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31st Annual Meeting of the American Society for Precision engineering, ASPE 2016

作者： Ametova, Evelina Ferrucci, Massimiliano Chilingaryan, Suren McCarthy, Michael Dewulf, Wim Department of Mechanical Engineering Katholieke Universiteit Leuven Leuven Belgium Engineering Measurement Division National Physical Laboratory Teddington United Kingdom Institute of Data Processing and Electronics Karlsruhe Institute of Technology Karlsruhe Germany

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Multi-label inductive matrix completion for joint MGMT and IDH1 status prediction for glioma patients 1

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20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017

作者： Chen, Lei Zhang, Han Thung, Kim-Han Liu, Luyan Lu, Junfeng Wu, Jinsong Wang, Qian Shen, Dinggang Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Department of Radiology and BRIC University of North Carolina Chapel Hill United States School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai China Department of Neurosurgery Huashan Hospital Fudan University Shanghai China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai China

ISBN: (数字)9783319661858

ISBN: (纸本)9783319661841

MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is laborious, invasive and time-consuming. Accurate presurgical prediction of their statuses based on preoperative imaging data is of great clinical value towards better treatment plan. In this paper, we propose a novel Multi-label Inductive Matrix Completion (MIMC) model, highlighted by the online inductive learning strategy, to jointly predict both MGMT and IDH1 statuses. Our MIMC model not only uses the training subjects with possibly missing MGMT/IDH1 labels, but also leverages the unlabeled testing subjects as a supplement to the limited training dataset. More importantly, we learn inductive labels, instead of directly using transductive labels, as the prediction results for the testing subjects, to alleviate the overfitting issue in small-sample-size studies. Furthermore, we design an optimization algorithm with guaranteed convergence based on the block coordinate descent method to solve the multivariate non-smooth MIMC model. Finally, by using a precious single-center multi-modality presurgical brain imaging and genetic dataset of primary HGG, we demonstrate that our method can produce accurate prediction results, outperforming the previous widely-used single- or multi-task machine learning methods. This study shows the promise of utilizing imaging-derived brain connectome phenotypes for prognosis of HGG in a non-invasive manner. © Springer International Publishing AG 2017.

关键词： Forecasting

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Beam energy dependence of the relativistic retardation effects of electrical fields on the π-/π+ratio in heavy-ion collisions

arXiv

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arXiv 2018年

作者： Wei, Gao-Feng Yong, Gao-Chan Ou, Li Zhi, Qi-Jun Long, Zheng-Wen School of Mechanical and Material Engineering Xi'An University of Arts and Sciences Xi'an710065 China School of Physics and Electronic Science Guizhou Normal University Guiyang550001 China Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China College of Physics and Technology Guangxi Normal University Guilin541004 China Guangxi Key Laboratory Breeding Base of Nuclear Physics and Technology Guangxi Normal University Guilin541004 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University Guiyang550001 China College of Physics Guizhou University Guiyang550025 China

In this article we investigate the beam energy dependence of relativistic retardation effects of electrical fields on the single and double π-/π+ratios in three heavy-ion reactions with an isospin- and momentum-dependent transport model IBUU11. With the beam energy increasing from 200 to 400 MeV/nucleon, effects of the relativistically retarded electrical fields on the π-/π+ratio are found to increase gradually from negligibly to considerably significant as expectedly;it is however, the interesting observation is the relativistic retardation effects of electrical fields on the π-/π+ratio are becoming gradually insignificant as the beam energy further increasing from 400 to 800 MeV/nucleon. That is to say, with the beam energy increasing, the competition of enhanced anisotropic features of retarded electrical fields and reduced duration time of the reactions gets effects of the relativistically retarded electrical fields on the π-/π+ratio to be maximum around 400 MeV/nucleon. Therefore, the relativistic retardation effects of electrical fields should be carefully considered in heavy-ion collisions at intermediate energy especially around 400 MeV/nucleon when using the π-/π+ratio as the probe of nuclear symmetry energy. Moreover, we also investigate the isospin dependence of relativistic retardation effects of electrical fields on the π-/π+ratio in two isobar reaction systems of 96Ru+96Ru and 96Zr+96Zr at the beam energies from 200 to 800 MeV/nucleon. It is shown that the relativistic retardation effects of electrical fields on the π-/π+ratio are independent of the isospin of reaction. Furthermore, we also examine the double π-/π+ratio in reactions of 96Zr+96Zr over 96Ru+96Ru at the beam energies from 200 to 800 MeV/nucleon with the static field and retarded field, respectively. It is shown the double π-/π+ratio from two reactions is still an effective observable of symmetry energy without the interference of electrical field due to using the relativistic calculation

关键词： Colliding beam accelerators

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Highly integrated SiC module with thick-film dielectric allows for high frequency operation

Highly integrated SiC module with thick-film dielectric allo...

