Wearable Computing - Part I: What is Wearable Computing?Daniel Roggen
1) The document discusses a wearable computing assistant to help patients with Parkinson's disease who experience freezing of gait.
2) Freezing of gait is difficulty initiating walking, which causes many falls, and does not respond well to medication.
3) The wearable assistant aims to help patients by providing rhythmic cues through sensors on the body to help initiate walking.
This document discusses different types of sensors that can be used for wearable computing applications. It describes sensors for measuring physical context like location, activity, and environment as well as internal states like emotions and cognition. Both software sensors from data on devices and hardware sensors are covered. Specific sensor technologies discussed include accelerometers, gyroscopes, inertial measurement units, GPS, radio fingerprints, capacitive sensing, electrooculography, and skin conductance sensors. Examples are given of how sensor data can be fused and analyzed to infer higher level context and activities. Challenges of using sensors on the body are also addressed.
COMP 4026 Lecture 6 on Wearable Computing and methods for rapid prototyping for Google Glass. Taught by Mark Billinghurst from the University of South Australian on September 1st 2016.
Jessica Ross is a concept artist, 3D modeler, and texture artist from Texas A&M University with skills in Maya, Houdini, Unity, Unreal, painting, drawing, photography, and web design. She has a Master of Science in Visualization expected in May 2017 and a Bachelor of Science in Visualization from Texas A&M University, where she held graduate and teaching assistantships and received honors including the Sociedad Honoraria Hispanica Award.
Kendall Standifer is a web and graphic designer with over 7 years of experience. She graduated from The Art Institute of Washington with an Associates in Web Design & Interactive Media. Her experience includes developing WordPress and HTML websites for Mosaic, stylizing Abila's CMS using HTML and CSS, and maintaining websites and creating marketing materials for Joy of Dance. She specializes in HTML5, CSS, content management systems, and responsive design.
Enterprise-level Green ICT Using virtualization to balance energy economicsIJARIDEA Journal
Abstract— The computing industry has been a significant contributor to global warming ever since its
inception. Performance maximization per unit has cost remained the prime focus of academic and industrial
research alike, ignoring environmental impacts in the process if any. However, the infamous global energy
crisis has inevitably pushed power and energy management up the priority list of computing design and
management activities for purely economic reasons today. Green IT lays emphasis on including the
dimensions of environmental sustainability, the offsets of energy efficiency, and the total cost of
disposal and recycling. A green computing initiative must be adaptive and flexible enough to be
able to address problems that keep on increasing in size and complexity with time. Cloud computing concepts
can invariably be applied to reduce e-waste generation. The service oriented architecture lends itself to
incorporating green computing as a process rather than a product. Re-usability, extensibility and flexibility
are some of the key characteristics which are inherent to the cloud and directly help address the vertical
specific challenges to reducing energy consumption in the long run.
Keywords— Cloud computing, Electronic waste, Green Information Technology, Service oriented architecture.
Marc Daenen is a 57 year old Dutch national who has extensive experience in education and international cooperation. He received multiple masters degrees from the University of Amsterdam focusing on Dutch language and literature, theatre science, and communication sciences. He then served in the Dutch army for 2 years. Currently, he runs two companies focused on language training, art, and intercultural communication consulting. He has held various teaching and advisory roles in the Netherlands, Germany, Indonesia, and the United States over the past 30 years.
This document is a resume for Allison Clem, a graphic design student at Iowa State University expected to graduate in May 2015. It lists her education and graphic design experience including internships at Meredith Corporation and the Memorial Union at Iowa State University. It also outlines her honors and awards as well as involvement in campus organizations such as VEISHEA Executive Board and Kappa Kappa Gamma sorority.
Wearable Computing - Part I: What is Wearable Computing?Daniel Roggen
1) The document discusses a wearable computing assistant to help patients with Parkinson's disease who experience freezing of gait.
2) Freezing of gait is difficulty initiating walking, which causes many falls, and does not respond well to medication.
3) The wearable assistant aims to help patients by providing rhythmic cues through sensors on the body to help initiate walking.
This document discusses different types of sensors that can be used for wearable computing applications. It describes sensors for measuring physical context like location, activity, and environment as well as internal states like emotions and cognition. Both software sensors from data on devices and hardware sensors are covered. Specific sensor technologies discussed include accelerometers, gyroscopes, inertial measurement units, GPS, radio fingerprints, capacitive sensing, electrooculography, and skin conductance sensors. Examples are given of how sensor data can be fused and analyzed to infer higher level context and activities. Challenges of using sensors on the body are also addressed.
