Category Archives: Data Mining
Top IT courses that you can do; check the best 5 here – HT Tech
Top IT courses that you can do; check the best 5 here Photo Credit: Pexels These IT courses will provide the kind of knowledge that will lead you towards a successful career. Check out the top 5 IT courses here. Photo Credit: Pexels If you have just passed your 12th and are looking for an Information Technology (IT) course, then you need to first understand your interests and career goals, and then choose the best course. Photo Credit: Pexels Here are the suggestions that will help you in mapping the best IT course for you. Photo Credit: Pexels Bachelor's Degree in IT (BE/B-Tech in IT): It will focus on Data Structures and Algorithms, Operating Systems, Databases, Programming, system development, and more. Photo Credit: Pexels Bachelor's Degree in software engineering: It will provide an extensive education in software development fundamentals, such as user interface design, programming language, methodologies, software testing, and more. Photo Credit: Pexels Bachelor's Degree in Data Sciences: It offers a wide range of subjects such as Applied Statistics, Data Mining, machine learning, data visualization across several sectors. Photo Credit: Pexels Bachelor in Cyber Security: It focuses on technology, people, information, systems, and processes to enable cyber operations. It can help you with careers in protecting data, system, and networks from cyber attacks. Photo Credit: Pexels Bachelor of Computer Application (BCA): This under-graduation program helps students in understanding Operating Systems, Java Programming, Computer Networks, Database Management Systems, and more. Check More
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Top IT courses that you can do; check the best 5 here - HT Tech
First woman to win an Indy 500 was Marcus Ericsson’s engineer in … – IndyStar
Indy 500 winner Marcus Ericsson looks back on his chances to win at IMS
Chip Ganassi Racing's Marcus Ericsson wins the 106th running of the Indianapolis 500.
Clark Wade, Indianapolis Star
INDIANAPOLIS -- Angela Ashmore had no idea she'd made Indy 500 history as she stood in victory circle at Indianapolis Motor Speedway, as she watched Marcus Ericsson with a wreath around his neck take a few glorious sips of whole milk, then pour the rest down his face.
All Ashmore knew was an indescribable feeling of watching her driver win the world's most iconic race. Knowing she had played a part in Ericsson's victory, as his engineer, was enough for her, more than enough.
But weeks after the May 29, 2022 Indy 500, Ashmore found out the racing world knew something she didn't know. Ashmore was the first woman on an Indy 500 team to ever win the race -- in any position -- in 106 years.
"It was pretty incredible. It's the biggest race in our sport, one of the biggest races in the world," said Ashmore, 35, a Purdue graduate and Chip Ganassi Racing engineer. "The race has a lot of history and being the first female to win, that's a big accomplishment."
Especially because Ashmore won the Indy 500 in a major role. She is the engineer on Ericsson's team who manages the telemetry of the car, the fuel mileage and strategy during the race. Throughout the season, she oversees the electronic system to ensure quality data is collected and turned into useful information.
In other words, Ashmore makes Ericsson's car go faster.
"From the driver perspective, the engineers are the ones you are the closest with," Ericsson said this week. "I spend a lot of time with Angela when I'm not in the car, sitting, talking and discussing strategy."
Yet as Ericsson drank the milk in 2022, just like Ashmore, he had no idea his win had catapulted her into racing history books. Not until weeks later when a driver and an engineer learned exactly what they had done.
"First of all, I was shocked when I heard it, that she was the first woman. I was sure it had happened before," said Ericsson. "It's crazy it hadn't happened before. It's so great to be part of that history and I'm hoping it will help push more women into the sport."
Ashmore wants that, too, to be a role model for young women trying to break into male-dominated industries, to show them gender doesn't matter, just their skills.
But first, Ericsson and Ashmore have a race to run. And on Sunday, their No. 8 Honda is competing to become the first back-to-back winner of the Indy 500 since Helio Castroneves won in 2001 and 2002. Can they recreate their 2022 magic for a repeat?
"Well, I never want to say that because I don't want to jinx it," said Ashmore. "But we have a fast car that races well in a pack. Chip Ganassi has four really good cars. I hope one of them, but especially the 8 car, takes home a win."
Ericsson doesn't hesitate when asked the same question: Can you repeat an Indy 500 victory? "That's the plan. That is the plan. That's what we're here for."
And with Ashmore on his team, Ericsson said, he is pretty sure the plan can become reality. "She's pretty amazing."
Ashmore grew up in Coopersville, a small town in western Michigan, with a dad who loved racing. The family spent many Saturday nights watching short-track events at the Berlin Raceway. Her dad and uncle even raced together, with a one-man pit crew, her dad.
On Sundays, Ashmore and her dad would settle in front of the television to watch NASCAR. "I literally fell in love with it watching it on TV by the time I was 4 or 5 years old," said Ashmore.
Inside her bedroom closet, her entire wardrobe consisted of racing T-shirts. "It was an obsession. I knew that's what I wanted to do for a career."
But what racing career, she wasn't sure. Maybe a driver or a pit crew member. Maybe one of those track announcers. Or maybe an engineer.
In high school, Ashmore excelled at math and science and took an intro to engineering class where the students built a car. If she had loved racing before, that class took it to a new level.
After she graduated high school, Ashmore was desperately searching for a way to get into racing. She took a chance and walked into Ponstein Racing, a Michigan team competing in the CRA late model series, with an offer.
"'Hey, I'll come work for you for free if you let me just observe and learn,'" Ashmore told the Ponstein team. They said yes.
Every afternoon after her summer day job, Ashmore would go to the shop and spend her nights working on race cars, sweeping floors, swapping out engines and rebuilding brakes.
"I just wanted the experience of being in a race shop no matter what I was doing," she said. "Just so I could learn."
As Ashmore entered her freshman year of college at Purdue, she knew exactly what she wanted to do in her racing career -- make those cars go faster. She wanted to be a racing engineer.
As a standout mechanical engineering student at Purdue, Ashmore landed a spot with Purdue's Formula SAE, a team ofabout 30 students that each year builds a single-seat open wheel race car and competes against other university teams.
On the SAE team, Ashmore was the suspension lead, spending countless hours in the machine shop building parts for the car. She also raced the cars.
After graduating from Purdue in 2010 with a bachelor's degree in mechanical engineering, Ashmore started searching for racing jobs. She soon learned just how hard it was to get a foot in the door in this industry.
"You either grew up in racing, your family did it, you knew somebody your dad was friends with or you knew somebody who did it," said Ashmore. "It's kind of a boys club. Being a female I didn't even know anyone in racing. I didn't know where to start."
