This document discusses file systems for cloud computing. It begins by providing context on the growth of the internet and cloud computing. It then defines what cloud computing and files are. The main points are:
- Distributed file systems provide access to data stored on servers using file system interfaces like opening, reading and writing files.
- HDFS is a popular distributed file system designed for large data sets stored on commodity hardware. It uses replication for reliability and has a single metadata node for coordination.
- HDFS is optimized for large streaming reads and writes. It partitions files into blocks and replicates them across multiple data nodes for reliability and load balancing.
Tutorial on Text Mining and Internet Content Filtering. 13th European Conference on Machine Learning (ECML\'02) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD\'02), Helsinki, Finland, 19-23 August 2002.
The document introduces the topic of data science and the programming language R. It defines data science and provides examples of using data science for social good. Additionally, it outlines some of the main features and pros and cons of using R for data science applications and statistical analysis.
II-PIC 2017: Artificial Intelligence, Machine Learning, And Deep Neural Netwo...Dr. Haxel Consult
Parthiban Srinivasan (VINGYANI, India)
When new technologies become easier to use, they transform industries. That's what's happening with artificial intelligence (AI) and big data. Machine learning is often described as a type of AI where computers learn to do something without being programmed to do it. Deep learning, a subset of machine learning, is proving to work especially well on classification. Big breakthroughs happen when what is suddenly possible meets what is desperately needed. For years, patent analysts have been searching and reviewing terabytes of information, not only patents but also non-patent information. Not only to find prior art but also to identify patents of interest, rate their quality, assess the potential value of patent clusters, and identify potential business partners or infringers. With the rapid increase in the number of patent documents worldwide, demand for their automatic clustering/categorization has grown significantly. Many information science researchers have started to experiment with machine learning tools, but the adoption in the patent information space has been sporadic. In this talk, we aim to review the prevailing machine learning techniques and present several sample implementations by various research groups. We will also discuss how data science compares with machine learning, deep learning, AI, statistics and applied mathematics.
Green Shoots:Research Data Management Pilot at Imperial College LondonTorsten Reimer
The document summarizes the results of a research data management (RDM) pilot project at Imperial College London. It describes how £100k in funding was provided for six academic projects to develop exemplars of best practices in RDM. The funded projects developed various tools and frameworks to improve data curation, sharing, and citation. Overall, the pilot demonstrated that innovative RDM is possible but also difficult and expensive to develop sustainably. It helped establish an initial RDM community at Imperial.
This document discusses file systems for cloud computing. It begins by providing context on the growth of the internet and cloud computing. It then defines what cloud computing and files are. The main points are:
- Distributed file systems provide access to data stored on servers using file system interfaces like opening, reading and writing files.
- HDFS is a popular distributed file system designed for large data sets stored on commodity hardware. It uses replication for reliability and has a single metadata node for coordination.
- HDFS is optimized for large streaming reads and writes. It partitions files into blocks and replicates them across multiple data nodes for reliability and load balancing.
Tutorial on Text Mining and Internet Content Filtering. 13th European Conference on Machine Learning (ECML\'02) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD\'02), Helsinki, Finland, 19-23 August 2002.
The document introduces the topic of data science and the programming language R. It defines data science and provides examples of using data science for social good. Additionally, it outlines some of the main features and pros and cons of using R for data science applications and statistical analysis.
II-PIC 2017: Artificial Intelligence, Machine Learning, And Deep Neural Netwo...Dr. Haxel Consult
Parthiban Srinivasan (VINGYANI, India)
When new technologies become easier to use, they transform industries. That's what's happening with artificial intelligence (AI) and big data. Machine learning is often described as a type of AI where computers learn to do something without being programmed to do it. Deep learning, a subset of machine learning, is proving to work especially well on classification. Big breakthroughs happen when what is suddenly possible meets what is desperately needed. For years, patent analysts have been searching and reviewing terabytes of information, not only patents but also non-patent information. Not only to find prior art but also to identify patents of interest, rate their quality, assess the potential value of patent clusters, and identify potential business partners or infringers. With the rapid increase in the number of patent documents worldwide, demand for their automatic clustering/categorization has grown significantly. Many information science researchers have started to experiment with machine learning tools, but the adoption in the patent information space has been sporadic. In this talk, we aim to review the prevailing machine learning techniques and present several sample implementations by various research groups. We will also discuss how data science compares with machine learning, deep learning, AI, statistics and applied mathematics.