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CIPS 2016;9th International Conference on Integrated Power Electronics Systems

作者： Michael Meisser Max Schmenger Martin Bernd Benjamin Leyrer Horst Demattio Dean Hamilton Philip Mawby Thomas Blank Institute for Data Processing and Electronics Karlsruhe Institute of Technology (KIT) School of Engineering University of Warwick

This paper encompasses the design, manufacture and static electrical characterisation of a full-SiC 1200 V half-bridge module with integrated gate drivers and DC-link capacitors. The module is based on copper thick-film (CTF) on a 850 mm(exp 2) AL2O3 substrate. At a heat-sink temperature of 80 deg C, the module can carry a continuous current of 25 A. CTF supports the implementation of fine-pitch SMD components while the use of conventional Al wire bond interconnects keeps the costs low. Combined, CTF and wire bonding could represent the next generation of fast-switching power modules. Simulations revealed that by integrating a 600 nF DC-link capacitance on the substrate, the total parasitic inductance of the power loop is reduced down to 1.4 nH at 1 MHz.

关键词： operating frequency Sink Temperature NFIC gene constant current thick films wire bonding DC link highly integrated

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Adaptive Neural Network Tracking for a Class of Markov Jump Stochastic Nonlinear Systems Based on Extreme Learning Machine

Adaptive Neural Network Tracking for a Class of Markov Jump ...

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2016 IEEE Chinese Guidance, Navigation and Control Conference (IEEE CGNCC2016)

作者： Pengpeng Wang Fei Long Yi Tan Institute of Intelligent Information Processing College of Big Data and Information EngineeringGuizhou University

ISBN: (纸本)9781467383196

In this paper,the tracking problem is proposed for a class stochastic nonlinear systems with Markov jump based on neural *** using backstepping method and Lyapunov function,the adaptive controller is designed to guarantee such the Markov jump stochastic nonlinear systems is asymptotically stable and track the desired reference *** single hidden layer feed-forward neural network(SLFNN) is employed to approximate the unknown nonlinear functions,and the hidden layer node parameters are trained by extreme learning machine(ELM) algorithms.A simulation example demonstrates the effectiveness of the proposed method.

关键词： Adaptive Neural Network Tracking for a Class of Markov Jump Stochastic Nonlinear Systems Based on Extreme Learning Machine Markov

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Optimal Estimation of Sensor Biases for Asynchronous Multi-Sensor data Fusion

arXiv

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arXiv 2017年

作者： Pu, Wenqiang Liu, Ya-Feng Yan, Junkun Liu, Hongwei Luo, Zhi-Quan National Laboratory of Radar Signal Processing Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi'an710071 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen518100 China

An important step in a multi-sensor surveillance system is to estimate sensor biases from their noisy asynchronous measurements. This estimation problem is computationally challenging due to the highly nonlinear transformation between the global and local coordinate systems as well as the measurement asynchrony from different sensors. In this paper, we propose a novel nonlinear least squares (LS) formulation for the problem by assuming the existence of a reference target moving with an (unknown) constant velocity. We also propose an efficient block coordinate decent (BCD) optimization algorithm, with a judicious initialization, to solve the problem. The proposed BCD algorithm alternately updates the range and azimuth bias estimates by solving linear least squares problems and semidefinite programs (SDPs). In the absence of measurement noise, the proposed algorithm is guaranteed to find the global solution of the problem and the true biases. Simulation results show that the proposed algorithm significantly outperforms the existing approaches in terms of the root mean square error (RMSE). Copyright © 2017, The Authors. All rights reserved.