Out of college, Ashmore went to work for Chrysler and got a master's degree in mechanical engineering from Purdue. She liked her job, but it wasn't her love. Racing was.
Then it finally happened. Five years out of college, Ashmore finally knew someone in racing who knew of an opening with a NASCAR team.
"It was kind of a low level spot," Ashmore said. She didn't care. This might be her chance. "I picked up my life and moved to North Carolina and finally got to prove myself."
Ashmore was the third engineer on a Roush Fenway race team, the assistant to the assistant engineer. She did data mining and collection and prepared reports for other engineers.
But soon she worked her way up to race engineer for Bubba Wallace's Roush Xfinity team and then she worked her way up to the NASCAR Cup Series as a race engineer for Trevor Bayne. And then she was promoted to David Ragan's lead engineer.
Ashmore was on track to make NASCAR history as the first female crew chief, probably within the next few years. She wanted that desperately but she also had IndyCar dreams raging in her head.
Leaving NASCAR was hard. Ashmore loved her job but the traveling was intense, 38 times a year versus 17 in IndyCar. And she was struggling being so far away from her family in the Midwest. IndyCar seemed like the perfect fit.
She landed an engineering job at Ganassi four years ago and has never once regretted the decision. She loves that she has more time between races to think her way through glitches and problems. She loves the creativity and strategizing that time allows her.
And she loves Ganassi's commitment to women in racing. "It is definitely a male dominated sport," she said. "You don't see a lot of women."
Ganassi is trying to change that. In 2022, PNC Bank and Ganassi collaborated to launch the Women In Motorsports program, part of the PNC Project 257, referring to the number of years, if things continue the way they are, it will take for women to be paid the same as men working in the same role.
"Which is insane," Ashmore said. "257 years."
The Women In Motorsports program offers free internships with housing to women in college and technical schools throughout the United States. Ashmore serves as a close mentor to the women, especially those in engineering, as they look to find their footing in the industry.'
"That was the hardest part, finding a way to get a foot in the door," she said. "This gives these women some opportunities that wouldn't otherwise exist, to get exposure to racing."
It also helps the teams, Ashmore said. "You are always stronger when you have diverse opinions and thoughts."
Having Ashmore on the Ganassi team has paid off in an Indy 500 victory and in making Indy 500 history in 2022. It's crazy to think, Ashmore said, that she will forever be the first woman on an IndyCar team to win an Indy 500.
And she wants all the young women who follow her to remember: "The qualifications for the role have nothing to do with gender. It has to do with your ability to do the job," she said. "And there is nothing that makes a man better than a woman based on those qualities.
"I want them to know they are welcome and wanted, and that they won't be the only women who are there."
Learn more about Ganassi's Women In Motorsports program.
Follow IndyStar sports reporter Dana Benbow on Twitter:@DanaBenbow. Reach her via email:dbenbow@indystar.com.
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First woman to win an Indy 500 was Marcus Ericsson's engineer in ... - IndyStar
The Digital Economy Is At The Forefront Of Qatar National … – MENAFN.COM
(MENAFN- The Peninsula) By Alex Zhang CEO Huawei Technologies LLC
Digital technologies have transformed society on an unprecedented scale over the last two decades. They have changed the ways we live, work, play, commute, and interact. Today, it is digital technology that has the potential to bring in widespread social changes and economic advancement.
The emergence of a digital-first world requires countries to prepare for a digital first economy. Leading economies are developing digital plans and policies, investing in key digital technology sectors and ICT infrastructure to rebuild and realize a new enlarged GDP.
The government of Qatar already leading based onthe future is digital direction, prioritizing digitalization as a cornerstone of national development. Qatar has all the right ingredients to become a globally renowned leader in technology and innovation. Qatar National Vision 2030, a blueprint for economic and social development.
ICT helped Qatar to record one of the highest GDP per capita figures in the world. Through open and close collaboration between private and public sectors, the Qatari digital economy can be more inclusive, more competitive, more convenient, and well-positioned for continued growth. Thanks to Qatar 2030 National vision that emphasize digital transformation as a key pillar for growth. The positive results have already been gained in various industries such as the energy sector, telecom, education, and healthcare.
The strong commitment to ICT infrastructure development in the past enabled Qatar to lead in the digital era. Key projects and achievements include national Fixed Broadband (FBB) of 99% national penetration, 5G of 96% nationwide coverage, fastest network in the world, building local datacenter & cloud infrastructure and much more.
Huawei is committed to continue playing an active role to support Qatar building advanced ICT infrastructure through leadership in FBB and 5G technologies through long-standing partnerships partnership ties with local telecom service providers and government entities.
Huawei works with Qatar telecom operators and other enterprises to add new dimensions to Qatar's ICT development through 5.5G network evolution and technological innovation, maintaining Qatar's leading networks capabilities, and enhancing its global positioning and influence in the telecom industry.
Huawei is dedicated to using advanced technologies such as data mining analysis and AI to help local partners realize their digital transformation. Through digital platforms and tools, we fully cooperate with telecom operators in MBB, FBB, and service digitalization to truly improve efficiency, experience, and revenue.
In line with Qatar National Vision 2030, Huawei is keen to actively cooperate with all ecosystem partners to drive Qatar's digital transformation to new milestones. As AI (Artificial Intelligence) is a key pillar for the new world, building a national artificial intelligence center will help form a new model for industrial development with inclusive computing power, promoting the implementation of the national artificial intelligence strategy, including supporting policies, major scientific research, industry agglomeration, industry-university-research collaboration, industry applications, talent cultivation, and new national business card of AI. Achieving this key target will require having the right policies and funds in place to ensure all is set for relevant players to contribute to this goal.
As digital transformation accelerate, new cybersecurity challenges emerge. We must continuously improve cyber security to safeguard the development of the digital economy, which entails both challenges and opportunities. That means building digital trust and making critical infrastructure both more secure and more resilient.
A true demonstration of this capability was during the Qatar FIFA world cup, through our World Cup network Assurance project, Huawei achieved along with its partners outstanding standards of operation quality and ensured the security of the network infrastructure during the Global event.
Looking into the future, Huawei Qatar strategy is fully aligned with the 2030 vision, focusing on supporting Qatar to maintain its leadership in connectivity through leveraging leadership in MBB where we are jointly developing plans with our partners for 5.5G technology deployment, enabling 10Gbps speed, massive IoT and much more, paving the way for the next generation, 6G.
