SC6 Workshop 1: Big Data Europe platform requirements and draft architecture:...BigData_Europe
Presentation by Martin Kaltenböck, Semantic Web Company, at the first workshop of Societal Challlenge 6 in the BigDataEurope project, taking place in Luxembourg on 18 November 2015.
http://www.big-data-europe.eu/social-sciences/
Space technology for mineral exploration on earthJustin Hayward
This document discusses using satellite technology for lithium exploration. It notes that lithium demand is expected to greatly increase due to electric vehicles, but there are an estimated 3.9 million metric tons of recoverable lithium. The document outlines using satellite data integration and analysis to generate prospectivity maps for lithium exploration, including analyzing geology, vegetation, faults, and environmental factors. It provides examples of satellite data that can be analyzed, such as vegetation anomalies, terrain models, and lithology. The overall goal is to use remote sensing techniques to map areas with higher probability of lithium occurrence to aid in exploration.
The document summarizes a workshop on big data technologies and applications held in Lyon on September 11, 2014. It discusses the evolution of big data technologies, analytics applications, emerging needs and trends, including the increasing importance of data interpretability and security concerns. Examples of industry applications like real-time prescriptive analytics for gas turbines are provided. The challenges of blending analytics with available computing and emerging needs like abstraction from underlying storage are also outlined.
The document discusses CSI Piemonte's smart data platform for analyzing big data from energy efficiency projects. It describes CSI Piemonte as a consortium that manages IT services for public administrations. The platform collects data from sensors in buildings and integrates static and real-time data to analyze energy consumption. It is being used in pilots that monitor energy usage in buildings and districts to identify opportunities for increased efficiency.
Vertrauen und Kollaboration – Erfolgsfaktoren für die Akzeptanz künftiger E-G...Arbeitskreis10
Vertrauen und Kollaboration discusses the importance of trust and collaboration for the acceptance of future e-government services. It argues that principles of open government like transparency and participation are key to involving citizens and businesses. Examples are given of projects that harness community input through brainstorming, discussion, and voting to improve patent processing, develop youth services, and give people a voice in politics. Trust and collaboration between government and those it serves are presented as critical success factors for digital public services.
What the Marine Environmental Data and Information Network (MEDIN) has been up to in order to improve access to marine data and promote the message of 'measure once, use many times'.
Geospatial intelligence satellite applications catapult pdf - july 23 2019Peter Bloomfield
The document provides an introduction to geospatial intelligence and Earth observation applications from the Satellite Applications Catapult. It discusses the growing market opportunity in Earth observation, examples of application areas like agriculture, urban planning, and infrastructure monitoring, and technologies like satellite sensors, change detection over time, and interferometric synthetic aperture radar. It emphasizes the potential of applying AI/ML to extract information from Earth observation data and highlights reasons to invest in developing related applications.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
SC6 Workshop 1: Big Data Europe platform requirements and draft architecture:...BigData_Europe
Presentation by Martin Kaltenböck, Semantic Web Company, at the first workshop of Societal Challlenge 6 in the BigDataEurope project, taking place in Luxembourg on 18 November 2015.
http://www.big-data-europe.eu/social-sciences/
Space technology for mineral exploration on earthJustin Hayward
This document discusses using satellite technology for lithium exploration. It notes that lithium demand is expected to greatly increase due to electric vehicles, but there are an estimated 3.9 million metric tons of recoverable lithium. The document outlines using satellite data integration and analysis to generate prospectivity maps for lithium exploration, including analyzing geology, vegetation, faults, and environmental factors. It provides examples of satellite data that can be analyzed, such as vegetation anomalies, terrain models, and lithology. The overall goal is to use remote sensing techniques to map areas with higher probability of lithium occurrence to aid in exploration.
The document summarizes a workshop on big data technologies and applications held in Lyon on September 11, 2014. It discusses the evolution of big data technologies, analytics applications, emerging needs and trends, including the increasing importance of data interpretability and security concerns. Examples of industry applications like real-time prescriptive analytics for gas turbines are provided. The challenges of blending analytics with available computing and emerging needs like abstraction from underlying storage are also outlined.
The document discusses CSI Piemonte's smart data platform for analyzing big data from energy efficiency projects. It describes CSI Piemonte as a consortium that manages IT services for public administrations. The platform collects data from sensors in buildings and integrates static and real-time data to analyze energy consumption. It is being used in pilots that monitor energy usage in buildings and districts to identify opportunities for increased efficiency.
Vertrauen und Kollaboration – Erfolgsfaktoren für die Akzeptanz künftiger E-G...Arbeitskreis10
Vertrauen und Kollaboration discusses the importance of trust and collaboration for the acceptance of future e-government services. It argues that principles of open government like transparency and participation are key to involving citizens and businesses. Examples are given of projects that harness community input through brainstorming, discussion, and voting to improve patent processing, develop youth services, and give people a voice in politics. Trust and collaboration between government and those it serves are presented as critical success factors for digital public services.
What the Marine Environmental Data and Information Network (MEDIN) has been up to in order to improve access to marine data and promote the message of 'measure once, use many times'.
Geospatial intelligence satellite applications catapult pdf - july 23 2019Peter Bloomfield
The document provides an introduction to geospatial intelligence and Earth observation applications from the Satellite Applications Catapult. It discusses the growing market opportunity in Earth observation, examples of application areas like agriculture, urban planning, and infrastructure monitoring, and technologies like satellite sensors, change detection over time, and interferometric synthetic aperture radar. It emphasizes the potential of applying AI/ML to extract information from Earth observation data and highlights reasons to invest in developing related applications.
4 Ways Artificial Intelligence Can Help Save the PlanetTyrone Systems
As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
The document discusses how big data and digital transformation can help address climate change challenges through the energy sector. It provides examples of digital use cases for power generation, transmission and distribution networks, retailers and aggregators, consumers and prosumers, and new market platforms. These use cases leverage technologies like predictive analytics, asset intelligence networks, demand response programs, and real-time energy visibility to improve grid reliability and efficiency, increase renewable energy integration, empower customers, and reduce costs.
