Category Archives: Data Mining
Cracking the code: The rising demand for data scientists in various … – Data Science Central
In the ever-evolving landscape of the digital era, the relentless quest for deriving actionable insights from a sea of information has become the cornerstone of innovation and strategy. As businesses and organizations strive to navigate the complex corridors of big data, the spotlight invariably falls upon the expertise of data scientists, the modern-day architects of data comprehension and utilization. These professionals stand at the intersection of analytics, programming, and sector-specific knowledge, meticulously deciphering patterns and trends that can steer pivotal decisions and strategies.
At this pivotal juncture, a burgeoning demand for data scientists is witnessed across industries, transcending traditional boundaries and embedding itself as a necessity in various sectors. As we stand on the cusp of a data-driven revolution, dissecting this soaring demand and delineating the pathways for aspiring individuals to embark on a promising journey in this field is imperative.
Data science emerges as a formidable chapter in the grand narrative of technological evolution, heralding a new era of informed decision-making and innovation. The discipline has metamorphosed from tracing its roots to statistical analysis and data mining, incorporating sophisticated algorithms and computational abilities into its arsenal. The synthesis of statistics, computer science, and domain expertise, which forms the cornerstone of data science, has evolved to tackle the complexities of modern-day data structures and voluminous datasets.
At its nascent stage, the focus was primarily on data collection and storage; however, as technology advanced, the emphasis shifted towards extracting meaningful insights from this stored data. A data scientist harnesses data and communicates the extracted information effectively to influence business strategies and policies. As we navigate further into the digital age, the evolution of data science becomes even more intricate, expanding its reach and influence and solidifying its crucial role in various industries around the globe.
As the world increasingly transitions to a data-centric modality, the role of a data scientist evolves into a vital pillar supporting the scaffold of contemporary industries. Being a data scientist is akin to being a storyteller, a detective, and a strategist. These professionals must weave through the labyrinthine pathways of data, sifting through the noise to discern patterns and draw actionable insights that foster innovation and drive business acumen.
At the heart of their skill set lies a robust foundation in mathematics and statistics, coupled with an adept understanding of programming languages and tools essential for data manipulation and analysis. Often, a Master in Data Science degree stands as testimony to their refined expertise, augmenting their ability to merge technical prowess with business intelligence. Moreover, they are expected to have a keen eye for detail and a profound understanding of their industry, allowing them to tailor their approaches to solving complex problems with data-driven solutions.
The allure of this profession lies in its dynamic nature, where no two days are the same. Daily, they grapple with new challenges, continuously innovating and enhancing their strategies to adapt to the changing tides of the business landscape. Thus, a data scientist emerges as a beacon of expertise, guiding organizations toward a future with informed decisions and calculated strides toward progress and growth.
In an epoch where data is dubbed the new oil, industries across the spectrum are witnessing an unprecedented surge in the demand for data scientists. This uptick is not confined to the realms of technology and finance but permeates into sectors as diverse as healthcare, e-commerce, and manufacturing.
Thus, the rising demand for data scientists across diverse industries is a testament to the professions versatility and the immense value it adds in deciphering complex data, fostering innovation, and driving informed strategies, promising a transformative impact on the global industrial landscape.
As the clamor for data science expertise escalates, the existing educational pathways are witnessing a metamorphosis to foster a brigade equipped with the requisite skills and knowledge. A vital instrument in this endeavor has been the proliferation of online data science courses, offering accessible and flexible avenues for learning. These platforms are meticulously curated to bridge the skill gap, paving the way for aspirants to venture into this lucrative field with a solid foundation.
In this dynamic scenario, continuous learning emerges as a quintessential aspect. The data science landscape is ever-evolving, necessitating professionals to keep up-to-date with the latest tools and techniques. These educational platforms serve as hubs of knowledge dissemination, fostering a community of learners keen to innovate and drive change.
Thus, in the wake of a data-driven era, the educational sphere is stepping up, offering diverse and robust channels to nurture the next generation of data scientists, ready to steer the wheel of innovation in various industries.
As we stand at the nexus of technological advancement and data proliferation, the role of data scientists crystallizes as instrumental in shaping a progressive future. From fostering innovation in healthcare to propelling advancements in finance and manufacturing, the prowess of data science is undeniably transformative. Aspiring professionals stand before an open vista of opportunities, where acquiring skills through a data science course can be the gateway to making significant strides in this dynamic field. In this data-centric epoch, a career in data science is a personal progression and a contribution to a global movement toward a brighter, more informed, innovative society.