Green Shoots:Research Data Management Pilot at Imperial College LondonTorsten Reimer
The document summarizes the results of a research data management (RDM) pilot project at Imperial College London. It describes how £100k in funding was provided for six academic projects to develop exemplars of best practices in RDM. The funded projects developed various tools and frameworks to improve data curation, sharing, and citation. Overall, the pilot demonstrated that innovative RDM is possible but also difficult and expensive to develop sustainably. It helped establish an initial RDM community at Imperial.
This document outlines a project between the Odum Institute and IQSS Dataverse team to integrate the Dataverse data repository system with iRODS, an open source data management system. The goals are to expand storage options for Dataverse, integrate curation workflows, and connect Dataverse to national research data infrastructure. A prototype will be developed to enable automated ingest of data from Dataverse to iRODS using rules and APIs. Challenges include migrating both systems to newer versions while maintaining authentication between them. An initial prototype is expected in August 2015.
The document discusses Maastricht UMC+'s goal of creating a central research data infrastructure for clinical and non-clinical data using iRODS. The data will use HL7 and ISA metadata standards enriched with ontologies to make the data findable, accessible, interoperable, and reusable. Workflows will pseudonymize personal data to ensure compliance with privacy laws. The infrastructure will have a development environment in Docker and partnerships with other Dutch organizations focused on FAIR data standards.
The document describes the design and implementation of a new high performance data transport protocol called UDT. UDT is implemented at the application layer over UDP to provide reliable, high-speed data transfer capabilities. It includes a new congestion control algorithm based on AIMD with decreasing increases that aims for efficiency, fairness and friendliness. Experimental results show UDT achieves high throughput and good fairness compared to TCP. The document also introduces a configurable framework called Composable UDT that allows new congestion control algorithms to be easily implemented and evaluated.
The document summarizes an Open Data Science Conference and iRODS User Group meeting. It discusses technologies like Julia, Stan, Scikit-learn, Apache Spark, Apache Hadoop, and Apache Hive that were presented. It provides information on keynote speakers and their affiliated companies. The document also lists topics for training workshops and good talks available online. Finally, it summarizes questions asked about iRODS and provides information on implementing data policy rules.
This document provides a cheat sheet overview of key concepts in the IRODS rule language, including numeric and string literals, arithmetic and comparison operators, functions for strings, lists, tuples, if/else statements, foreach loops, defining functions and rules, handling errors, and inductive data types. It describes syntax for defining data types using constructors, and using pattern matching to define functions over data types.
Numerous scientific teams use the HDF5 format to store very large datasets. Efficient use of this data in a distributed environment depends on client applications being able to read any subset of the data without transferring the entire file to the local machine. The goal of the HDF5-iRODS Project was to develop an HDF5-iRODS module for the iRODS datagrid server that supported this capability, and to apply the technology to an NCSA/SDSC Strategic Applications Program (SAP) project, FLASH.
A joint team from The HDF Group (representing NCSA) and the SDSC SRB group collaborated to accomplish the project goal. The team implemented five HDF5 microservices functions on the iRODS server, and developed an iRODS FLASH slice client application. The client implementation also includes a JNI interface that allows HDFView, a standard tool for browsing HDF5 files, to access HDF5 files stored remotely in iRODS. Finally, three new collection client/server calls were added to the iRODS APIs, making it easier for users to query the content of an iRODS collection.
This document discusses accessing Earth observation data through the OGC Web Coverage Service (WCS) 2.0 with an Earth Observation Application Profile (EO AP). It describes how the WCS EO AP maps Earth observation terminology to the WCS model, outlines the implementation of the WCS EO AP including supported data formats and products, and discusses future work such as adding more data support and integrating with other OGC services.
iRODS is an open source data management software developed by DICE at UNC and UCSD as a follow-on to SRB. It provides a customizable, policy-driven framework for implementing data grids and managing data across heterogeneous storage resources. Key features include modularity, extensibility through microservices and rules, and interoperability with systems like HDF5, NetCDF, and storage systems through integration extensions. RENCI provides support and commercial offerings around iRODS through their E-iRODS distribution.
