Introduction to Redis Data Structures ScaleGrid.io
Bitmaps are a compact data structure in Redis that store boolean values to save memory space. They are useful for applications needing real-time analytics on large datasets like MOOCs. Bitmaps map boolean values to bits and support bitwise operations through commands like SETBIT, GETBIT, and BITCOUNT. While sets are easier to use for smaller datasets, bitmaps are better suited for domains with more than 232 bits due to their compact memory storage.
The document discusses the shifting landscape of business analytics and a roadmap for data warehouse modernization. It outlines challenges like traditional BI strategies no longer being sufficient and business taking over analytics. It then introduces the concept of bimodal IT, with Mode 1 focusing on reliability and Mode 2 on agility. The roadmap involves embracing self-service BI, using a cloud data platform like Google BigQuery, offering personal sandboxes, experimenting with citizen tools, building core datasets in the cloud, and migrating to a future data warehouse with a full data lake. The goal is providing a powerful environment combining personal sandboxes and core datasets.
Stad Lier: Transforming raw data into business infoGIM_nv
This document discusses how raw data can be transformed into business information. It describes the process of collecting, processing, and analyzing data from various sources to create structured information that can be reported and distributed. Various techniques and products are used, including BPMN for process modeling, FME for extract-transform-load tasks, PostgreSQL with PostGIS for the data warehouse, and QlikView for analytics and reporting. FME is highlighted as a powerful tool that can integrate different data types and sources, perform quality checks and enhancements, and distribute data to the appropriate systems and formats.
Topic: Streamlining BIM Workflow by Standardising Design Process
Speaker: Desmond Leung
Hong Kong Revit User Group
HKIBIM-CIC BIM Academic Papers Presentation and Showcase 2015
Date: 12-Dec-2015 (Sat)
Time: 1:30 p.m. to 4:30 p.m.
Venue: LT-02, IVE (Morrison Hill), 6 Oi Kwan Road. Wan Chai, Hong Kong
Organizer: The Hong Kong Institute of Building Information Modelling (HKIBIM)
Sponsor: Construction Industry Council (CIC)
Co-organizer:
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University (PolyU)
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology (HKUST)
Hong Kong Institute of Vocational Education (IVE)
Hong Kong Revit User Group (HKRUG)
Event Secretary:
Engineering Discipline In-service Training Office, Vocational Training Council (EDiTO)
This document proposes a software project for an online shopping application called Global Shopping. It will allow users to shop online, provide merchants a platform to market their products, and be developed using PHP and MySQL on Windows and Linux environments. The project scope is outlined, including security measures. Methodologies like feasibility studies, data flow diagrams, database design, hardware/software requirements, and a project schedule are presented to develop this online shopping application.
Targeted Marketing: How Marketing Companies can use Big Data to Target Custom...Ray Février
This presentation will show how an outdoor advertising company used the Oracle Big Data environment to provide real time statistics and high-value insights to their customers. Using data from providers such as Pinsight Media and Perconix data from Axciom, they are able to accurately show the demographics of the consumers in the viewshed of their billboards and other digital assets. With the need to get useful information out of the terabyte of data they were receiving, our client use Oracle BDCS, specifically, Hive to create external tables connecting to flat files or MongoDB and Impala to analyze the data. The data was then loaded into Oracle DBCS for to be accessed by OACS for further analysis and dashboarding.
NeoDash - Building Neo4j Dashboards In MinutesNeo4j
NeoDash is an open-source, low-code dashboard builder for Neo4j that allows users to build interactive dashboards with graphs, tables, charts and other visualizations using Cypher queries. It has over 500 active users across 50 countries. Dashboards created in NeoDash can be customized and published to predefined users. The presentation demonstrates how to use NeoDash to build dashboards from Neo4j data in minutes without extensive programming knowledge. Support options for NeoDash include training, extensions and help with installation from Neo4j professional services.
Introduction to Redis Data Structures ScaleGrid.io
Bitmaps are a compact data structure in Redis that store boolean values to save memory space. They are useful for applications needing real-time analytics on large datasets like MOOCs. Bitmaps map boolean values to bits and support bitwise operations through commands like SETBIT, GETBIT, and BITCOUNT. While sets are easier to use for smaller datasets, bitmaps are better suited for domains with more than 232 bits due to their compact memory storage.
