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Microstructure and Properties of Plasma-Nitrided Fe-Based Superalloy Fe-25Ni-15Cr

METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE 2017年第7期48A卷 3357-3369页

作者： Xu, Xiaolei Yu, Zhiwei Hou, Caiyun Song, Weixiu Wang, Yingzhu Dalian Maritime Univ Dept Mat Sci & Engn Dalian Peoples R China

Fe-based superalloy Fe-25Ni-15Cr was plasma nitrided at a low temperature of 723 K (450 A degrees C). The nitrided layer was characterized by optical microscopy (OPM) and scanning electron microscopy (SEM) and X-ray diffraction (XRD) through stepwise mechanical polishing and transmission electron microscopy (TEM). The results indicated that the double expanded austenite (gamma (N1) and gamma (N2)) was developed on the nitrided surface. Energy-dispersive X-ray spectrum (EDS) revealed that separate expanded austenite layers with distinctly different nitrogen contents occurred: high (18.98 to 11.49 at. pct) in the surface layer and low (5.87 to 5.32 at. pct) in the subsurface. XRD analysis indicated that large lattice expansion and distortion relative to the untreated austenite of an idea face-centered-cubic (fcc) structure occurred on the gamma (N1), but low expansion and less distortion on the gamma (N2). No obvious lattice distortion on the gamma (N1) was determined by calculating its electron diffraction pattern (EDP), except for detectable lattice expansion. Inconformity between XRD and EDP results suggested that the high compressive residual stress in the gamma (N1) was mainly responsible for the lattice distortion of the gamma (N1). TEM indicated that the gamma (N1) layer exhibited the monotonous contrast characteristic of an amorphous phase contrast to some extent, and corresponding EDP showed a strong diffuse scattering effect. It was suggested that the pre-precipitation took place in the gamma (N1) in the form of strongly bonded Cr-N clusters or pairs. Decomposition of the gamma (N1) into CrN and gamma occurred at the grain boundaries, and the orientation of both phases remained cubic and cubic relationship, i.e., the planes and the directions with identical Miller indices in both phases were parallel. The nitrided surface was found to have significantly improved wear resistance. Further, the nitrided surface showed no adverse effect in the corrosion resistan

关键词： Scanning Electron Microscope compressive residual stress superalloys N1 Stage Finding electronic data processing x-ray diffraction (XRD) surface layers lattice distortion corrosion resistance Phase Microstructure

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Fault Detection and Diagnosis Based on Sparse PCA and Two-Level Contribution Plots

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2017年第1期56卷 225-240页

作者： Luo, Lijia Bao, Shiyi Mao, Jianfeng Tang, Di Zhejiang Univ Technol Inst Proc Equipment & Control Engn Engn Res Ctr Proc Equipment & Remfg Minist Educ Hangzhou 310014 Zhejiang Peoples R China

A hovel process monitoring method is proposed based on sparse principal component analysis (SpPCA). To reveal meaningful variable correlations from process data, the SpPCA is developed to sequentially extract a set of sparse loading vectors from process data. To build a high-performance monitoring model, a fault detectability matrix is applied to select the sparse loading vectors used for process modeling from all sparse loading vectors obtained by SpPCA. The fault detectability matrix ensures that the faults related to any monitored process variable are detectable in the principal component subspace and no overlapped (or redundant) loading vectors are involved in the monitoring model. Moreover, the selected sparse loading vectors classify all process variables into nonoverlapping groups according to variable correlations. Two-level contribution plots, which consist of group-wise and group-variable-wise contribution plots, are used for fault diagnosis. The first-level group-wise contribution plot describes the individual contribution of each variable group to the fault. The second-level group variable-wise contribution plot reflects the individual contribution of each process variable to the fault. The two-level contribution plots not only utilize meaningful correlations between process variables in the same group, but also effectively remove the interference from process variables in other groups. Therefore, the fault diagnosis reliability and accuracy are significantly improved. The implementation, performance, and advantages of the proposed methods are illustrated with an industrial case study.