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Cracking the code: The rising demand for data scientists in various ... - Data Science Central
Interdisciplinary Rice team tackles the future of semiconductors – Rice News
An interdisciplinary team of Rice University scientists has won a $1.9 million National Science Foundation grant for research on materials that could serve as the basis for next-generation energy-efficient computing devices.
The team led by Kaiyuan Yang and including co-investigators Ramamoorthy Ramesh, Yimo Han, Douglas Natelson, Shengxi Huang and Lane Martin will focus on multiferroics, materials with distinctive electric and magnetic properties that carry transformative technological potential, said Ramesh, who is a leading expert in the field. Specifically, the researchers will seek to leverage the spin and charge of electrons in multiferroics in order to process and store information.
The project is supported by the NSF Future of Semiconductors (FuSe) program through a public-private partnership between the NSF and four leading technology corporations. The FuSe initiative aims to enable rapid progress in new semiconductor technologies and manufacturing as well as workforce development, according to the agencys website.
By 2030, about 25% of global energy demand will come from electronics thats a pretty huge number, said Ramesh, Rices executive vice president for research and professor of materials science and nanoengineering and of physics and astronomy. With this FuSe grant, our goal is to lower energy consumption for computing. We put together a perfect team to help push the limits of the science and take significant strides toward actually making these low-energy computing devices a reality.
Rices project, titled Ultra-Low-Energy Logic-in-Memory Computing using Multiferroic Spintronics, is one of 24 research and education projects funded under the $45.6 million initiative, which includes funding from the 2022 CHIPS and Science Act keystone bipartisan legislation that aims to secure a leading role for the U.S. in numerous technological fields including nanotechnology, quantum computing, artificial intelligence and clean energy.
Existing computing devices are based on silicon and complementary metal-oxide-semiconductor (CMOS) chips, Yang said. This technology has major limitations that lead to high energy consumption and limited throughput for large-scale artificial intelligence (AI) computing and massive data mining applications. One of these limitations is that all CMOS-based semiconductor devices generate a certain amount of thermal noise (random heat).
Lowering operating voltage is the prerequisite to improving these devices energy consumption, but the technology is facing an impasse.
You cannot lower your operating voltage below a certain value, or your signal will get drowned out in that thermal noise, said Yang, an associate professor of electrical and computer engineering.
Another major limitation in current mainstream processors is that computing and memory tasks are performed separately, leading to major inefficiencies.
Most of the time, youre just moving information back and forth between where memory is stored and where logic operations take place, Ramesh said. Up to 70% of the energy consumed is squandered in this transfer. Imagine needing to move funds between bank accounts in New York and, say, Zurich every few hours youd lose so much in commissions you could go broke.
The hope is that multiferroics-based devices would not only improve computing energy efficiency by as much as three orders of magnitude, but that it would also enable a seamless integration of memory and logic functions.
A single device could simultaneously be both a memory cell and a computing gate, said Yang, whose expertise is rooted in circuit design and processing architectures. I will help lead the knowledge derived from fundamental research on multiferroics toward an actual computing application.
In order for that to happen, the team will work on gaining an in-depth understanding of multiferroics.
Huang, an associate professor of electrical and computer engineering, plans to use high-throughput, noninvasive methods to characterize the materials, their interfaces and the devices made from them.
I will work closely with the PIs on material synthesis, atomic characterization and device fabrication to achieve the goal of multiferroic spintronic devices and systems, said Huang, who hopes such materials and devices will play a part in overcoming energy bottlenecks in current mainstream technologies.
Han, an assistant professor of materials science and nanoengineering, will perform advanced, atomic-level imaging to help improve and debug the material.
Low-power computing is a very important direction for the semiconductor industry to pursue, and were developing the materials that will enable it to do so, said Han, who emphasized the timeliness and urgency of the research by noting that the energy needed to train an AI-powered language model like ChatGPT could power the city of Houston for a whole year.
Natelson, whose research group will help with the device fabrication and electrical measurements of the multiferroics critical properties, said the top notch combination of people and expertise will hopefully find creative ways to combine logic and memory in individual devices that operate at much lower voltages than present technologies.
Its great that the Rice team has been selected to be part of this important program, said Natelson, a professor of physics and astronomy. This is an opportunity to have a major impact on this urgent technical need while doing some excellent basic research.
Team members span a broad range of expertise from fundamental materials research to device physics to circuit design and architectures, showcasing a core Rice strength of working across disciplinary boundaries and fueling innovation through collaboration.
Real problems are at the boundaries between research fields, said Martin, who leads the Rice Advanced Materials Institute (RAMI) one of a constellation of recent university initiatives intended to foster research collaboration and accelerate innovation. No single person could take on what is truly an existential challenge for the computing field, so weve put together a great combination of people across different programs and departments.