The document discusses the private cloud architecture being implemented at the University of the Witwatersrand. It outlines plans to build a private cloud infrastructure using open source technologies like OpenStack, Fedora, iRODS and Zimbra. The cloud will provide scalable compute and storage resources along with hosted services and a digital archive. Key steps are identifying support staff, collaborating with technology partners, and having the initial infrastructure in place by mid-November.
The document discusses file management and various utilities used for organizing, viewing, and maintaining files and the operating system. It describes the hierarchical structure of directories, drives, folders and subfolders used to organize files. It also discusses naming conventions for files including allowed/prohibited characters and filename extensions. Various utility programs are covered like disk cleanup and defragmenter for system maintenance, and display utilities for customizing desktop settings.
White Paper: Life Sciences at RENCI, Big Data IT to Manage, Decipher and Info...EMC
This white paper explains how the Renaissance Computing Institute (RENCI) of the University of North Carolina uses EMC Isilon scale-out NAS storage, Intel processor and system technology, and iRODS-based data management to tackle Big Data processing, Hadoop-based analytics, security and privacy challenges in research and clinical genomics.
The document discusses how operating systems manage files and memory allocation. It explains that from the computer's perspective, there are no actual files, only blocks of allocated and unallocated memory. The file manager in the operating system creates the illusion of files and folders by tracking memory locations and implementing file allocation policies. Files can be stored contiguously, non-contiguously, or through indexed allocation with pointers. Access controls determine which users can access which files.
The document discusses big data and how it is being generated from various sources like social media, sensors, and mobile devices. It describes the key characteristics of big data known as the three V's - volume, velocity and variety. It then explains how Hadoop uses HDFS for storage and MapReduce for processing large datasets in parallel across clusters of computers. The conclusion states that big data presents both opportunities and challenges for industries in creating value from large and diverse datasets.
Big data refers to large and complex datasets that are difficult to process using traditional database tools. It is data in the terabytes or petabytes range generated by enterprises, the web, social media, and more. Hadoop was designed to process big data across large clusters of commodity servers in a distributed, reliable, and scalable way. It allows companies like Yahoo, AOL, and Facebook to gain insights from massive user data and improve services.
The document discusses how empowering transformational science through open data access, optimized data formats, and open-source tools. It argues that traditional methods of accessing large datasets can be inefficient, with 80% of time spent on data preparation and only 10% on analysis. New approaches using analytics optimized data stores (AODS) like Zarr, and tools like Xarray and Dask, allow accessing large datasets with a single line of code and performing analyses within minutes by leveraging lazy loading and parallel computing. This represents a paradigm shift from traditional project timelines that can reduce barriers to science and increase reproducibility, empowering more researchers to efficiently analyze data and focus on scientific questions.
For the past several decades the rising tide of technology -- especially the increasing speed of single processors -- has allowed the same data analysis code to run faster and on bigger data sets. That happy era is ending. The size of data sets is increasing much more rapidly than the speed of single cores, of I/O, and of RAM. To deal with this, we need software that can use multiple cores, multiple hard drives, and multiple computers.
That is, we need scalable data analysis software. It needs to scale from small data sets to huge ones, from using one core and one hard drive on one computer to using many cores and many hard drives on many computers, and from using local hardware to using remote clouds.
R is the ideal platform for scalable data analysis software. It is easy to add new functionality in the R environment, and easy to integrate it into existing functionality. R is also powerful, flexible and forgiving.
I will discuss the approach to scalability we have taken at Revolution Analytics with our package RevoScaleR. A key part of this approach is to efficiently operate on "chunks" of data -- sets of rows of data for selected columns. I will discuss this approach from the point of view of:
- Storing data on disk
- Importing data from other sources
- Reading and writing of chunks of data
- Handling data in memory
- Using multiple cores on single computers
- Using multiple computers
- Automatically parallelizing "external memory" algorithms
The Dendro research data management platform: Applying ontologies to long-ter...João Rocha da Silva
It has been shown that data management should start as early as possible in the research workflow to minimize the risks of data loss. Given the large numbers of datasets produced every day, curators may be unable to describe them all, so researchers should take an active part in the process. However, since they are not data management experts, they must be provided with user-friendly but powerful tools to capture the context information necessary for others to interpret and reuse their datasets. In this paper, we present Dendro, a fully ontology-based collaborative platform for research data management. Its graph data model innovates in the sense that it allows domain-specific lightweight ontologies to be used in resource description, acting as a staging area for later deposit in long-term preservation solutions.
