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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Zhang, Zeliang Li, Xiongfei Yang, Chengjia Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Beihua University Jilin China

ISBN: (纸本)9781424497638

Visual speech-lip reading, making the computer understands what do speakers want to express through observing the lip direction of them. The most simply method of lip reading in early stage is to compare between characters from the frozen pictures and templates being stored. It neglects the character is changing with time. This method is very simply, but it only can classify the simple elements not the words, so it couldn't render great serves to speech recognition. Afterwards the adoption of behavioral characteristics is becoming more widespread. Because of the superior of Hidden Markov model (HMM), it can be applied in speech recognition widely. In recent years, it is also used in the research of lip-reading recognition. The classical HMM model makes two hypotheses: hidden expropriation hypothesis: the state at t+1 is only conditioned by the state at t, not the state before;the expropriation hypothesis from hidden state to visible state: the visible state at t only conditioned by the hidden state at t, not the state before. Such kind of hypothesis is not very reasonable in some practical application (such as lip-reading). In some kind condition, the state at t is not only conditioned by t-1, but also t-2. Therefore this thesis revises the assumed condition classical HMM to derive a new HMM model and algorithm, and applying it into lip-reading recognition to increase the discrimination. © 2011 IEEE.

关键词： Hidden Markov models

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A Morphology Focused Cell Detection Model for Histopathology Images

A Morphology Focused Cell Detection Model for Histopathology...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Wang, Zhe Wei, Fangyue Guo, Shuyu Che, Xiaoting Bai, Tian Jilin University College of Computer Science and Technology Changchun China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

ISBN: (纸本)9798350337488

The accurate automatic recognition of cell locations is of great significance for downstream tasks in pathology. Due to the various size and distribution of different cell types, previous cell detection methods applied fixed circles as labels to localize cell position by default, which makes less precise and more difficult to adapt various cell morphology. In this paper, we integrate adaptive areas of interests based on morphology to address the limitation in detecting cells with irregular shapes in pathological images. Moreover, a EGSI module is proposed to extract global distribution of cells in slices, which enables model to acquire more rich semantic information. We exhibit favorable F1 score of our method on four public datasets. Experimental results demonstrate that the proposed method could detect cells more accurately in those images with different cell morphologies and dense cell distribution. © 2023 IEEE.

关键词： cell detection cellular morphology digital pathology medical image analysis

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A layered graph representation for complex regions

A layered graph representation for complex regions

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12th International Conference on Principles of knowledge Representation and Reasoning, KR 2010

作者： Li, Sanjiang Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Broadway Sydney NSW 2007 Australia Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9781577354512

This paper proposes a layered graph model for representing the internal structure of complex plane regions, where each node represents the closure of a connected component of the interior or exterior of a complex region. The model provides a complete representation in the sense that the (global) nineintersections between the interiors, the boundaries, and the exteriors of two complex regions can be determined by the (local) RCC8 relations between associated simple regions. Copyright © 2010, Association for the Advancement of Artificial Intelligence.

关键词： Graph theory

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A hybrid discrete PSO-SA algorithm to find optimal elimination orderings for Bayesian networks

A hybrid discrete PSO-SA algorithm to find optimal eliminati...

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2010 2nd International Conference on Industrial and Information Systems, IIS 2010

作者： Dong, Xuchu Ouyang, Dantong Cai, Dianbo Zhang, Yonggang Ye, Yuxin Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424482177

In this paper, a hybrid algorithm named DPSO-SA is proposed to find near-to-optimal elimination orderings in Bayesian networks. DPSO-SA is a discrete particle swarm optimization method enhanced by simulated annealing. computational tests show that this hybrid method is very effective and robust for the elimination ordering problem. © 2010 IEEE.

关键词： Simulated annealing

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Warburg Effects in Cancer and Normal Proliferating Cells:Two Tales of the Same Name

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Genomics, Proteomics & Bioinformatics 2019年第3期17卷 273-286页

作者： Huiyan Sun Liang Chen Sha Cao Yanchun Liang Ying Xu The China-Japan Union Hospital Jilin UniversityChangchun 130033China MOE Key Laboratory of Symbolic Computation and Knowledge Engineering College of Computer Science and TechnologyJilin UniversityChangchun 130012China Computational Systems Biology Lab Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensGA 30602USA Faculty of Health Sciences University of MacaoTaipaMacao SAR 999078China Department of Biostatistics School of MedicineIndiana UniversityIndianapolisIN 46202USA Zhuhai Laboratory of MOE Key Laboratory of Symbolic Computation and Knowledge Engineering Zhuhai College of Jilin UniversityZhuhai 519041China

It has been observed that both cancer tissue cells and normal proliferating cells(NPCs)have the Warburg *** goal here is to demonstrate that they do this for different *** accomplish this,we have analyzed the transcriptomic data of over 7000 cancer and control tissues of 14 cancer types in TCGA and data of five NPC types in *** analyses reveal that NPCs accumulate large quantities of ATPs produced by the respiration process before starting the Warburg effect,to raise the intracellular pH from 6.8 to 7.2 and to prepare for cell division *** cell cycle starts,the cells start to rely on glycolysis for ATP generation followed by ATP hydrolysis and lactic acid release,to maintain the elevated intracellular pH as needed by cell division since together the three processes are pH *** cells go back to the normal respirationbased ATP production once the cell division phase *** comparison,cancer cells have reached their intracellular pH at 7.4 from top down as multiple acid-loading transporters are up-regulated and most acid-extruding ones except for lactic acid exporters are *** cells use continuous glycolysis for ATP production as way to acidify the intracellular space since the lactic acid secretion is decoupled from glycolysis-based ATP generation and is pH balanced by increased expressions of acid-loading ***-expression analyses suggest that lactic acid secretion is regulated by external,non-pH related ***,our data strongly suggest that the two cell types have the Warburg effect for very different reasons.