The institute led by Martin will be housed in the Ralph S. OConnor Building for Engineering and Science, a landmark new research facility the university hopes will attract and retain talented faculty and graduate students with its customizable, cutting-edge labs and amenities.
In a sense, RAMI is the embodiment of the collaborative, interdisciplinary spirit that brought this team together, said Martin, Rices Welch Professor of Materials Science and Nanoengineering and a professor of physics and astronomy. The institute seeks to amplify the impact generated by research collaborations such as this one in order to address some of these generational challenges like the limitations of current computing technologies.
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329111
https://news-network.rice.edu/news/files/2023/09/230728_Dao_Fitlow_015.jpg CAPTION: Kaiyuan Yang is an associate professor of electrical and computer engineering at Rice University. (Photo by Jeff Fitlow/Rice University)
https://news-network.rice.edu/news/files/2023/09/230126_Ramesh_Fitlow.jpg CAPTION: Ramamoorthy Ramesh is Rices Executive Vice President for Research and a professor of materials science and nanoengineering and of physics and astronomy. (Photo by Jeff Fitlow/Rice University)
https://news-network.rice.edu/news/files/2023/09/230606_Yimo_Han__Fitlow_472-9.jpg CAPTION: Yimo Han is an assistant professor of materials science and nanoengineering at Rice University. (Photo by Jeff Fitlow/Rice University)
https://news-network.rice.edu/news/files/2023/09/Shengxi-H-small.jpg CAPTION: Shengxi Huang is an associate professor of electrical and computer engineering. (Photo courtesy of Shengxi Huang/Rice University)
https://news-network.rice.edu/news/files/2023/09/230404_Lane_Fitlow_001-12.jpgCAPTION: Lane Martin is Rices Welch Professor of Materials Science and Nanoengineering and director of the Rice Advanced Materials Institute (RAMI). (Photo by Jeff Fitlow/Rice University)
https://news-network.rice.edu/news/files/2023/09/image0.jpeg CAPTION: Douglas Natelson is a professor of physics and astronomy, electrical and computer engineering and materials science and nanoengineering at Rice University. (Photo courtesy of the Natelson research group/Rice University)
NSF backs Rice processor design, chip security research: https://news.rice.edu/news/2023/nsf-backs-rice-processor-design-chip-security-research
Rice announces commitment to advance interdisciplinary research at new and existing research institutes:https://news.rice.edu/news/2023/rice-announces-commitment-advance-interdisciplinary-research-new-and-existing-research
Yimo Han wins NSF CAREER Award:https://msne.rice.edu/news/yimo-han-wins-nsf-career-award
Shengxi Huang Awarded Welch Foundation Grant:https://www.ece.rice.edu/news/shengxi-huang-awarded-welch-foundation-grant
Rice U. vice president for research named to AAU task force on expanding India partnerships:https://news.rice.edu/news/2023/rice-u-vice-president-research-named-aau-task-force-expanding-india-partnerships
Rice selects Lane Martin to lead new Advanced Materials Institute:https://news.rice.edu/news/2023/rice-selects-lane-martin-lead-new-advanced-materials-institute
Ramesh named Rice Universitys vice president for research:https://news.rice.edu/news/2022/ramesh-named-rice-universitys-vice-president-research
Rice Quantum Initiative hires first two faculty:https://engineering.rice.edu/news/rice-quantum-initiative-hires-first-two-faculty
Department of Physics and Astronomy: https://physics.rice.edu/
Department of Electrical and Computer Engineering: https://eceweb.rice.edu/
Department of Materials Science and NanoEngineering: msne.rice.edu
Ken Kennedy Institute: https://kenkennedy.rice.edu/
Rice Quantum Initiative: https://quantum.rice.edu/
Smalley-Curl Institute: https://sci.rice.edu/
Bioscience Research Collaborative: https://brc.rice.edu/
Han lab: http://hanlab.blogs.rice.edu/
SCOPE lab: https://scopelab.rice.edu/
Secure and Intelligent Micro-Systems (SIMS) lab: https://vlsi.rice.edu/
Natelson research group: https://natelson.rice.edu/group.html
George R. Brown School of Engineering: https://engineering.rice.edu
Located on a 300-acre forested campus in Houston, Rice University is consistently ranked among the nations top 20 universities by U.S. News & World Report. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy. With 4,552 undergraduates and 3,998 graduate students, Rices undergraduate student-to-faculty ratio is just under 6-to-1. Its residential college system builds close-knit communities and lifelong friendships, just one reason why Rice is ranked No. 1 for lots of race/class interaction and No. 4 for quality of life by the Princeton Review. Rice is also rated as a best value among private universities by Kiplingers Personal Finance.