This document outlines a project between the Odum Institute and IQSS Dataverse team to integrate the Dataverse data repository system with iRODS, an open source data management system. The goals are to expand storage options for Dataverse, integrate curation workflows, and connect Dataverse to national research data infrastructure. A prototype will be developed to enable automated ingest of data from Dataverse to iRODS using rules and APIs. Challenges include migrating both systems to newer versions while maintaining authentication between them. An initial prototype is expected in August 2015.
The document discusses Maastricht UMC+'s goal of creating a central research data infrastructure for clinical and non-clinical data using iRODS. The data will use HL7 and ISA metadata standards enriched with ontologies to make the data findable, accessible, interoperable, and reusable. Workflows will pseudonymize personal data to ensure compliance with privacy laws. The infrastructure will have a development environment in Docker and partnerships with other Dutch organizations focused on FAIR data standards.
The document describes the design and implementation of a new high performance data transport protocol called UDT. UDT is implemented at the application layer over UDP to provide reliable, high-speed data transfer capabilities. It includes a new congestion control algorithm based on AIMD with decreasing increases that aims for efficiency, fairness and friendliness. Experimental results show UDT achieves high throughput and good fairness compared to TCP. The document also introduces a configurable framework called Composable UDT that allows new congestion control algorithms to be easily implemented and evaluated.
The document summarizes an Open Data Science Conference and iRODS User Group meeting. It discusses technologies like Julia, Stan, Scikit-learn, Apache Spark, Apache Hadoop, and Apache Hive that were presented. It provides information on keynote speakers and their affiliated companies. The document also lists topics for training workshops and good talks available online. Finally, it summarizes questions asked about iRODS and provides information on implementing data policy rules.
This document provides a cheat sheet overview of key concepts in the IRODS rule language, including numeric and string literals, arithmetic and comparison operators, functions for strings, lists, tuples, if/else statements, foreach loops, defining functions and rules, handling errors, and inductive data types. It describes syntax for defining data types using constructors, and using pattern matching to define functions over data types.
Numerous scientific teams use the HDF5 format to store very large datasets. Efficient use of this data in a distributed environment depends on client applications being able to read any subset of the data without transferring the entire file to the local machine. The goal of the HDF5-iRODS Project was to develop an HDF5-iRODS module for the iRODS datagrid server that supported this capability, and to apply the technology to an NCSA/SDSC Strategic Applications Program (SAP) project, FLASH.
A joint team from The HDF Group (representing NCSA) and the SDSC SRB group collaborated to accomplish the project goal. The team implemented five HDF5 microservices functions on the iRODS server, and developed an iRODS FLASH slice client application. The client implementation also includes a JNI interface that allows HDFView, a standard tool for browsing HDF5 files, to access HDF5 files stored remotely in iRODS. Finally, three new collection client/server calls were added to the iRODS APIs, making it easier for users to query the content of an iRODS collection.
This document discusses accessing Earth observation data through the OGC Web Coverage Service (WCS) 2.0 with an Earth Observation Application Profile (EO AP). It describes how the WCS EO AP maps Earth observation terminology to the WCS model, outlines the implementation of the WCS EO AP including supported data formats and products, and discusses future work such as adding more data support and integrating with other OGC services.
iRODS is an open source data management software developed by DICE at UNC and UCSD as a follow-on to SRB. It provides a customizable, policy-driven framework for implementing data grids and managing data across heterogeneous storage resources. Key features include modularity, extensibility through microservices and rules, and interoperability with systems like HDF5, NetCDF, and storage systems through integration extensions. RENCI provides support and commercial offerings around iRODS through their E-iRODS distribution.
