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System Dynamics and Adaptive Control of MEMS Gyroscope Sensor

IFAC Proceedings Volumes 2011年第1期44卷 3551-3556页

作者： Juntao Fei Weili Dai Mingang Hua Yuncan Xue Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology College of Computer and Information Hohai University Changzhou 213022 P.R.China

Abstract This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is developed and established. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems are established with the proposed adaptive control strategies. Numerical simulations are investigated to verify the effectiveness of the proposed control schemes.

关键词： Adaptive control sliding mode control MEMS gyroscope

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A Novel Approach to Edge Detection of Color Image Based on Quaternion Fractional Directional Differentiation

A Novel Approach to Edge Detection of Color Image Based on Q...

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The 2011 International Conference on Automation and Robotics(ICAR 2011)

作者： Chaobang Gao Jiliu Zhou Fangnian Lang Qiang Pu Chang Liu College of Computer Science and Technology Chengdu University School of Computer Science Sichuan University Key Laboratory of Pattern Recognition and Intelligent Information Processing

In this paper, we denote a color image by a quaternion function, then find edge points by solving the maximum of quaternion fractional directional differentiation(QFDD)'s norm. This method is called edge detection based on QFDD. Experiments indicate that the method has special advantages. Comparing with Canny, LOG, Sobel, and general fractional differentiation, we discover that QFDD has fewer false negatives in the textured regions and is also better at detecting edges which are partially defined by texture, which means we will obtain better results in the interesting regions by QFDD and these results are more consistent with the characteristics of human visual system.

关键词： quaternion fractional differentiation QFDD norm similarity

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Particle swarm optimization for automatic parameters determination of pulse coupled neural network

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Journal of computers 2011年第8期6卷 1546-1553页

作者： Xinzheng, Xu Shifei, Ding Zhongzhi, Shi Zuopeng, Zhao Hong, Zhu School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Pulse coupled neural network (PCNN), a wellknown class of neural networks, has original advantage when applied to image processing because of its biological background. However, when PCNN is used, the main problem is that its parameters aren't self-adapting according to different image which limits the application range of PCNN. Considering that, this paper proposed a new method based on particle swarm optimization (PSO) to determine automatically the parameters of PCNN. In this method, the algorithm of PSO is applied to search automatically optimum in the solution space of PCNN's parameters until finding global optimal solution. Experimental results demonstrate that the proposed method is accurate and robust for image segmentation, and its performance is better than the methods of Otsu, manual adjustment of parameters when mutual information is adopted as evaluation criteria. © 2011 ACADEMY PUBLISHER.

关键词： Image segmentation

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A rough RBF neural networks optimized by the genetic algorithm

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Advances in information Sciences and Service Sciences 2011年第7期3卷 332-339页

作者： Ding, Shifei Ma, Gang Xu, Xinzheng School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

The large-scale data parallelism processing is an inherent characteristic of artificial neural networks, but the networks bring the efficiency problems of data processing. As one of the artificial neural networks, Radial Basis Function (RBF) neural networks have the same problem. Therefore, how to reduce the scale of data to improve the efficiency of data processing has been a hot issue among the artificial intelligence scholars. Based on the traditional RBF neural networks, this paper puts forward a method which determines the important degree of the sample attributes based on knowledge entropy of Rough set by analyzing the relationship between the knowledge entropy and the weight of the sample attributes, and assesses the importance of the sample attributes between the input layer and the hidden layer, namely the attribution reduction, so as to achieve reduce the scale of data processing. The ultimate aim of training RBF neural networks is to seek a set of suitable networks parameters which makes the sample output error achieve the minimum or required accuracy, while Genetic Algorithm (GA) has the properties of finding out the optimal solution through multiplepoint random search in the solution space, so Genetic Algorithm is used to optimize the centers, the widths and the weights between the hidden layer and the output layer of RBF neural networks in training the networks. Finally, a model about A Rough RBF Neural Networks Optimized by the Genetic Algorithm (GA-RS-RBF) is proposed in this paper. The simulation results show that the rough RBF neural network optimized by the Genetic Algorithm is better than the traditional RBF neural networks in classification about Iris datasets.