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Interdisciplinary Rice team tackles the future of semiconductors - Rice News
Lundin Mining Corporation’s (TSE:LUN) institutional investors lost 8.8% last week but have benefitted from longer-term gains – Simply Wall St
Key Insights
Every investor in Lundin Mining Corporation (TSE:LUN) should be aware of the most powerful shareholder groups. And the group that holds the biggest piece of the pie are institutions with 43% ownership. Put another way, the group faces the maximum upside potential (or downside risk).
No shareholder likes losing money on their investments, especially institutional investors who saw their holdings drop 8.8% in value last week. Still, the 33% one-year gains may have helped mitigate their overall losses. But they would probably be wary of future losses.
Let's delve deeper into each type of owner of Lundin Mining, beginning with the chart below.
See our latest analysis for Lundin Mining
Institutional investors commonly compare their own returns to the returns of a commonly followed index. So they generally do consider buying larger companies that are included in the relevant benchmark index.
We can see that Lundin Mining does have institutional investors; and they hold a good portion of the company's stock. This can indicate that the company has a certain degree of credibility in the investment community. However, it is best to be wary of relying on the supposed validation that comes with institutional investors. They too, get it wrong sometimes. It is not uncommon to see a big share price drop if two large institutional investors try to sell out of a stock at the same time. So it is worth checking the past earnings trajectory of Lundin Mining, (below). Of course, keep in mind that there are other factors to consider, too.
We note that hedge funds don't have a meaningful investment in Lundin Mining. Our data shows that Capital Research and Management Company is the largest shareholder with 15% of shares outstanding. For context, the second largest shareholder holds about 15% of the shares outstanding, followed by an ownership of 4.9% by the third-largest shareholder.
A closer look at our ownership figures suggests that the top 17 shareholders have a combined ownership of 50% implying that no single shareholder has a majority.
While it makes sense to study institutional ownership data for a company, it also makes sense to study analyst sentiments to know which way the wind is blowing. There are plenty of analysts covering the stock, so it might be worth seeing what they are forecasting, too.
The definition of company insiders can be subjective and does vary between jurisdictions. Our data reflects individual insiders, capturing board members at the very least. The company management answer to the board and the latter should represent the interests of shareholders. Notably, sometimes top-level managers are on the board themselves.
Most consider insider ownership a positive because it can indicate the board is well aligned with other shareholders. However, on some occasions too much power is concentrated within this group.
Our most recent data indicates that insiders own less than 1% of Lundin Mining Corporation. But they may have an indirect interest through a corporate structure that we haven't picked up on. It is a pretty big company, so it would be possible for board members to own a meaningful interest in the company, without owning much of a proportional interest. In this case, they own around CA$20m worth of shares (at current prices). Arguably, recent buying and selling is just as important to consider. You can click here to see if insiders have been buying or selling.
The general public-- including retail investors -- own 42% stake in the company, and hence can't easily be ignored. This size of ownership, while considerable, may not be enough to change company policy if the decision is not in sync with other large shareholders.
It seems that Private Companies own 15%, of the Lundin Mining stock. It might be worth looking deeper into this. If related parties, such as insiders, have an interest in one of these private companies, that should be disclosed in the annual report. Private companies may also have a strategic interest in the company.
It's always worth thinking about the different groups who own shares in a company. But to understand Lundin Mining better, we need to consider many other factors. For instance, we've identified 3 warning signs for Lundin Mining that you should be aware of.
But ultimately it is the future, not the past, that will determine how well the owners of this business will do. Therefore we think it advisable to take a look at this free report showing whether analysts are predicting a brighter future.
NB: Figures in this article are calculated using data from the last twelve months, which refer to the 12-month period ending on the last date of the month the financial statement is dated. This may not be consistent with full year annual report figures.
Find out whether Lundin Mining is potentially over or undervalued by checking out our comprehensive analysis, which includes fair value estimates, risks and warnings, dividends, insider transactions and financial health.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
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Two XEMC 120 t battery electric mining trucks begin tests in Brazil … – International Mining
Posted by Paul Moore on 6th October 2023
Brazil-based AIZ Group has been providing solutions for the mining market since 2018 which through subsidiary AIZM includes offeringon a rental or sales basis yellow primary mining machines as well as light and heavy trucks, almost all available as all electric or conventional diesel combustion-powered, to offer customers the most diverse options for tailor made projects.
The company told IM that its solutions are adapted to the standards of Brazilian mining companies, plus many units have additional electronic safety systems and some are available for remote control and autonomous operations for specific applications such as tailings dam decommissioning.