COMP 4026 Lecture 6 on Wearable Computing and methods for rapid prototyping for Google Glass. Taught by Mark Billinghurst from the University of South Australian on September 1st 2016.
Jessica Ross is a concept artist, 3D modeler, and texture artist from Texas A&M University with skills in Maya, Houdini, Unity, Unreal, painting, drawing, photography, and web design. She has a Master of Science in Visualization expected in May 2017 and a Bachelor of Science in Visualization from Texas A&M University, where she held graduate and teaching assistantships and received honors including the Sociedad Honoraria Hispanica Award.
Kendall Standifer is a web and graphic designer with over 7 years of experience. She graduated from The Art Institute of Washington with an Associates in Web Design & Interactive Media. Her experience includes developing WordPress and HTML websites for Mosaic, stylizing Abila's CMS using HTML and CSS, and maintaining websites and creating marketing materials for Joy of Dance. She specializes in HTML5, CSS, content management systems, and responsive design.
Enterprise-level Green ICT Using virtualization to balance energy economicsIJARIDEA Journal
Abstract— The computing industry has been a significant contributor to global warming ever since its
inception. Performance maximization per unit has cost remained the prime focus of academic and industrial
research alike, ignoring environmental impacts in the process if any. However, the infamous global energy
crisis has inevitably pushed power and energy management up the priority list of computing design and
management activities for purely economic reasons today. Green IT lays emphasis on including the
dimensions of environmental sustainability, the offsets of energy efficiency, and the total cost of
disposal and recycling. A green computing initiative must be adaptive and flexible enough to be
able to address problems that keep on increasing in size and complexity with time. Cloud computing concepts
can invariably be applied to reduce e-waste generation. The service oriented architecture lends itself to
incorporating green computing as a process rather than a product. Re-usability, extensibility and flexibility
are some of the key characteristics which are inherent to the cloud and directly help address the vertical
specific challenges to reducing energy consumption in the long run.
Keywords— Cloud computing, Electronic waste, Green Information Technology, Service oriented architecture.
Marc Daenen is a 57 year old Dutch national who has extensive experience in education and international cooperation. He received multiple masters degrees from the University of Amsterdam focusing on Dutch language and literature, theatre science, and communication sciences. He then served in the Dutch army for 2 years. Currently, he runs two companies focused on language training, art, and intercultural communication consulting. He has held various teaching and advisory roles in the Netherlands, Germany, Indonesia, and the United States over the past 30 years.
This document is a resume for Allison Clem, a graphic design student at Iowa State University expected to graduate in May 2015. It lists her education and graphic design experience including internships at Meredith Corporation and the Memorial Union at Iowa State University. It also outlines her honors and awards as well as involvement in campus organizations such as VEISHEA Executive Board and Kappa Kappa Gamma sorority.
This document provides information about an online Hadoop training course offered by MSR Trainings. The course covers all aspects of Hadoop including HDFS, MapReduce, Pig, Hive, Sqoop, Flume, Oozie, Impala, Hue and HBase. It also includes hands-on exercises for students to practice what they learn. The course aims to help students learn Hadoop from basic to advanced level concepts so they are prepared for jobs working with big data.
The document provides information about an online Hadoop training course offered by Rs Trainings. The course covers Hadoop and related technologies like HDFS, MapReduce, HBase, Pig, Hive, Sqoop and ZooKeeper. All instructors have real-world experience and can provide 24/7 technical support. The training includes placement assistance, mock interviews, resume building and status exams after each week. Flexible timings are available.
This document outlines the topics covered in a Cloudera Hadoop Developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. It also provides contact information for the training.
The document outlines the topics that will be covered in a Cloudera Hadoop Developer training course, including an introduction to big data and Hadoop, Hadoop concepts like HDFS and MapReduce, and real-life use cases. Attendees will learn about Hadoop ecosystems, writing and reading files from HDFS, and developing MapReduce applications. The training will also cover related tools like Pig, Hive, Oozie, and HBase. Contact information is provided for those interested in the course.