The document discusses the private cloud architecture being implemented at the University of the Witwatersrand. It outlines plans to build a private cloud infrastructure using open source technologies like OpenStack, Fedora, iRODS and Zimbra. The cloud will provide scalable compute and storage resources along with hosted services and a digital archive. Key steps are identifying support staff, collaborating with technology partners, and having the initial infrastructure in place by mid-November.
The document discusses file management and various utilities used for organizing, viewing, and maintaining files and the operating system. It describes the hierarchical structure of directories, drives, folders and subfolders used to organize files. It also discusses naming conventions for files including allowed/prohibited characters and filename extensions. Various utility programs are covered like disk cleanup and defragmenter for system maintenance, and display utilities for customizing desktop settings.
White Paper: Life Sciences at RENCI, Big Data IT to Manage, Decipher and Info...EMC
This white paper explains how the Renaissance Computing Institute (RENCI) of the University of North Carolina uses EMC Isilon scale-out NAS storage, Intel processor and system technology, and iRODS-based data management to tackle Big Data processing, Hadoop-based analytics, security and privacy challenges in research and clinical genomics.
The document discusses how operating systems manage files and memory allocation. It explains that from the computer's perspective, there are no actual files, only blocks of allocated and unallocated memory. The file manager in the operating system creates the illusion of files and folders by tracking memory locations and implementing file allocation policies. Files can be stored contiguously, non-contiguously, or through indexed allocation with pointers. Access controls determine which users can access which files.
The document discusses big data and how it is being generated from various sources like social media, sensors, and mobile devices. It describes the key characteristics of big data known as the three V's - volume, velocity and variety. It then explains how Hadoop uses HDFS for storage and MapReduce for processing large datasets in parallel across clusters of computers. The conclusion states that big data presents both opportunities and challenges for industries in creating value from large and diverse datasets.
Big data refers to large and complex datasets that are difficult to process using traditional database tools. It is data in the terabytes or petabytes range generated by enterprises, the web, social media, and more. Hadoop was designed to process big data across large clusters of commodity servers in a distributed, reliable, and scalable way. It allows companies like Yahoo, AOL, and Facebook to gain insights from massive user data and improve services.
The document discusses how empowering transformational science through open data access, optimized data formats, and open-source tools. It argues that traditional methods of accessing large datasets can be inefficient, with 80% of time spent on data preparation and only 10% on analysis. New approaches using analytics optimized data stores (AODS) like Zarr, and tools like Xarray and Dask, allow accessing large datasets with a single line of code and performing analyses within minutes by leveraging lazy loading and parallel computing. This represents a paradigm shift from traditional project timelines that can reduce barriers to science and increase reproducibility, empowering more researchers to efficiently analyze data and focus on scientific questions.
For the past several decades the rising tide of technology -- especially the increasing speed of single processors -- has allowed the same data analysis code to run faster and on bigger data sets. That happy era is ending. The size of data sets is increasing much more rapidly than the speed of single cores, of I/O, and of RAM. To deal with this, we need software that can use multiple cores, multiple hard drives, and multiple computers.
That is, we need scalable data analysis software. It needs to scale from small data sets to huge ones, from using one core and one hard drive on one computer to using many cores and many hard drives on many computers, and from using local hardware to using remote clouds.
R is the ideal platform for scalable data analysis software. It is easy to add new functionality in the R environment, and easy to integrate it into existing functionality. R is also powerful, flexible and forgiving.
I will discuss the approach to scalability we have taken at Revolution Analytics with our package RevoScaleR. A key part of this approach is to efficiently operate on "chunks" of data -- sets of rows of data for selected columns. I will discuss this approach from the point of view of:
- Storing data on disk
- Importing data from other sources
- Reading and writing of chunks of data
- Handling data in memory
- Using multiple cores on single computers
- Using multiple computers
- Automatically parallelizing "external memory" algorithms
The Dendro research data management platform: Applying ontologies to long-ter...João Rocha da Silva
It has been shown that data management should start as early as possible in the research workflow to minimize the risks of data loss. Given the large numbers of datasets produced every day, curators may be unable to describe them all, so researchers should take an active part in the process. However, since they are not data management experts, they must be provided with user-friendly but powerful tools to capture the context information necessary for others to interpret and reuse their datasets. In this paper, we present Dendro, a fully ontology-based collaborative platform for research data management. Its graph data model innovates in the sense that it allows domain-specific lightweight ontologies to be used in resource description, acting as a staging area for later deposit in long-term preservation solutions.