On the FBB domain, we are enhancing fiber technologies through F5.5 evolution. To accelerate cloud adoption in Qatar, Huawei developed an extensive cloud offering to support large enterprises as well as SMEs in Qatar to embrace digital transformation and migrate to cloud-native applications, accelerating investment in AI technology, and providing applications and use cases that benefit the Qatari market to boost productivity, reduce the workforce skills gap, and achieve full automation.
A sustainable digital economy will require more than connectivity. Green ICT solutions must also be prioritized. Huawei can help Qatar achieve a reduction in carbon emissions through intelligence and smart operation.
A sustainable digital economy demands a large pool of local talents that is proficient in the latest technologies and able to adapt to new developments quickly. Governments and businesses must continue to invest in training and education programs to ensure that workers have the skills they need to succeed in the digital economy.
Huawei is highly committed to supporting one of Qatar's key priorities, nurturing ICT local talent and building the ICT talent pool ecosystem. This is crucial to mold all-rounded graduates prepared for a dynamic digital-led workplace. Huawei will continue doing its part to advance the country's ICT skills with flagship initiatives and programs such as the ICT Competition, Seeds for the Future and Huawei ICT Academy.
Together with our partners in Qatar, we join forces to cultivate an ecosystem that is conducive to healthy and coordinated cross-sector development, driving the digital economy forward, accelerating digital transformation, and helping to speed up the arrival of an intelligent world.
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The Digital Economy Is At The Forefront Of Qatar National ... - MENAFN.COM
Legacy Overhaul & Data Mining at Top of Mind for Health Care … – GovCon Wire
Photo by Chor muang / Shutterstock.com
Due to the demands of the COVID-19 pandemic, the healthcare space has been pummeled over the last few years to answer the manifold and ever-growing needs of citizens. Many of these needs have solutions that can only be resolved through agencies information technology systems.
For us, during COVID, it was really about, how quickly can we leverage our growing capabilities in cloudWe stood up data analytics and visualization platforms. In partnership with Microsoft, we rapidly stood up a COVID bot on the website that enabled citizens to determine what they needed to do with regard to COVID symptoms. And we rapidly put in place border health monitoring capabilities, again, all leveraging cloud, said Centers for Disease Control Deputy Chief Information OfficerJason Bonander. The executive shared his thoughts during a recent event hosted by GovCon Wire.
Data administration and the replacement of legacy systems were the primary themes that arose in this discussion between private and public sector healthcare technology professionals. GCWs2nd Annual Healthcare IT Digital Transformation Forum featured Leidos Health Group Vice PresidentBobby Saxon as moderator for the Whats Next for Modernization panel.Leidos was also a Platinum sponsor of the May 17 event alongsideCore4ce and Silver sponsorUnanet.
If you missed the event, you can watch the full slate of discussion here. You can also browse and register for upcoming GCW eventshere and those from sister service Potomac Officers Clubhere.
Bonander went on to say that cloud is less a renegade modernization practice at this point than it is core infrastructure, a given. Still, he says it offers evergreen possibilities that the CDC is still mining in post-pandemic efforts where the agency has been prompted into realizing they must fundamentally modernize and change how [they] develop applications, how and where [they] host those applications. He says theyre operating at a quick pace in remaking and reimagining their offerings.
Fellow panelist Dr.Susan Monarez, deputy director of the Advanced Research Projects Agency Health, reported that her organization has the distinct benefit of being brand new, so it doesnt have any legacy systems to overturn. With regard to making progress in the government health technology space, Monarez said that the goal is to avoid getting into a situation where something that could be realized via an innovative tool or strategy in a matter of three to five years ends up taking 10 to 20 years.
To do so, Monarez says ARPA-H is attempting to break new ground in its field.
How do we take core concepts for the health ecosystem we talk about, from the molecular to the societal, and think about the problems in ways that just are fundamentally different than the way that folks have been thinking about the problemsHow could we actually start to address those problems in a way that hasnt been done before? Monarez explained of the research and development hubs mindset.
When Saxon queried the panelists about how their organizations are aiding decision support, Bonander said its about turning the massive amounts of data the CDC receives and processes into actionable insights in a way that benefits state and local health partners as well as the average citizen.
Data is the lifeblood of public health, Bonander stated, while Monarez said she loses a lot of sleep from excitement in thinking about the possibilities of creating a full-scale way to make health sector data actionable.
Core4ce CEOJack Wilmer noted the utility of artificial intelligence technologies in sorting through large amounts of data to boost decision making, but also said that its important to implement explainable AI whose choices and determinations can be legible to the citizen user.
In looking to the future, Wilmer, who previously worked for the Department of Defense, believes that, despite critiques that say the opposite, the government can actually be incredibly forward leaning in its modernization and innovation practices. Specifically, he referenced biosurveillance initiatives where existing data is being exploited in productive ways. Such practices might, Wilmer said, even help in the mission to predict or identify the next pandemic before its too late.
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Legacy Overhaul & Data Mining at Top of Mind for Health Care ... - GovCon Wire
The Power of AI in Data Mining: Unearthing Insights and Driving … – CityLife
The Power of AI in Data Mining: Unearthing Insights and Driving Business Decisions
In todays data-driven world, businesses are increasingly relying on the power of artificial intelligence (AI) to make informed decisions and gain a competitive edge. One area where AI has made a significant impact is data mining, the process of discovering patterns and extracting valuable insights from large datasets. As the volume of data generated by businesses continues to grow exponentially, AI-driven data mining has become an essential tool for organizations to unearth hidden insights and drive better business decisions.
Data mining has been around for decades, but the advent of AI has revolutionized the field by enabling more efficient and accurate analysis of vast amounts of data. Traditional data mining techniques often involve manual processes and require significant human intervention, making them time-consuming and prone to errors. In contrast, AI-powered data mining tools can automatically identify patterns and trends in data, enabling businesses to quickly uncover valuable insights and make data-driven decisions.
One of the key advantages of using AI in data mining is its ability to process and analyze unstructured data, such as text, images, and videos. This type of data is often difficult to analyze using traditional data mining techniques, as it requires complex algorithms and advanced natural language processing capabilities. AI-driven data mining tools can easily handle unstructured data, allowing businesses to gain insights from a wider range of sources and make more informed decisions.
Another significant benefit of AI-driven data mining is its ability to learn and adapt over time. As AI algorithms are exposed to more data, they can continuously improve their performance and accuracy, enabling businesses to gain deeper insights and make better decisions. This self-learning capability is particularly valuable in industries where data is constantly changing, such as finance, healthcare, and retail.
Moreover, AI-powered data mining can help businesses identify previously unknown relationships and correlations between different data points. This can lead to the discovery of new opportunities and the development of innovative strategies that may have been overlooked using traditional data mining techniques. For example, AI-driven data mining can help retailers identify new customer segments, predict demand for specific products, and optimize pricing strategies to maximize revenue.