Estimating the Impact of Agriculture on the Environment of Catalunya by means...Andreas Kamilaris
Because of insufficient accessible arable land, intensive farming has been linked to excessive accumulation of phosphorous, heavy metals, and other soil contaminants, as well as to significant groundwater pollution with nitrate. Deterioration of soil water quality is especially worrying at the bioclimatic Mediterranean area, especially under the current context of climate change. Hence, it is necessary to develop a common body of knowledge, shared at the local and regional levels of the countries involved and affected, so as to allow an effective monitoring of cropping systems, fertilization and water demands, and impacts of climate change, with a focus on the sustainability and the protection of the physical environment.
In this presentation, we describe AgriBigCAT, an online software platform that combines geophysical information from various diverse sources, together with big data analysis, in order to estimate the impact of the agricultural sector on the environment, considering land, water, biodiversity and natural areas requiring protection, such as forests and wetlands. Based on the P-Sphere project, this platform intends to promote more sustainable agriculture, by designing and developing an information and knowledge-based platform, using a big data approach for managing and analyzing a wide range of geospatial and mainstream information, which can be accessible by standard communication technologies such as the internet/web and mobile apps. this platform can also assist both the farmers' decision-taking processes and the administration planning and policy making, with the ultimate objective of meeting the challenge of increasing food production at a lower environmental impact.
The document summarizes Switzerland's national spatial data infrastructure (SDI) called geo.admin.ch, which is operated by swisstopo, the Federal Office of Topography. Some key points:
- Geo.admin.ch provides easy and rapid access to Switzerland's authoritative geodata through web services, maps, and APIs in compliance with the Federal Act on Geoinformation.
- It serves over 10,000 daily users and peaks at over 35,000, delivering over 1,300 map tiles per second.
- The SDI utilizes cloud computing, open standards, open source software and open APIs to boost innovation and generate value-added services while ensuring scalability and reasonable costs.
Solving advanced research problems with real time open data from satellites a...Wolfgang Ksoll
The project NextGEOSS brings wit its data hub based on CKAN and its 10 pilot programs a new quality in the usage of earth observation open data from satellites and in situ.
The document discusses challenges around data management and analytics for smart grids with distributed generation. It notes that smart grids are aimed at improving grid resilience, facilitating new energy markets, and better integrating renewable energy. However, a lack of unified data models presents a challenge for analyzing the large volumes of diverse data from smart meters, weather sensors, and other sources. The author proposes collaborating with Big Data Europe to define use cases around technical grid management and market forecasting that leverage big data analytics to help decarbonize energy systems with high renewable penetration.
The NextGEOSS project, a European contribution to GEOSS (Global Earth Observation System of Systems), proposes to develop the next generation data hub for Earth Observations, where the users can connect to access data and deploy data-driven applications.
The document discusses empowering communities with big data technologies through lowering barriers to using big data. It describes the Big Data Europe consortium and platform, which consists of three layers - hardware, a resource manager, and big data applications. The platform packages big data components like HDFS, Spark, and Kafka in Docker containers to solve specific problems, and provides installation instructions and technical support contacts.
The project uses mathematical modeling to determine optimal locations for beehives to maximize pollination. A partnership between the University of Essex and Simul Systems Ltd aims to develop an app to help beekeepers improve productivity by analyzing maps and mathematical models of plant distributions. Funding from the UK Technology Strategy Board supported a prototype, with hopes of further development and commercialization.
Artificial intelligence and machine learning can help analyze large amounts of environmental data to better understand climate change and predict future impacts. AI is used to identify patterns in data from sensors monitoring conditions around the world. This data provides insights into vulnerabilities and helps predict extreme weather events. AI technologies can also optimize renewable energy production and design more energy efficient systems, buildings and consumer products to mitigate climate change. However, training AI models also contributes to carbon emissions which must be addressed.
Engaging earth observation in the platform economyterradue
This document discusses engaging earth observation data in the platform economy. It outlines three challenges: making data open, building on existing platforms through APIs, and exploiting network effects. The author describes their MELODIES project which developed a platform as a service for earth observation data. This allows rapid prototyping, seamless data access, and automated processing. Ongoing work involves furthering these outcomes and forming partnerships to ensure sustainability. The goal is to support open science, government, and commercial applications using earth observation data.
The document discusses BCeMAP, a web-based mapping application that provides a common operating picture for emergency responders in British Columbia. BCeMAP integrates data from various sources like weather alerts, earthquake data, wildfire information and more. It allows different agencies to share relevant information through open standards while maintaining control over their own data. The demo shows how BCeMAP authenticates users and aggregates dynamic data feeds to be viewed on an ArcGIS map for emergency response and management.
Mmea program - from sensors to services. Keynote from Dr. Tero Eklin CLEEN_Ltd
CLEEN's MMEA program organised an international seminar on cleaner air - Outdoor and indoor air quality together with Zhejiang University and assistant organizer Insigma group.
This is one of the keynote presentations in the seminar.
More info in www.mmea.fi
The cleantech field is expanding rapidly and Finnish companies are committed to working for a better environment in the fields of energy efficiency, air quality and monitoring. The world-class Cleantech know-how from Finland and the cooperation with Chinese partners and the results were highlighted in the MMEA seminar. Some of the leading Finnish cleantech companies together with Finnish and Chinese research institutions were present at the event. The seminars focused on cooperation between Finland and China concerning indoor and outdoor air quality and solutions to make them better.
The document summarizes a presentation about accelerating green energy development in China through smart grid technology and US-China cooperation. It discusses China's growing electricity needs and transition to renewable and nuclear energy. Smart grid applications could significantly reduce carbon emissions by improving efficiency, integrating renewable energy, and enabling electric vehicles. Joint US-China programs through non-profits like JUCCCE provide expertise and technologies to support China's green energy goals.
Global Atlas for Renewable Energy - application to MauritaniaIRENA Global Atlas
One of the key activities in IRENA is the development of renewable readiness assessments (RRAs). An RRA is a holistic assessment of conditions for renewable energy deployment in a country, and the actions necessary to further improve these conditions. An RRA is a rapid assessment of how a country can increase readiness and overcome the main barriers to the deployment of renewable energy technologies. It covers all services (transport, heat, electricity and motive power), and sources of renewable energy, with countries selecting those of relevance. The RRA comprises a process and a methodology that includes completing a set of templates and a final report. On the occasion of the RRA Mauritania, the Global Atlas was presented, as a potential supplier of data, data infrstructure and education for zoning renewable energy hotspots.