关键词： Cancer Warburg effect Fenton reaction Cell proliferation pH homeostasis

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Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks

Cooperative coevolutionary genetic algorithms to find optima...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Dong, Xuchu Yu, HaiHong Ouyang, Dantong Cai, Dianbo Ye, Yuxin Zhang, Yonggang Department of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun Jilin China Network Monitor Maintenance Centre Jilin Branch China Telecom Corporation Limited Changchun Jilin China

ISBN: (纸本)9781424464388

According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem. © 2010 IEEE.

关键词： Bayesian networks

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Improving incremental diagnosis with choosing measurement order

Improving incremental diagnosis with choosing measurement or...

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2010 International Conference of Information Science and Management engineering, ISME 2010

作者： Zhao, Xiangfu Ouyang, Dantong College of Mathematics Physical and Information Engineering Zhejiang Normal University Jinhua China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769541327

There may be many groups of candidate results after the step of candidate generation in model-based diagnosis. Hwee Tou Ng proposed the Inc-Diagnose approach to further reduce the candidate results. However, the efficiency of Inc-Diagnose may not be very good. Firstly, we give some correction of Inc-Diagnosis by applying it to a real example. Then, we propose an improved approach with choosing the order of measurements for incremental diagnosis. Example results show that our approach has better efficiency. © 2010 IEEE.

关键词： Incremental diagnosis Measurement order Model-based diagnosis

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Singleton arc consistency based on failure-first principle

Singleton arc consistency based on failure-first principle

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International Conference on Machine Learning and Cybernetics

作者： Li, Zhan-Shan Xing, Shi-Mei Yang, Feng-Jie Du, Hui-Ying Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Changchun 130012 China

ISBN: (纸本)9781424465262

Constraint satisfaction problems play a significant role in the field of Artificial Intelligence. Reducing the search space can improve the efficiency of solving the problems before the search of solutions. Applying in preprocessing step, arc consistency technique can remove some values which are arc inconsistent, so that it can reduce the search space. Using heuristic strategies can improve the efficiency of the algorithms. In this paper we propose a new singleton arc consistency algorithm based on failure-first principle, which improves the practical time efficiency through the earlier detection of variables which contain null values and removal of the values which are arc inconsistency during the preprocessing step. © 2010 IEEE.

关键词： Constraint satisfaction problems

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Caption-Aware Multimodal Relation Extraction with Mutual Information Maximization 24

Caption-Aware Multimodal Relation Extraction with Mutual Inf...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhang, Zefan Zhang, Weiqi Li, Yanhui Bai, Tian College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9798400706868

Multimodal Relation Extraction (MRE) has achieved great improvements. However, modern MRE models are easily affected by irrelevant objects during multimodal alignment which are called error sensitivity issues. The main reason is that visual features are not fully aligned with textual features and the reasoning process may suppress redundant and noisy information at the risk of losing critical information. In light of this, we propose a Caption-Aware Multimodal Relation Extraction Network with Mutual Information Maximization (CAMIM). Specifically, we first generate detailed image captions through the Large Language Model (LLM). Then, the Caption-Aware Module (CAM) hierarchically aligns the fine-grained visual entities and textual entities for reasoning. In addition, for preserving crucial information within different modalities, we leverage a Mutual Information Maximization method to regulate the multimodal reasoning module. Experiments show that our model outperforms the state-of-the-art MRE models on the benchmark dataset MNRE. Further ablation studies prove the pluggable and effective performance of our Caption-Aware Module and Mutual Information Maximization method. Our code is available at https://***/zefanZhang-cn/CAMIM. © 2024 ACM.

关键词： Modeling languages

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A Method for Extracting Electronic Medical Record Entities by Fusing Multichannel Self-Attention Mechanism with Location Relationship Features 9th

A Method for Extracting Electronic Medical Record Entities b...

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9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

作者： Xu, Hongyan Wang, Hong Feng, Yong Wang, Rongbing Zhang, Yonggang College of Information Liaoning University Shenyang110036 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9789819959709

With the implementation of the "Internet+" strategy, electronic medical records are generally applied in the medical field. Deep mining of electronic medical record content data is an effective means to obtain medical knowledge and analyse patients’ states, but the existing methods for extracting entities from electronic medical records have problems of redundant information, overlapping entities, and low accuracy rates. Therefore, this paper proposes an entity extraction method for electronic medical records based on the network framework of BERT-BiLSTM, which incorporates a multichannel self-attention mechanism and location relationship features. First, the text input sequence was encoded using the BERT-BiLSTM network framework, and the global semantic information of the sentence was mined more deeply using the multichannel self-attention mechanism. Then, the position relation characteristic was used to extract the local semantic message of the text, and the position relation characteristic of the word and the position embedding matrix of the whole sentence were obtained. Next, the extracted global semantic information was stitched with the positional embedding matrix of the sentence to obtain the current entity classification matrix. Finally, the proposed method was validated on the dataset of Chinese medical text entity relationship extraction and the 2010i2b2/VA relationship corpus, and the experimental results indicate that the proposed method surpasses existing methods in terms of precision, recall, F1 value and training time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Location

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