The document outlines the topics that will be covered in a Cloudera Hadoop Developer training course, including an introduction to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Attendees will learn about big data challenges, Hadoop technologies, MapReduce workflows, writing and reading HDFS files, and implementing MapReduce algorithms. Contact information is provided for those interested in the training.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Contact information is also provided for the training organization. Real-life use cases and concepts like HDFS, clusters, racks, and algorithms will be discussed alongside hands-on exercises like writing and reading from HDFS and solving problems using MapReduce flows and programming.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, real-life use cases, writing and reading files from HDFS, MapReduce workflows, and developing MapReduce applications. Contact information is also provided for the training organization.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Contact information is also provided for the training organization. Real-life use cases and concepts like HDFS, clusters, racks, and algorithms will be discussed alongside hands-on exercises like writing and reading from HDFS and solving problems using MapReduce.
This document outlines the objectives, content, and structure of a 28-30 hour training course on Hadoop and its ecosystem. The course will provide both theoretical and hands-on instruction on topics such as Hadoop architecture and components, HDFS, MapReduce, YARN, Hive, Pig, Sqoop, HBase, and Oozie. Participants will learn how to install Hadoop clusters, develop MapReduce programs, integrate Hadoop components, and apply best practices for Hadoop development, administration, and management. The goal is for attendees to gain the skills needed to architect Hadoop projects and leverage its ecosystem for data analysis and storage.
This document provides an overview of the objectives covered in a Hadoop certification training course. The course will introduce students to big data concepts and the Hadoop ecosystem. Students will learn about Hadoop features like MapReduce, Pig, Hive, Oozie, and HBASE. They will also learn real-life use cases and how to develop MapReduce applications.
This document outlines the topics covered in a Cloudera Hadoop Developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Real-life use cases and the history and architecture of Hadoop are also covered.
This document provides an overview of the course objectives for a training on big data and Hadoop. The course will cover introductory concepts of big data and Hadoop, components of the Hadoop ecosystem including MapReduce, Pig, Hive, Oozie, Flume, HBase, and Hue. It will teach how to set up Hadoop clusters and the Hadoop distributed file system. Students will learn how to develop MapReduce applications and use programming languages like Hive and Pig. The course will also cover using tools like Sqoop, common MapReduce algorithms, and data visualization with Tableau. Hands-on exercises are included to reinforce concepts taught.
The document discusses the topics covered in a Hadoop training course, including an introduction to big data and Hadoop, Hadoop concepts like MapReduce, HDFS, and YARN, and real-life use cases. Students will learn about Hadoop ecosystems, writing and reading files from HDFS, and developing MapReduce applications. The course aims to provide students with the skills needed to work with Hadoop and big data.
This document provides an overview of the objectives and topics covered in a Hadoop training and certification course. The course introduces students to big data concepts, the Hadoop ecosystem including HDFS, MapReduce, Pig, Hive, Oozie, and HBase. It covers real-life use cases and dives into key Hadoop technologies like clusters, workflows, and developing MapReduce applications. Contact information is provided to learn more about the course.
Hadoop is an open source framework that stores and processes large data sets across clusters of computers using simple programming models. It is written in Java and allows for the distributed processing of large data sets across clusters of computers using simple programming models. This document provides information on learning Hadoop and big data technologies from Eduonix, including an overview of Hadoop, popular job roles, salaries, course topics covered, requirements, and how to access the self-paced online video tutorials and materials. The course aims to help professionals master MapReduce and Hadoop fundamentals to address the growing need for big data skills.
This three-day course provides instructor-led classroom training in big data analytics using Hadoop. The course introduces students to Hadoop and how to leverage the Hadoop platform to analyze terabyte-scale data using tools like Pig, Hive, and Pentaho. No prerequisites are required, but knowledge of Java, programming languages, and databases is helpful. The course structure includes introductions to Hadoop fundamentals, MapReduce, HDFS, the Hadoop ecosystem, and hands-on exercises in setting up Hadoop clusters, running programs, and analyzing data with Pig, Hive and Pentaho. Students will learn about big data, Hadoop fundamentals, the Hadoop ecosystem, setting up Hadoop, running programs, analyzing
This 4-day training course provides participants with the skills needed to operate and maintain an Apache Hadoop cluster. The course covers topics such as hardware requirements, HDFS configuration, YARN and MapReduce, installing and configuring Hive and Pig, Hadoop security with Kerberos, and monitoring and troubleshooting clusters. It is intended for IT professionals interested in learning Cloudera administration or preparing for the Cloudera Certified Administrator for Apache Hadoop certification exam.
This document outlines a big data developer training course that covers Hadoop concepts including the Hadoop ecosystem, MapReduce, Pig, Hive, Oozie, HBase, and real-life use cases. The course introduces big data and Hadoop, explores Hadoop technologies like HDFS and MapReduce, teaches typical workflows for writing and reading files from HDFS, and helps develop MapReduce applications.