Upcoming Datasets: Global wind map, Jake Badger ( Risoe DTU)IRENA Global Atlas
Upcoming Datasets: Global wind map. A presentation by Jake Badger ( Risoe DTU) during the Global Atlas side event which held at the World Future Energy Summit in 2014
Chris Atherton (GEANT) and Andres Steijaert (OCRE) presentation about the Open Clouds for Research Environments (OCRE) project and GÉANT's National Research and Education Networks and their Infrastructure support for global Cloud Computing at the 4th GEO Data Technology Workshop.
Vienna, Austria
25th of April 2019
Lennart Landsberg, Research associate, Cologne University of Applied Sciences, Germany - Using Existing Data to Support Operational Emergency Response in Germany - Current Use Cases, Opportunities and Challenges
Raising the benefits of meteorological services and satellitesEUMETSAT
In this presentation, given at the WMO side event during the 2014 EUMETSAT Meteorological Satellite Conference in Geneva, Stephan Bojinski (Satellite Utilization and Products Division, Space Programme, WMO) demonstrates how the WMO assists in raising the benefits from meteorological services and satellites and discusses the challenges faced in the future.
The document describes an emergency response demonstration that uses semantic web technologies to help coordinate emergency services. The demonstration involves a cargo plane crashing in London, causing multiple fires. It shows how an emergency response system could help the Joint Emergency Services Control Centre make sense of the emergency, handle information requests, and make tactical decisions by integrating technologies like ontology mapping, image retrieval, and data management. The goal is to effectively acquire, analyze, and use information in real-time during an emergency response.
Kenneth McNamee discusses net zero energy airports and definitions. The document outlines steps to gather energy and water consumption data for airports categorized by passenger volume and climate region to benchmark performance. This identifies opportunities to improve building systems and understand that airports are large energy consumers. A path toward net zero energy airports is presented with examples from Europe of regulatory support for low carbon aviation.
It introduces and illustrates use cases, benefits and problems for Kerberos deployment on Hadoop; how Token support and TokenPreauth can help solve the problems. It also briefly introduces Haox project, a Java client library for Kerberos.
Real time big data analytical architecture for remote sensing applicationLeMeniz Infotech
Real time big data analytical architecture for remote sensing application
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Web : http://www.lemenizinfotech.com
Web : http://www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Blog : http://ieeeprojectspondicherry.weebly.com
Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/
Youtube:https://www.youtube.com/watch?v=eesBNUnKvws
The document discusses how big data and digital transformation can help address climate change challenges through the energy sector. It provides examples of digital use cases for power generation, transmission and distribution networks, retailers and aggregators, consumers and prosumers, and new market platforms. These use cases leverage technologies like predictive analytics, asset intelligence networks, demand response programs, and real-time energy visibility to improve grid reliability and efficiency, increase renewable energy integration, empower customers, and reduce costs.
Estimating the Impact of Agriculture on the Environment of Catalunya by means...Andreas Kamilaris
Because of insufficient accessible arable land, intensive farming has been linked to excessive accumulation of phosphorous, heavy metals, and other soil contaminants, as well as to significant groundwater pollution with nitrate. Deterioration of soil water quality is especially worrying at the bioclimatic Mediterranean area, especially under the current context of climate change. Hence, it is necessary to develop a common body of knowledge, shared at the local and regional levels of the countries involved and affected, so as to allow an effective monitoring of cropping systems, fertilization and water demands, and impacts of climate change, with a focus on the sustainability and the protection of the physical environment.
In this presentation, we describe AgriBigCAT, an online software platform that combines geophysical information from various diverse sources, together with big data analysis, in order to estimate the impact of the agricultural sector on the environment, considering land, water, biodiversity and natural areas requiring protection, such as forests and wetlands. Based on the P-Sphere project, this platform intends to promote more sustainable agriculture, by designing and developing an information and knowledge-based platform, using a big data approach for managing and analyzing a wide range of geospatial and mainstream information, which can be accessible by standard communication technologies such as the internet/web and mobile apps. this platform can also assist both the farmers' decision-taking processes and the administration planning and policy making, with the ultimate objective of meeting the challenge of increasing food production at a lower environmental impact.
The document summarizes Switzerland's national spatial data infrastructure (SDI) called geo.admin.ch, which is operated by swisstopo, the Federal Office of Topography. Some key points:
- Geo.admin.ch provides easy and rapid access to Switzerland's authoritative geodata through web services, maps, and APIs in compliance with the Federal Act on Geoinformation.
- It serves over 10,000 daily users and peaks at over 35,000, delivering over 1,300 map tiles per second.
- The SDI utilizes cloud computing, open standards, open source software and open APIs to boost innovation and generate value-added services while ensuring scalability and reasonable costs.
Solving advanced research problems with real time open data from satellites a...Wolfgang Ksoll
The project NextGEOSS brings wit its data hub based on CKAN and its 10 pilot programs a new quality in the usage of earth observation open data from satellites and in situ.
The document discusses challenges around data management and analytics for smart grids with distributed generation. It notes that smart grids are aimed at improving grid resilience, facilitating new energy markets, and better integrating renewable energy. However, a lack of unified data models presents a challenge for analyzing the large volumes of diverse data from smart meters, weather sensors, and other sources. The author proposes collaborating with Big Data Europe to define use cases around technical grid management and market forecasting that leverage big data analytics to help decarbonize energy systems with high renewable penetration.
The NextGEOSS project, a European contribution to GEOSS (Global Earth Observation System of Systems), proposes to develop the next generation data hub for Earth Observations, where the users can connect to access data and deploy data-driven applications.
The document discusses empowering communities with big data technologies through lowering barriers to using big data. It describes the Big Data Europe consortium and platform, which consists of three layers - hardware, a resource manager, and big data applications. The platform packages big data components like HDFS, Spark, and Kafka in Docker containers to solve specific problems, and provides installation instructions and technical support contacts.
The project uses mathematical modeling to determine optimal locations for beehives to maximize pollination. A partnership between the University of Essex and Simul Systems Ltd aims to develop an app to help beekeepers improve productivity by analyzing maps and mathematical models of plant distributions. Funding from the UK Technology Strategy Board supported a prototype, with hopes of further development and commercialization.
