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6th international conference on Big Data Analytics, BDA 2018

ISBN: (纸本)9783030047795

the proceedings contain 29 papers. the special focus in this conference is on Big Data Analytics. the topics include: Automated credibility assessment of web page based on genre;cbI: Improving credibility of user-generated content on facebook;a parallel approach to detect communities in evolving networks;modeling sparse and evolving data;polystore data management systems for managing scientific data-sets in big data archives;MPP SQL query optimization with RTCG;big data analytics framework for spatial data;an ingestion based analytics framework for complex event processing engine in internet of things;An energy-efficient greedy mapreduce scheduler for heterogeneous hadoop YARN cluster;blockchain-powered big data analytics platform;Analysis of narcolepsy based on single-channel EEG signals;formal methods, artificial intelligence, big-data analytics, and knowledge engineering in medical care to reduce disease burden and health disparities;*** based soil N-P-K prediction model for soil and crop specific data: A predictive modelling approach;deep neural network based image captioning;oversample based large scale support vector machine for online class imbalance problem;using crowd sourced data for music mood classification;applying big data intelligence for real time machine fault prediction;PRISMO: Priority based spam detection using multi optimization;malware detection using machine learning and deep learning;spatial co-location pattern mining;humble data management to big data analytics/science: A retrospective stroll;Fusion of game theory and big data for AI applications;distributed financial calculation framework on cloud computing environment;testing concept drift detection technique on data stream;homogenous ensemble of time-series models for indian stock market.

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Biomedical Engineering Systems and Technologies 1st ed. 2017

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丛书名： Communications in Computer and Information Science

2017年

作者： Ana Fred Hugo Gamboa

ISBN: (数字)9783319547176

ISBN: (纸本)9783319547169

this book constitutes the thoroughly refereed post-conference proceedings of the 9th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016, held in Rome, Italy, in February 2016. the 22 revised full papers presented were carefully reviewed and selected from a total of 321 submissions. the papers are organized in topical sections onbiomedical electronics and devices; bioimaging; bioinformatics models, methods and algorithms; bio-inspired systems and signal processing; health informatics.

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6th international conference on Numerical Analysis and Its Applications, NAA 2016

6th International Conference on Numerical Analysis and Its A...

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6th international conference on Numerical Analysis and Its Applications, NAA 2016

ISBN: (纸本)9783319570983

the proceedings contain 90 papers. the special focus in this conference is on Numerical Analysis and Applications. the topics include: Behavior of weak solutions to the boundary value problems for second order elliptic quasi-linear equation with constant and variable nonlinearity exponent in a neighborhood of a conical boundary point;CVA computing by PDE models;chaotic dynamics of structural members under regular periodic and white noise excitations;convergence order of a finite volume scheme for the time-fractional diffusion equation;convergence of alternant theta-method with applications;a numerical study on the compressibility of subblocks of schur complement matrices obtained from discretized Helmholtz equations;convergence outside the initial layer for a numerical method for the time-fractional heat equation;multi-preconditioned domain decomposition methods in the krylov subspaces;use of asymptotics for new dynamic adapted mesh construction for periodic solutions with an interior layer of reaction-diffusion-advection equations;a singularly perturbed boundary value problems with fractional powers of elliptic operators;a higher order difference scheme for the time fractional diffusion equation with the steklov nonlocal boundary value problem of the second kind;local discontinuous galerkin methods for reaction-diffusion systems on unstructured triangular meshes;numerical modeling of fluid flow in liver lobule using double porosity model;algorithms for numerical simulation of non-stationary neutron diffusion problems;regularization methods of the continuation problem for the parabolic equation and computer simulation of plasma dynamics in open plasma trap.

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2nd international conference on Future Data and Security Engineering, FDSE 2015 and 9th international conference on Advanced Computing and Applications ACOMP 2015

2nd International Conference on Future Data and Security Eng...

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2nd international conference on Future Data and Security Engineering, FDSE 2015 and 9th international conference on Advanced Computing and Applications ACOMP 2015

ISBN: (纸本)9783662541722

the proceedings contain 6 papers. the special focus in this conference is on Future Data and Security Engineering. the topics include: User-centered design of geographic interactive applications;applying data analytic techniques for fault detection;protecting biometrics using fuzzy extractor and non-invertible transformation methods in Kerberos authentication protocol;parallel learning of local SVM algorithms for classifying large datasets;contractual specifications of business services;modeling, formalization, proximity and energy-saving virtual machine scheduling in cloud computing with fixed interval constraints.

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Anytime algorithms for Adaptive Robust Optimization with OWA and WOWA 5th

Anytime Algorithms for Adaptive Robust Optimization with OWA...