AIZ has partnerships with key Chinese OEMs including XCMG, LGMG and XEMC and in 2022 it acquired two all battery electric 120E-2 rigid truck units from XEMC based in Xiangtan to increase its capacity to offer all electric solutions to the mining market. XEMC has also spun off its own green mining truck company, Igreencle, along with partnerstelecomms/5G group Datang and Huolinhe mine owner, energy group SPIC. Its offering also includes battery electric water trucks for mine operation.
The 120E-2 heavy trucks are currently being tested at AIZs headquarters in So Jos dos Pinhais in Parana state, and at the end of this stage AIZ says it will have concrete performance data to better indicate to its customers.
It works with large companies in Brazilian mining including Vale, ArcelorMittal and Anglo American plus its battery electric equipment includes units fromother manufacturers such as CAMC, Volkswagen and BYD trucks as well as SOCMA forklifts.
The headquarters has its own development team and a complete manufacturing park. A showroom also operates at this location, with 35,000 m2 dedicated to products ready for delivery. Its innovations have already included a remote control, cabless 84 haul truck with double cylinder and double walled body equipped with heating to always ensure full unloading of the transported waste material. It is equipped with mining tyres for greater flexibility on mining roads plus has a lower operating height that facilitates loading with a wheel loader for greater productivity.
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Two XEMC 120 t battery electric mining trucks begin tests in Brazil ... - International Mining
Investors in Andrada Mining (LON:ATM) have seen strong returns of 184% over the past three years – Yahoo Finance
It hasn't been the best quarter for Andrada Mining Limited (LON:ATM) shareholders, since the share price has fallen 16% in that time. But in three years the returns have been great. The share price marched upwards over that time, and is now 184% higher than it was. After a run like that some may not be surprised to see prices moderate. The thing to consider is whether the underlying business is doing well enough to support the current price.
With that in mind, it's worth seeing if the company's underlying fundamentals have been the driver of long term performance, or if there are some discrepancies.
See our latest analysis for Andrada Mining
Given that Andrada Mining didn't make a profit in the last twelve months, we'll focus on revenue growth to form a quick view of its business development. Shareholders of unprofitable companies usually expect strong revenue growth. That's because it's hard to be confident a company will be sustainable if revenue growth is negligible, and it never makes a profit.
Andrada Mining's revenue trended up 62% each year over three years. That's much better than most loss-making companies. Along the way, the share price gained 42% per year, a solid pop by our standards. But it does seem like the market is paying attention to strong revenue growth. That's not to say we think the share price is too high. In fact, it might be worth keeping an eye on this one.
The company's revenue and earnings (over time) are depicted in the image below (click to see the exact numbers).
earnings-and-revenue-growth
Balance sheet strength is crucial. It might be well worthwhile taking a look at our free report on how its financial position has changed over time.
It's nice to see that Andrada Mining shareholders have received a total shareholder return of 44% over the last year. That's better than the annualised return of 14% over half a decade, implying that the company is doing better recently. Someone with an optimistic perspective could view the recent improvement in TSR as indicating that the business itself is getting better with time. While it is well worth considering the different impacts that market conditions can have on the share price, there are other factors that are even more important. Take risks, for example - Andrada Mining has 1 warning sign we think you should be aware of.
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Of course Andrada Mining may not be the best stock to buy. So you may wish to see this free collection of growth stocks.
Please note, the market returns quoted in this article reflect the market weighted average returns of stocks that currently trade on British exchanges.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
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Mining Waste Management Market Size, Share, Competitive Insights … – GlobeNewswire
Wilmington,Delaware, Oct. 04, 2023 (GLOBE NEWSWIRE) -- Global Mining Waste Management Market size was valued at US$ 25.3 billion in 2023 and is predicted to rise at a substantial CAGR of 2.5% during the forecast period of 2023 and 2030 according to RationalStat analysis.
Market Definition, Market Scope, and Report Overview
The mining waste management market is concerned with the disposal and management of waste generated during mining activities. Tailings (fine-grained residue), slag (non-metallic residues), overburden (soil and rock removed to reach mineral resources), and other byproducts are all produced by mining processes. Proper mining waste management is critical for mitigating environmental impacts, protecting ecosystems, and ensuring the safety and well-being of neighboring communities.
Mining waste management policies and standards have been implemented by governments and environmental organizations all over the world. Mining businesses must comply with these requirements, which necessitates the use of innovative waste management technology and practices.