In addition to driving better business decisions, AI-driven data mining can also help organizations improve their overall efficiency and productivity. By automating the data analysis process, AI-powered tools can significantly reduce the time and resources required to mine data, allowing businesses to focus on more strategic tasks and initiatives. Furthermore, AI-driven data mining can help organizations identify and address potential issues and inefficiencies, such as bottlenecks in production processes or areas where resources are being underutilized.
Despite its numerous benefits, the adoption of AI-driven data mining is not without challenges. One of the primary concerns is the potential for bias in AI algorithms, which can lead to inaccurate or misleading insights. To mitigate this risk, businesses must ensure that their AI tools are trained on diverse and representative datasets and regularly evaluate their performance to identify and address any potential biases.
Another challenge is the need for skilled professionals who can effectively leverage AI-driven data mining tools and interpret the insights they generate. As the demand for AI expertise continues to grow, businesses must invest in training and development programs to ensure their workforce is equipped with the necessary skills to harness the power of AI in data mining.
In conclusion, the power of AI in data mining has the potential to transform the way businesses make decisions and gain a competitive edge. By leveraging AI-driven tools to unearth valuable insights from vast amounts of data, organizations can make more informed decisions, improve efficiency, and drive innovation. As AI technology continues to advance, the impact of AI-driven data mining on businesses is only set to increase, making it an essential tool for organizations looking to stay ahead in todays data-driven world.
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The Power of AI in Data Mining: Unearthing Insights and Driving ... - CityLife
Celonis Launches New Process Mining Innovations to Deliver Fast, Substantial Value to Customers – Yahoo Finance
Showcasing new product capabilities during 10-city World Tour, including new object-centric data model and a more intuitive, open and intelligent platform
NEW YORK & MUNICH, May 23, 2023--(BUSINESS WIRE)--Celonis, the global leader in Process Mining, today showcases a series of powerful new product capabilities that enable companies to rapidly find and capture business value within their processes. At the Celonis World Tour 2023 - that kicked off today in Munich, Germany - the company demonstrates how it helps its customers to improve the performance of their core business processes. The new features demonstrate how the company has extended and enhanced its core platform and underscore how Celonis continues to reinvent process mining.
Object-Centric Data Model
Following on from the launch of Object-Centric Process Mining at Celosphere 2022, Celonis now introduces the Object-Centric Data Model, a new and powerful single data representation of an entire business that enables companies to dramatically accelerate the speed with which they can model their process data, gain critical insights, and take action to start realizing value. Celonis Object-Centric Data Model reduces the work needed to transform the data from source systems and operates side by side with Event Log Data Models, making the transition non-disruptive. It also powers Celonis new End-to-End Lead Times App - also launching today - which enables supply chain leaders to fully comprehend end-to-end lead times and understand the impact of each process to accelerate cash conversion and exceed service levels.
Benefits of Celonis Object-Centric Data Model include:
Simplicity. Businesses can work with a data model that uses the same language they do - for invoices, orders, deliveries rather than the language of source systems, to better model the business;
System agnosticity. Companies can take advantage of Celonis apps and process content, no matter which ERP, SCM, CRM or other source system they use, leveraging standardized business definitions and prebuilt transformations for core processes;
Flexibility. With traditional process mining, a business needs a data model for each process it wants to examine. With the new object-centric data model, organizations can dynamically adjust process analyses, switching perspectives from process to process without needing to go back to the source data. This significantly reduces onboarding time, and allows organizations to get to insights and key actions much faster.
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"I look forward to extending our usage of Celonis market-leading process mining solution throughout our organization," said Travis Cain, Senior Director Enterprise Architecture & Data Science Experience for Dell Technologies. "The Celonis Execution Management System has already provided us with tremendous benefits, including the ability to more easily find bottlenecks in our processes and get to deeper business insights more quickly. Using Celonis process mining capabilities gives us insights into the complexity of our operations and helps us to drive rapid business value by improving the performance of our core business processes."
"Object-centric process mining allows users to easily navigate through processes based on real-life objects and events, and fully unleashes the power of process mining," said Alex Rinke, co-founder and co-CEO at Celonis. "Customers can build and interact with their data more naturally, in a way they are already familiar with. With this new expanded data foundation, as well as the additional capabilities we are unveiling during this years World Tour, I am thrilled to show customers how Celonis provides them with unparalleled visibility, helps them disseminate process intelligence, and enables intelligent actions across the enterprise."
An Intuitive Platform: Process Intelligence Accessible to All Users
Celonis Business Miner, the industrys first intelligent process investigation technology and collaboration workspace, arms every business user with a breakthrough new way to easily, and independently investigate, communicate, and team up around process problems and opportunities. With it, Celonis deepens and democratizes the power of process mining so that everyone in an organization, not just analysts, can understand and improve process performance. No technical background is needed to be able to take advantage of process mining.
Celonis Business Miner is now generally available with process-specific explorations in Celonis core processes: Accounts Payable, Accounts Receivable, Procurement, and Order Management, as well as for additional process-agnostic explorations that focus on topics like cycle times, rework, and undesired activities.
With its intuitive question-and-answer-based exploration that provides quick and consumable insights, Celonis makes this powerful communication and collaboration tool accessible to all users with a Celonis Execution Management System (EMS) license, enabling unparalleled scalability and performance.
An Open Platform: Intelligence API
Celonis is also focused on providing its customers with an open platform - a critical strength recently recognized by Gartner.
First announced at Celosphere 2022 and generally available since March 2023, the Celonis Intelligence API is designed to provide governed access to Celonis process intelligence for use within third party applications.
The Intelligence API enables Celonis to bring unique process intelligence to tools as varied as PowerBI for reporting at scale, Slack for instant communication about process insights, and ServiceNow for rapid action triggered by process mining. Celonis itself uses Intelligence API to surface critical process insights within Salesforce to help its teams within software environments where they already work.
This makes the Intelligence API more open and accessible to an entire organization and enables intelligent orchestration and process-intelligent applications. Emporix, who launched their Commerce Execution Platform (CXP) at Celosphere 2022, are pioneering in this space. The Emporix CXP is a workflow engine that helps organizations optimize their business outcomes by leveraging process insights from Celonis.
Celonis provides the process context while Emporix orchestrates the end customers experience and interactions so that Emporix is delivering a better, more tailored customer experience as well as more efficient and cost-effective operations for customers.
