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International Conference on Electronics, InformationTechnology and Intellectualization, EITI 2014

作者： Ye, S.S. Wang, S.C. Ye, Y.X. Zhao, G.X. Teng, F. Institute of Mineral Resources Prediction with Synthetic Information Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China National Engineering Research Center of Geophysics Exploration Instruments Changchun Jilin University Changchun China Tianjin Institute of Geology and Mineral Resources Tianjin China

ISBN: (纸本)9781138027411

The application of intelligent geophysical interpreting, technology of mapping and database building based on GIS have been discussed under the guidance of the theory and the method of the mineral resources prediction of synthetic information in this paper. The automatic extraction of regional gravity and magnetic structures to build databases has been realized. With the prediction of the iron mine as a case, the whole process of the application of synthetic information in minerals’ prediction of GIS technology has been stated. Through the realization of the data process of regional gravity and magnetic data, and of line-ring structure extraction, geophysical spatial information and map databases have been automatically built. Through a combination of geological and geophysical interpretation, the spatial information and map databases of geophysical ore-finding (iron mine) have been built. Through model units, an ore-finding model of comprehensive information has been built. Through geological units, geophysical-geological spatial information and map databases of synthetic information of predictive models have been built. According to the requirement of different mathematical models for mineral prediction of synthetic information for the data models, the spatial information in the synthetic information databases of predictive models has been extracted, and the geological variables have been converted, and then converted mutually into a digital geological multivariate statistical variable matrix. Different statistic prediction models of the multivariate statistical methods have been established to complete the whole process of metallogenic prediction by the computer. © 2015 Taylor & Francis Group, London.

关键词： Forecasting

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Author Correction: Altered structural brain asymmetry in autism spectrum disorder in a study of 54 datasets

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Nature communications 2021年第1期12卷 7260页

作者： Merel C Postema Daan van Rooij Evdokia Anagnostou Celso Arango Guillaume Auzias Marlene Behrmann Geraldo Busatto Filho Sara Calderoni Rosa Calvo Eileen Daly Christine Deruelle Adriana Di Martino Ilan Dinstein Fabio Luis S Duran Sarah Durston Christine Ecker Stefan Ehrlich Damien Fair Jennifer Fedor Xin Feng Jackie Fitzgerald Dorothea L Floris Christine M Freitag Louise Gallagher David C Glahn Ilaria Gori Shlomi Haar Liesbeth Hoekstra Neda Jahanshad Maria Jalbrzikowski Joost Janssen Joseph A King Xiang Zhen Kong Luisa Lazaro Jason P Lerch Beatriz Luna Mauricio M Martinho Jane McGrath Sarah E Medland Filippo Muratori Clodagh M Murphy Declan G M Murphy Kirsten O'Hearn Bob Oranje Mara Parellada Olga Puig Alessandra Retico Pedro Rosa Katya Rubia Devon Shook Margot J Taylor Michela Tosetti Gregory L Wallace Fengfeng Zhou Paul M Thompson Simon E Fisher Jan K Buitelaar Clyde Francks Department of Language & Genetics Max Planck Institute for Psycholinguistics Nijmegen The Netherlands. Department of Cognitive Neuroscience Donders Institute for Brain Cognition and Behaviour Donders Centre for Cognitive Neuroimaging Radboud University Medical Centre Nijmegen The Netherlands. Bloorview Research Institute Holland Bloorview Kids Rehabilitation Hospital and Department of Pediatrics University of Toronto Toronto ON USA. Child and Adolescent Psychiatry Department Gregorio Marañón General University Hospital School of Medicine Universidad Complutense IiSGM CIBERSAM Madrid Spain. Institut de Neurosciences de la Timone UMR 7289 Aix Marseille Université CNRS Marseille France. Department of Psychology Carnegie Mellon University Pittsburgh PA USA. Laboratory of Psychiatric Neuroimaging (LIM-21) Departamento e Instituto de Psiquiatria Hospital das Clinicas HCFMUSP Faculdade de Medicina Universidade de Sao Paulo Sao Paulo SP Brazil. IRCCS Stella Maris Foundation viale del Tirreno 331 56128 Pisa Italy. Department of Clinical and Experimental Medicine University of Pisa Pisa Italy. Department of Child and Adolescent Psychiatry and Psychology Hospital Clinic Psychiatry Unit Department of Medicine 2017SGR881 University of Barcelona IDIBAPS CIBERSAM Barcelona Spain. Department of Forensic and Neurodevelopmental Sciences Institute of Psychiatry Psychology & Neuroscience King's College London London UK. Institute for Pediatric Neuroscience NYU Child Study Center New York NY USA. Department of Psychology Ben-Gurion University of the Negev Beer Sheva Israel. Brain Center Rudolf Magnus Department of Psychiatry University Medical Center Utrecht Utrecht The Netherlands. Department of Child and Adolescent Psychiatry Psychosomatics and Psychotherapy University Hospital Goethe University Frankfurt am Main Frankfurt Germany. Imaging Genetics Center Mark and Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine of USC University o