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Global Mining Waste Management Market: Segmental and Market Share Analysis
Report Synopsis
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Competition Analysis and Market Structure
Some of the prominent players adopt various strategies in order to reinforce their market share and gain a competitive edge over other competitors in the market. Mergers & acquisitions, and partnerships and collaborations are some of the strategies followed by industry players, some of the key developments in the global mining waste management market include,
Some of the prominent players and suppliers operating and contributing significantly to the global mining waste management market growth include AMEC Foster Wheeler Plc (John Wood Group Plc), Ausenco Limited, Enviropacific Services Limited, EnviroServ Waste Management Ltd., Golder Associates Inc. (Enterra Holdings Ltd.), Hatch Ltd., Interwaste Holdings Limited (Sch South Africa Proprietary Limited), Teck Resources Limited, Tetra Tech Inc., Veolia Environnement S.A., and Ramboll Group A/S, among others.
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RationalStat has segmented the global mining waste management market based on mining type, waste type, commodity and region
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Key Questions Answered in the Mining Waste Management Report:
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RationalStat has developed a state-of-the-art research methodology to crunch numbers and provide the best possible real-time insights to clients. We combine a varied range of industry experience, data analytics, and experts viewpoint to create a research methodology for market sizing and forecasting.
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Mining Waste Management Market Size, Share, Competitive Insights ... - GlobeNewswire
Atalaya Mining Plc’s (LON:ATYM) institutional investors lost 9.5% over the past week but have profited from longer-term gains – Simply Wall St
Key Insights
A look at the shareholders of Atalaya Mining Plc (LON:ATYM) can tell us which group is most powerful. With 61% stake, institutions possess the maximum shares in the company. Put another way, the group faces the maximum upside potential (or downside risk).
Institutional investors endured the highest losses after the company's market cap fell by UK43m last week. However, the 36% one-year return to shareholders might have softened the blow. They should, however, be mindful of further losses in the future.
In the chart below, we zoom in on the different ownership groups of Atalaya Mining.
View our latest analysis for Atalaya Mining
Institutional investors commonly compare their own returns to the returns of a commonly followed index. So they generally do consider buying larger companies that are included in the relevant benchmark index.
We can see that Atalaya Mining does have institutional investors; and they hold a good portion of the company's stock. This suggests some credibility amongst professional investors. But we can't rely on that fact alone since institutions make bad investments sometimes, just like everyone does. When multiple institutions own a stock, there's always a risk that they are in a 'crowded trade'. When such a trade goes wrong, multiple parties may compete to sell stock fast. This risk is higher in a company without a history of growth. You can see Atalaya Mining's historic earnings and revenue below, but keep in mind there's always more to the story.
Since institutional investors own more than half the issued stock, the board will likely have to pay attention to their preferences. We note that hedge funds don't have a meaningful investment in Atalaya Mining. Our data shows that Farringford Foundation is the largest shareholder with 22% of shares outstanding. With 4.1% and 3.4% of the shares outstanding respectively, BlackRock, Inc. and Fidelity International Ltd are the second and third largest shareholders.
A deeper look at our ownership data shows that the top 25 shareholders collectively hold less than half of the register, suggesting a large group of small holders where no single shareholder has a majority.
While it makes sense to study institutional ownership data for a company, it also makes sense to study analyst sentiments to know which way the wind is blowing. There are plenty of analysts covering the stock, so it might be worth seeing what they are forecasting, too.
The definition of an insider can differ slightly between different countries, but members of the board of directors always count. Management ultimately answers to the board. However, it is not uncommon for managers to be executive board members, especially if they are a founder or the CEO.
I generally consider insider ownership to be a good thing. However, on some occasions it makes it more difficult for other shareholders to hold the board accountable for decisions.
Our most recent data indicates that insiders own less than 1% of Atalaya Mining Plc. However, it's possible that insiders might have an indirect interest through a more complex structure. It has a market capitalization of just UK425m, and the board has only UK1.8m worth of shares in their own names. Many tend to prefer to see a board with bigger shareholdings. A good next step might be to take a look at this free summary of insider buying and selling.
The general public-- including retail investors -- own 17% stake in the company, and hence can't easily be ignored. This size of ownership, while considerable, may not be enough to change company policy if the decision is not in sync with other large shareholders.
It seems that Private Companies own 22%, of the Atalaya Mining stock. It might be worth looking deeper into this. If related parties, such as insiders, have an interest in one of these private companies, that should be disclosed in the annual report. Private companies may also have a strategic interest in the company.
It's always worth thinking about the different groups who own shares in a company. But to understand Atalaya Mining better, we need to consider many other factors. To that end, you should be aware of the 3 warning signs we've spotted with Atalaya Mining .
