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Change detection of hyperspectral remote sensing images based on deep belief network

International Journal of Earth Sciences and engineering 2016年第5期9卷 2096-2105页

作者： Huang, Fenghua Xu, Chao Zhu, Zhangzhi Fuzhou University Fuzhou350116 China Yango College Fuzhou350015 China Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education Fuzhou University Fuzhou350002 China National Engineering Research Centre of Geospatial Information Technology Fuzhou University Fuzhou350002 China Spatial Information Engineering Research Centre of Fujian Province Fuzhou University Fuzhou350002 China

To address the performance bottlenecks of existing methods for change detection of hyperspectral remote sensing (HSRS) images, a new scheme for change detection of HSRS based on deep belief network (CDHSRS-DBN) is proposed. First, the HSRS images collected at two different phases (dual-temporal HSRS images) are pre-processed and registered, and then the spectral-difference images of the dual-temporal images are computed. Next, the endmember spectrums and the abundance-difference images are extracted using the pixel unmixing method based on independent component analysis (ICA). The low-layer feature vector of deep learning in CDHSRS-DBN adopts the integrated feature vector that consists of the pixel spectral-difference vector, endmember abundance-difference vector and the pixel spectral feature angle vector. Finally, a deep belief network (DBN) model that contains multi-layer restricted Boltzmann machines (RBM) and a support vector machine (SVM) is devised, and the weights of connections between visible and hidden layers are adjusted through pre-training. The accuracy of change detection is further improved by fine-tuning all the weights via the SVM classifier. In order to evaluate the performance of the proposed CDHSRS-DBN method, four pairs of EO-1 Hyperion test images at different phases, which collected in four different experimental zones, are used as the test data and CDHSRS-DBN is compared with six other typical HSRS change detection algorithms (CDHSRS-SCD, CDHSRS-MPD, CDHSRS-ICA, IR-MAD, CD-PCA and PCCD). The experiments focus on the detection of land-use changes. The average recall and precision reach 90.39% and 87.10%, respectively. The average value of F-Score and time consumption is 0.8871 and 242.5, respectively. Experimental results demonstrate the better performance of CDHSRS-DBN to detect changes of multi-temporal HSRS images accurately and efficiently. © 2016 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.

关键词： Change detection

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Enable Privacy Preservation and Result Verification for Top-k Query in Two-Tiered Sensor Networks

Enable Privacy Preservation and Result Verification for Top-...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Hui Peng Xiaoying Zhang Hong Chen Yuncheng Wu Yao Wu Juru Zeng Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing China

ISBN: (纸本)9781467379533

Wireless sensor network is an important part of the Internet of Things. Preservation of privacy and integrity in wireless sensor networks is extremely urgent and challenging. This paper proposes an efficient mechanism, called PTK, for define and solve the practical and challenging problem of privacy-preserving and verifiable Top-k query processing in two-tier sensor network. PTK prevents adversaries from gaining sensitive information of both queries issued by users and data collected by sensor nodes while allows the ink to verify whether the results are valid. It offers confidentiality of queries and data by constructing a special code, and also achieves high defense capability against the background analysis attack through the implementation of obfuscation coding mechanism. Moreover, PTK provides integrity verification by the correlation among data. Finally, the experimental results show the high performance of proposed schemes in terms of privacy preservation and query efficiency.

关键词： data privacy Privacy Wireless sensor networks Protocols Query processing Cryptography data models

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Enable Privacy Preservation for k-NN Query in Two-tiered Wireless Sensor Networks

Enable Privacy Preservation for k-NN Query in Two-tiered Wir...

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IEEE International Conference on Communications

作者： Hui Peng Xiaoying Zhang Hong Chen Yao Wu Juru Zeng Deying Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China

ISBN: (纸本)9781467364300

Wireless sensor network is an important part of the Internet of Things. Preservation of privacy and integrity in wireless sensor networks is extremely urgent and challenging. To address this problem, we propose PPKN, an efficient and privacy-preserving k-NN query protocol in two-tiered wireless sensor networks. Our proposal prevents adversaries from gaining sensitive information of both queries issued by users and data collected by sensor nodes while allows the sink to verify whether results are valid. It offers confidentiality of queries and data by constructing a special code, provides integrity verification by the correlation among data. Moreover, by the implementation of KNQ query framework, PPKN also achieves high efficient in query response and energy consumption. Finally, the theoretical analysis and experiment results show the high performance of PPKN in terms of privacy preservation and query efficiency.