This document provides an overview of digital libraries, including definitions, benefits, limitations, components, standards, and challenges. It defines a digital library as a collection of information stored and accessed electronically, extending the functions of a traditional library digitally. Benefits include improved access and searchability, easier information sharing and preservation. Emerging technologies discussed include metadata standards, XML, and protocols like OAI-PMH for metadata harvesting. Common digital library software includes DSpace, Greenstone, and EPrints. Challenges involve digitization, description, legal issues, presentation of heterogeneous resources, and economic sustainability.
This document provides an overview of digital libraries, including definitions, benefits, limitations, components, standards, and challenges. It defines a digital library as a collection of information stored and accessed electronically, extending the functions of a traditional library digitally. Benefits include improved access, information sharing, and preservation, while limitations include technological obsolescence and rights management. Key components discussed include digital objects, metadata, and tools like DSpace and Greenstone for developing digital libraries. Emerging standards around identifiers, encoding, and metadata are also summarized.
This document introduces big data by defining it as large, complex datasets that cannot be processed by traditional methods due to their size. It explains that big data comes from sources like online activity, social media, science, and IoT devices. Examples are given of the massive scales of data produced each day. The challenges of processing big data with traditional databases and software are illustrated through a fictional startup example. The document argues that new tools and approaches are needed to handle automatic scaling, replication, and fault tolerance. It presents Apache Hadoop and Spark as open-source big data tools that can process petabytes of data across thousands of nodes through distributed and scalable architectures.
Hopsworks in the cloud Berlin Buzzwords 2019 Jim Dowling
This talk, given at Berlin Buzzwords 2019, describes the recent progress in making Hopsworks a cloud-native platform, with HA data-center support added for HopsFS.
How to Radically Simplify Your Business Data ManagementClusterpoint
Relational databases were designed for tabular data storage model. It requires complex software: schemas, encoded data, inflexible relations, sophisticated indexes. Complexity of your IT systems increases over your database life-time many-fold. Your costs too. Yet, we have a solution for this.
Research Data (and Software) Management at Imperial: (Everything you need to ...Sarah Anna Stewart
A presentation on research data management tools, workflows and best practices at Imperial College London with a focus on software management. Presented at the 2017 session of the HPC Summer School (Dept. of Computing).
Presentations at the FIREworks Strategy Workshop September 11, 2008.
http://www.ict-fireworks.eu/events/fireweek-in-september/fireworks-strategy-workshop/programme.html
The document discusses scaling web data at low cost. It begins by presenting Javier D. Fernández and providing context about his work in semantic web, open data, big data management, and databases. It then discusses techniques for compressing and querying large RDF datasets at low cost using binary RDF formats like HDT. Examples of applications using these techniques include compressing and sharing datasets, fast SPARQL querying, and embedding systems. It also discusses efforts to enable web-scale querying through projects like LOD-a-lot that integrate billions of triples for federated querying.
Research and technology explosion in scale-out storageJeff Spencer
A view of the directions storage is taking in science & technology from Ryan Sayre, technical strategist in the office of the CTO for EMC Isilon, using examples from recent work in life science genomics and other industries taking advantage of the combination of extreme computing (HPC) and big data. As presented at the Bull sponsored Science & Innovation 2013 conference Westminster.
Solving the Really Big Tech Problems with IoTEric Kavanagh
The Briefing Room with Dr. Robin Bloor and HPE Security
The Internet of Things brings new technological problems: sensor communications are bi-directional, the scale of data generation points has no precedent and, in this new world, security, privacy and data protection need to go out to the edge. Likely, most of that data lands in Hadoop and Big Data platforms. With the need for rapid analytics never greater, companies try to seize opportunities in tighter time windows. Yet, cyber-threats are at an all-time high, targeting the most valuable of assets—the data.
Register for this episode of The Briefing Room to hear Analyst Dr. Robin Bloor explain the implications of today's divergent data forces. He’ll be briefed by Reiner Kappenberger of HPE, who will discuss how a recent innovation -- NiFi -- is revolutionizing the big data ecosystem. He’ll explain how this technology dramatically simplifies data flow design, enabling a new era of business-driven analysis, while also protecting sensitive data.