Furthermore, the Intelligence API is a key component of Celonis platform strategy, as the company continuously aims to deliver a more intuitive, more open and more intelligent platform to its customers.
"The current macroeconomic climate demands better ways of working, which means organizations urgently need to improve their core business processes," says R "Ray" Wang, CEO and Principal Analyst, Constellation Research, Inc. "Processes are the fabric of every business, but many do not deliver much value - if any. With features such as the Object-Centric Data Model, Business Miner, and Intelligence APIs, customers can rapidly improve processes to achieve cost savings, increase customer satisfaction, meet regulatory requirements and boost overall performance."
The Celonis World Tour kicks off on May 23 and covers 10 stops across the US, Europe and Japan. It is Celonis global process mining roadshow where customers, prospects and partners share how, with Celonis, they are able to find and capture business value within processes, enabling them to perform at levels they never thought possible. The Celonis World Tour kicked off shortly after Celonis was named a leader in Gartners first-ever Magic Quadrant for Process Mining Tools. The report catapulted process mining into C-level consciousness and placed Celonis highest and farthest to the right on both axes, Ability to Execute and Completeness of Vision.
About Celonis
Celonis enables customers to optimize their business processes. Powered by its leading process mining technology, Celonis provides a unique set of capabilities for business executives and users to continuously find improvement opportunities within and across processes, and execute targeted actions to rapidly enhance process performance. This optimization yields immediate cash impact, radically improves customer experience, and reduces carbon emissions. Celonis has thousands of implementations with global customers and is headquartered in Munich, Germany and New York City, USA with more than 20 offices worldwide.
2022 Celonis SE. All rights reserved. Celonis, Execution Management System, EMS and the Celonis "droplet" logo are trademarks or registered trademarks of Celonis SE in Germany and other jurisdictions. All other product and company names are trademarks or registered trademarks of their respective owners.
View source version on businesswire.com: https://www.businesswire.com/news/home/20230523005621/en/
Contacts
Celonis press@celonis.com
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What are some controversies surrounding natural language … – FOX Bangor/ABC 7 News and Stories
As machine learning technology continues to shock the world, popular artificial intelligence tools such as natural language processing may generate unforeseen issues for humanity.
For instance, natural language processing can have implicit biases, create a significant carbon footprint, and stoke concerns about AI sentience. Natural language processing is a field in machine learning where a computer processes human language through vast amounts of data to understand, translate, extract, and organize information. However, the language processing tools such as Open AI's Chat GPT and other tools run into some challenges, such as misspellings, speech recognition, and the ability of a computer to understand the nuances of human language.
One of the biggest rising concerns regarding natural language processing is artificial intelligence programs' ability to have implicit bias and perpetuate stereotypes. One of the most essential tasks of natural language learning models is to study and learn patterns from data sets in order to understand how humans communicate with one another. Sometimes, these data sets can have implicit bias thinking that may affect how an AI learns the language and communicates its findings.
WORLD'S FIRST AI UNIVERSITY PRESIDENT SAYS TECH WILL DISRUPT EDUCATION TENETS, CREATE RENAISSANCE SCHOLARS
For example, suppose a dataset has language that assigns certain roles to men, such as computer programmers or doctors but assigns roles, like homemaker or nurse, to women. In that case, the AI program will implicitly apply those terms to men and women when communicating in real time. Therefore, stereotypes existing within the data set can lead to algorithms having language that applies unfair stereotypes based on race, gender, and sexual preference.
Political bias is another real concern for natural language processing programs that may lead to the impression of information based on the political preference of the data set used to train the AI. For instance, in February 2023, ChatGPT users discovered that the language processing program refused to communicate information about the Hunter Biden laptop story and speak about former President Donald Trump positively despite doing the same for President Joe Biden.
The political biases of machine learning language processing tools often result directly from the programmer or the dataset it is trained with. If the programmer refuses to correct those biases, it often leads to the suppression of news and information that may anger one side of the political spectrum.
Read below to discover other controversies and concerns regarding natural language processing.
One concern that individuals have had about the AI industry for years is a machine learning programs' ability to seemingly think for themselves and express feelings. Natural language processing models are often the version of AI that concerns individuals in this regard due to the computer's ability to mimic and present written text in a way that expresses the same emotions and thought patterns as humans.
AI TOOL HELPS DOCTORS MAKE SENSE OF CHAOTIC PATIENT DATA AND IDENTIFY DISEASES: 'MORE MEANINGFUL' INTERACTION
However, just because an AI program is coherent or as the ability to readily generate information does not mean the machine is sentient. It is not possible for AI to register experiences or feelings because it does not have the ability to think, feel, or perceive the world with a sentient mind.
Artificial intelligence, in general, but specifically natural language processing models, creates an environmental footprint that is comparable to the oil industry. Data mining, which is essential for the existence of artificial intelligence, consumes a large amount of electricity which releases carbon dioxide into the air. For instance, the data mining generated from cryptocurrency and AI-related programs between 2021-22 was responsible for an excess of 27.4 million tons of carbon dioxide into the air.
Natural language processing is a lucrative commodity yet has one of the largest environmental impacts out of all the other fields in the artificial intelligence realm. The process used to train, experiment, and fine-tune a natural language process model has been estimated to create on average more CO2 emissions than two Americans annually.
Some natural language processing programs that use neural architecture search created even more CO2 emissions that experts have estimated to be nearly five times more than the carbon footprint of a normal American car driver.
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What are some controversies surrounding natural language ... - FOX Bangor/ABC 7 News and Stories
High-Speed Engine Market to reach USD 29.9 billion by 2029 at a … – InvestorsObserver
High-Speed Engine Market to reach USD 29.9 billion by 2029 at a CAGR of 3.9 percent says Maximize Market Research
Pune, May 25, 2023 (GLOBE NEWSWIRE) -- A global Material & Chemical business consulting firm, Maximize Market Research has published a market intelligence and competitive landscape report on the High-Speed Engine Market . The report is a combination of primary data and secondary data and domain experts have analyzed the High-Speed Engine Market from a global point and regional standpoint. Over the forecast period, Maximize Market Research expects the market to grow from USD 23.6 Bn. in 2022 to USD 29.9 Bn. in 2029 at a CAGR of 3.9 percent.
High-Speed Engine Market Report Scope and Research Methodology
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The High-Speed Engine Market report includes a comprehensive analysis of emerging trends, market drivers, growth opportunities, and major restraints in the industry. It also provides a detailed analysis of the major segments of the High-Speed Engine Market with their sub-segments. The report covers historical data for understanding the past and forecasting future trends in the High-Speed Engine industry. To understand the structure of the market and the prevailing competition in the industry, a thorough regional and competitive analysis of the High-Speed Engine Market is covered in the report. The competitive landscape includes key players in the market along with new entrants. Regional analysis of the market is covered at global, regional, and country levels for understanding the market penetration, dominant players, and growth strategies used by them.