关键词： FAULT diagnosis (Chemical engineering) CHEMICAL process control MULTIPLE correspondence analysis (Statistics) electronic data processing VECTORS (Calculus) VARIABLES (Mathematics)

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Standard Protocol for Exchange of Health-checkup data Based on SGML: The Health-checkup data Markup Language (HDML)

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Methods of Information in Medicine 2018年第3期41卷 220-223页

作者： H. Sugimori K. Yoshida S. Hara K. Furumi I. Tofukuji T. Kubodera T. Yoda M. Kawai

Objectives: To develop a health/medical data interchange model for efficient electronic exchange of data among health-checkup facilities. Results: A Health-checkup data Markup Language (HDML) was developed on the basis of the Standard Generalized Markup Language (SGML), and a feasibility study carried out, involving data exchange between two health checkup facilities. The structure of HDML is described. Results: The transfer of numerical lab data, summary findings and health status assessment was successful. Conclusions: HDML is an improvement to laboratory data exchange. Further work has to address the exchange of qualitative and textual data.

关键词： database data linkage computer communication networks electronic data processing

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Big data Is the Answer ... But What Is the Question?

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OSIRIS 2017年第1期32卷 328-345页

作者： Strasser, Bruno J. Edwards, Paul N. Univ Geneva Biol Sect CH-1211 Geneva 4 Switzerland Yale Univ Sch Med Sect Hist Med New Haven CT 06510 USA Stanford Univ Ctr Int Secur & Cooperat C-226 Encina Hall Stanford CA 94309 USA Univ Michigan Sch Informat 105 South State St Ann Arbor MI 48109 USA

Rethinking histories of data requires not only better answers to existing questions, but also better questions. We suggest eight such questions here. What counts as data? How are objects related to data? What are digital data? What makes data measurable, and what does quantification do to data? What counts as an information age? Why do we keep data, and how do we decide which data to lose or forget? Who owns data, and who uses them? Finally, how does Big data transform the geography of science? Each question is a provocation to reconsider the meanings and uses of data not only in the past but in the present as well.

关键词： BIG data HISTORY electronic data processing electronic information resources INFORMATION society INFORMATION resources management

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FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web

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BIOINFORMATICS 2018年第8期34卷 1433-1435页

作者： Probst, Daniel Reymond, Jean-Louis Univ Bern Dept Chem & Biochem NCCR TransCure CH-3012 Bern Switzerland

Motivation: During the past decade, big data have become a major tool in scientific endeavors. Although statistical methods and algorithms are well-suited for analyzing and summarizing enormous amounts of data, the results do not allow for a visual inspection of the entire data. Current scientific software, including R packages and Python libraries such as ggplot2, matplotlib and ***, do not support interactive visualizations of datasets exceeding 100 000 data points on the web. Other solutions enable the web-based visualization of big data only through data reduction or statistical representations. However, recent hardware developments, especially advancements in graphical processing units, allow for the rendering of millions of data points on a wide range of consumer hardware such as laptops, tablets and mobile phones. Similar to the challenges and opportunities brought to virtually every scientific field by big data, both the visualization of and interaction with copious amounts of data are both demanding and hold great promise. Results: Here we present FUn, a framework consisting of a client (Faerun) and server (Underdark) module, facilitating the creation of web-based, interactive 3D visualizations of large datasets, enabling record level visual inspection. We also introduce a reference implementation providing access to SureChEMBL, a database containing patent information on more than 17 million chemical compounds.

关键词： VISUALIZATION ALGORITHMS PYTHON (Computer program language) SOFTWARE frameworks electronic data processing

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HaVec: An Efficient de Bruijn Graph Construction Algorithm for Genome Assembly

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INTERNATIONAL JOURNAL OF GENOMICS 2017年第1期2017卷 1-12页

作者： Limon, Mahfuzer Rahman Sharker, Ratul Biswas, Sajib Rahman, M. Sohel BUET Dept CSE ECE Bldg West Palasi Dhaka 1205 Bangladesh

Background. The rapid advancement of sequencing technologies has made it possible to regularly produce millions of high-quality reads from the DNA samples in the sequencing laboratories. To this end, the de Bruijn graph is a popular data structure in the genome assembly literature for efficient representation and processing of data. Due to the number of nodes in a de Bruijn graph, the main barrier here is the memory and runtime. Therefore, this area has received significant attention in contemporary literature. Results. In this paper, we present an approach called HaVec that attempts to achieve a balance between the memory consumption and the running time. HaVec uses a hash table along with an auxiliary vector data structure to store the de Bruijn graph thereby improving the total memory usage and the running time. A critical and noteworthy feature of HaVec is that it exhibits no false positive error. Conclusions. In general, the graph construction procedure takes the major share of the time involved in an assembly process. HaVec can be seen as a significant advancement in this aspect. We anticipate that HaVec will be extremely useful in the de Bruijn graph-based genome assembly.