But ultimately it is the future, not the past, that will determine how well the owners of this business will do. Therefore we think it advisable to take a look at this free report showing whether analysts are predicting a brighter future.
NB: Figures in this article are calculated using data from the last twelve months, which refer to the 12-month period ending on the last date of the month the financial statement is dated. This may not be consistent with full year annual report figures.
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Selenium for Web Scraping and Data Extraction – Robotics and Automation News
In the realm of web development and data analysis, the ability to extract data from websites and web applications holds critical importance.
In todays digital age, assembling and evaluating data is crucial to attaining valuable insights into diverse industries and markets. Data is booming like never before in an unstructured manner.
It is estimated that by the end of this decade, there will be approximately 100s of zettabytes of data, out of which 80% will be unstructured.
The unstructured data consists of images, text, videos, audio, and so on, which cant be utilized directly for model building. Putting the suited method to implementation can fetch useful insight.
Web scraping, questionnaires, focus groups, surveys, and so on, are a few of the widely utilized mechanisms for assembling insightful data. Nonetheless, web scraping is deemed the most efficient and steadfast data collection technique out of all these techniques.
Web scraping, also known as web data extraction, is an automatic technique for scraping enormous data from websites. Web scraping parses the HTML code of a webpage to extract relevant data, such as textual information, which can then be organized and stored in data frames or a database for further manipulation.
Selenium is a powerful automation testing tool that can assist developers and data analysts in streamlining the process of web scraping and data extraction, rendering it an integral tool for both organizations and individuals.
Selenium is an open-source software suite that facilitates end-users to automate web browsers and accomplish tasks such as clicking links, filling out forms, and extracting data from web pages. It extends its support to myriad browsers like Chrome, Safari, Edge, Firefox, and Internet Explorer.
This blog will take an in-depth look at how Selenium can be utilized for web scraping and data extraction, furnishing you with the knowledge and skills necessary to harness the power of this versatile tool.
Web scraping refers to the process of automatically extracting content and data from websites or other online resources. Web scraping extracts the HTML code beneath a webpage, in contrast to screen scraping.
After accessing the webpage, users can proceed to process its HTML code to extract relevant data. This facilitates them to effectively carry out essential tasks such as data cleaning, manipulation, and analysis. Also, significant volumes of this data can be stored in a database for extensive data analysis initiatives.
The importance and requirement for data analysis, along with the raw data that can be generated utilizing web scrapers, has ushered in the development of custom-tailored Python packages that simplify web scraping as pie.
Web scraping utilizing Selenium facilitates you to efficiently extract the desired data by employing browser automation through the Selenium Webdriver. Selenium shuffles the mark URL webpage and assembles data at scale.
Here are a few common uses for Web Scraping:
You can leverage the true capability of Selenium testing using cloud based platforms like LambdaTest. LambdaTest is an AI-powered test orchestration and execution platform that helps you to perform both manual and automation testing processes over 3,000 real desktop browsers, devices, and operating system combinations.
It functions as a browser testing platform, facilitating browser automation through Selenium, Appium, and various other frameworks.
Scaling up your testing processes for parallel execution is a breeze with the cloud-based Grid feature. Upon signing up on LambdaTest, remember to jot down your user-name and access-key from your LambdaTest profile section.
Utilizing the cloud-based Selenium automation grid offered by LambdaTest streamlines the entire process, eliminating the need for manual configuration in both development and production environments.
This test automation solution accommodates a diverse range of browsers and operating systems. Notably, LambdaTest provides access to a Selenium Grid hosted in the cloud, streamlining the execution of extensive cross-browser testing tasks across a multitude of browsers, platforms, and screen resolutions.
With the help of specialized tools and techniques, web scraping authorizes users to extract large amounts of data from websites swiftly and efficiently. From market research to competitor analysis, web scraping can furnish valuable insights that would otherwise be difficult or impossible to obtain.
Below are the applications of web scraping and how it can be utilized to streamline various business processes:
The process of web scraping entangles locating and extracting specific data elements from a website. In Selenium, this is attained through the use of locators, which are unique identifiers for the different elements on a webpage.
Selenium furnishes various types of locators, such as ID, class name, name, link text, and XPath, that can be employed to locate elements.
Once an element is located, it can be interacted with utilizing various methods such as clicking, typing, and selecting. This authorizes the extraction of data from web pages and the automation of tasks without manual intervention.
Nonetheless, it is vital to keep in mind that web scraping should only be conducted on websites where it is legally allowed. Besides, websites may have measures in place to prevent web scraping, so it is vital to be mindful of these restrictions and use Selenium responsibly.