The bottom-up approach was used to estimate the global and regional High-Speed Engine Market size. The main research methodology used by the Maximize Market Research team is data triangulation which involves data mining , analysis of the impact of data variables on the High-Speed Engine Market, and primary (industry expert) validation. The report includes extensive use of secondary sources directories and databases such as Bloomberg, Hoovers, Statista and other government associations. The company websites and private websites have also been used to identify and collect information useful for the technical, market-oriented and commercial study of the High-Speed Engine Market. To provide strengths, weaknesses, opportunities, and threats in the High-Speed Engine Market, a SWOT analysis was used. PESTLE was employed to understand the potential impact of the micro-economic and macro-economic factors affecting the High-Speed Engine Market.
High-Speed Engine Market Overview
High-Speed Engine engines are typically used in high-performance vehicles, including sports cars, supercars, and race cars. They are designed to deliver exceptional power, torque, and acceleration, enabling the vehicles to achieve top speeds. Continuous advancements in engine technology contribute to the growth of the high-speed engine market.
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High-Speed Engine Market Dynamics
Advancements in engine technology are crucial for the high-speed engine market, playing a pivotal role in enhancing engine performance, efficiency, and reliability. Manufacturers are continuously innovating to improve these aspects by integrating technologies such as direct injection, turbocharging, variable valve timing, and lightweight materials into high-speed engines. These advancements result in increased power output, responsiveness, and fuel efficiency, fostering competition among manufacturers and driving the development of more powerful and efficient high-speed engines.
The automotive industry is currently undergoing a notable transition towards electric and hybrid powertrains. This shift presents both challenges and opportunities for the high-speed engine market. The increasing demand for electric vehicles (EVs) and hybrid vehicles has significantly influenced the market dynamics. In this context, Ferrari holds a prominent position in the high-speed engine market. The company is renowned for its exceptional V8 and V12 engines, which power its sports cars and supercars, solidifying its presence in the industry.
High-Speed Engine Market Regional Insights
North America is expected to be the leading revenue contributor in the High-Speed Engine market during the forecast period. The presence of a well-established industrial sector, technological advancements, and a strong focus on energy efficiency and emissions regulations drive the demand for high-speed engines. The North American high-speed engine market is highly competitive with the presence of both domestic and international manufacturers. Prominent manufacturers in the region include Cummins Inc., Caterpillar Inc., and MTU America among others. These companies offer a wide range of high-speed engines with varying power outputs and applications catering to the diverse needs of industries in North America.
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High-Speed Engine Market Segmentation
By Speed
By Power Output
High-Speed Engine Market's Key Competitors include:
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Key Offerings:
Key questions answered in the High-Speed Engine Market are:
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Maximize Market Research is a multifaceted market research and consulting company with professionals from several industries. Some of the industries we cover include medical devices, pharmaceutical manufacturers, science and engineering, electronic components, industrial equipment, technology and communication, cars and automobiles, chemical products and substances, general merchandise, beverages, personal care, and automated systems. To mention a few, we provide market-verified industry estimations, technical trend analysis, crucial market research, strategic advice, competition analysis, production and demand analysis, and client impact studies.
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High-Speed Engine Market to reach USD 29.9 billion by 2029 at a ... - InvestorsObserver
Time-series analysis of satellite imagery for detecting vegetation … – Nature.com
Regional context
Indonesia (officially the Republic of Indonesia) is the largest archipelago country (over 17,000 islands) and the 14th largest country by area (about 2 million km2) in the world 19. The archipelago covers tropical rainforest, tropical monsoon, and tropical savanna climates, where there are more than 300 ethnic groups 19. Indonesia consists of 38 provinces, and the governance system is decentralized since the end of the twentieth century 19,20. In Indonesia, regencies (kabupaten) and representative cities (kota) are positioned at the same administrative level (level 2); the average size of regencies/cities is 3622 km2 (ranging from 10 to 44,013 km2). Regencies/cities are administratively separated by geographic conditions and historical (social, cultural, and political) backgrounds, with each regency/city having homogeneous environmental conditions and a socioeconomic status. 16.
The main drivers of the rapid deforestation in Indonesia were population growth and economic expansion, including the illegal clearance of forests 21,22. Indonesias economy has grown by>5% per year on average since 2000 until the Covid-19 pandemic; GDP PPP (international dollars) increased about three times from 1 Trillion USD in 2000 to 3.33 Trillion USD in 2019 23. Additionally, its population has increased by 1.14% annually, leading to an approximately 30% growth during this period (i.e., from 211 Million in 2000 to 273 Million in 2020), making it the most populous and prosperous country in Southeast Asia 19. Indonesia is also one of the largest emitters of greenhouse gases (GHG) 24.
In contrast, the Indonesian government is committed to unconditionally reduce its GHG emission by 29% and up to 41% if international assistance for finance, technology transfer, and capacity building are provided25. The land-use and energy sectors are to minimize the national GHG emission. Therefore, Indonesia first introduced moratorium on new forest clearance in 2011 26 and made it permanent in 2019 3. This moratorium mainly targeted Kalimantan, Sumatra, and Papua (New Guinea), which had been center of deforestation in the beginning of 2000s 3,27.
Meanwhile, agriculture has expanded in this century, with the primary export goods (e.g., oil palm and rubber plantations) coming from Sumatra and Kalimantan 5. Conversely, since the turn of the century, sustainable forestry policies in Java have caused a surge in the forestation of local smallholders 6. There are indications that forests on Java Island are recovering 7,8. Due to improved forestry policies and reforestation activities, the deforestation rate has decreased since 2011 9. Deforestation has been reported from all over Indonesia, but the causes of deforestation were different from one region to another because of geographic conditions and socioeconomic statuses 28.
Many studies have demonstrated that the NDVI is related to the leaf area, green biomass, percent green cover, and a fraction of absorbed photosynthetically active radiation (fAPAR) 18,29,30; moreover, NDVI is a global-based vegetation index. We utilized the product of NASA's MODIS Terra Program version 6.1. This product provides data at 16-day intervals (i.e., composite data for a 16-day period derived from images that are acquired almost every day) at 250m spatial resolution after correction for atmospheric effects (aerosols and gases) and sensor degradation, angular consideration, and minimization of the influence of daily cloud covers for consistent spatial and temporal comparisons of vegetation 17,18. The NDVI runs from1 to+1 (acceptable range for the NDVI of the MODIS: from0.2 to+1) and is determined from the visible and near-infrared light reflected by the quantity (biomass) and/or composition of vegetation.