This document outlines the topics covered in a Hadoop certification training course, including introductions to big data, Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, real-life use cases, HDFS, cluster understanding, typical workflows, writing and reading files from HDFS, rack awareness, the MapReduce programming model, developing MapReduce applications, data types and file formats.
This big data developer training course covers concepts related to Hadoop, including an introduction to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig concepts, Hive concepts, Oozie workflow concepts, HBase concepts, and real-life use cases. The course also discusses the history of Hadoop, HDFS, statistics, understanding clusters, typical workflows, writing and reading files from HDFS, rack awareness, and developing MapReduce applications.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
This document provides information about an online Hadoop training course offered by MSR Trainings. The course covers all aspects of Hadoop including HDFS, MapReduce, Pig, Hive, Sqoop, Flume, Oozie, Impala, Hue and HBase. It also includes hands-on exercises for students to practice what they learn. The course aims to help students learn Hadoop from basic to advanced level concepts so they are prepared for jobs working with big data.
The document provides information about an online Hadoop training course offered by Rs Trainings. The course covers Hadoop and related technologies like HDFS, MapReduce, HBase, Pig, Hive, Sqoop and ZooKeeper. All instructors have real-world experience and can provide 24/7 technical support. The training includes placement assistance, mock interviews, resume building and status exams after each week. Flexible timings are available.
This document outlines the topics covered in a Cloudera Hadoop Developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. It also provides contact information for the training.
The document outlines the topics that will be covered in a Cloudera Hadoop Developer training course, including an introduction to big data and Hadoop, Hadoop concepts like HDFS and MapReduce, and real-life use cases. Attendees will learn about Hadoop ecosystems, writing and reading files from HDFS, and developing MapReduce applications. The training will also cover related tools like Pig, Hive, Oozie, and HBase. Contact information is provided for those interested in the course.
The document outlines the topics that will be covered in a Cloudera Hadoop Developer training course, including an introduction to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Attendees will learn about big data challenges, Hadoop technologies, MapReduce workflows, writing and reading HDFS files, and implementing MapReduce algorithms. Contact information is provided for those interested in the training.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Contact information is also provided for the training organization. Real-life use cases and concepts like HDFS, clusters, racks, and algorithms will be discussed alongside hands-on exercises like writing and reading from HDFS and solving problems using MapReduce flows and programming.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, real-life use cases, writing and reading files from HDFS, MapReduce workflows, and developing MapReduce applications. Contact information is also provided for the training organization.
This document outlines the topics covered in a Hadoop developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Contact information is also provided for the training organization. Real-life use cases and concepts like HDFS, clusters, racks, and algorithms will be discussed alongside hands-on exercises like writing and reading from HDFS and solving problems using MapReduce.
This document outlines the objectives, content, and structure of a 28-30 hour training course on Hadoop and its ecosystem. The course will provide both theoretical and hands-on instruction on topics such as Hadoop architecture and components, HDFS, MapReduce, YARN, Hive, Pig, Sqoop, HBase, and Oozie. Participants will learn how to install Hadoop clusters, develop MapReduce programs, integrate Hadoop components, and apply best practices for Hadoop development, administration, and management. The goal is for attendees to gain the skills needed to architect Hadoop projects and leverage its ecosystem for data analysis and storage.
This document provides an overview of the objectives covered in a Hadoop certification training course. The course will introduce students to big data concepts and the Hadoop ecosystem. Students will learn about Hadoop features like MapReduce, Pig, Hive, Oozie, and HBASE. They will also learn real-life use cases and how to develop MapReduce applications.
This document outlines the topics covered in a Cloudera Hadoop Developer training course, including introductions to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, use cases, and developing MapReduce applications. Real-life use cases and the history and architecture of Hadoop are also covered.
This document provides an overview of the course objectives for a training on big data and Hadoop. The course will cover introductory concepts of big data and Hadoop, components of the Hadoop ecosystem including MapReduce, Pig, Hive, Oozie, Flume, HBase, and Hue. It will teach how to set up Hadoop clusters and the Hadoop distributed file system. Students will learn how to develop MapReduce applications and use programming languages like Hive and Pig. The course will also cover using tools like Sqoop, common MapReduce algorithms, and data visualization with Tableau. Hands-on exercises are included to reinforce concepts taught.