The document discusses the shifting landscape of business analytics and a roadmap for data warehouse modernization. It outlines challenges like traditional BI strategies no longer being sufficient and business taking over analytics. It then introduces the concept of bimodal IT, with Mode 1 focusing on reliability and Mode 2 on agility. The roadmap involves embracing self-service BI, using a cloud data platform like Google BigQuery, offering personal sandboxes, experimenting with citizen tools, building core datasets in the cloud, and migrating to a future data warehouse with a full data lake. The goal is providing a powerful environment combining personal sandboxes and core datasets.
Stad Lier: Transforming raw data into business infoGIM_nv
This document discusses how raw data can be transformed into business information. It describes the process of collecting, processing, and analyzing data from various sources to create structured information that can be reported and distributed. Various techniques and products are used, including BPMN for process modeling, FME for extract-transform-load tasks, PostgreSQL with PostGIS for the data warehouse, and QlikView for analytics and reporting. FME is highlighted as a powerful tool that can integrate different data types and sources, perform quality checks and enhancements, and distribute data to the appropriate systems and formats.
Topic: Streamlining BIM Workflow by Standardising Design Process
Speaker: Desmond Leung
Hong Kong Revit User Group
HKIBIM-CIC BIM Academic Papers Presentation and Showcase 2015
Date: 12-Dec-2015 (Sat)
Time: 1:30 p.m. to 4:30 p.m.
Venue: LT-02, IVE (Morrison Hill), 6 Oi Kwan Road. Wan Chai, Hong Kong
Organizer: The Hong Kong Institute of Building Information Modelling (HKIBIM)
Sponsor: Construction Industry Council (CIC)
Co-organizer:
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University (PolyU)
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology (HKUST)
Hong Kong Institute of Vocational Education (IVE)
Hong Kong Revit User Group (HKRUG)
Event Secretary:
Engineering Discipline In-service Training Office, Vocational Training Council (EDiTO)
This document proposes a software project for an online shopping application called Global Shopping. It will allow users to shop online, provide merchants a platform to market their products, and be developed using PHP and MySQL on Windows and Linux environments. The project scope is outlined, including security measures. Methodologies like feasibility studies, data flow diagrams, database design, hardware/software requirements, and a project schedule are presented to develop this online shopping application.
Targeted Marketing: How Marketing Companies can use Big Data to Target Custom...Ray Février
This presentation will show how an outdoor advertising company used the Oracle Big Data environment to provide real time statistics and high-value insights to their customers. Using data from providers such as Pinsight Media and Perconix data from Axciom, they are able to accurately show the demographics of the consumers in the viewshed of their billboards and other digital assets. With the need to get useful information out of the terabyte of data they were receiving, our client use Oracle BDCS, specifically, Hive to create external tables connecting to flat files or MongoDB and Impala to analyze the data. The data was then loaded into Oracle DBCS for to be accessed by OACS for further analysis and dashboarding.
NeoDash - Building Neo4j Dashboards In MinutesNeo4j
NeoDash is an open-source, low-code dashboard builder for Neo4j that allows users to build interactive dashboards with graphs, tables, charts and other visualizations using Cypher queries. It has over 500 active users across 50 countries. Dashboards created in NeoDash can be customized and published to predefined users. The presentation demonstrates how to use NeoDash to build dashboards from Neo4j data in minutes without extensive programming knowledge. Support options for NeoDash include training, extensions and help with installation from Neo4j professional services.
This document discusses customer data platforms (CDPs), beginning with defining a CDP and describing its core components and functions. It then addresses various myths and realities about CDPs, noting that while they provide benefits like unified customer profiles and quick deployment, their value depends on use cases, data availability, and organizational support. Finally, it provides guidance on when and how to use a CDP effectively within a company's marketing technology stack.
The document discusses network management and the Internet standard framework. It describes the key components of the framework, including the Structure of Management Information (SMI) which defines management objects, the Management Information Base (MIB) which stores the managed objects, and the Simple Network Management Protocol (SNMP) used to communicate between managing and managed devices. The framework also includes security and administration capabilities added in SNMPv3.
Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.
This document provides an overview of the architecture of the Big Data Europe (BDE) Integrator platform. It discusses the goals of being open source, simple to use for big data, supporting various use cases, and integrating custom components. It describes the different user categories and the component lifecycle. It also provides information on developing Spark applications with Docker and BDE, the UI integrator application, using a reverse proxy, and links to code demos.