关键词： Mean square error

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Software Watermarking Scheme Based on Multivariate Public Key Cryptosystem

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Wuhan University Journal of Natural Sciences 2016年第3期21卷 257-261页

作者： SUN Xiaoyan ZHANG Maosheng MAO Shaowu REN Zhengwei ZHANG Huanguo Guangxi Universities Key Laboratory of Complex SystemOptimization and Big Data Processing Yulin Normal UniversityYulin 537000 Guangxi China School of Computer Wuhan University Wuhan 430072Hubei China Wuhan Digital and Engineering Institute Wuhan 430205Hubei China

Software watermarking is an efficient tool to verify the copyright of software. Public key cryptosystem-based watermarking is widely researched. However, the popular public key cryptosystem is not secure under quantum algorithm. This paper proposes a novel soft-ware watermarking scheme based on multivariate public key cryptosystem. The copyright information generated by copyright holder is transformed into copyright numbers using multivariate quadratic polynomial equations inspired by multivariate public key cryptosystem （MPKC）. Every polynomial is embedded into the host program independently. Based on the security performance of MPKC, the robustness and invisibility of the proposed scheme is significantly improved in comparison with the RSA-based watermarking method.

关键词： software watermarking multivariate cryptosystem copyright

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Enhancement and Analysis of Conversational Speech: JSALT 2017

Enhancement and Analysis of Conversational Speech: JSALT 201...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Neville Ryanta Elika Bergelson Kenneth Church Alejandrina Cristia Jun Du Sriram Ganapathy Sanjeev Khudanpur Diana Kowalski Mahesh Krishnamoorthy Rajat Kulshreshta Mark Liberman Yu-Ding Lu Matthew Maciejewski Florian Metze Jan Profant Lei Sun Yu Tsao Zhou Yu Linguistic Data Consortium University of Pennsylvania Philadelphia PA USA Department of Psychology and Neuroscience Duke University Durham NC USA IBM Yorktown Heights NY USA Laboratoire de Sciences Cognitives et Psycholinguistique ENS Paris France University of Science and Technology of China Hefei China Electrical Engineering Department Indian Institute of Science Bangalore India Center for Language and Speech Processing Johns Hopkins University Baltimore MD USA University of Illinois at Urbana-Champaign Champaign IL USA Apple Cupertino CA USA Language Technologies Institute Carnegie Mellon University Pittsburgh PA USA Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Brno University of Technology Brno Czech Republic Department of Computer Science University of California Davis Davis CA USA

ISBN: (纸本)9781538646595

Automatic speech recognition is more and more widely and effectively used. Nevertheless, in some automatic speech analysis tasks the state of the art is surprisingly poor. One of these is "diarization", the task of determining who spoke when. Diarization is key to processing meeting audio and clinical interviews, extended recordings such as police body cam or child language acquisition data, and any other speech data involving multiple speakers whose voices are not cleanly separated into individual channels. Overlapping speech, environmental noise and suboptimal recording techniques make the problem harder. During the JSALT Summer Workshop at CMU in 2017, an international team of researchers worked on several aspects of this problem, including calibration of the state of the art, detection of overlaps, enhancement of noisy recordings, and classification of shorter speech segments. This paper sketches the workshop's results, and announces plans for a "Diarization Challenge" to encourage further progress.

关键词： diarization overlap detection speech enhancement automatic speech recognition Speech recognition Speech enhancement Speech state of the art monuron Recordings

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Connector-less SiC power modules with integrated shunt — Low-profile design for low inductance and low cost

Connector-less SiC power modules with integrated shunt — Lo...

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European Conference on Power Electronics and Applications

作者： Michael Meisser Horst Demattio Dean Hamilton Thomas Blank KARLSRUHE INSTITUTE OF TECHNOLOGY INSTITUTE FOR DATA PROCESSING AND ELECTRONICS Eggenstein-Leopoldshafen Germany UNIVERSITY OF WARWICK SCHOOL OF ENGINEERING Coventry United Kingdom

This paper presents the design, manufacture and characterization of connector-less 1200 V SiC MOSFET half-bridge power modules based on AlN DCB substrate. The modules contain four MOSFETs and no external antiparallel diodes. They are rated for a current of 40 A and include a shunt. Static and dynamic measurement results are presented. Multiphysics simulations are used to validate the measured data. The modules show a power path inductance below 3 nH. The power rating of the implemented chip shunt resistors is sufficient for the performed characterizations but requires revision. The switching loss at turn-on is 340 μJ at 23 A, 800 V, the turn-off loss is well below 50 μJ, principally allowing MHz operation in resonant mode.

关键词： Substrates Inductance Logic gates Resistors Wires Temperature measurement Copper

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