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The Pacific Symposium on Biocomputing (PSB) 2015 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2015 will be held from January 4 - 8, 2015 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2015 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is...
Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based regular...
Fuzzy logic is vital to applications in the electrical, industrial, chemical and engineering realms, as well as in areas of management and environmental issues. Data mining is indispensible in dealing with big data, massive data, and scalable, parallel and distributed algorithms. This book presents papers from FSDM 2022, the 8th International Conference on Fuzzy Systems and Data Mining. The conference, originally scheduled to take place in Xiamen, China, was held fully online from 4 to 7 November 2022, due to ongoing restrictions connected with the COVID-19 pandemic. This year, FSDM received 196 submissions, of which 47 papers were ultimately selected for presentation and publication after a...
The XXth General Assembly of the International Astronomical Union was held in Baltimore, Maryland USA from August 02 to 11, 1988. The Inaugural Ceremony on August 02 was held in the presence of representatives of the United States Governn:ent, t~e S~ate of Maryland, the City of Baltimore and the host institution -the Johns Hopkins Umverslty- as well as of the National and Local Organising Committees. The scientific programme maintained the high standards of the Union and the scientific proceedings may be found either in this volume or in volume 8 of Highlights of Astronomy. The scientific programme was organised by the 40 Commission Presidents and coordinated by the General Secretary (1985-1988), Dr. J.-P. Swings. The local arrangements were effectively made through the National Organising Committee under the Chairmanship of Prof. F. Drake and the Local Organising Committee under the co-Chairmanship of Prof. A. Oavidsen and Dr. R. Giacconi. The smooth day to day operation of the meeting resulted from the incomparable dedication of Karen Weinstock and Harold Screen.
This book presents the outcomes of the 2017 International Conference on Applications and Techniques in Cyber Security and Intelligence, which focused on all aspects of techniques and applications in cyber and electronic security and intelligence research. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods and applications on all aspects of cyber and electronic security and intelligence.
IAU Transactions XXIIB summarizes the work of the XXIInd General Assembly. The discourses given during the Inaugural and Closing Ceremonies are reproduced in Chapters I and III, respectively. The proceedings of the two sessions of the General Assembly will be found in Chapter II, which includes the Resolutions and the report of the Finance Committee. The Statutes, Bye-Laws and a few working rules of the Union are published in Chapter IV. The Accounts and other aspects of the administration of the Union are recorded in Chapter V, together with the report of the Executive Committee for this last triennium, and provide the permanent record for the Union in the period 1991-1994. This volume also contains the Commission reports from The Hague compiled by the Presidents of the Commissions (Chapter VI). Finally, Chapter VII contains the list of countries adhering to the Union and the alphabetical, geographical and commission membership lists of about 8000 individual members. The IAU still appears to be unique among the scientific Unions in maintaining this category of individual membership which contributes in a crucial way to the spirit and the aims of the Union.
The LNCS volume 12878 constitutes the proceedings of the 15th Chinese Conference on Biometric Recognition, held in Shanghai, China, in September 2021. The 53 papers presented in this book were carefully reviewed and selected from 72 submissions. The papers cover a wide range of topics such as multi-modal biometrics and emerging biometrics; hand biometrics; facial biometrics; and speech biometrics.
Due to numerous biomedical information sensing devices, such as Computed Tomography (CT), Magnetic Resonance (MR) Imaging, Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc. a large amount of biomedical information was gathered these years. However, identifying how to develop new advanced imaging methods and computational models for efficient data processing, analysis and modelling from the collected data is important for clinical applications and to understand the underlying biological processes. Deep learning approaches have been rapidly developed in recent years, both in terms of methodologies and practical applications. Deep learning techniques provide computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. Deep Learning allows to implicitly capture intricate structures of large-scale data and ideally suited to some of the hardware architectures that are currently available.
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