Artificial intelligence and machine learning can help analyze large amounts of environmental data to better understand climate change and predict future impacts. AI is used to identify patterns in data from sensors monitoring conditions around the world. This data provides insights into vulnerabilities and helps predict extreme weather events. AI technologies can also optimize renewable energy production and design more energy efficient systems, buildings and consumer products to mitigate climate change. However, training AI models also contributes to carbon emissions which must be addressed.
Engaging earth observation in the platform economyterradue
This document discusses engaging earth observation data in the platform economy. It outlines three challenges: making data open, building on existing platforms through APIs, and exploiting network effects. The author describes their MELODIES project which developed a platform as a service for earth observation data. This allows rapid prototyping, seamless data access, and automated processing. Ongoing work involves furthering these outcomes and forming partnerships to ensure sustainability. The goal is to support open science, government, and commercial applications using earth observation data.
The document discusses BCeMAP, a web-based mapping application that provides a common operating picture for emergency responders in British Columbia. BCeMAP integrates data from various sources like weather alerts, earthquake data, wildfire information and more. It allows different agencies to share relevant information through open standards while maintaining control over their own data. The demo shows how BCeMAP authenticates users and aggregates dynamic data feeds to be viewed on an ArcGIS map for emergency response and management.
Mmea program - from sensors to services. Keynote from Dr. Tero Eklin CLEEN_Ltd
CLEEN's MMEA program organised an international seminar on cleaner air - Outdoor and indoor air quality together with Zhejiang University and assistant organizer Insigma group.
This is one of the keynote presentations in the seminar.
More info in www.mmea.fi
The cleantech field is expanding rapidly and Finnish companies are committed to working for a better environment in the fields of energy efficiency, air quality and monitoring. The world-class Cleantech know-how from Finland and the cooperation with Chinese partners and the results were highlighted in the MMEA seminar. Some of the leading Finnish cleantech companies together with Finnish and Chinese research institutions were present at the event. The seminars focused on cooperation between Finland and China concerning indoor and outdoor air quality and solutions to make them better.
The document summarizes a presentation about accelerating green energy development in China through smart grid technology and US-China cooperation. It discusses China's growing electricity needs and transition to renewable and nuclear energy. Smart grid applications could significantly reduce carbon emissions by improving efficiency, integrating renewable energy, and enabling electric vehicles. Joint US-China programs through non-profits like JUCCCE provide expertise and technologies to support China's green energy goals.
Global Atlas for Renewable Energy - application to MauritaniaIRENA Global Atlas
One of the key activities in IRENA is the development of renewable readiness assessments (RRAs). An RRA is a holistic assessment of conditions for renewable energy deployment in a country, and the actions necessary to further improve these conditions. An RRA is a rapid assessment of how a country can increase readiness and overcome the main barriers to the deployment of renewable energy technologies. It covers all services (transport, heat, electricity and motive power), and sources of renewable energy, with countries selecting those of relevance. The RRA comprises a process and a methodology that includes completing a set of templates and a final report. On the occasion of the RRA Mauritania, the Global Atlas was presented, as a potential supplier of data, data infrstructure and education for zoning renewable energy hotspots.
Upcoming Datasets: Global wind map, Jake Badger ( Risoe DTU)IRENA Global Atlas
Upcoming Datasets: Global wind map. A presentation by Jake Badger ( Risoe DTU) during the Global Atlas side event which held at the World Future Energy Summit in 2014
Chris Atherton (GEANT) and Andres Steijaert (OCRE) presentation about the Open Clouds for Research Environments (OCRE) project and GÉANT's National Research and Education Networks and their Infrastructure support for global Cloud Computing at the 4th GEO Data Technology Workshop.
Vienna, Austria
25th of April 2019
Lennart Landsberg, Research associate, Cologne University of Applied Sciences, Germany - Using Existing Data to Support Operational Emergency Response in Germany - Current Use Cases, Opportunities and Challenges
Raising the benefits of meteorological services and satellitesEUMETSAT
In this presentation, given at the WMO side event during the 2014 EUMETSAT Meteorological Satellite Conference in Geneva, Stephan Bojinski (Satellite Utilization and Products Division, Space Programme, WMO) demonstrates how the WMO assists in raising the benefits from meteorological services and satellites and discusses the challenges faced in the future.
The document describes an emergency response demonstration that uses semantic web technologies to help coordinate emergency services. The demonstration involves a cargo plane crashing in London, causing multiple fires. It shows how an emergency response system could help the Joint Emergency Services Control Centre make sense of the emergency, handle information requests, and make tactical decisions by integrating technologies like ontology mapping, image retrieval, and data management. The goal is to effectively acquire, analyze, and use information in real-time during an emergency response.
Kenneth McNamee discusses net zero energy airports and definitions. The document outlines steps to gather energy and water consumption data for airports categorized by passenger volume and climate region to benchmark performance. This identifies opportunities to improve building systems and understand that airports are large energy consumers. A path toward net zero energy airports is presented with examples from Europe of regulatory support for low carbon aviation.
It introduces and illustrates use cases, benefits and problems for Kerberos deployment on Hadoop; how Token support and TokenPreauth can help solve the problems. It also briefly introduces Haox project, a Java client library for Kerberos.
Real time big data analytical architecture for remote sensing applicationLeMeniz Infotech
Real time big data analytical architecture for remote sensing application
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Web : http://www.lemenizinfotech.com
Web : http://www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Blog : http://ieeeprojectspondicherry.weebly.com
Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/
Youtube:https://www.youtube.com/watch?v=eesBNUnKvws
Generating Insight from Big Data in Energy and the EnvironmentDavid Wallom
The document discusses using big data in energy and the environment to generate insights. It provides examples of using data to cluster electricity load profiles, analyze commercial energy consumption under different pricing strategies, and model high impact weather events. Specifically, it analyzed UK winter 2014 floods through over 39,000 weather simulations to determine how climate change has increased risks of very wet winters.
Big Data, Big Content, and Aligning Your Storage StrategyHitachi Vantara
Fred Oh's presentation for SNW Spring, Monday 4/2/12, 1:00–1:45PM
Unstructured data growth is in an explosive state, and has no signs of slowing down. Costs continue to rise along with new regulations mandating longer data retention. Moreover, disparate silos, multivendor storage assets and less than optimal use of existing assets have all contributed to ‘accidental architectures.’ And while they can be key drivers for organizations to explore incremental, innovative solutions to their data challenges, they may provide only short-term gain. Join us for this session as we outline the business benefits of a truly unified, integrated platform to manage all block, file and object data that allows enterprises can make the most out of their storage resources. We explore the benefits of an integrated approach to multiprotocol file sharing, intelligent file tiering, federated search and active archiving; how to simplify and reduce the need for backup without the risk of losing availability; and the economic benefits of an integrated architecture approach that leads to lowering TCSO by 35% or more.