关键词： DNA sequencing DE Bruijn graph data structures (Computer science) electronic data processing GRAPH theory

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SeqArray-a storage-efficient high-performance data format for WGS variant calls

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BIOINFORMATICS 2017年第15期33卷 2251-2257页

作者： Zheng, Xiuwen Gogarten, Stephanie M. Lawrence, Michael Stilp, Adrienne Conomos, Matthew P. Weir, Bruce S. Laurie, Cathy Levine, David Univ Washington Dept Biostat Seattle WA 98195 USA Genentech Inc Bioinformat & Computat Biol San Francisco CA 94080 USA

Motivation: Whole-genome sequencing (WGS) data are being generated at an unprecedented rate. Analysis of WGS data requires a flexible data format to store the different types of DNA variation. Variant call format (VCF) is a general text-based format developed to store variant genotypes and their annotations. However, VCF files are large and data retrieval is relatively slow. Here we introduce a new WGS variant data format implemented in the R/Bioconductor package 'SeqArray' for storing variant calls in an array-oriented manner which provides the same capabilities as VCF, but with multiple high compression options and data access using high-performance parallel computing. Results: Benchmarks using 1000 Genomes Phase 3 data show file sizes are 14.0Gb (VCF), 12.3 Gb (BCF, binary VCF), 3.5Gb (BGT) and 2.6Gb (SeqArray) respectively. Reading genotypes in the SeqArray package are two to three times faster compared with the htslib C library using BCF files. For the allele frequency calculation, the implementation in the SeqArray package is over 5 times faster than PLINK v1.9 with VCF and BCF files, and over 16 times faster than vcftools. When used in conjunction with R/Bioconductor packages, the SeqArray package provides users a flexible, feature-rich, high-performance programming environment for analysis of WGS variant data.

关键词： DNA sequencing data structures (Computer science) GENOTYPE electronic data processing

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Network data Analytics 1st ed. 2018

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丛书名： Computer Communications and Networks

2018年

作者： K. G. Srinivasa Siddesh G. M. Srinidhi H.

ISBN: (数字)9783319778006

ISBN: (纸本)9783319777993

In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.

关键词： electronic data processing Machine learning. Big data. Internet of things

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Practical Enterprise data Lake Insights 1st ed.

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2018年

作者： Saurabh Gupta Venkata Giri

ISBN: (数字)9781484235225

ISBN: (纸本)9781484235218

Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model Who This Book Is ForBig data architects and solution architects

关键词： Information storage and retrieval systems. Big data. Management. Distributed processing electronic data processing

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Software-Defined Cloud Centers 1st ed. 2018

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丛书名： Computer Communications and Networks

2018年

作者： Pethuru Raj Anupama Raman

ISBN: (数字)9783319786377

ISBN: (纸本)9783319786360

This practical text/reference provides an exhaustive guide to setting up and sustaining software-defined data centers (SDDCs). Each of the core elements and underlying technologies are explained in detail, often supported by real-world examples. The text illustrates how cloud integration, brokerage, and orchestration can ensure optimal performance and usage of data resources, and what steps are required to secure each component in a SDDC. The coverage also includes material on hybrid cloud concepts, cloud-based data analytics, cloud configuration, enterprise DevOps and code deployment tools, and cloud software engineering. Topics and features: highlights how technologies relating to cloud computing, IoT, blockchain, and AI are revolutionizing business transactions, operations, and analytics; introduces the concept of Cloud 2.0, in which software-defined computing, storage, and networking are applied to produce next-generation cloud centers; examines software-defined storage for storage virtualization, covering issues of cloud storage, storage tiering, and deduplication; discusses software-defined networking for network virtualization, focusing on techniques for network optimization in data centers; reviews the qualities and benefits of hybrid clouds, that bridge private and public cloud environments; investigates the security management of a software-defined data center, and proposes a framework for managing hybrid IT infrastructure components; describes the management of multi-cloud environments through automated tools, and cloud brokers that aim to simplify cloud access, use and composition; covers cloud orchestration for automating application integration, testing, infrastructure provisioning, software deployment, configuration, and delivery. This comprehensive work is an essential reference for all practitioners involved with software-defined data center technologies, hybrid clouds, cloud service management, cloud-based analytics, and cloud-based software engine

关键词： Cloud computing electronic data processing Software-defined networking (Computer network technology) Management. Distributed processing Management.

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