How to combine Db2 on Z, IBM Db2 Analytics Accelerator and IBM Machine Learni...Gustav Lundström
This document provides an overview and demonstration of combining Db2 on Z, IBM Db2 Analytics Accelerator, and IBM Machine Learning on z/OS for credit scoring applications. It discusses machine learning basics and the machine learning workflow. It then reviews how the Db2 Analytics Accelerator can be used for in-database analytics and machine learning. Finally, it demonstrates IBM Machine Learning for z/OS, including model creation, management, deployment, and continuous performance monitoring capabilities. A live demonstration of a credit scoring application that leverages these technologies is also provided.
iVEDiX is a leader in data architecture design and mobile business intelligence. It provides a platform called miVEDiX that allows for direct mobile access to enterprise data. The miVEDiX platform offers benefits such as being scalable, secure, fast to deploy, customizable, and providing ongoing technical support and improvements. It provides a flexible way for business users to access, analyze and share data across an organization through mobile devices.
The document provides an overview of creating visualizations using Microsoft Power BI. It outlines the key steps to import data into Power BI Desktop, clean and transform the data, and create different types of charts and visualizations. It also discusses deploying reports to Power BI Online and interacting with the reporting engine to ask questions about the data. The overall document serves as a hands-on activity guide to explore the basic features and functionalities of Power BI for data visualization.
About knowledge graph driven portal project for telco operators we built for Nokia (Siemens) Network a while ago. Reuploaded some older, but relevant stuff, since noticed this ser became hidden after LinkedIn took over SlideShare :-?
IMS on Mainframe host many Enterprise Critical assets, transactional and batch applications as well as data. Analytics solutions apply to both!
Contact me for more details
The document provides an overview of learning big data, including what big data is, the Hadoop ecosystem, common big data job roles and their salaries, skills needed, and steps for getting started. Big data refers to the large and complex data sets that are difficult to analyze using traditional systems. Hadoop is a framework for storing and processing big data, with components like HDFS for storage and MapReduce for processing. The document recommends learning Hadoop fundamentals, then building sample data pipelines using tools like Hive and Pig to start working with big data.
The document provides an overview of learning big data, including what big data is, the Hadoop ecosystem, common big data job roles and their salaries, skills needed, and steps for getting started. Big data refers to the large and complex data sets that are difficult to analyze using traditional systems. Hadoop is a framework for storing and processing big data, with components like HDFS for storage and MapReduce for processing. The document recommends learning Hadoop fundamentals, then building sample data pipelines using tools like Hive and Pig to start working with big data.
The document discusses big data and Hadoop. It notes that big data is characterized by volume, variety, velocity, and veracity. Hadoop is an open-source platform for distributed storage and processing of large datasets across clusters of commodity hardware. Hadoop consists of HDFS for storage and MapReduce as a programming model. Limitations of Hadoop 1.x include lack of horizontal scalability and high availability, while Hadoop 2.x addresses these with features like HDFS federation and YARN to support multiple workloads.
This resume is for Pavan Kumar B.N., who has over 4.5 years of experience in data warehousing and business intelligence systems. He currently works as a developer for Aviva UKGI, where he uses tools like Informatica and Teradata to develop ETL processes and manage data integration projects. Prior to this role, he worked at Tata Consultancy Services where he gained experience with technologies such as Guidewire, Oracle, and Informatica. He holds a Bachelor's degree in Computer Science and seeks a position that allows him to continue growing professionally.
Big data provides opportunities for businesses through increased efficiency, strategic direction, improved customer service, and new products and markets. However, challenges remain around capturing, storing, searching, sharing, analyzing, and visualizing large, diverse datasets. Issues include inconsistent or incomplete data, privacy concerns when data is outsourced, and verifying integrity of remotely stored information. Technologies like Hadoop facilitate distributed processing and storage at scale through components such as HDFS for storage and MapReduce for parallel processing.
DataDevOps: A Manifesto for a DevOps-like Culture Shift in Data & AnalyticsDr. Arif Wider
A talk given by Dr. Arif Wider (ThoughtWorks) and Sebastian Herold (Zalando) at OOP 2018 in Munich.
Abstract:
More and more companies migrate their monolithic applications to a microservices architecture. However, maintaining a consistent and usable data landscape has only become more challenging by this: huge amounts of structured and unstructured data, and hundreds of data sources.