关键词： Wireless sensor networks Energy consumption data privacy Privacy Protocols Cryptography Storage management

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A multistage method for road extraction from optical remotely sensed imagery

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Journal of Information Hiding and Multimedia Signal Processing 2016年第2期7卷 438-447页

作者： Xu, Rui Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Spatial Information Research Center of Fujian Province Fuzhou University No.523 Gongye Road Fuzhou350002 China College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Fuzhou350108 China

This paper presents a multistage framework for road extraction from remotely sensed imagery. The framework is a combination of multifeature-based mean shift, SVM classifier, and shape feature filter. Mean shift is first employed to cluster the remotely sensed images in the fusion of spectral-texture features and then a classifier of SVM is applied to classify the segmented images into two classes: the road class and the non-road class. Finally, the road class is refined by using road shape features. The experimental results show that this method is efficient in extracting road from remotely sensed imary. © 2016.

关键词： Classification (of information)

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Co-design of information systems with digital records management: A proposal for research 7

Co-design of information systems with digital records manage...

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7th International Joint Conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2015

作者： Xie, Sherry L. Key Laboratory of Data Enginerring and Knowledge Engineering Ministry of Education Beijing China Center for Electronic Records Management Research Beijing China School of Information Resource Management Renmin Univeristy of China 59 Zhonguancun Ave Beijing China

ISBN: (纸本)9789897581588

This position paper, via rationalizing the potentials of carrying out a carefully crafted research project, argues that the three fields of enterprise information system, business process management, and digital records management should join forces in serving the needs of organizations, regardless of their types. By preliminary findings uncovered during the conceiving process of the project, it advocates that the best point of convergence is the design phase, a basic step for all of the three fields and an increasingly critical one in today's digital environment. © 2015 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Information systems

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A novel method for road centerline extraction from high spatial resolution satellite images

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Journal of Information Hiding and Multimedia Signal Processing 2016年第5期7卷 1069-1080页

作者： Xu, Rui Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education Spatial Information Research Center of Fujian Province Fuzhou University No.523 Gongye Road Fuzhou350002 China College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Fuzhou350108 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No.3 Xueyuan Road University Town Fuzhou350108 China

An integrated method for road centerline extraction has been proposed in this paper which consists of four main steps. First, the Graph Cut algorithm using proposed similarity function is employed to segment the image, and the segmented image is thresholded to initial binary skeleton. Second, the road skeleton is refined by using a series of morphology operations and shape features. Third, the curvilinear feature of road skeleton is detected by a set of multiple filtering detectors. Finally,a regression method is performed to extract smooth and accurate road centerlines. Validation tests show that the proposed method is able to achieve a comparatively good performance in road centerline extraction from high spatial resolution satellite images. © 2016, Ubiquitous International. All Rights Reserved.

关键词： Regression analysis

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A hierarchical object-based method for suburban road extraction from remote sensing image

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ICIC Express Letters, Part B: Applications 2016年第12期7卷 2671-2676页

作者： Xu, Rui College of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Fuzhou350118 China Key Lab of Spatial Data Mining and Information Sharing of Ministry of Education Spatial Information Research Center of Fujian Province Fuzhou University No. 523 Gongye Road Fuzhou350002 China

Road extraction from remote sensing image is a very popular topic. There are many methods dealing with this problem, but few of them focus on suburban roads. This paper presents a hierarchical object-based method for suburban road extraction. First, the image is preprocessed by the Normalized Difference Vegetation Index (NDVI) and the Hue-Saturation-Intensity (HSI) Index. Vegetation regions, shadows and water areas are then removed. Second, texture features are applied to classifying the preprocessed image into two categories: road and non-road. Homogeneous property is combined to remove false classification so as to generate initial road skeleton. Third, the road skeleton is refined by using a series of morphology operations and shape features. Fourth, the curvilinear feature of road skeleton is detected by a set of multiple filtering detectors. Finally, a regression method is performed to extract smooth and accurate road centerlines. The experimental results indicate that the proposed method is suitable for suburban road extraction. © 2016 ISSN 2185-2766.

关键词： Vegetation

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A Secure Collusion-Aware and Probability-Aware Range Query Processing in Tiered Sensor Networks

A Secure Collusion-Aware and Probability-Aware Range Query P...

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Reliable Distributed Systems

作者： Lei Dong Xuan Chen Jianxiang Zhu Hong Chen Ke Wang Cuiping Li Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Beijing China School of Information Renmin University of China Beijing China School of Computing Science Simon Fraser University Burnaby BC Canada Key Lab. of Data Eng. & Knowledge Eng. of Minist. of Educ. Beijing China

With high expansibility and efficient power usage, tiered wireless sensor networks are widely deployed in many fields as an important part of Internet of Things (IoTs). It is challenging to process range query while protecting sensitive data from adversaries. Moreover, most existing work focuses on privacy-preserving range query neglecting collusion attacks and probability attacks, which are more threatening to network security. In this paper, we first propose a secure range query protocol called secRQ, which not only protects data privacy, but also resists collusion attacks and probability attacks in tiered wireless sensor networks. Generalized inverse matrices and distance-based range query mechanism are used to guarantee security as well as high efficiency and accuracy. Besides, we propose the mutual verification scheme to verify the integrity of query results. Finally, both theoretical analysis and experimental results confirm the security, efficiency and accuracy of secRQ.