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Selective and incremental fusion for fuzzy and uncertain data based on probabilistic graphical model

Selective and incremental fusion for fuzzy and uncertain dat...

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作者： Zhu, Yungang Liu, Dayou Li, Yong Wang, Xinhua College of Computer Science and Technology Jilin University No. 2699 Qianjin Street Changchun China State Key Laboratory of Applied Optics Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Mathematics Jilin University Changchun China

Active and dynamic fusion for fuzzy and uncertain data have key challenges such as high complexity and difficult to guarantee accuracy, etc. In order to resolve the challenging issues, in this article a selective and incremental data fusion approach based on probabilistic graphical model is proposed. General Bayesian networks are adopted to represent the relationship among the data and fusion result. It purposively selects the most informative and decision-relevant data for fusion based on Markov Blanket in probabilistic graphical model. Meanwhile we present a special incremental learning method for updating the fusion model to reflect the temporal changes of environment. Theoretical analysis and experimental results all demonstrate the proposed method has higher accuracy and lower time complexity than existing state-of-the-art methods. © 2015 - IOS Press and the authors. All rights reserved.

关键词： Data fusion

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A fast rigid registration algorithm for medical images

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Journal of Fiber Bioengineering and Informatics 2014年第3期7卷 409-418页

作者： Feng, Yuncong Li, Xiongfei Zhang, Xiaoli Ding, Tienan Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China Department of Computer Science and Technology Changchun China

Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high e±ciency. In the registration algorithm, we firstly segmented the reference image and °oat image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.

关键词： Image registration

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Integration of scanning and image processing algorithms for lane detection based on fuzzy method

Integration of scanning and image processing algorithms for ...

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作者： Zhang, Jindong Jia, Xiaoyan Li, Jinfeng College of Computer Science and Technology Jilin University Changchun China Department of Hand Surgery First Hospital of Jilin University Changchun130021 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun China

In order to detect lane rapidly and accurately, the integration of scanning and image processing algorithms (SIP) based on the fuzzy method is proposed. Further, combination of the proposed algorithm with an adaptive threshold value for image binarization, the least-square method and Bessel curve algorithm are proposed for detection and to fit the lane. The proposed SIP algorithm was evaluated by various tests. The experimental results indicate that the average time consumed for the detection of lane in each frame is 16.7639ms, and the accuracy of lane detection is 95. The proposed algorithm demonstrates good robustness, and can be used as the core algorithm for further application in lane departure warning systems. © 2015 - IOS Press and the authors. All rights reserved.

关键词： Computer vision

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Using a random forest method for epistasis detection in genome-wide association studies

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Journal of computational Information Systems 2014年第18期10卷 8043-8050页

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

Detecting susceptibility genes and gene-gene interactions (epistasis) is an important issue in genetic association analysis and genetic epidemiology. Due to the huge number of single nucleotide polymorphisms (SNPs) and inappropriate statistical tests, epistasis detection is a computational and statistical challenge and becomes a "needle-in-a-haystack" problem. Also some epistasis detection algorithms proposed in lots of literature have demonstrated their successes for small scale data, while most of them cannot be directly applied into genome-wide association studies (GWAS) and the pathogenesis of many common complex human diseases is mysterious. Here we adopted a random forest method incorporating information theory and a powerful statistical test, B-stat to detect epistasis. We conducted sufficient artificial experiments on a wide range of simulated datasets and compared performance of our random forest method with its two competitors, COE and BEAM. Experimental results demonstrated that this method is quite available and time efficiency for the haystack problem. We also presented the results of the application of the method to the WTCCC type 1 diabetes dataset. We reported some previously well known genes as well as some significant SNP interactions.

