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A randomized diversification strategy for solving satisfiability problem with long clauses

Science China(Information Sciences) 2017年第9期60卷 121-131页

作者： Jian GAO Ruizhi LI Minghao YIN College of Computer Science Northeast Normal University College of Information Science and Technology Dalian Maritime University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

Satisfiability problem(SAT) is a central problem in artificial intelligence due to its computational complexity and usefulness in industrial applications. Stochastic local search(SLS) algorithms are powerful to solve hard instances of satisfiability problems, among which CScore SAT is proposed for solving SAT instances with long clauses by using greedy mode and diversification mode. In this paper, we present a randomized variable selection strategy to improve efficiency of the diversification mode, and thus propose a new SLS *** perform a number of experiments to evaluate the new algorithm comparing with the recently proposed algorithms, and show that our algorithm is comparative with others for solving random instances near the phase transition threshold.

关键词： SAT local search randomized diversification strategy phase transition long clause

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Super-resolution reconstruction from fluorescein angiogram sequences

Super-resolution reconstruction from fluorescein angiogram s...

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International Conference on Intelligent Computing, ICIC 2005

作者： Guo, Xiaoxin Xu, Zhiwen Lu, Yinan Liu, Zhanhui Pang, Yunjie Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Qianjin Road 10# Changchun 130012 China

ISBN: (纸本)9783540282266

Intensity degradations are a familiar problem for fluorescein angiogram sequences. In this paper, we attempt to super-resolve a fluorescein angiogram, and to keep the high intensity pixels from degrading. To this end, we incorporate a new constraint, called intensity constraint, to Miller's regularization formulation with a smoothness constraint. Considering the specified requirement for fluorescein angiograms, we also modify the Q-th order converging algorithm for implementation purpose. In our scheme, including its formulation and implementation, super-resolution reconstruction can not only handle the traditional problems, such as blur, decimation, and noise, but also achieve an important feature, intensity preservation. The experiments show that our approach has satisfactory results in the two aspects. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image reconstruction

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Image annotation refinement using dynamic weighted voting based on mutual information

Journal of Software

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Journal of Software 2011年第11 SPEC. ISSUE期6卷 2239-2246页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

Automatic image annotation is a promising solution to narrow the semantic gap between low-level content and high-level semantic concept, which has been an active research area in the fields of image retrieval, pattern recognition, and machine learning. However, even the most dedicated annotation algorithms are often unsatisfactory. Image annotation refinement has attracted much more attention recently. In this paper, a novel refinement algorithm using dynamic voting based on mutual information is proposed. Unlike the traditional refinement algorithm, the proposed algorithm adopts dynamic weighted voting to measure the dependence between the candidate annotations, which not only permits that the annotations with higher probabilities deny the annotations with lower probabilities, but also permits that the annotations with lower probabilities deny the annotations with higher probabilities. The proposed refinement algorithm adopts progressive method instead of iterative, which can significantly decrease the time cost of refining annotations. In order to further improve efficiency without sacrificing precision, we propose the block-based normalized cut algorithm to segment image. Experiments conducted on standard Washington Ground Truth Image Database demonstrate the effectiveness and efficiency of our proposed approach for refining image annotations. © 2011 ACADEMY PUBLISHER.

关键词： Image annotation

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A RFID authentication protocol with index inner table used in reader

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第2期6卷 119-127页

作者： Jialiang, He Dantong, Ouyang Haiyan, Wang College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University China

Special physical characters and limited resources in tags make existing RFID systems being confronted with many security and privacy concerns. In this paper, a RFID authentication protocol is proposed, with a novel scheme called index inner table used in the reader. Index inner table may efficiently utilize calculation capacity and storage space of the reader to construct a filter which can sift authentication applications from tags, thus, it could alleviate workload of the backend server and resist replay attack from an adversary. The structure, filter algorithm, update and sorting algorithm, eraser algorithm of index inner table would be introduced detailedly in this paper. In addition, this protocol is particularly suitable for the low-cost RFID systems;the security and performance of this protocol are analyzed as well.

关键词： Radio frequency identification (RFID)

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Adaptive feature selection and extraction approaches for image retrieval based on region

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Journal of Multimedia 2010年第1期5卷 85-92页

Image retrieval based on region is one of the most promising and active research directions in recent year's CBIR, while region segmentation, feature selection and feature extraction of region are key issues. However, the existing approaches always adopt a uniform approach of segmentation and feature extraction for all images in the same system. In this paper, we propose adaptive image segmentation and feature extraction approach according to different category image for image retrieval system. To improve performance, we propose adaptive segmentation approach according to different category image. Textured image is segmented by Gaussian Mixture Models (GMM), while non-textured image is segmented by our proposed block-based normalized cut. To accurately describe feature of region, we propose weight assignment method for centroid pixel and its neighbor by convolution with normal distribution when image segmentation by GMM. To improve generalization, we propose adaptive number of Fourier descriptors of shape signature which depends on the energy distribution of Fourier descriptors, instead of fixed number by experience. To simply and efficiently describe the spatial relationships of multi-object or multi-region in same image, we apply simplified topological relationships. The experiments demonstrate that proposed approaches are superior to the traditional approaches. © 2010 ACADEMY PUBLISHER.