Are you excited and want to learn Big Data Technologies? Do you feel that internet is loaded with free materials is complicated for a newbie?
There are many things that may go wrong when learning a new technology. Free internet material are sometimes can of worms for a beginner and training is advised for a jumpstart.
Open-BDA Big Data Hadoop Developer Training which is going to be held on 11th & 12th May 2015 @ Marriott Hotel Karachi, will cover everything you need to know to start a career in Hadoop technology and achieve expertise to a level where you can take certification exams with MAPR, Cloudera & Hortonworks with confidence. You can start as a beginner and this course will help you become a certified professional.
Utilities are facing an explosion of data from smart meter and grid technologies that they are ill-equipped to manage and analyze. This data, if properly analyzed, could provide strategic insights but utilities currently lack capabilities to interpret usage patterns, forecast demand, and leverage data for competitive advantage. The future requires utilities to develop competencies in data management, cross-functional analysis, and demand response programs in order to unlock value from consumer data and gain competitive advantages over other utilities.
The document discusses security features in Hortonworks Data Platform (HDP) and Pivotal HD. It covers authentication with Kerberos, authorization and auditing using Apache Ranger, perimeter security with Apache Knox, and data encryption at rest and in transit. Various security flows are illustrated including typical access to Hive through Beeline and adding authorization, firewall routing, and encryption. Installation and configuration of Ranger and Knox are also outlined.
The only way to get where we need to be in security analysis is if we use Security Intelligence. This means working harder and understanding the big picture of your data.
Building hadoop based big data environmentEvans Ye
The document discusses building and deploying Hadoop environments. It covers building custom Hadoop versions by adding patches, using Bigtop to package Hadoop distributions, configuring Hadoop deployments, and automating deployments with tools like Hadooppet and Puppet to simplify configuration management and testing. Continuous integration, release engineering, and development environments for Hadoop are also addressed.
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Dat...APNIC
MATATABI: Cyber Threat Analysis and Defense Platform using Huge Amount of Datasets, by Yuji Sekiya.
Presented at the APNIC 40 APOPS 1 session, Tue 8 Sep 2015.
To Serve and Protect: Making Sense of Hadoop Security Inside Analysis
HP Security Voltage provides data-centric security solutions to protect sensitive data in Hadoop environments. Their solutions leverage tokenization and encryption to safeguard data at rest, in motion, and in use across the data lifecycle. They presented use cases where their technology helped secure financial, healthcare, and telecommunications customer data in Hadoop and other platforms. Questions from analysts focused on implementation experience, performance impacts, integration with authentication, costs, and supported environments and partnerships.
Balancing Mobile UX & Security: An API Management Perspective Presentation fr...CA API Management
This document discusses reconciling user experience and security in mobile applications. It explores techniques for user authentication on mobile that can disrupt user experience if not implemented properly. It proposes balancing authentication complexity and frequency to improve user experience without compromising security. The document also examines using biometrics, risk-based authentication, and single sign-on across mobile apps and third-party apps to improve both security and user experience on mobile. It describes components of a solution including API routing, brokering, and protected endpoints to enable secure access to APIs from mobile applications.
Big Data Analytics (BDA) is rapidly turning out to be a significant global enterprise need. It aims to facilitate the storage, querying and analysis of enterprise big data, which is getting more complicated and time-consuming with traditional database technologies. Apache Hadoop is a well-known Open-source BDA enterprise solution which is seeing an annual application growth rate of 60% globally.
With the rise of Apache Hadoop, a next-generation enterprise data architecture is emerging that allows organizations to efficiently rein in their big data business transactions. Hadoop is uniquely capable of storing, aggregating, querying and analyzing big data sources into formats that fuel new business insights. Organizations that embrace solution architectures focused on maximizing data-driven insights will put themselves in a position to drive more business, enhance productivity, maintain competitive edge or discover new and lucrative business opportunities. Over the coming years, Hadoop could be in a position to process more than half the world’s data.
To educate organizations about how best to leverage Apache Hadoop as a key component of their enterprise big data architecture, Innovative Management Services is pleased to host the 1st annual Open-BDA Hadoop Summit 2014 which is scheduled to be held on 18th & 19th November, 2014 at Marriott Hotel, Karachi.
Enterprise Approach towards Cost Savings and Enterprise AgilityNUS-ISS
Presented by Mr Poon See Hong, Deputy Director (Planning), Police Logistics Department, Singapore Police Force, at our 14th Architecture Community of Practice Forum on 21 Jul 2016.
Building Hadoop Data Applications with Kite by Tom WhiteThe Hive
With a such a large number of components in the Hadoop ecosystem, writing Hadoop applications can be a big challenge for newcomers. In this talk Tom looks at best practices for building data applications that run on Hadoop, and introduces the Kite SDK, an open source project created at Cloudera with the goal of simplifying Hadoop application development by codifying many of these best practices.
Meet with Tom White:
Tom White is one of the foremost experts on Hadoop. He has been an Apache Hadoop committer since February 2007, and is a Member of the Apache Software Foundation. Tom is a software engineer at Cloudera, where he has worked, since its foundation, on the core distributions from Apache and Cloudera. Previously he was an independent Hadoop consultant, working with companies to set up, use, and extend Hadoop. He has written numerous articles for O’Reilly, java.net and IBM’s developerWorks, and has spoken at many conferences, including ApacheCon and OSCON. Tom has a B.A. in mathematics from the University of Cambridge and an M.A. in philosophy of science from the University of Leeds, UK. He currently lives in Wales with his family.
As Hadoop becomes a critical part of Enterprise data infrastructure, securing Hadoop has become critically important. Enterprises want assurance that all their data is protected and that only authorized users have access to the relevant bits of information. In this session we will cover all aspects of Hadoop security including authentication, authorization, audit and data protection. We will also provide demonstration and detailed instructions for implementing comprehensive Hadoop security.
Big Data and the Energy domain (vis-a-vis the respective H2020 Societal Challenge) - Opportunities, Challenges and Requirements. As presented and discussed in the public launch of the BigDataEurope project.