The document discusses the topics covered in a Hadoop training course, including an introduction to big data and Hadoop, Hadoop concepts like MapReduce, HDFS, and YARN, and real-life use cases. Students will learn about Hadoop ecosystems, writing and reading files from HDFS, and developing MapReduce applications. The course aims to provide students with the skills needed to work with Hadoop and big data.
This document provides an overview of the objectives and topics covered in a Hadoop training and certification course. The course introduces students to big data concepts, the Hadoop ecosystem including HDFS, MapReduce, Pig, Hive, Oozie, and HBase. It covers real-life use cases and dives into key Hadoop technologies like clusters, workflows, and developing MapReduce applications. Contact information is provided to learn more about the course.
Hadoop is an open source framework that stores and processes large data sets across clusters of computers using simple programming models. It is written in Java and allows for the distributed processing of large data sets across clusters of computers using simple programming models. This document provides information on learning Hadoop and big data technologies from Eduonix, including an overview of Hadoop, popular job roles, salaries, course topics covered, requirements, and how to access the self-paced online video tutorials and materials. The course aims to help professionals master MapReduce and Hadoop fundamentals to address the growing need for big data skills.
This three-day course provides instructor-led classroom training in big data analytics using Hadoop. The course introduces students to Hadoop and how to leverage the Hadoop platform to analyze terabyte-scale data using tools like Pig, Hive, and Pentaho. No prerequisites are required, but knowledge of Java, programming languages, and databases is helpful. The course structure includes introductions to Hadoop fundamentals, MapReduce, HDFS, the Hadoop ecosystem, and hands-on exercises in setting up Hadoop clusters, running programs, and analyzing data with Pig, Hive and Pentaho. Students will learn about big data, Hadoop fundamentals, the Hadoop ecosystem, setting up Hadoop, running programs, analyzing
This 4-day training course provides participants with the skills needed to operate and maintain an Apache Hadoop cluster. The course covers topics such as hardware requirements, HDFS configuration, YARN and MapReduce, installing and configuring Hive and Pig, Hadoop security with Kerberos, and monitoring and troubleshooting clusters. It is intended for IT professionals interested in learning Cloudera administration or preparing for the Cloudera Certified Administrator for Apache Hadoop certification exam.
This document outlines a big data developer training course that covers Hadoop concepts including the Hadoop ecosystem, MapReduce, Pig, Hive, Oozie, HBase, and real-life use cases. The course introduces big data and Hadoop, explores Hadoop technologies like HDFS and MapReduce, teaches typical workflows for writing and reading files from HDFS, and helps develop MapReduce applications.
This document outlines the topics covered in a Hadoop certification training course, including introductions to big data, Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig, Hive, Oozie, HBase, real-life use cases, HDFS, cluster understanding, typical workflows, writing and reading files from HDFS, rack awareness, the MapReduce programming model, developing MapReduce applications, data types and file formats.
This big data developer training course covers concepts related to Hadoop, including an introduction to big data and Hadoop, the Hadoop ecosystem, MapReduce concepts, Pig concepts, Hive concepts, Oozie workflow concepts, HBase concepts, and real-life use cases. The course also discusses the history of Hadoop, HDFS, statistics, understanding clusters, typical workflows, writing and reading files from HDFS, rack awareness, and developing MapReduce applications.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
1. Hadoop Online & Classroom Training
Course Name : Hadoop 24*7 Technical Support
Duration : 35 hours
sun trainings is a best hadoop online training institute in hyderabad . We are
providing good online training on Hadoop.
Highlights in our training:
* Very in depth course material with real time scenarios.
* We are providing class with highly qualified trainer.
* We will provide class and demo session at student flexible timings.
* In training case studies and real time scenarios covered.
* We will give 24*7 technical supports.
* Each topic coverage with real time solutions.
* We are providing normal track,weekend,fast track classes.
* We will give every recorded session for play later.
* We are giving placement support by multiple consultancies in INDIA, USA,
Australia, UK etc.
* We are providing certification oriented trainings with 100% pass guarantee.
* We will give full support while attending the interviews and contact me any time
after completion of the course.
HADOOP ADMINISTATION AND DEVELOPMENT
Course Objective Summary
During this course, you will learn:
• Introduction to Big Data and Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
2. • Pig concepts
• Hive concepts
• Oozie workflow concepts
• Flume Concepts
• Hue Concepts
• HBASE Concepts
• Real Life Use Cases
Course Name : Hadoop 24*7 Technical Support
Duration : 35 hours
Faculty : Realtime experience
sun trainings is a best hadoop online training institute in hyderabad . We are
providing good online training on Hadoop.