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5th international conference on Algorithmic Decision theory, ADT 2017

作者： Bourdache, Nadjet Perny, Patrice Sorbonne Universités UPMC Univ Paris 06 UMR 7606 LIP6 CNRS UMR 7606 LIP6 4 Place Jussieu Paris75005 France

ISBN: (纸本)9783319675039

We consider optimization problems in graphs where the utilities of solutions depend on different scenarios. In this context, we study incremental approaches for the determination of robust solutions, i.e. solutions yielding good outcomes in all scenarios. Our approach consists in interleaving adaptive preference elicitation methods aiming to assess the attitude of the Decision Maker towards robustness or risk with combinatorial optimization algorithms aiming to determine a robust solution. Our work focuses on the use of ordered weighted average (OWA) and weighted ordered weighted average (WOWA) to respectively model preferences under uncertainty and risk while accounting for the idea of robustness. these models are parameterized by weighting coefficients or weighting functions that must be fitted to the value system of the Decision Maker. We introduce and justify anytime algorithms for the adaptive elicitation of these parameters until a robust solution can be determined. We also test these algorithms on the robust assignment problem. © 2017, Springer international Publishing AG.

关键词： Decision making

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international conference on Computer Safety, Reliability, and Security, SAFECOMP 2017 and 5th international Workshop on Assurance Cases for Software-Intensive Systems, ASSURE 2017, 12th Workshop on Dependable Embedded and Cyber-physical Systems and Systems-of Systems, DECSoS 2017, 6th international Workshop on Next Generation of System Assurance Approaches for Safety Critical Systems, SASSUR 2017, 3rd international Workshop on Technical and Legal Aspects of Data Privacy and Security, TELERISE 2017 and 2nd international Workshop on the Timing Performance in Safety Engineering, TIPS 2017

International Conference on Computer Safety, Reliability, an...

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international conference on Computer Safety, Reliability, and Security, SAFECOMP 2017 and 5th international Workshop on Assurance Cases for Software-Intensive Systems, ASSURE 2017, 12th Workshop on Dependable Embedded and Cyber-physical Systems and Systems-of Systems, DECSoS 2017, 6th international Workshop on Next Generation of System Assurance Approaches for Safety Critical Systems, SASSUR 2017, 3rd international Workshop on Technical and Legal Aspects of Data Privacy and Security, TELERISE 2017 and 2nd international Workshop on the Timing Performance in Safety Engineering, TIPS 2017

ISBN: (纸本)9783319662831

the proceedings contain 39 papers. the special focus in this conference is on Computer Safety, Reliability, and Security. the topics include: Making the case for safety of machine learning in highly automated driving;a thought experiment on evolution of assurance cases —from a logical aspect;a thought experiment on evolution of assurance cases from a logical aspect;uniform model interface for assurance case integration with system models;integrated model-based development of system and safety cases;a web based GSN editor for multiple stakeholders;towards combined safety and security constraints analysis;reconciling systems-theoretic and component-centric methods for safety and security co-analysis;reconciling systems-theoretic and component-centric methods for safety and security co-analysis;increasing dependability in safety critical CPSs using reflective statecharts;a survey of hardware technologies for mixed-critical integration explored in the project EMC2;a model-based design approach;GSN support of mixed-criticality systems certification;concepts for reliable communication in a software-defined network architecture and combining safety and security analysis for industrial collaborative automation systems.

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6th international conference on theory and Practice of Natural Computing, TPNC 2017

6th International Conference on Theory and Practice of Natur...

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6th international conference on theory and Practice of Natural Computing, TPNC 2017

ISBN: (纸本)9783319710686

the proceedings contain 24 papers. the special focus in this conference is on theory and Practice of Natural Computing. the topics include: An evolutionary algorithm based on graph theory metrics for fuzzy cognitive maps learning;fuzzy petri nets with linear orders for intervals;networks of polarized splicing processors;robust combinatorial circuits in chemical reaction networks;watson-crick partial words;Topological classification of RNA structures via intersection graph;splicing-inspired recognition and composition of musical collectives styles;regularized stacked auto-encoder based pre-training for generalization of multi-layer perceptron;historical markings in neuroevolution of augmenting topologies revisited;a formal framework for composing qualitative models of biological systems;Long-short term memory network for RNA structure profiling super-resolution;hamming distance kernelisation via topological quantum computation;typing quantum superpositions and measurement;heat-bath algorithmic cooling with correlated-qubits relaxation;time-space complexity advantages for quantum computing;a statistical approach to the identification of diploid cellular automata;modelling curvature effects using L-systems: From discrete and deterministic to continuous and stochastic;exploring target change related fitness reduction in the moving point dynamic environment;a smart discovery service in internet of things using swarm intelligence;GPU-accelerated evolutionary induction of regression trees;Bezier curve parameterization methods for solving optimal control problems of SIR model;Learning interval-valued fuzzy cognitive maps with PSO algorithm for abnormal stock return prediction.

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Integrating Prior Information with Bayesian Feature Selection 17

Integrating Prior Information with Bayesian Feature Selectio...