关键词： Statistical tests

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A survey on virtual network embedding in cloud computing centers

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Open Automation and Control Systems Journal 2014年第1期6卷 414-425页

作者： Wei, Xiaohui Hu, Shoufeng Li, Hongliang Yang, Fan Jin, Yue College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

Bridging virtualized environments with physical environments, virtual network plays an important role in Cloud Computing infrastructures. How to allocate physical resources for virtual nodes/links to construct virtual network is known as Virtual Network Embedding (VNE) problem. It is a crucial issue that draws wide attention. This paper surveys existing VNE methods and algorithms and how they work under different application scenarios. First, a survey of different VNE objective metrics is presented;then several VNE algorithms are presented and categorized;finally, the performance of different VNE solutions are compared and discussed. © 2010, Bentham Science Publishers B.V. All rights reserved.

关键词： Cloud computing

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Simplifying Calculation of Graph Similarity Through Matrices

Simplifying Calculation of Graph Similarity Through Matrices

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The 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Xu Wang Jihong Ouyang Guifen Chen College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of Information Technology Jilin Agricultural University

ISBN: (纸本)9783319483535

A method to simplify the calculation in the process of measuring graph similarity is proposed, where lots of redundant operations are avoided in order to quickly obtain the initial tickets matrixIn this proposal, the element value of the initial tickets matrix is assigned to 1 when it is positive in corresponding position of the paths matrix at the first timeThe proposed method calculates the initial tickets matrix value based on the positive value in the paths matrix in a forward and backward wayAn example is provided to illustrate that the method is feasible and effective.

关键词： Graph similarity measure Paths and tickets Adjacency matrix Forward and backward Simplifying calculation

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A Dynamic Multi-path Routing for VANET

A Dynamic Multi-path Routing for VANET

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2015 International Conference on Automation,Mechanical and Electrical engineering(AMEE 2015)

作者： Z.Y.Yuan D.Wei J.Q.Zhu Y.J.Hou M.Li T.Sun College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Regional Road Transportation Administrative Bureau

Compared with traditional VANET(Vehicular Ad-Hoc Networks) routing techniques, geographic routing has been proven to be more fittable for highly mobile scenes. Traditional routings use greedy modes or fixed forwarding paths to sent packets. But, the dynamic features of VANET such as fast changed topology, vehicles density and radio obstacles, could cause local maximum and sparse connectivity. Due to the characteristics of wireless channel, while there are too many packets transmit through a path, the delay and the number of packets loss will both increase clearly. We propose DMPR, a Dynamic Multipath Routing, combined with node location and digital map. The proposed DMPR detects transmission delay of different paths every once in a period of time, and dynamically determine the transmission ratio of each path. We execute NS2 simulation to exhibit that DMPR routing protocol significantly outperform three well known VANET ones in terms of the average packet delivery ratio and end-to-end delay.

关键词： VANET dynamic multi-path routing digital map transmission delay detection

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TDRec: Enhancing Social Recommendation Using Both Trust and Distrust Information

TDRec: Enhancing Social Recommendation Using Both Trust and ...

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European Network Intelligence Conference (ENIC)

作者： Tiansheng Bai Bo Yang Fei Li School of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China Computer Science Department George Mason University Fairfax VA USA

ISBN: (纸本)9781467375931

Traditional Collaborative Filtering has been one of the most widely used recommender systems, unfortunately it suffers from cold-start and data sparsity problems. With the development of social networks, more recommendation systems are trying to generate more eligible recommendation through excavating users' potential preferences using their social relationships. Almost all social recommender systems employ only positive inter-user relations such as friendship or trust information. However, incorporating negative relations in recommendation has not been investigated thoroughly in literature. In this paper, we propose a novel model-based method which takes advantage of both positive and negative inter-user relations. We apply matrix factorization techniques and utilize both rating and trust information to learn users' reasonable latent preference. We also incorporate two regularization terms to take distrust information into consideration. Our experiments on real-world and open datasets demonstrate the superiority of our model over the other state-of-the-art methods.

关键词： Europe

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