检索结果-内蒙古大学图书馆

A semi-automatic segmentation for tooth on cone beam CT volume following the anatomic guidance

Journal of Information Hiding and Multimedia Signal Processing 2017年第4期8卷 774-783页

作者： Zou, Zheng Luo, San-Ding Pan, Jeng-Shyang Liu, Shi-Jian Liao, Sheng-Hui School of Information Science and Engineering Central South University No.932 Lushannan Road ChangshaHunan410005 China School of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Minhou FuzhouFujian350118 China The Key Laboratory of Big Data Mining and Applications of Fujian Province Fujian University of Technology No.3 Xueyuan Road University Town Minhou FuzhouFujian350118 China

Cone beam computed tomography(CBCT) technique is popular in three dimension imaging of the jaw bones and teeth due to its high resolution and relatively lower radiation exposure compared with multi-slice computed tomography(MSCT). But segmentation of the tooth from CBCT is challenging due to reasons such as the lower bone signal-to-noise and the topology variances. In order to accurately segment the teeth, we propose a novel volume-based interactive segmentation framework. First, valley-emphasized image is generated from original images to enhance voxels in high relief to assist the separation of tooth region from the alveolar bone with the similar intensity. Meanwhile the information about root canal is abstracted to guide the segmentation. In order to obtain the root canal curve, an energy minimization combined with the directional characterise is introduced in our method. Incorporated with the constraint offered by the root canal curve, a edge-aware harmonic field is designed to avoid leakage and shrinkage problems in the segmentation process. The experimental results demonstrated that our method is better than two other most cited methods in accuracy and efficiency. © 2017, Ubiquitous International. All rights reserved.

关键词： Bone

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The Regime Characteristics of Chinese Stock Market Industry Sectors

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Procedia Computer Science 2016年 91卷 512-518页

作者： Jiangjian Shen Wen Long CAS Research Center On Ficititious Economy & Data Science BeiJing 100190 Chian School of Economics and Management UCAS BeiJing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences BeiJing 100190 China

This article uses Markov regime Switching ARCH (SWARCH) model to research the volatility of Chinese stock market industry sectors, finding that all industry sectors were able to be significantly divided into two regimes, the high volatility regime and the low volatility regime. For different regime transfer, we can classify all sectors into three categories. Further the article analyzes the regime characteristics of industry sectors. The results show that the correlation coefficient in high volatility regime is higher than that in low volatility regime.

关键词： Industry sectors High volatility regime Low volatility regime Correlation

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Numerical Evaluation of Two Management Schemes for Sharing Limited Bandwidth 3

Numerical Evaluation of Two Management Schemes for Sharing L...

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3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

作者： Wang, Chia-Hung Wu, Mu-En College of Information Science and Engineering Fujian University of Technology Fuzhou City Fujian Province China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Province China Department of Mathematics Soochow University Taipei City Taiwan

ISBN: (纸本)9781509010936

In this paper, we study the managerial insights of two bandwidth sharing schemes on communication networks with multi-class traffic under the budget constraint. Through an analysis of the trade-off between efficiency versus fairness, decision makers would make their own choices for sharing the limited bandwidth. Taking the blocking probability into account, two management schemes are introduced to allocate bandwidth under the limited budget control. In the numerical experiments, we conduct a sensitivity analysis for different traffic classes through varying the limited budget. The contributions of this paper are the performance evaluation and sensitivity analysis of relationship between model parameters and performance measures of interest. © 2016 IEEE.

关键词： Sensitivity analysis

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A novel fingerprint classification method based on deep learning

A novel fingerprint classification method based on deep lear...

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International Conference on Pattern Recognition

作者： Ruxin Wang Congying Han Tiande Guo School of Mathematical Science University of Chinese Academy of Sciences (UCAS) Beijing School of Mathematical Science Key Laboratory of Big Data Mining and Knowledge Management UCAS

ISBN: (纸本)9781509048489

Fingerprint classification is an effective technique for reducing the candidate numbers of fingerprints in the stage of matching in automatic fingerprint identification system (AFIS). In recent years, deep learning is an emerging technology which has achieved great success in many fields, such as image processing, computer vision. In this paper, we have a preliminary attempt on the traditional fingerprint classification problem based on the new depth neural network method. For the four-class problem, only choosing orientation field as the classification feature, we achieve 91.4% accuracy using the stacked sparse autoencoders (SAE) with three hidden layers in the NIST-DB4 database. And then two classification probabilities are used for fuzzy classification which can effectively enhance the accuracy of classification. By only adjusting the probability threshold, we get the accuracy of classification is 96.1% (setting threshold is 0.85), 97.2% (setting threshold is 0.90) and 98.0% (setting threshold is 0.95) with a single layer SAE. Applying the fuzzy method, we obtain higher accuracy.

关键词： Machine learning databases Feature extraction Training Fingerprint recognition Neural networks Image reconstruction

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Active and Passive Factors of Oil Prices

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Journal of Donghua University(English Edition) 2015年第2期32卷 284-287页

作者：海豹申立勇 School of Mathematical Sciences University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Nanagement Chinese Academy of Sciences

Price volatility analysis is a basic problem in the price modification,financial risk estimation and management *** the global commodities,oil plays an important role in the development of modern industry and *** the price of crude oil analysis is a hot *** is also a difficult topic since there are so many factors associating the price *** some factors give the different influences in the different *** on data computing,people generally classify the factors into positive and negative *** some factors do not affect the price as the nominal *** instance,the output of OPEC gave the positive contributions to the oil price in the past long ***,the investigation of the historic WTI oil price is well proposed and the factors are classified into active and passive *** then the better explanations are given using this type of classification.