关键词： Feature extraction

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Describing the semantic relation of the deep web query interfaces using ontology extended LAV

Journal of Software

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Journal of Software 2010年第1期5卷 89-98页

作者： Liang, Hao Zuo, Wan-Li Ren, Fei Department of Computer Science and Technology Jilin University Jilin Changchun China Department of Information Changchun Taxation College Jilin Changchun China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema. © 2010 ACADEMY PUBLISHER.

关键词： Ontology

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On-demand tile preload for large-scale seismic data 3D-visualization

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Journal of computational Information Systems 2015年第4期11卷 1513-1520页

作者： Wei, Xiaohui Bai, Xin Bai, Sen Li, Hongliang College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

Real-time three-dimensional visualization for seismic data is difficult when seismic data are large-scale and usually exceed the limitation of host memories. This paper proposed a dynamic caching framework based on OCTree data structure to dynamically load data blocks (Tiles) within ROI (Region of Interest) into memory for render in runtime. In order to improve the hit rate of the cache and ensure the smoothness of interaction, an On-Demand tile Preload (ODP) mechanism and algorithm is proposed and implemented. It preloads data tiles based on tile hot zones and ROI track prediction when loading threads are idle. Experiments show that ODP achieved 21% rendering speedup on average in real-time interaction while causing none additional costs. 1553-9105/Copyright © 2015 Binary Information Press

关键词： Visualization

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Crossed-Time Delay Neural Network for Speaker Recognition 1

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27th International Conference on MultiMedia Modeling, MMM 2021

作者： Chen, Liang Liang, Yanchun Shi, Xiaoshu Zhou, You Wu, Chunguo Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun130012 China Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education School of Computer Zhuhai College of Jilin University Zhuhai519041 China

ISBN: (数字)9783030678326

ISBN: (纸本)9783030678319

Time Delay Neural Network (TDNN) is a well-performing structure for deep neural network-based speaker recognition systems. In this paper we introduce a novel structure, named Crossed-Time Delay Neural Network (CTDNN) to enhance the performance of current TDNN for speaker recognition. Inspired by the multi-filters setting of convolution layers from convolution neural networks, we set multiple time delay units with different context size at the bottom layer and construct a multilayer parallel network. The proposed CTDNN gives significant improvements over original TDNN on both speaker verification and identification tasks. It outperforms in VoxCeleb1 dataset in verification experiment with a 2.6% absolute Equal Error Rate improvement. In few shots condition, CTDNN reaches 90.4% identification accuracy, which doubles the identification accuracy of original TDNN. We also compare the proposed CTDNN with another new variant of TDNN, Factorized-TDNN, which shows that our model has a 36% absolute identification accuracy improvement under few shots condition. Moreover, the proposed CTDNN can handle training with a larger batch more efficiently and hence, utilize calculation resources economically. © 2021, Springer Nature Switzerland AG.

关键词： Convolution

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Nutrition feature basis of food classification in traditional chinese medicine 7

Nutrition feature basis of food classification in traditiona...

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7th International Conference on Big Data Computing and Communications, BigCom 2021

作者： Zhao, Fucheng Han, Xiaosong Zhang, Yikun Niu, Peiyu Cheng, Jun Yi, Wan Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Changchun130012 China

ISBN: (纸本)9781665442527

In TCM (Traditional Chinese Medicine) theory, the cold-and-hot property of food is considered as an important information to guide people's daily diet and keep them healthy. But the classification of this property mostly relies on experience from medical books, which lacks corresponding molecular chemistry basis and makes differentiation very difficult for ordinary people. To solve above question, in this paper, we collected 500 kinds of food and their nutrients, used ANOVA algorithm for feature selection to find out the nutrient feature that have a greater correlation with the cold and hot properties of food, and then used LightGBM algorithm to classify the processed data set. Finally, we constructed a reliable and accurate classification model and found the related nutritional elements are Tyrosine, Arginine, Thiamine, Vitamin B6 and Selenium. © 2021 IEEE.

关键词： Machine learning

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Identification of transcription factor binding sites using GA and PSO

Identification of transcription factor binding sites using G...

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6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)

作者： Chang, Xiao-Yu Zhou, Chun-Guang Li, Yan-Wen Hu, Ping Key Laboratory of Symbol Computation and J Knowledge Engineering Jilin University Ministry of Education China Department of Computer Science Northeast Normal University Changchun 130012 China

ISBN: (纸本)0769525288

Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: Genetic, Algorithm (GA) and Particle Swarm Optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast Saccharomyces Cerevisiae transcription factor binding sites and CRP binding sites. The results on Saccharomyces Cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs Sampler.

关键词： Binding sites

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