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8th ACM international conference on bioinformatics, Computational Biology,and Health Informatics (ACM-BCB)

作者： Pour, Ali Foroughi Dalton, Lori A. Ohio State Univ Elect & Comp Engn Dept 2015 Neil Ave Columbus OH 43210 USA

ISBN: (纸本)9781450347228

Biomarker discovery aims to find biomarkers involved in biological mechanisms of a disease under study that can be further utilized for diagnosis, prognosis, drug development, etc. Although current high throughput technologies provide a deluge of data per point, research is usually constrained to small samples, impeding reliable biomarker discovery. Given the ongoing research on biomarker discovery during the past decades there exists an incredibly useful, but still limited, prior knowledge on cancer biology, such as small gene sets already known to be involved in cancer. this information, if properly integrated with feature selection, could potentially help to detect new biomarkers. However, most current methods used for biomarker discovery cannot easily be extended to account for such prior knowledge. Recent work proposes a hierarchical Bayesian framework for feature selection which places priors on both the identity of all features and identity-conditioned feature distribution. Various models are obtained based on this framework, including dependent good dependent bad (DGDB) model. An approximate solution of DGDB has been used with a set selection heuristic to successfully find genes involved in colon cancer and multiple sclerosis. While the approximate solution only relies on training data, we propose a new algorithm that takes advantage of previously known biomarkers to find additional biomarkers, hereafter called Informed Approximate 3MNC-DGDB (IA-3MNC). In three synthetic simulations we illustrate (a) IA-3MNC outperforms many popular feature selection algorithms, and (b) prior knowledge helps to correctly detect additional biomarkers, particularly under small samples. We apply IA-3MNC to colon cancer and breast cancer datasets deposited on gene expression omnibus with accession numbers GSE1456 and GSE41850, respectively. Studying top 20 selected genes of IA-3MNC and top 10 enriched pathways we find many of highly ranked genes and pathways are suggested to be

关键词： feature selection Bayesian analysis biomarker discovery prior construction

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A study on the application of topic models to motif finding algorithms

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BMC bioinformatics 2016年第SUPPL 19期17卷 129-138页

作者： Gutierrez, Josep Basha Nakai, Kenta Univ Tokyo Grad Sch Frontier Sci Dept Computat Biol & Med Sci Chiba 2778561 Japan Univ Tokyo Inst Med Sci Human Genome Ctr Minato Ku 4-6-1 Shirokane Dai Tokyo 1088639 Japan

Background: Topic models are statistical algorithms which try to discover the structure of a set of documents according to the abstract topics contained in them. Here we try to apply this approach to the discovery of the structure of the transcription factor binding sites (TFBS) contained in a set of biological sequences, which is a fundamental problem in molecular biology research for the understanding of transcriptional regulation. Here we present two methods that make use of topic models for motif finding. First, we developed an algorithm in which first a set of biological sequences are treated as text documents, and the k-mers contained in them as words, to then build a correlated topic model (CTM) and iteratively reduce its perplexity. We also used the perplexity measurement of CTMs to improve our previous algorithm based on a genetic algorithm and several statistical coefficients. Results: the algorithms were tested with 56 data sets from four different species and compared to 14 other methods by the use of several coefficients both at nucleotide and site level. the results of our first approach showed a performance comparable to the other methods studied, especially at site level and in sensitivity scores, in which it scored better than any of the 14 existing tools. In the case of our previous algorithm, the new approach with the addition of the perplexity measurement clearly outperformed all of the other methods in sensitivity, both at nucleotide and site level, and in overall performance at site level. Conclusions: the statistics obtained show that the performance of a motif finding method based on the use of a CTM is satisfying enough to conclude that the application of topic models is a valid method for developing motif finding algorithms. Moreover, the addition of topic models to a previously developed method dramatically increased its performance, suggesting that this combined algorithm can be a useful tool to successfully predict motifs in different ki

关键词： Transcription Factor Binding Site Topic Model Nucleotide Level Motif Finding Site Level

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A Monte Carlo framework for low dose CT reconstruction testing 2nd

A Monte Carlo framework for low dose CT reconstruction testi...

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2nd international Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2017 Held in Conjunction with the 20th international conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017

作者： Mason, Jonathan H. Nailon, Willam H. Davies, Mike E. Institute for Digital Communications University of Edinburgh EdinburghEH9 3JL United Kingdom Department of Oncology Physics Western General Hospital Edinburgh Cancer Centre EdinburghEH4 2XU United Kingdom

ISBN: (纸本)9783319681269

We propose a framework using freely available tools for the synthesis of physically realistic CT measurements for low dose reconstruction development and validation, using a fully sampled Monte Carlo method. this allows the generation of test data that has artefacts such as photon starvation, beam-hardening and scatter, that are both physically realistic and not unfairly biased towards model-based iterative reconstruction (MBIR) algorithms. Using the open source Monte Carlo tool GATE and spectrum simulator SpekCalc, we describe how physical elements such as source, specimen and detector may be modelled, and demonstrate the construction of fan-beam and cone-beam CT systems. We then show how this data may be consolidated and used with image reconstruction tools. We give examples with a low dose polyenergetic source, and quantitatively analyse reconstructions against the numerical ground-truth for MBIR with simulated and ‘inverse crime’ data. the proposed framework offers a flexible and easily reproducible tool to aid MBIR development, and may reduce the gap between synthetic and clinical results. © 2017, Springer international Publishing AG.

关键词： Monte Carlo methods

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