The document discusses how declining oil prices have created challenges for the oil and gas industry but also opportunities to improve efficiency through digital transformation. It notes that while companies have traditionally responded to price drops by cutting costs, the current situation requires embracing new technologies like the Internet of Things. The document highlights that survey respondents identified operational efficiency of existing projects as a key investment area. It also found that oil and gas companies need most improvement in leveraging the large amounts of data now available to drive better decision making. Embracing digital technologies could help automate processes and optimize operations to boost competitiveness in lower price environments.
Solving Geophysics Problems with PythonPaige Bailey
This document discusses using Python for solving problems in geophysics. It begins by defining geophysics as the application of physics to the study of the Earth, its environments, and its processes. It then discusses various geophysical themes like gravity, heat flow, electricity, fluid dynamics, magnetism, radioactivity, and vibration. The rest of the document focuses on different geophysical libraries and software that can be used with Python, applications of geophysics to energy exploration and production, and challenges of dealing with big data in upstream oil and gas.
Zinc8 Energy Solutions: Getting de-risked and raised by a global network of c...Stephan Bogner
When some of the world´s brightest people and biggest companies unite, there must be an urgency to solve a bigger problem. In order to build a smarter, more sustainable future for the planet, a far-reaching multidisciplinary effort is needed to speed up the rate of greentech innovation together – and to finance the economies of the future.
Right now, there is an innovation-based industrial revolution going on to re-shape our world for the better.
Unfortunately, it´s happening too slow. Innovations and new technologies take too long to enter the market and to then scale in a meaningful way. Capital, capabilities (know-how) and connections are the greatest limiting factors.
Reservoir simulation is a sophisticated technique of forecasting future recoverable volumes and production rates that is becoming commonplace in the management and development of oil and gas reservoirs, small and large. Calculation and estimation of reserves continues to be a necessary process to properly assess the value and manage the development of an oil and gas producer’s assets. These methods of analysis, while generally done for different purposes, require knowledge and expertise by the analyst (typically a reservoir engineer) to arrive at meaningful and reliable results. Increasingly, the simulation tool is being incorporated into the reserves process. However, as with any reservoir engineering technique, certain precautions must be taken when relying on reservoir simulation as the means for estimating reserves. This discussion highlights some of the important facets one should consider when applying numerical simulation methods to use for, or augment, reserves estimates. The main take away will be an appreciation for the areas to focus on to arrive at meaningful and defendable estimates of reserves that are based on reservoir models.
This presentation by GTM Research discusses trends in the grid edge space including:
- Global AMI meter installations will surpass 1 billion by 2022.
- Voice assistant devices are supporting home automation and energy management functions in US homes.
- Grid-interactive devices and demand response are bringing greater flexibility to reduce peak demand in the US.
- Blockchain is unlocking new ways to transact energy and attributes through applications like transactive energy, asset tokenization, and accounting.
- European energy giants like Enel and E.ON have been actively investing in distributed energy companies and building out their distributed energy practices.
10 Secrets of Virtual Storytelling: A Guide For Better Online PresentationsJeremy Waite
To help everyone stuck at home and forced to work on their online presentation skills, I recorded an extended seminar where I share a collection of the best pieces of communications advice I have picked up from some of the best speakers in the world about virtual storytelling. These are the slides. Maybe you'll find them helpful.
Seminar link: https://vimeo.com/398317345 [86 minutes]
The document discusses the history of big data in the energy industry. It describes how early well logging in 1927 and the first seismograph in 1921 helped advance oil exploration by providing more data about subsurface conditions. Over time, technology improvements like 2D and 3D seismic imaging generated exponentially larger datasets. Today's datasets can exceed 100 terabytes from sources like coil seismic surveys. Advanced data collection and reservoir modeling are needed to optimize extraction from unconventional resources and maximize recovery rates from existing wells. Data now impacts the entire oil and gas value chain and will continue shaping the future of the energy industry.
SMi Group's 18th annual Gas to Liquids 2015 conferenceDale Butler
This document provides information about an upcoming conference on gas to liquids (GTL). The two-day conference will explore the latest developments and long term trends in the GTL industry, including technological advances in small-scale GTL and the economic viability of GTL projects. Speakers will discuss topics such as risk mitigation strategies, product marketing, project financing, and construction issues. Attendees can learn about GTL and network with leading experts in the field.
The document discusses 360factors, a company that provides cloud-based software and services to help oil and gas companies manage regulatory compliance and risk. It faces challenges from increased regulations in areas like safety, sustainability, and transparency. 360factors' flagship software, Predict360, integrates regulations, policies, risks, audits, training, and other compliance elements in one platform. This helps companies navigate regulatory changes more efficiently and improve performance. 360factors has 30 years of experience in environmental consulting for the oil and gas industry. Its solutions are designed to break down silos and reduce costs while simplifying compliance management.
Shell uses big data analytics to more efficiently explore for oil and gas reserves. Sensors collect over a million readings during seismic surveys to identify potential drilling locations, which is analyzed against global data to assess probability of productive wells. Equipment sensors also monitor performance to forecast maintenance needs. This approach has increased Shell's ability to drill productive wells by 1%, generating 3 additional years of global energy. They utilize large-scale infrastructure from AWS and analytics teams to optimize exploration and extraction costs in facing challenges of limited resources.
Over the next 25 years, oil demand is expected to increase by 11 million barrels per day, with over 90% of the additional oil coming from the Middle East and North Africa. This will require $2.7 trillion of investment in the region's oil exploration and production as existing oil fields decline and new sources are harder and more expensive to access. The oil and gas industry also faces acute shortages of skilled workers like petroleum engineers and geologists as experienced employees retire, which could lead to operational challenges if not addressed. Skills development and training programs are needed to ensure continued supply of expertise.
PANEL 3: Post-2020 Global Chemicals Supply Chains – What will be the drivers for market supply and demand and will chemicals product safety emerge a winner or loser? - Rafael Cayuela, Chief Economist, Dow, USA
4th Energy Wave Fuel Cell and Hydrogen Annual Review, 2015Kerry-Ann Adamson
The 2015 4th Energy Wave Fuel Cell and Hydrogen Annual Review is the latest in an unbroken record of publishing a qualitative and quantitative analysis of the global fuel cell industry.