The information used was from LP DAAC, a part of NASAs Earth Observing System Data and Information System run in cooperation between the US Geological Survey and NASA. We utilized the shapefile of Administrative Level 2 in April 2020 created by the Indonesian Bureau of Statistics (BPS). This was made available through the Humanitarian Data Exchange program (HDX) of the United Nations Office for Coordination of Humanitarian Affairs (OCHA) (https://data.humdata.org/) 31. The Administrative Level 2 consisted of 93 cities (kota), five administrative cities (kota administrasi), 415 regencies (kabupaten), and one administrative regency (kabupaten administrasi) (Supplementary Table 1). Each MOD13Q1 picture was dissected for the Administrative Level 2 and pixel reliability (1: no data; 0: excellent data; 1: poor data; 2: snow/ice; and 3: cloud). The coastal regions, where the pixels had recorded water cover, experienced the pixel reliability of MOD13Q1 with1 (no data). The NDVI was unreliable when the pixels were classified as level 2 (snow/ice). No NDVI was available for the pixels covered in clouds (pixel reliability=3). These cases were disregarded from further analysis. Hence, the average NDVI was determined for regions in each regency/city at each time point with a pixel reliability range of 0 or 1. Seribu Islands was the sole administrative regency, which was omitted from the studies because it was composed of a number of tiny islands, and all pixels covering it had some sea in them. Accordingly, further evaluations were conducted for 513 regencies and cities throughout a 20-year span (i.e., every 16days; 460 time points). We downloaded a total of 5520 pictures since 12 MOD13Q1 images at each time point cover the whole Indonesia.
We split the NDVI changes in the MOD13Q1 data into trends, seasonal changes, and residuals using a stochasticlevel and deterministic seasonal state space model (SSM). We performed time-series studies based on SSM 32 using two steps 16: (1) the NDVI data were averaged for each geographic unit (regency or city); and (2) stochasticlevel and deterministic seasonal models were used. The time-series change in this model was divided into trends, cycles, and residuals while excluding noises. The slopes and the levels were determined by a stochastic process, seasonal changes (annual cycle), and irregular changes with interporation of missing datasmoothed by the Kalman filter. The maximum likelihood estimation was made for the following equations:
$${y}_{t}={mu }_{t}+ {gamma }_{t}+ {varepsilon }_{t}, {varepsilon }_{t}sim mathrm{NID} left(0, {sigma }_{varepsilon }^{2}right)$$
$${mu }_{t+1}={mu }_{t}+{xi }_{t}, { xi }_{t}sim mathrm{NID}(0,{sigma }_{xi }^{2})$$
$${gamma }_{1, t+1}= {-gamma }_{1, t} {-gamma }_{2, t}dots {-gamma }_{22, t}$$
$${gamma }_{2, t+1}= {gamma }_{1, t}$$
$${gamma }_{22, t+1}= {gamma }_{21, t}$$
for t=1, n, where ({y}_{t}) is the observation (NDVI) at time t; ({mu }_{t}) is the unobserved level at time t; ({gamma }_{t}= {gamma }_{1, t}) denotes the seasonal component; ({varepsilon }_{t}) is the observation disturbance term at time t; and ({xi }_{t}) is called the level disturbance term at time t. The level ({mu }_{t}) was allowed to vary over time in the stochasticlevel and deterministic seasonal model. The seasonal changes, trends, and residuals are represented by , , and , respectively. R Software version 4.1.2 with dlm package was used for the analysis 33.
The USGS Earth Resources Observation and Science Center and the Climate Hazard Center of the University of California in Santa Barbara developed climate hazards group infrared precipitation with station (CHIRPS) v2p0, which provide data on rainfall estimates from rain gauge and satellite observations and is available for the entire world, including areas with sparse surface data 34. CHIRPS provide moderate resolution (0.05) gridded precipitation information. We obtained the CHIRPS monthly data for Indonesia from 2001 to 2020 and masked them at the administrative 1 (province) level (data compiled by Indonesian Statistical Office and available at OCHA HDX) because the resolution of CHIRPS is coarser than that of MOD13Q1. Using the same SSM model with the NDVI data, we decomposed the precipitation data into trends and seasonal cycles while excluding noises.Furthermore, the monthly average precipitation for each province over the course of 20 years was calculated from this dataset (rainfall level).
We used the population density data and the GDP at the regency/city level issued by the Ministry of Internal Affairs of the Republic of Indonesia 35. However, we were unable to study the time-series changes in socioeconomic development over a 20-year period because the administrative units increased from 397 in 2001 to 514 in 2020 due to the administrative reforms brought about by population and economic growth. The data used in this study were (1) the population densities in 2020, (2) GDP proportion from agriculture, forestry, and fisheries (as an indicator of the land-use intensities for agricultural and forestry development), and (3) GDP proportion from financial and insurance activities (as urban development). These indicators reflected the socioeconomic conditions of Indonesia, where the inequality in development among regions is very high. The total GDP was not used because it was closely correlated with the three variables used in this work.
After obtaining results of time-series analyses, we also conducted field observations in 2022 in North Sumatra, the Special Capital Region of Jakarta, Central Java, the Special Region of Yogyakarta, and South Sulawesi. We visited regencies and cities showing very consistent increases or decreases in NDVI, rapid loss or growth in NDVI, or dramatically irregular changes (e.g., disasters); furthermore, we observed the reasons behind such changes. In addition, we observed vegetation changes between 2014 and 2017 in parts of East Nusa Tenggara 16.
We defined the Pearsons correlation coefficients of the NDVI trend (after noise and cycle elimination) with time (every 16day) as the NDVI consistent trend. Furthermore, we defined the NDVI variation between 2001 and 2020 (in other words, differences in the average NDVI between 2020 and 2001) as the NDVI value change. Pettitts Test was used to identify the trend change-points 36. For precipitation, the correlation of the trend with time and the difference in the NDVI between 2020 and 2001 were also computed (CHIPRS data).