Software Analytics: Data Analytics for Software EngineeringTao Xie
This document summarizes a presentation on software analytics and its achievements and opportunities. It begins by noting how both how software and how it is built and operated are changing, with data becoming more pervasive and development more distributed. It then defines software analytics as enabling analysis of software data to obtain insights and make informed decisions. It outlines research topics covering different areas of the software domain throughout the development cycle. It describes target audiences of software practitioners and outputs of insightful and actionable information. Selected projects demonstrating software analytics are then summarized, including StackMine for performance debugging at scale, XIAO for scalable code clone analysis, and others.
District 29-I July 2016 Lions newsletterMark Conrad
This document discusses District Governor Cindy Glass's message to Lions in District 29-I about International President Bob Corlew's theme of "New Mountains to Climb" for the upcoming Lions year. It highlights key points of the international theme, including continuing to lead through service, enhancing service to communities, and inducting new members. It also mentions efforts by Lions in District 29-I to assist with flood relief in West Virginia and recognizes Lion Wayne Worth for his dedication to flood victims.
The document provides an update from the District 29-I Lions governor. It discusses upcoming events in March, including club visits, the Lions Eyes Across WV event on March 19th, and the WV Lions State Convention from April 8-10. It also lists new club members, upcoming fundraisers and pancake breakfasts, and a story about the Lions motto "We Serve." The governor encourages clubs to work on membership and complete upcoming elections and reports.
The Lions Club of West Virginia conducted a vision screening for multiple age groups at an unspecified event location. They screened individuals ages 6 months to 18 years old using Pediavision or PlusOptix equipment and those 19 years and older using tonometry or visual acuity tests. The report provides the number screened and referred in each age group along with volunteer hours. Results are to be mailed or emailed to the Lions contact for reporting.
The document discusses the history and use of the Mobile Eye Screening Unit (MESU) by the West Virginia Lions Sight Conservation Foundation, noting that after over a decade of service screening eyes across West Virginia, the aging vehicle was sold so its components could continue aiding others through a religious organization; it also provides updates on vision screenings at events like the state fair organized by Lions clubs, and financial reports on sight and hearing expenses covered by the Foundation for those in need.
The document provides updates from District 29-I Lions Clubs. It discusses heavy snowfall from a winter storm, an upcoming leap year with an extra day, and goals to increase membership by June. Clubs are encouraged to invite new members and hold officer elections. Upcoming meetings and events are announced, including the District Governor election. Club activities like vision screenings and food donations are summarized. The District's representation at a leadership retreat is recognized.
January 2016 District 29-1 Lions NewsletterMark Conrad
The District Governor provided an update on his first half year visiting Lions clubs in the district. Membership numbers show a net loss of 7 members after gaining 90 new members but losing 97. The District Governor encourages clubs to focus on membership retention and growth. Clubs in the district have donated over $57,000 to various Lions causes through the Parade of Checks fundraiser. The District Governor reminds Lions to register for the upcoming West Virginia Lions Leadership Retreat at the end of the month.
The document is a newsletter from the District Governor of Lions Club District 29-I. It provides updates on club activities, upcoming events, and encourages clubs to focus on membership growth and retention. It highlights charitable works clubs will be doing over the holidays to help those in need. It also provides the District Governor's calendar of upcoming club visits and events.
The document announces the upcoming District 29-I Fall Conference in October and encourages Lions to attend. It provides details about the conference location, dates, registration fees, and activities. It notes that the keynote speaker will be International Director Ed Farrington and encourages Lions to "seize the moment" and be part of the conference fun and fellowship with other Lions.
Keyser Lions Club Newsletter March 2015Mark Conrad
This document summarizes upcoming events for the Keyser Lions Club in March and May 2015. It announces two special events on March 12th and 19th featuring speakers from the Lions Clubs of Mineral County and the district governor. It also provides information on the 93rd Annual West Virginia Lions State Convention from May 1-3, 2015 in Charleston including registration details.