Authored since 2008 by Dr. Kerry-Ann Adamson, then of Fuel Cell Today and now the CEO of 4th Energy Wave, the report presents the only review of the growing sector produced from primary information gathering.
The document discusses technological innovation in the petroleum industry. It discusses how oil companies may need to share more data to remain competitive as alternative energy sources rise. It also discusses the Colombian Oil Congress as a place for experts to discuss current issues and innovations in the industry. Additionally, it highlights how data sharing can lead to improved performance, as shown by a company that shared offshore drilling technology 50 years ago and is now benefiting from other companies using that technology as well.
This document discusses dollar-driven mine planning from a corporate perspective to operational mine planning. It covers four key components of planning: strategic planning looking 20 years ahead to position the company for future outcomes; business planning on a 5 year horizon to coordinate divisions and establish goals; annual planning for the budget; and mine planning at the local level to acquire resources, develop projects, and manage production. Success requires quality resources, project development, and production management. Planning is essential to maximize value from resources by eliminating waste and targeting best practices throughout the mining process.
Digital Transformation in the Oil & Gas Industry | 2021Social Friendly
The document discusses how digital transformation can help the oil and gas industry build resilience. It outlines several ways that digital technologies like industrial IoT, sensors, digital twins, cloud computing, artificial intelligence and mobile technologies can help reduce costs, increase efficiency and productivity, and make better data-driven decisions. Specifically, these technologies allow for real-time monitoring of assets and operations, predictive maintenance, remote asset management, and optimized decision making through analytics. The document argues that digitalization is critical for oil and gas operators to succeed in an environment of low prices and high volatility.
This document discusses a dissertation that evaluates whether company size affects bankruptcy risk in the oil and gas industry. It uses Altman's z-score model to calculate bankruptcy probabilities for 19 public oil companies from 2008-2012. The study collects financial data from annual reports to calculate ratios used in the z-score formula. This allows comparing z-scores between large and small companies over the research period. The goal is to determine if larger companies face lower bankruptcy risk, as found in prior research, or if company size is less influential in the oil industry.
4. Global X ASX Investor Day 2022.pptxWANG YINGJIE
This document provides a summary of a presentation on three investment themes: electric vehicles, decarbonization, and robotics/AI. It notes that predicting the future is difficult, but investing requires predicting themes that will impact the future. The presentation discusses how each theme is reaching an inflection point and identifies related risks like potential lithium supply constraints that could slow electric vehicle adoption. Investment opportunities in materials and technologies supporting these themes are also examined.
Schlumberger Business Consulting's President, Antoine Rostand shared his view...Energy Intelligence
Schlumberger Business Consulting's president, Antoine Rostand shared his views on the challenges of execution from discovery to production within the energy industry and the ability to be able to transform reserves into production.
Five market trends that are re-shaping C&I energy management and procurementOmar Saadeh
The market for building energy management and procurement solutions is vast and today’s large electricity customers are exposed to an increasingly complex array of opportunities. A growing number of new solutions and upgrades continue to promise enhanced energy consumption and awareness, streamlined day-to-day business processes, and improved operational efficiency. Apart from proven applications such as demand response or commercial solar, an emerging class of utility and wholesale programs further offer energy managers new options to optimize their investments and realize positive project cash flows.
As we build out our C&I Customer Network and coverage into energy procurement and management for large energy consumers, we expect to produce more content in these areas. We’re happy to include folks in this space and take briefing from solution providers including vendors, developers, ESCOs and utilities. Please do reach-out.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Software Engineering and Project Management - Software Testing + Agile Method...Prakhyath Rai
Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
Agile Methodology: Before Agile – Waterfall, Agile Development.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.
Gas agency management system project report.pdfKamal Acharya
The project entitled "Gas Agency" is done to make the manual process easier by making it a computerized system for billing and maintaining stock. The Gas Agencies get the order request through phone calls or by personal from their customers and deliver the gas cylinders to their address based on their demand and previous delivery date. This process is made computerized and the customer's name, address and stock details are stored in a database. Based on this the billing for a customer is made simple and easier, since a customer order for gas can be accepted only after completing a certain period from the previous delivery. This can be calculated and billed easily through this. There are two types of delivery like domestic purpose use delivery and commercial purpose use delivery. The bill rate and capacity differs for both. This can be easily maintained and charged accordingly.
27. 2000 - 2010 :
Decade of “Big Data”
2010 - 2020 :
Decade of Sensing
28. “Oil and gas industry leaders continue to look to digital technologies as a way to address
some of the key challenges the industry faces today in this lower crude oil price cycle.
Making the most of big data, IIoT and automation are indeed the next big opportunities for
energy and oilfield services companies, and many are already starting work in these areas.
They are increasing investments in enabling people and assets, with a growing emphasis on
developing data supply chains to support analytics projects that can improve efficiencies,
manage cost and provide a competitive edge.
Companies who do not continue to invest in
digital technologies risk being left behind.”
The views expressed in this program do not represent the views of my employer. In fact, they would probably be really disturbed by the amount of cursing (if I curse) or if I mess up on anything
I’m also not able to tell you anything specifically about the way we structure data in our environment, or appear to endorse anything
Insert logo for PyLadies-HTX, Rice University, mention that you’re a geophysicist who works full-time for an oil company in downtown Houston, say something about the toolkit that you use at work (Python, R, Hadoop)
Go into a bit of an explanation of what a well log is
well logging parameters:
- resistivity
- image / dipmeter
- porosity
- density
- neutron porosity
- gamma ray
- self potential
- caliper
- NMR
1927 by Conrad Schlumberger, though he’d been formulating the idea since 1919
He sent down a sonde (sensor attached to a wire) into a 500m deep well in the Alsace region of France and started collecting information
“Electrical resistivity log”
All measurements were made by hand
Go into a bit of an explanation on what seismic is
1921 by J. Clarence Karcher, who was an Electrical Engineer
This is the means by which the majority of the world’s oil reserves have been discovered
Founded Geophysical Service Incorporated in 1930, which eventually turned into Texas Instruments
Got the idea because his assignment in World War I, the assignment that took him out of grad school, was to locate heavy artillery batteries in France by studying the acoustic waves the guns generated in the air.