关键词： Wireless sensor networks Protocols data privacy Biomedical monitoring Query processing Monitoring Heart rate

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Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

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eClinicalMedicine 2023年 64卷 102193-102193页

作者： Wu, Dongze Jin, Yingzhao Xing, Yuhan Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abd-Allah, Foad Abdelmasseh, Michael Abdollahifar, Mohammad-Amin Abdulah, Deldar Morad Abedi, Aidin Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abuabara, Katrina Abyadeh, Morteza Addo, Isaac Yeboah Adeniji, Kayode Nelson Adepoju, Abiola Victor Adesina, Miracle Ayomikun Adnani, Qorinah Estiningtyas Sakilah Afarideh, Mohsen Aghamiri, Shahin Agodi, Antonella Agrawal, Anurag Arriagada, Constanza Elizabeth Aguilera Ahmad, Aqeel Ahmad, Danish Ahmad, Sohail Ahmadi, Ali Ahmed, Ayman Aithala, Janardhana P. Ajadi, Abdullateef Abiodun Ajami, Marjan Akbarzadeh-Khiavi, Mostafa Alahdab, Fares AlBataineh, Mohammad T. Alemi, Sharifullah Al-Gheethi, Adel Ali Saeed Ali, Liaqat Alif, Sheikh Mohammad Almazan, Joseph Uy Almustanyir, Sami Alqahtani, Jaber S. Alqasmi, Ibrahim Altaf, Ihsan Ullah Khan Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Al-Worafi, Yaser Mohammed Aly, Hany Amani, Reza Amu, Hubert Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Ansar, Adnan Ansariniya, Hossein Anyasodor, Anayochukwu Edward Arabloo, Jalal Arefnezhad, Reza Arulappan, Judie Asghari-Jafarabadi, Mohammad Ashraf, Tahira Atata, Jamila Abdulhamid Athari, Seyyed Shamsadin Atlaw, Daniel Atout, Maha Moh'd Wahbi Aujayeb, Avinash Awan, Asma Tahir Ayatollahi, Haleh Azadnajafabad, Sina Azzam, Ahmed Y. Badawi, Alaa Badiye, Ashish D. Bagherieh, Sara Baig, Atif Amin Bantie, Berihun Bantie Barchitta, Martina Bardhan, Mainak Barker-Collo, Suzanne Lyn Barone-Adesi, Francesco Batra, Kavita Bayileyegn, Nebiyou Simegnew Behnoush, Amir Hossein Belgaumi, Uzma Iqbal Bemanalizadeh, Maryam Bensenor, Isabela M. Beyene, Kebede A. Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhaskar, Sonu Bhat, Ajay Nagesh Bitaraf, Saeid Bitra, Veera R. Boloor, Archith Bora, Kaustubh Botelho, João Silva Buchbinder, Rachelle Calina, Daniela Cámera, Luis Alberto Carvalho, Andre F. Chan, Jeffrey Shi Kai Chattu, Vijay Kumar Abebe, Endeshaw Chekol Department of Rheumatology and Immunology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China China Department of Medicine & Therapeutics The Chinese University of Hong Kong Hong Kong Department of Paediatrics The Chinese University of Hong Kong Hong Kong School of Pharmacy The Chinese University of Hong Kong Hong Kong Jockey Club School of Public Health and Primary Care The Chinese University of Hong Kong Hong Kong Department of Nursing Woldia University Woldia Ethiopia Department of Orthopedic Surgery Harvard University Boston MA United States Postgraduate Medical Education Harvard University Boston MA United States Maternal Fetal Care Center Harvard University Boston MA United States Department of Health Policy and Oral Epidemiology Harvard University Boston MA United States Division of General Internal Medicine Harvard University Boston MA United States Department of Orthopaedic Surgery Shahid Beheshti University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Biotechnology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran National Nutrition and Food Technology Research Institute Shahid Beheshti University of Medical Sciences Tehran Iran Department of Immunology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran Iran Center for Comprehensive Genetic Services Shahid Beheshti University of Medical Sciences Tehran Iran Cancer Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Functional Neuro

Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rh

关键词： Global burden of disease study Immune-mediated inflammatory disease Incidence Trend

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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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