Keyser Lions club newsletter January 2015Mark Conrad
The Keyser Lions Club held their Christmas dinner in December with good food and fun. At their January meeting, they will hear from a representative from the WV Department of Environmental Protection about recycling. Upcoming events include a zone meeting on January 27th and the WV Lions Leadership School from January 30th to February 1st. In March, the Keyser Lions Club will host an event to talk about the support Lions Clubs provide to local schools.
The District 29-I Lions newsletter provides updates on upcoming events and encourages clubs to focus on membership recruitment and retention, leadership development, and service projects. It highlights various reading programs supported by Lions clubs and invites donations for the Braille Challenge event in March. It also provides information on applying for sight and hearing assistance through the WV Lions Foundation and announces the Clarksburg Lions Club's 91st anniversary celebration in March.
The newsletter provides updates from District 29-I Governor Doug Long. It discusses the service work Lions clubs have been doing across the state, including feeding the hungry, providing vision care, and engaging youth. Governor Long's goals for the year include increasing membership and donations to LCIF, which so far exceed $56,000. Upcoming events highlighted include the West Virginia Lions Leadership School in January and the district conference in March.
Keyser, WV November 2014 Lions Club newsletterMark Conrad
The Keyser Lions Club held several events over the summer and fall of 2014. At their annual picnic in September, members enjoyed food and conversation. In October, guests spoke about mission work in Haiti and promoting nutrition education. Several members attended the District 29-I Annual Conference in October. Upcoming events included the November meetings and Christmas dinner. The newsletter provided club leadership and committee member details.
Lions District 29-I November 2014 newsletterMark Conrad
The newsletter discusses the recent successful District 29-I Fall Conference. It thanks the Lions who organized and attended the conference, highlights some of the events including speeches and presentations, and encourages clubs to continue their service efforts over the coming months. International Director John Pettis was a keynote speaker and several awards were presented at the conference banquet. The newsletter provides an update on upcoming district events and the district governor's club visit schedule.
WV Lions Leadership First timers District 29-I scholarship applicationMark Conrad
The document is a scholarship application for first-time attendees of the 2015 West Virginia Lions Leadership School being held from January 30 to February 1, 2015 at Days Hotel in Flatwoods, West Virginia. It requests the applicant's contact information and for them to write a brief statement about why they are interested in attending, any club offices they have held, and when they joined the Lions. A maximum of five scholarships will be awarded to cover registration and meals but not lodging.
This document is a registration form for the West Virginia Lions Leadership School taking place from January 30 to February 1, 2015 at the Days Hotel in Flatwoods, West Virginia. The registration fee is $135 if paid by January 15, 2015, or $115 if paid after that date. It requests contact information, club and district affiliation, dietary requirements, and payment details for attendees.
District 29-I Lions September newsletterMark Conrad
The document provides information about upcoming events and initiatives for Lions Club District 29-I. It includes the district governor's message encouraging clubs to focus on membership recruitment and participate in fall conference. It also lists the district governor's visitation calendar and provides details about the fall conference, including registration information and scheduled activities. Various club activities and service projects are highlighted, and upcoming district goals and initiatives related to membership growth and youth engagement are discussed.
Lions District 29-I 2014 conference flyerMark Conrad
Sign up now with Lion Sue Long at splong51@yahoo.com to play golf at the District 29I conference for a $46 fee, which includes a cart. Tee times will be determined later based on responses. Contact Lion Deb Abe at dabe@mris.com if donating a silent auction item, and remember to bring donations for door prizes and to reserve rooms by September 17th for the upcoming conference.
The District Governor provides an update on Lions activities in District 29-I. He discusses attending the International Convention in Toronto where he saw Lions from around the world strengthen their commitment to service. Membership in the district is down slightly from the previous year and he encourages clubs to address retention. The Governor also reminds Lions to schedule official visits early and attend the upcoming fall conference.
Keyser, WV Lions Club Newsletter 2014 AugustMark Conrad
The document provides information about upcoming meetings and events for the Keyser Lions Club. It summarizes meetings that were held in June and July 2014, including discussing results of a user satisfaction survey and touring food service facilities at Potomac State College. Upcoming events include an annual picnic in September and a district conference in October. Club members are asked to think about items to donate for a silent auction at the conference. The document also lists the club's officers and committee assignments for the 2014-2015 year.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.