关键词： Genetic algorithms

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Erratum to: Search for supersymmetry in events containing a same-flavour opposite-sign dilepton pair, jets, and large missing transverse momentum in ... TeV pp collisions with the ATLAS detector

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The European Physical Journal. C, Particles and Fields. 2015年第10期75卷 1页

作者： Aad, G Abbott, B Abdallah, J Abdinov, O Aben, R Abolins, M Abouzeid, O S Abramowicz, H Abreu, H Abreu, R Abulaiti, Y Acharya, B S Adamczyk, L Adams, D L Adelman, J Adomeit, S Adye, T Affolder, A A Agatonovic-jovin, T Aguilar-saavedra, J A Agustoni, M Ahlen, S P Ahmadov, F Aielli, G Akerstedt, H Åkesson, T P A Akimoto, G Akimov, A V Alberghi, G L Albert, J Albrand, S Alconada Verzini, M J Aleksa, M Aleksandrov, I N Alexa, C Alexander, G Alexopoulos, T Alhroob, M Alimonti, G Alio, L Alison, J Alkire, S P Allbrooke, B M M Allport, P P Aloisio, A Alonso, A Alonso, F Alpigiani, C Altheimer, A Alvarez Gonzalez, B Piqueras, D Álvarez Alviggi, M G Amako, K Amaral Coutinho, Y Amelung, C Amidei, D Amor Dos Santos, S P Amorim, A Amoroso, S Amram, N Amundsen, G Anastopoulos, C Ancu, L S Andari, N Andeen, T Anders, C F Anders, G Anderson, K J Andreazza, A Andrei, V Angelidakis, S Angelozzi, I Anger, P Angerami, A Anghinolfi, F Anisenkov, A V Anjos, N Annovi, A Antonelli, M Antonov, A Antos, J Anulli, F Aoki, M Aperio Bella, L Arabidze, G Arai, Y Araque, J P Arce, A T H Arduh, F A Arguin, J-f Argyropoulos, S Arik, M Armbruster, A J Arnaez, O Arnal, V Arnold, H Arratia, M Arslan, O Artamonov, A Artoni, G Asai, S Asbah, N Ashkenazi, A Åsman, B Asquith, L Assamagan, K Astalos, R Atkinson, M Atlay, N B Auerbach, B Augsten, K Aurousseau, M Avolio, G Axen, B Ayoub, M K Azuelos, G Baak, M A Baas, A E Bacci, C Bachacou, H Bachas, K Backes, M Backhaus, M Badescu, E Bagiacchi, P Bagnaia, P Bai, Y Bain, T Baines, J T Baker, O K Balek, P Balestri, T Balli, F Banas, E Banerjee, Sw Bannoura, A A E Bansil, H S Barak, L Baranov, S P Barberio, E L Barberis, D Barbero, M Barillari, T Barisonzi, M Barklow, T Barlow, N Barnes, S L Barnett, B M Barnett, R M Barnovska, Z Baroncelli, A Barone, G Barr, A J Barreiro, F Barreiro Guimarães Da Costa, J Bartoldus, R Barton, A E Bartos, P Bassalat, A Basye, A Bates, R L Batista, S J Batley, J R Battaglia, M Bauce, M Bauer, F Bawa, H S Beacham, J B Beattie, M D Beau, T Beauchemin, P H Beccherle, R Bechtle, 85.CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France 113.Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA 152.Institute of Physics Academia Sinica Taipei Taiwan 11.Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan 107.Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam The Netherlands 90.Department of Physics and Astronomy Michigan State University East Lansing MI USA 159.Department of Physics University of Toronto Toronto ON Canada 154.Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel 153.Department of Physics Technion: Israel Institute of Technology Haifa Israel 30.CERN Geneva Switzerland 147.Department of Physics Stockholm University Stockholm Sweden 227.The Oskar Klein Centre Stockholm Sweden 165.INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy 229.ICTP Trieste Italy 38.Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland 25.Physics Department Brookhaven National Laboratory Upton NY USA 108.Department of Physics Northern Illinois University De Kalb IL USA 100.Fakult?t für Physik Ludwig-Maximilians-Universit?t München Munich Germany 131.Particle Physics Department Rutherford Appleton Laboratory Didcot UK 74.Oliver Lodge Laboratory University of Liverpool Liverpool UK 13.Institute of Physics University of Belgrade Belgrade Serbia 126.Laboratorio de Instrumentacao e Fisica Experimental de Particulas LIP Lisbon Portugal 215.Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain 17.Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland 22.Department of Physics Boston University Boston MA USA 65.Joint Institute for Nuclear Research JINR Dubna Dubna Russia 134.INFN Sezione di Roma Tor Vergata Rome Ita

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Context-specific miRNA regulation network predicts cancer prognosis

Context-specific miRNA regulation network predicts cancer pr...