Furthermore, data-driven product development multiplies the analytics requirements: every product team needs constantly updated and specially tailored metrics which often combine product specific data with company wide data.
Having a centralized data team does not scale in this setting as it becomes the bottleneck between data producers and data consumers.
We created a Manifesto of seven principles which break with traditional separation of roles and show a path how to deal with distributed data in a federal and scalable fashion. This leads to DataDev: a culture shift similar to DevOps in which application developers own their data and take over responsibilities for data & analytics.
Learn about our experiences and best practices with facilitating this cultural transformation at Scout24, the provider of Europe’s largest online markets for cars and real estate.
Big data refers to large volumes of diverse data that traditional data processing systems are unable to handle. Hadoop is an open-source software framework for distributed storage and processing of big data across clusters of commodity hardware. It allows for the reliable, scalable, and distributed processing of large data sets across clusters of commodity servers. Hadoop features include scalable and reliable data storage with HDFS and distributed processing of large data sets with MapReduce. Popular companies that use Hadoop include Google, Facebook, and Amazon for its abilities to process massive amounts of data in a cost-effective manner.
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords such as “big data,” “NoSQL,” “data scientist,” and so on. Few realize that any and all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, Data Modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important are the data models driving the engineering and architecture activities o
IRJET- Big Data-A Review Study with Comparitive Analysis of HadoopIRJET Journal
This document provides an overview of Hadoop and compares it to Spark. It discusses the key components of Hadoop including HDFS for storage, MapReduce for processing, and YARN for resource management. HDFS stores large datasets across clusters in a fault-tolerant manner. MapReduce allows parallel processing of large datasets using a map and reduce model. YARN was later added to improve resource management. The document also summarizes Spark, which can perform both batch and stream processing more efficiently than Hadoop for many workloads. A comparison of Hadoop and Spark highlights their different processing models.
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)eitps1506
Description:
Dive into the fascinating realm of solid-state physics with our meticulously crafted online PowerPoint presentation. This immersive educational resource offers a comprehensive exploration of the fundamental concepts, theories, and applications within the realm of solid-state physics.
From crystalline structures to semiconductor devices, this presentation delves into the intricate principles governing the behavior of solids, providing clear explanations and illustrative examples to enhance understanding. Whether you're a student delving into the subject for the first time or a seasoned researcher seeking to deepen your knowledge, our presentation offers valuable insights and in-depth analyses to cater to various levels of expertise.
Key topics covered include:
Crystal Structures: Unravel the mysteries of crystalline arrangements and their significance in determining material properties.
Band Theory: Explore the electronic band structure of solids and understand how it influences their conductive properties.
Semiconductor Physics: Delve into the behavior of semiconductors, including doping, carrier transport, and device applications.
Magnetic Properties: Investigate the magnetic behavior of solids, including ferromagnetism, antiferromagnetism, and ferrimagnetism.
Optical Properties: Examine the interaction of light with solids, including absorption, reflection, and transmission phenomena.
With visually engaging slides, informative content, and interactive elements, our online PowerPoint presentation serves as a valuable resource for students, educators, and enthusiasts alike, facilitating a deeper understanding of the captivating world of solid-state physics. Explore the intricacies of solid-state materials and unlock the secrets behind their remarkable properties with our comprehensive presentation.
Anti-Universe And Emergent Gravity and the Dark UniverseSérgio Sacani
Recent theoretical progress indicates that spacetime and gravity emerge together from the entanglement structure of an underlying microscopic theory. These ideas are best understood in Anti-de Sitter space, where they rely on the area law for entanglement entropy. The extension to de Sitter space requires taking into account the entropy and temperature associated with the cosmological horizon. Using insights from string theory, black hole physics and quantum information theory we argue that the positive dark energy leads to a thermal volume law contribution to the entropy that overtakes the area law precisely at the cosmological horizon. Due to the competition between area and volume law entanglement the microscopic de Sitter states do not thermalise at sub-Hubble scales: they exhibit memory effects in the form of an entropy displacement caused by matter. The emergent laws of gravity contain an additional ‘dark’ gravitational force describing the ‘elastic’ response due to the entropy displacement. We derive an estimate of the strength of this extra force in terms of the baryonic mass, Newton’s constant and the Hubble acceleration scale a0 = cH0, and provide evidence for the fact that this additional ‘dark gravity force’ explains the observed phenomena in galaxies and clusters currently attributed to dark matter.