关键词： instance classify nominal classified volatility expectation contributions crude Correlation normalized

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Formalizing UML Model Metrics Using Z Language

Formalizing UML Model Metrics Using Z Language

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作者： Fangjun Wu School of Information Technology Jiangxi University of Finance and Economics Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics

Till now, a large variety of researchers have carried out lots of efforts on object-oriented and UML model metrics from different views. They put forward numerous of metrics and carried out some series of theoretical and experimental verifications on understandability, analyzability, maintainability, fault-proneness, change-proneness and reuse. However, there is no formal semantic specification for UML model metrics, which may lead to potential semantic inconsistency and ambiguity. To solve this problem, this paper provided formalization for UML model metrics at the level of UML Meta models. This formalization can not only help people to understand the meaning of UML model metrics, but also can be used in the application domain of UML model metrics in a more rigorous way.

关键词： software measurement object-oriented UML class diagrams Z language empirical validation theoretical verification

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A Triple Structure of Rough Sets Based on Selection Function

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Annals of data Science 2015年第3期2卷 245-259页

作者： Wang, Bo Shi, Yong Tian, Yingjie Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

Different from rough sets in Pawlak’s sense, which is a binary approximation operations based structure, in this paper, we propose a new rough equivalence relation based on triple approximation operations induced by selection function. The same as traditional rough sets research, we consider the algebra issue of new rough sets system and construct lattice structure in an algebraic fashion. An isomorphic relationship is studied between proposed rough sets algebra structure and that in Pawlak’s sense. In addition, some examples are shown and studied in order to indicate the effectiveness of new equivalence relation in distinguishing and describing subsets of universe. Besides, we also study restriction of selection congruence on subalgebra built by covering of universe. Finally, conclusion on the axioms of middle approximation operation are shown to clarify properties of new structure. © 2015, Springer-Verlag Berlin Heidelberg.

关键词： Algebra

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A Novel Control Algorithm for Interaction Between Surface Waves and A Permeable Floating Structure

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China Ocean engineering 2016年第2期30卷 161-176页

作者： Pei-Wei TSAI A.ALSAEDI T.HAYAT Cheng-Wu CHEN College of information Science and Engineering Fujian University of TechnologyFuzhou 350118China Fujian Provincial Key Laboratory of Big Data Mining and Applications(Fujian University of Technology) Fuzhou 350118China Nonlinear Analysis and Applied Mathematics(NAAM)Research Group King Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics Quaid-I-Azam UniversityIslamabad 44000Pakistan Department of Maritime Information and Technology National Kaohsiung Marine UniversityKaohsiung 80543China Faculty of Engineering King Abdulaziz UniversityJeddah 21589Saudi Arabia

An analytical solution is undertaken to describe the wave-induced flow field and the surge motion of a permeable platform structure with fuzzy controllers in an oceanic *** the design procedure of the controller,a parallel distributed compensation（PDC） scheme is utilized to construct a global fuzzy logic controller by blending all local state feedback controllers.A stability analysis is carried out for a real structure system by using Lyapunov *** corresponding boundary value problems are then incorporated into scattering and radiation *** are analytically solved,based on separation of variables,to obtain series solutions in terms of the harmonic incident wave motion and surge *** dependence of the wave-induced flow field and its resonant frequency on wave characteristics and structure properties including platform width,thickness and mass has been thus drawn with a parametric *** which mathematical models are applied for the wave-induced displacement of the surge motion.A nonlinearly inverted pendulum system is employed to demonstrate that the controller tuned by swarm intelligence method can not only stabilize the nonlinear system,but has the robustness against external disturbance.

关键词： fuzzy Lyapunov function Takagi?Sugeno form swarm intelligence algorithm

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A Survey on Feature Selection

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Procedia Computer Science 2016年 91卷 919-926页

作者： Jianyu Miao Lingfeng Niu School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100019 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Research Center on Fictitious Economy & Data Science Chinese Academy of Sciences Beijing 100190 China

Feature selection, as a dimensionality reduction technique, aims to choosing a small subset of the relevant features from the original features by removing irrelevant, redundant or noisy features. Feature selection usually can lead to better learning performance, i.e., higher learning accuracy, lower computational cost, and better model interpretability. Recently, researchers from computer vision, text mining and so on have proposed a variety of feature selection algorithms and in terms of theory and experiment, show the effectiveness of their works. This paper is aimed at reviewing the state of the art on these techniques. Furthermore, a thorough experiment is conducted to check if the use of feature selection can improve the performance of learning, considering some of the approaches mentioned in the literature. The experimental results show that unsupervised feature selection algorithms benefits machine learning tasks improving the performance of clustering.

关键词： feature selection machine learning unsupervised clustering

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Exploring Big data Analysis: Fundamental Scientific Problems

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Annals of data Science 2015年第4期2卷 363-372页

作者： Xu, Zongben Shi, Yong Department of Mathematics Xi’an Jiaotong University Xi’an China The Key Research Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

Although Big data has been one of most popular topics since last several years, how to effectively conduct Big data analysis is a big challenge for every field. This paper tries to address some fundamental scientific problems in Big data analysis, such as opportunities, challenges, and difficulties encountered in the analysis. The challenges rise from multiple domains that include how Management Science influences data acquisition and data management, Information Science for data access and processing, Mathematics and Statistics for data understanding and engineering for data applications. The paper outlines six open research problems on Big data. It also reports some advances on current Big data research, particularly in high-dimensional data and non-structured data processing. Finally, remarks on how to develop a Big data algorithm are provided. © 2016, Springer-Verlag Berlin Heidelberg.

关键词： Big data

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