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5th IEEE International Conference on Systems Biology, ISB 2011

作者： Zhou, Xionghui Liu, Juan Liu, Changning Rayner, Simon Liang, Fengji Ju, Jingfang Li, Yinghui Chen, Shanguang Xiong, Jianghui School of Computer Science Wuhan University Wuhan China Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Virology Wuhan Institute of Virology Chinese Academy of Sciences Wuhan China Department of Pathology Stony Brook University Medical Center NY United States

ISBN: (纸本)9781457716669

MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context). The microarray gene expression profile of brain tumors from 356 patients (The Cancer Genome Atlas dataset) was converted into a CoMi activity pattern, and showed significant positive correlation with the corresponding miRNA expression pattern. In a breast cancer cohort, the differential CoMi activity between good prognosis (longer survival) vs. bad prognosis patients forms a scale-free network, which highlighted a group of important cancer-related microRNAs and GO terms, e.g. hsa-miR-34a and 'cell adhesion'. Then two breast cancer cohorts were used in outcome prediction in an independent test. Using a popular T-test feature selection method and a support vector machine (SVM) classifier with 10-fold cross-validation, the CoMi activity feature achieves an area under curve (AUC) of 0.7155, better than the AUC value of 0.6339 for feature selection based on mRNA expression. In an independent test, CoMi feature selection achieved an AUC of 0.6874. Survival analysis also shows signatures defined by CoMi activity was predictive of survival and superior to mRNAs signatures. In short, we have demonstrated the first interrogation of dynamic remodeling of context specific miRNAs regulation networks in cancer. The altered microRNAs regulation on specific contexts could be used to predi

关键词： Diseases

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China's grain security warning based on multifactor information fusion

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2011年第5期27卷 183-189页

作者： Su, Xiaoyan Zhang, Huijie Li, Zhiqiang Deng, Yong School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing 100081 China College of Computer and Information Sciences Southwest University Chongqing 400715 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China

China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: as well as quantitative and qualitative information. In order to get the grain security status comprehensively, we proposed a method to evaluate risk in grain security based on multifactor information fusion. In the method, the quantitative and qualitative information were used to construct the basic probability assignment, and the attribute weights was got based on the Analytic Hierarchy Process method. After that, the multifactor fusion results were got based on the Dempster combination rule. The effectiveness of the method was verified with a numeric example that the data comes from the yearbook of China in 2007. The Results show that the method is effective and can correctly reflect the grain safety warning degrees.

关键词： Analytic hierarchy process

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A Kind of Wireless MAC Protocol to Improve Survivability of WSN

A Kind of Wireless MAC Protocol to Improve Survivability of ...

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Yin Kai Yang Xiong School of Computer &Information Engineering Key Laboratory of Changzhou Software Technology Research and Application Changzhou Institute of Technology Changzhou Jiangsu China

In Wireless Sensor Network (WSN), the ability to avoid collision directly impacts on node energy consumption and network performance. Based on introduction of CSMA/CA protocol, the paper laid emphasis on shortcoming of binary back off algorithm affect survivability time of WSN. On this basis, a kind of CSMA/CA protocol based on improved binary back off algorithm was proposed. The algorithm reasonably scheduled competition and back off time of nodes and improved fairness of the network to increase network survival cycle. Network simulation results shows that the improved protocol effectively improves network survivable cycle in case of fixed network size. The performance of network delay and throughput also improved to a certain extent.

关键词： Media Access Protocol Wireless sensor networks Delay Multiaccess communication Energy consumption Collision avoidance

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Double-Row Cascade Labeling Algorithm for Hyper-Scale Issue

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Procedia Engineering 2011年 15卷 4047-4051页

作者： Yebin Fan Hualong Zhao Department of Computer Science Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multi-Spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

An efficient algorithm is presented to label the connected components in the case that the primary memory is smaller than the image data. Our algorithm uses only the memory of two image rows to label the huge image or any image larger than the available memory. The search path compression is a applied for improving the performance further. An extensive comparison with the state-of-art algorithms is proposed, both on random and real datasets. Our algorithm shows an impressive speedup, while the auxiliary memory is not required at all comparing with all competitors.

关键词： Connected components labeling page fault hyper-scalar union-find

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Research and comparison of granularity cluster analysis methods

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International Journal of Advancements in Computing technology 2011年第7期3卷 154-159页

作者： Ding, Shifei Tong, Chang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China

As an important component of data mining, Cluster Analysis (CA) has being attached importance to artificial intelligence, machine learning and other fields. Traditional clustering methods have been studied for a relatively long time;their technologies are mature and consequently they are well-applied. However, they are insufficient in clustering accuracy, noise sensitivity, along with effect on mass of data and non-convex clustering. Granular computing, which is regarded as a label of theories, methodologies, techniques, and tools, is an emerging conceptual and computing par information processing. It plays an important role information processing for fuzzy, uncertainty, partial truth and soft computing and is one of the main study stream in A.I. This paper introduces some new clustering methods, such as Fuzzy clustering, Clustering Algorithm Based on Rough Set, and clustering algorithm based on quotient space theory, emphatically expounds the basic thought and typical algorithms of these methods, and comparative analysis is carried out among these methods. Finally, new clustering algorithms are prospected and we put forward the value of research direction.

关键词： Data mining

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