This document discusses customer data platforms (CDPs), beginning with defining a CDP and describing its core components and functions. It then addresses various myths and realities about CDPs, noting that while they provide benefits like unified customer profiles and quick deployment, their value depends on use cases, data availability, and organizational support. Finally, it provides guidance on when and how to use a CDP effectively within a company's marketing technology stack.
The document discusses network management and the Internet standard framework. It describes the key components of the framework, including the Structure of Management Information (SMI) which defines management objects, the Management Information Base (MIB) which stores the managed objects, and the Simple Network Management Protocol (SNMP) used to communicate between managing and managed devices. The framework also includes security and administration capabilities added in SNMPv3.
Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.
This document provides an overview of the architecture of the Big Data Europe (BDE) Integrator platform. It discusses the goals of being open source, simple to use for big data, supporting various use cases, and integrating custom components. It describes the different user categories and the component lifecycle. It also provides information on developing Spark applications with Docker and BDE, the UI integrator application, using a reverse proxy, and links to code demos.
How to combine Db2 on Z, IBM Db2 Analytics Accelerator and IBM Machine Learni...Gustav Lundström
This document provides an overview and demonstration of combining Db2 on Z, IBM Db2 Analytics Accelerator, and IBM Machine Learning on z/OS for credit scoring applications. It discusses machine learning basics and the machine learning workflow. It then reviews how the Db2 Analytics Accelerator can be used for in-database analytics and machine learning. Finally, it demonstrates IBM Machine Learning for z/OS, including model creation, management, deployment, and continuous performance monitoring capabilities. A live demonstration of a credit scoring application that leverages these technologies is also provided.
iVEDiX is a leader in data architecture design and mobile business intelligence. It provides a platform called miVEDiX that allows for direct mobile access to enterprise data. The miVEDiX platform offers benefits such as being scalable, secure, fast to deploy, customizable, and providing ongoing technical support and improvements. It provides a flexible way for business users to access, analyze and share data across an organization through mobile devices.
The document provides an overview of creating visualizations using Microsoft Power BI. It outlines the key steps to import data into Power BI Desktop, clean and transform the data, and create different types of charts and visualizations. It also discusses deploying reports to Power BI Online and interacting with the reporting engine to ask questions about the data. The overall document serves as a hands-on activity guide to explore the basic features and functionalities of Power BI for data visualization.
About knowledge graph driven portal project for telco operators we built for Nokia (Siemens) Network a while ago. Reuploaded some older, but relevant stuff, since noticed this ser became hidden after LinkedIn took over SlideShare :-?
IMS on Mainframe host many Enterprise Critical assets, transactional and batch applications as well as data. Analytics solutions apply to both!
Contact me for more details
The document provides an overview of learning big data, including what big data is, the Hadoop ecosystem, common big data job roles and their salaries, skills needed, and steps for getting started. Big data refers to the large and complex data sets that are difficult to analyze using traditional systems. Hadoop is a framework for storing and processing big data, with components like HDFS for storage and MapReduce for processing. The document recommends learning Hadoop fundamentals, then building sample data pipelines using tools like Hive and Pig to start working with big data.
The document provides an overview of learning big data, including what big data is, the Hadoop ecosystem, common big data job roles and their salaries, skills needed, and steps for getting started. Big data refers to the large and complex data sets that are difficult to analyze using traditional systems. Hadoop is a framework for storing and processing big data, with components like HDFS for storage and MapReduce for processing. The document recommends learning Hadoop fundamentals, then building sample data pipelines using tools like Hive and Pig to start working with big data.
The document discusses big data and Hadoop. It notes that big data is characterized by volume, variety, velocity, and veracity. Hadoop is an open-source platform for distributed storage and processing of large datasets across clusters of commodity hardware. Hadoop consists of HDFS for storage and MapReduce as a programming model. Limitations of Hadoop 1.x include lack of horizontal scalability and high availability, while Hadoop 2.x addresses these with features like HDFS federation and YARN to support multiple workloads.
This resume is for Pavan Kumar B.N., who has over 4.5 years of experience in data warehousing and business intelligence systems. He currently works as a developer for Aviva UKGI, where he uses tools like Informatica and Teradata to develop ETL processes and manage data integration projects. Prior to this role, he worked at Tata Consultancy Services where he gained experience with technologies such as Guidewire, Oracle, and Informatica. He holds a Bachelor's degree in Computer Science and seeks a position that allows him to continue growing professionally.
