale problem, the structure learning is intractable. In some domains the training data is very limited and noisy, so learning the DBN structure only with training data is impractical. Domain knowledge may improve both the efficiency and the accuracy of the learning algorithm. But usually, the domain knowledge is uncertainty, unclear and even with conflict. This paper presents a novel algorithm for learning the structure of DBN, which consider the data and domain knowledge simultaneously, empirical experiment shows that the proposed algorithm improved the efficiency and the accuracy of the DBN structure learning. © 2012 IEEE.

关键词： Bayesian networks

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RMADV-Hop: An improved DV-Hop localization algorithm

RMADV-Hop: An improved DV-Hop localization algorithm

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7th International Conference on Information Technology - New Generations, ITNG 2010

作者： Yi, Tingting Fang, Zhiyi Li, Ruixue College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China

ISBN: (纸本)9780769539843

In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of the localization algorithms are not well suitable for the wireless sensor network, positioning error is relatively large. Based on the regular moving anchor node and RSSI ranging technique assisting positioning, in this paper, we proposed the RMADV-Hop (Regular Moving Anchor DV-Hop) localization algorithm to improve the DV-Hop algorithm. In the same network condition, we simulated these two localization algorithms using the omnet++ simulation software. Simulation results show that RMADV-Hop algorithm uses less anchor nodes than the DV-Hop algorithm, reduces the cost of network hardware, approximately achieves the evenly distribution of anchor nodes, and can get higher positioning accuracy than the DV-Hop algorithm in the randomly distributed network. © 2010 IEEE.

关键词： Sensor nodes

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