Highlights in our training:
* Very in depth course material with real time scenarios.
* We are providing class with highly qualified trainer.
* We will provide class and demo session at student flexible timings.
* In training case studies and real time scenarios covered.
* We will give 24*7 technical supports.
* Each topic coverage with real time solutions.
* We are providing normal track,weekend,fast track classes.
* We will give every recorded session for play later.
* We are giving placement support by multiple consultancies in INDIA, USA,
Australia, UK etc.
* We are providing certification oriented trainings with 100% pass guarantee.
* We will give full support while attending the interviews and contact me any time
after completion of the course.
HADOOP ADMINISTATION AND DEVELOPMENT
Course Objective Summary
During this course, you will learn:
• Introduction to Big Data and Hadoop
• Hadoop ecosystem - Concepts
• Hadoop Map-reduce concepts and features
• Developing the map-reduce Applications
• Pig concepts
3. • Hive concepts
• Oozie workflow concepts
• Flume Concepts
• Hue Concepts
• HBASE Concepts
• Real Life Use Cases
Virtual box/VM Ware
• Basics
• Installations
• Backups
• Snapshots
Linux
• Basics
• Installations • Commands
Hadoop
• Why Hadoop?
• Scaling
• Distributed Framework
• Hadoop v/s RDBMS
• Brief history of hadoop
Setup hadoop
• Pseudo mode
• Cluster mode
• Ipv6
• Ssh
• Installation of java, hadoop
• Configurations of hadoop
• Hadoop Processes ( NN, SNN, JT, DN, TT)
• Temporary directory
• UI
• Common errors when running hadoop cluster, solutions
HDFS- Hadoop distributed File System
4. • HDFS Design and Architecture
• HDFS Concepts
• Interacting HDFS using command line
• Interacting HDFS using Java APIs
• Dataflow
• Blocks
• Replica
Hadoop Processes
• Name node
• Secondary name node
• Job tracker
• Task tracker
• Data node
Map Reduce
• Developing Map Reduce Application
• Phases in Map Reduce Framework
• Map Reduce Input and Output Formats
• Advanced Concepts
• Sample Applications
• Combiner
Joining datasets in Mapreduce jobs
• Map-side join
• Reduce-Side join
Map reduce – customization
• Custom Input format class
• Hash Partitioner
• Custom Partitioner
• Sorting techniques
• Custom Output format class
Hadoop Programming Languages :-
I).HIVE
5. • Introduction
• Installation and Configuration
• Interacting HDFS using HIVE
• Map Reduce Programs through HIVE
• HIVE Commands
• Loading, Filtering, Grouping….
• Data types, Operators…..
• Joins, Groups….
• Sample programs in HIVE
II).PIG
• Basics
• Installation and Configurations
• Commands….
OVERVIEW HADOOP DEVELOPER
Introduction
The Motivation for Hadoop
• Problems with traditional large-scale systems
• Requirements for a new approach
Hadoop: Basic Concepts
• Map-side join
• Reduce-Side join
Introduction
• An Overview of Hadoop
• The Hadoop Distributed File System
• Hands-On Exercise
• How MapReduce Works
• Hands-On Exercise
• Anatomy of a Hadoop Cluster
• Other Hadoop Ecosystem Components
Writing a MapReduce Program
6. • The MapReduce Flow
• Examining a Sample MapReduce Program
• Basic MapReduce API Concepts
• The Driver Code
• The Mapper
• The Reducer
• Hadoop’s Streaming API
• Using Eclipse for Rapid Development
• Hands-on exercise
• The New MapReduce API
Common MapReduce Algorithms
• Sorting and Searching
• Indexing
• Machine Learning With Mahout
• Term Frequency – Inverse Document Frequency
• Word Co-Occurrence
• Hands-On Exercise.
PIG Concepts..
• Data loading in PIG.
• Data Extraction in PIG.
• Data Transformation in PIG.
• Hands on exercise on PIG.
Hive Concepts.
• Hive Query Language.
• Alter and Delete in Hive.
• Partition in Hive.
• Indexing.
• Joins in Hive.Unions in hive.
• Industry specific configuration of hive parameters.
• Authentication & Authorization.
• Statistics with Hive.
• Archiving in Hive.
• Hands-on exercise
Working with Sqoop