Big data provides opportunities for businesses through increased efficiency, strategic direction, improved customer service, and new products and markets. However, challenges remain around capturing, storing, searching, sharing, analyzing, and visualizing large, diverse datasets. Issues include inconsistent or incomplete data, privacy concerns when data is outsourced, and verifying integrity of remotely stored information. Technologies like Hadoop facilitate distributed processing and storage at scale through components such as HDFS for storage and MapReduce for parallel processing.
DataDevOps: A Manifesto for a DevOps-like Culture Shift in Data & AnalyticsDr. Arif Wider
A talk given by Dr. Arif Wider (ThoughtWorks) and Sebastian Herold (Zalando) at OOP 2018 in Munich.
Abstract:
More and more companies migrate their monolithic applications to a microservices architecture. However, maintaining a consistent and usable data landscape has only become more challenging by this: huge amounts of structured and unstructured data, and hundreds of data sources.
Furthermore, data-driven product development multiplies the analytics requirements: every product team needs constantly updated and specially tailored metrics which often combine product specific data with company wide data.
Having a centralized data team does not scale in this setting as it becomes the bottleneck between data producers and data consumers.
We created a Manifesto of seven principles which break with traditional separation of roles and show a path how to deal with distributed data in a federal and scalable fashion. This leads to DataDev: a culture shift similar to DevOps in which application developers own their data and take over responsibilities for data & analytics.
Learn about our experiences and best practices with facilitating this cultural transformation at Scout24, the provider of Europe’s largest online markets for cars and real estate.
Big data refers to large volumes of diverse data that traditional data processing systems are unable to handle. Hadoop is an open-source software framework for distributed storage and processing of big data across clusters of commodity hardware. It allows for the reliable, scalable, and distributed processing of large data sets across clusters of commodity servers. Hadoop features include scalable and reliable data storage with HDFS and distributed processing of large data sets with MapReduce. Popular companies that use Hadoop include Google, Facebook, and Amazon for its abilities to process massive amounts of data in a cost-effective manner.
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords such as “big data,” “NoSQL,” “data scientist,” and so on. Few realize that any and all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, Data Modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important are the data models driving the engineering and architecture activities o
IRJET- Big Data-A Review Study with Comparitive Analysis of HadoopIRJET Journal
This document provides an overview of Hadoop and compares it to Spark. It discusses the key components of Hadoop including HDFS for storage, MapReduce for processing, and YARN for resource management. HDFS stores large datasets across clusters in a fault-tolerant manner. MapReduce allows parallel processing of large datasets using a map and reduce model. YARN was later added to improve resource management. The document also summarizes Spark, which can perform both batch and stream processing more efficiently than Hadoop for many workloads. A comparison of Hadoop and Spark highlights their different processing models.
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)eitps1506
Description:
Dive into the fascinating realm of solid-state physics with our meticulously crafted online PowerPoint presentation. This immersive educational resource offers a comprehensive exploration of the fundamental concepts, theories, and applications within the realm of solid-state physics.
From crystalline structures to semiconductor devices, this presentation delves into the intricate principles governing the behavior of solids, providing clear explanations and illustrative examples to enhance understanding. Whether you're a student delving into the subject for the first time or a seasoned researcher seeking to deepen your knowledge, our presentation offers valuable insights and in-depth analyses to cater to various levels of expertise.
Key topics covered include:
Crystal Structures: Unravel the mysteries of crystalline arrangements and their significance in determining material properties.
Band Theory: Explore the electronic band structure of solids and understand how it influences their conductive properties.
Semiconductor Physics: Delve into the behavior of semiconductors, including doping, carrier transport, and device applications.
Magnetic Properties: Investigate the magnetic behavior of solids, including ferromagnetism, antiferromagnetism, and ferrimagnetism.
Optical Properties: Examine the interaction of light with solids, including absorption, reflection, and transmission phenomena.
With visually engaging slides, informative content, and interactive elements, our online PowerPoint presentation serves as a valuable resource for students, educators, and enthusiasts alike, facilitating a deeper understanding of the captivating world of solid-state physics. Explore the intricacies of solid-state materials and unlock the secrets behind their remarkable properties with our comprehensive presentation.