We used classification and regression trees (CART), a decision tree model data mining method that explains how a target variable is predicted by other variables based on categorizing samples into binary classes 37; exponential was used for NDVI consistent trend. The decision tree regression analysis was conducted to explore factors contributing to the consistent trend of the NDVI and the NDVI value changes. To minimize overfitting, the complexity parameter (cp) value for the biggest cross-validated prediction error of less than the minimal relative error plus the cross-validated prediction standard deviation was used as the cut-off (pruning tree model). To reflect the differences in agricultural intensities and main tree crops, all regencies and cities were classified into Sumatra, Western Kalimantan, Eastern Kalimantan, Western Java, Eastern Java, Nusa Tenggara, Northern Sulawesi, Southern Sulawesi, Maluku, and Papua (Supplementary Fig.1). QGIS 3.22.4 Biaowiea (QGIS Development Team) (https://qgis.org/) was utilized for the map creation.
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Time-series analysis of satellite imagery for detecting vegetation ... - Nature.com
Energy Web Launches Certification for Sustainable Bitcoin Mining – GlobeNewswire
ZUG, Switzerland, May 24, 2023 (GLOBE NEWSWIRE) -- Energy Web, an independent non-profit that develops open-source software for clean energy solutions, today announced the launch of Green Proofs for Bitcoin (GP4BTC), a first-of-its kind initiative to establish an independent, standardized energy measurement system for the Bitcoin mining industry.
GP4BTC will provide transparency into the decarbonization efforts of Bitcoin miners and hosting companies, supporting the industry on its journey to net-zero. As part of the solution, certifications will be issued to Bitcoin miners based on their clean energy use and contributions to grid stability via demand response. By delivering verifiable metrics that are consistent across companies and geographies, GP4BTC will provide recognition and reputational benefit for companies mining sustainably, as well as improved access to institutional finance and other returns on their investments into sustainability practices.
Speaking on the launch of the certification initiative, Amy Westervelt, Senior Delivery Lead and head of the GP4BTC initiative at Energy Web, said Today Bitcoin is scrutinized for its electricity consumption and associated climate impact. While leading miners are pursuing strategies to reduce their carbon footprints, the industry lacks a unifying definition of sustainable mining, as well as a shared framework for assessing and verifying miners sustainability practices. Green Proofs for Bitcoin seeks to provide this.
Launched with five certified miners, the GP4BTC certification platform and registry assesses miners via a Clean Energy Score and a Grid Impact Score, each of which are calculated based on operational information including location and energy consumption data. Together, these scores reflect miners procurement of renewable electricity, siting operations in regions with low grid carbon intensity, and their contributions to grid stability through demand flexibility.
Developed in partnership with over 35 miners, NGOs, grid operators, and other energy and crypto market participants, this approach to scoring is aligned with best practices for sustainability leadership in other industries, and to approaches to corporate ESG reporting in the financial sector and beyond.
Until now, efforts to standardize clean energy procurement practices and drive collective action across the Bitcoin mining sector have been siloed and inconsistent, added Westervelt. While other electricity-intensive industries have benefited from custom decarbonization roadmaps, Bitcoin has largely been ignored, creating a negative feedback loop where climate-conscious miners are left to forge their own paths. Our goal is to create a virtuous cycle where clean mining is easier to define, pursue, and monetizeso that it eventually becomes the status quo.
For miners, GP4BTC offers a solution for miners to provide evidence of clean energy practices. Using Energy Webs privacy-first Green Proofs technology, miners retain full ownership and control of their data. For Bitcoin users and institutions, GP4BTC provides a one-stop-shop for discovering and validating miners' sustainability credentials so they can make data-driven decisions regarding commercial strategy and policy. At launch, certified miners and data centers include Argo Blockchain, Cowa, DMG Blockchain Solutions, Hive Blockchain Technologies, and Gryphon Digital Mining.
DMGs CEO,SheldonBennett, commented, We are pleased to be included among the initial Green Proofs for Bitcoin miner participants. We believe Energy Webs launch of Green Proofs for Bitcoin represents a real first step towards recognizing a broad swath of industry participants for powering their data center equipment utilizing primarily carbon neutral energy sources.
This initiative will settle the basis for long term sustainability within the Bitcoin mining industry. We are proud to contribute to the growth of the ecosystem and to have the ability to certify our commitment towards sustainability, said Fiorenzo Manganiello, co-founder of Cowa.
Decarbonization represents one of the main priorities for the sector, and by providing standardized and verifiable metrics, as well as acknowledging best practices with certifications, initiatives such as Energy Webs Green Proofs for Bitcoin serve a fundamental role in driving industry standards. At Argo, sustainable mining has been at the core of our business model and growth strategy ever since our foundation. We are proud of our GP4BTC certification, and we look forward to contributing to the impact and success of this exciting initiative,said Seif El-Bakly, Interim CEO at Argo Blockchain.
President and CEO of Hive Blockchain Technologies Aydin Kilic commented, In our commitment to be green energy focusedwhich has been our mandate since HIVE went public back in 2017 as the first publicly traded crypto minerwe are glad to see the industry embracing this strategy, and advocates like Energy Web helping to validate and certify the renewable aspects of crypto miners. This makes our industry stronger. We hope that the public, along with policy makers and utility companies, realize that a large contingent of crypto miners are utilizing renewable energy.
Gryphon Digital Minings CEO Rob Chang urges the Bitcoin mining industry to start providing concrete evidence of sustainable mining practices. We need to move past pandering press releases and start offering tangible, coordinated, third-party certifications that confirm clean energy use, Chang emphasized. We believe in GP4BTCs mission and proudly announce that Gryphon is one of the first recipients of its certification. As Bitcoin mining continues to grow, it is critical to prioritize sustainable practices and hold the industry accountable for its impact on the environment.
Energy Web is keen to work with any Bitcoin miner or other party interested in using Green Proofs for Bitcoin. Miners and data centers can learn more about the solution and apply for certification directly at http://www.GP4BTC.org or by contacting gp4btc@energyweb.org.
About Energy Web
Energy Web is a global non-profit accelerating the clean energy transition by developing open-source technology solutions for energy systems. Our enterprise-grade solutions improve coordination across complex energy markets, unlocking the full potential of clean, distributed energy resources for businesses, grid operators, and customers. Our solutions for enterprise asset management, data exchange, and Green Proofs, our tool for registering and tracking low-carbon products, are underpinned by the Energy Web Chain, the worlds first public blockchain tailored to the energy sector. The Energy Web ecosystem comprises leading utilities, renewable energy developers, grid operators, corporate energy buyers, automotive, IoT, telecommunications leaders, and more. More information on Energy Web can be found atwww.energyweb.orgor follow us on Twitter@EnergyWebX
Media contact
Daniyal AjdadiEnergy Webdaniyal.ajdadi@energyweb.org
Gavin CahillSillionGavin.cahill@sillion.co.uk+44 20 3858 7800
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Energy Web Launches Certification for Sustainable Bitcoin Mining - GlobeNewswire