He noticed an unexpected event in his research and switch his concentration to seismic waves in the earth
He thoughts it would be possible to determine the depths of the underlying geologic strata by vibrating the earth’s surface while precisely recording and timing the waves of energy
Earliest known oil wells were drilled in China, in 347 AD
These wells had depths of up to about 790 feet, and were drilled using bits attached to bamboo poles
Egyptians were using asphalt more than 4000 years ago, in the construction of the walls of Babylon. Ancient Persians were using petroleum for medicinal and lighting uses. The first streets of Baghdad were paved with tar.
Befuddled “shoot the ground and gusher comes up” situations. Producing dozens of barrels a day, maybe hundreds, but recovery rates were exceptionally low, and you weren’t really finding anything interesting.
I guess the point that I’m trying to make is that…
[read slide]
Advances in technology create a marked step change in petroleum exploration. Those advances are primarily in terms of better hardware / equipment, which give explorers better data about the subsurface. The data is the key.
Now, I’m a geophysicist – so those advances are the ones I’m best at spotting.
Point out the upticks for 2D seismic, better resolution for 3D seismic
80’s: 2D data acquired, pre-stack and post-stack imaging, Cray supercomputers
90’s: 3D narrow azimuth data, 3D post-stack and pre-stack imaging, Unix
00’s: 3D wide azimuth data, imaging, reverse time migration; Linux clusters
Now: coil shooting, continuous machine-generated sensory data
Mathematical insights – mention that last night you found out that the guy who first discovered the FFT was a Chevron employee, ain’t no thing
Point out fracking boom, mention that the crazy upward tick has continued, though the steepness of the slope has decreased a bit due to the drop in oil prices
Shamelessly stolen from wikipedia
7 out of 10 of the largest public, state-owned, and private businesses – and a huge proportion of the overall list. Trillions of dollars of revenue.
Direct link to reserves and success of a company. We’re selling a thing; the margins on the beef jerky you buy in a gas station are higher than the margins for a barrel of oil
Oil companies are all in the business of getting barrels out of the ground – so characterizing the subsurface is incredibly important. Both of those bits of data that I mentioned before – that came so late in the game – were huge technological step changes for the industry, and drastically impacted oil discovery.
Improved resolution within the reservoir is critical because deepwater wells cost a lot - $100 million or more – and fully exploiting assets is essential
The oil industry is a bit like an ecosystem. This particular piece is subsurface characterization – the earth science-y and engineering bits
Every image you see here has a data type (or more!) associated with it, and, though it’s getting better, a shortage of standards
So these components of the energy ecosystem, and this subsurface data workflow can be grouped into “earth science-y bits” and “engineering bits” with this kind of fuzzy area in between with petrophysicsEarth scientists record millions and billions of data points called “seismic” and they don’t trust any of them unless you put them all together
Engineers trust pressure readings in the well, the stuff they can measure with sensors – and trust it everywhere, and extrapolate everywhere
Something that I should also mention is that this is an iterative process. I put a loop here, but in reality, all of these steps can feed back into one another – and a change to one component of the subsurface model drastically impacts all other components
New sorts of geology: horizontal drilling and hydraulic fracturing combined have been revolutionary
For example: “Unconventional resources” such as shale gas and tight oil supply 20% of the gas used in the USA and is expanding rapidly around the globe.
But want to hammer in: currently, recovery rates are only about 50%. The biggest risk is finding the oil; the second biggest risk is getting it out of the ground safely.
Seismic industry has evolved over the last decade by increasing the volume of data that is typically acquired and processed by about an order of magnitude every five years (2000)
But that’s changed
It’s exponential growth
In the 80’s, seismic was gigabytes in size; some people were still hand-interpreting on paper
5D interpolation: can produce file sets that exceed 100 TB in size
Chevron’s internal IT traffic alone exceeds 1.5 TB a day – and that’s 2013 numbers.
Shell is using fiberoptic cables created in a special partnership with HP for their sensors, and this data is transferred to AWS servers – 1TB / day
Coil seismic has replaced lines and grids – explain why, and explain why that impacts the size of the data that you’re looking at
CAT scanning of cores
What you’re seeing here is a subsection of the well – A&M has the largest set of core samples in the world housed at a refrigerated warehouse on campus actually, if you’re dying to go see
Pore-scale imaging (.01 to 10 microns) can generate large data sets, as well: a centimeter cubed can exceed 10GB, and when you take into account that you’re measuring 1000 meters of core, that’s 1 exabyte
Reducing the approximations, improving the equations
Images taken from Schlumberger
All that I mentioned before was earth sciences or drilling related – impacting the “upstream” components of the oil industry.
But in reality, data impacts every single component of the oil and gas value chain. And what’s more: it’s a variety of data, coming in at asynchronous rates.
How we get it, how we transport it, how we process it, how we use it – and of these components have the opportunity to be honed by analytics insights.
Streamlining the transport, refinement, and distribution of O&G is vital.
Just a few examples:
Refineries have limited capacity, and fuel needs to be produced as close as possible to its point of end use to minimize transportation costs. Complex algorithms take into account the cost of producing the fuel as well as diverse data such as economic indicators and weather patterns to determine demand, allocate resources and set prices at the pumps.
- With projects demanding more expensive drilling and production technology and profound changes in government regulations and commodities, companies need to exercise operational prudence and strategic foresight to ensure success.
- Greater competition for assets, and a smaller margin for error
- Studies show that a gradual shift to a data and technology-driven oilfield is expected to tap into 125 billion barrels of oil, equal to the current estimated reserves of Iraq
So this past decade, the first one of the thousands, 2000 – 2010, has been the decade of “big data”.
Kind of a buzzword, right? Like “in the cloud”.
and if you thought there was a lot of data in this first decade, you realize there's going to be a heck of a lot more in the second.
In a recent study (May 2015) from Microsoft and Accenture, 86 – 90% of respondents said that increasing their analytical, mobile, and internet of things capabilities would increase the value of their business
In the near term during the current low crude price cycle, approximately 3 out of 5 respondents said they plan to invest the same amount (32%) or more or significantly more (25%) in digital technologies
Mobility, infrastructure, and collaboration technologies currently are the biggest investment areas
In the next three to five years, investments are expected to increase in big data, the industrial IoT, and automation
89% noted that leveraging more analytics capabilities would add business value
- 90% felt more mobile tech in the field would add business value
- 86% leveraging more IIoT and automation would boost value
Rich Holsman, Accenture (global head of digital in Accenture’s energy industry group)