Anti-Universe And Emergent Gravity and the Dark UniverseSérgio Sacani
Recent theoretical progress indicates that spacetime and gravity emerge together from the entanglement structure of an underlying microscopic theory. These ideas are best understood in Anti-de Sitter space, where they rely on the area law for entanglement entropy. The extension to de Sitter space requires taking into account the entropy and temperature associated with the cosmological horizon. Using insights from string theory, black hole physics and quantum information theory we argue that the positive dark energy leads to a thermal volume law contribution to the entropy that overtakes the area law precisely at the cosmological horizon. Due to the competition between area and volume law entanglement the microscopic de Sitter states do not thermalise at sub-Hubble scales: they exhibit memory effects in the form of an entropy displacement caused by matter. The emergent laws of gravity contain an additional ‘dark’ gravitational force describing the ‘elastic’ response due to the entropy displacement. We derive an estimate of the strength of this extra force in terms of the baryonic mass, Newton’s constant and the Hubble acceleration scale a0 = cH0, and provide evidence for the fact that this additional ‘dark gravity force’ explains the observed phenomena in galaxies and clusters currently attributed to dark matter.
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdfSelcen Ozturkcan
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
PPT on Alternate Wetting and Drying presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...Sérgio Sacani
We present the JWST discovery of SN 2023adsy, a transient object located in a host galaxy JADES-GS
+
53.13485
−
27.82088
with a host spectroscopic redshift of
2.903
±
0.007
. The transient was identified in deep James Webb Space Telescope (JWST)/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Photometric and spectroscopic followup with NIRCam and NIRSpec, respectively, confirm the redshift and yield UV-NIR light-curve, NIR color, and spectroscopic information all consistent with a Type Ia classification. Despite its classification as a likely SN Ia, SN 2023adsy is both fairly red (
�
(
�
−
�
)
∼
0.9
) despite a host galaxy with low-extinction and has a high Ca II velocity (
19
,
000
±
2
,
000
km/s) compared to the general population of SNe Ia. While these characteristics are consistent with some Ca-rich SNe Ia, particularly SN 2016hnk, SN 2023adsy is intrinsically brighter than the low-
�
Ca-rich population. Although such an object is too red for any low-
�
cosmological sample, we apply a fiducial standardization approach to SN 2023adsy and find that the SN 2023adsy luminosity distance measurement is in excellent agreement (
≲
1
�
) with
Λ
CDM. Therefore unlike low-
�
Ca-rich SNe Ia, SN 2023adsy is standardizable and gives no indication that SN Ia standardized luminosities change significantly with redshift. A larger sample of distant SNe Ia is required to determine if SN Ia population characteristics at high-
�
truly diverge from their low-
�
counterparts, and to confirm that standardized luminosities nevertheless remain constant with redshift.
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Sérgio Sacani
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
6. 1. It is not rule based but maps prior knowledge as well as individual user knowledge
- DICOM header information
- PAR(/REC) header information
- P*.7 header information
- Nifti header information
- File system information
- Plugin
2. The gathered information is stored in a flexible and human readable yaml file, the bidsmap
3. You can easily edit the yaml file / bidsmap to your needs
4. BIDScoin tools run automatically and require no programming knowledge
BIDScoin
7. Workflow
Step 1: Run the bidsmapper
usage: bidsmapper.py [-h] [-t TEMPLATE] [-n SUBPREFIX] [-m SESPREFIX]
sourcefolder bidsfolder
Step 2: Run the bidseditor
usage: bidseditor.py [-h] [-s SOURCEFOLDER] [-b BIDSMAP] [-t TEMPLATE]
bidsfolder
Step 3: Run the bidscoiner
usage: bidscoiner.py [-h] [-p PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
[-f] [-s] [-b BIDSMAP] [-n SUBPREFIX] [-m SESPREFIX] [-v]
sourcefolder bidsfolder
10. An open-source python toolkit that converts ("coins") source-level (raw)
neuroimaging data-sets to the BIDS standard
The user does not need programming knowledge and can directly edit the mapping
with a GUI
Institutes can provide their users with a custom template already containing the
mappings for the scans that are typically performed in the institute
Tested over a broad spectrum of (DICOM) input data, including fieldmaps, mutli-
echo data, multi-coil data, PET scans and various kinds of anatomical, diffusion
and functional MRI scans.
BIDScoin