Web scraping and parsing are elementary techniques employed in data extraction to fetch data from websites. Web scraping has emerged as a crucial method for gathering and analyzing data from myriad websites in light of the increasing implications of big data.
Selenium is widely employed in the field of web scraping and data extraction as an open-source library that automates web browsers with outstanding efficiency and dependability.
Scraping and parsing web pages utilizing Selenium authorizes users to collect data from web pages and extract meaningful information that can be employed for research, data analysis, and business intelligence.
Selenium delivers users the valuable capability to simulate user actions, such as clicking buttons and filling out forms, which can effectively automate monotonous tasks.
The utilization of Selenium has enormously enhanced the process of web page scraping and parsing for efficient and effective data collection and analysis.
Web scraping and data extraction are implied tasks for organizations and individuals striving to glean valuable insights from online sources. Selenium is a widely recognized and employed tool that permits the automation of web browsers and facilitates web scraping activities with outstanding speed and efficacy.
One of Seleniums pivotal functionalities is its proficient extraction of data from websites, which plays a critical role in the web scraping method.
Selenium boosts the seamless extraction of myriad types of data, including but not limited to text, images, links, and HTML components, from websites.
This makes it a valuable tool for organizations striving to gather and assess substantial quantities of data from numerous websites. Besides, the flexibility and versatility of Selenium renders it an advantageous tool for accomplishing data extraction assignments.
The tool is versatile in its application as it is compatible with multiple programming languages, including Java, Python, and C#. Besides, it can be seamlessly integrated with myriad tools and frameworks, such as BeautifulSoup and Scrapy, for maximized efficiency and amenity.
Handling dynamic content on websites is one of the most crucial aspects of web scraping and data extraction. Contemporary websites frequently incorporate dynamic technologies such as Ajax, permitting dynamically changing content on a page without necessitating a full page refresh.
This poses a considerable challenge for web scrapers, as they ought to be able to handle this dynamic content to extract the data they need accurately.
Fortunately, Selenium furnishes a powerful solution for handling dynamic content on websites. Selenium authorizes developers to automate interactions with web pages, including clicking on buttons, filling out forms, and scrolling down pages to load additional content.
By utilizing these functionalities, software developers can guarantee that they obtain all essential data from a website, regardless of the dynamic nature of the content.
Selenium is a powerful tool for web scraping and data extraction. Its ability to interact with a website like a real user makes it immaculate for automating tasks that would otherwise demand manual endeavor.
Selenium is a widely preferred tool among developers and data analysts owing to its user-friendly API and comprehensive documentation.
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Selenium for Web Scraping and Data Extraction - Robotics and Automation News
Identification and validation of FPR1, FPR2, IL17RA and TLR7 as … – Nature.com
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Why AI in cybersecurity needs to be part of business strategy to boost resilience – Forbes India
India ranks second in the world (as of 2022) when it comes to the number of data breach cyber-attacks on its enterprises and ranks 14th globally in average data breach costs, according to Surfshark.Image: Shutterstock
According to Surfshark, India ranks second in the world (as of 2022) when it comes to the number of data breach cyber-attacks on its enterprises and ranks 14th globally in average data breach costs. Here, the term 'data' refers to any information impacting an enterprise's effective business continuity (BC). More specifically, India's average data breach cost in 2022 amounted to a record high of Rs17.6 crore (approximately $2.2 million)a 6.6 percent increase from Rs16.5 crore in 2021 and a 25 percent increase from Rs14 crore in 2020 (as reported by the IBM Security Data Breach Report of 2022 that analysed data breaches affecting more than 550 companies in India). Moreover, India's average per-record data breach cost reached an 11-year high of Rs6100a 3.3 percent increase from Rs5900 in 2021 and a 10.4 percent increase from Rs5522 in 2020.
According to Viswanath Ramaswamy, the Vice President of IBM Technology Sales and IBM India/South Asia, "cyber-attacks are the biggest challenge to enterprise cyber-resilience in India". Ramaswamy also goes on to say that the three factors that majorly contribute to the (multi-party) costs incurred by companies due to data breach-related cyber-attacks are
In addition to this, less than 35 percent of cyber-security expertise slots are filled up, out of which some are entry-level security analysts who take time to develop the skills, confidence, and intuition to investigate data breach cyber-attacks.
Moreover, on the psychological front, many cybersecurity personnel suffer from job fatigue. This is due to
Finally, it is well-documented and widespread knowledge that approximately 95 percent of enterprise cyber-breaches are initially rooted in 'human in the loop' issues.
All these factors add up to the likelihood that a cyber-security expertise team within an enterprise would be an important indicator of enterprise compromise by cyber-attack vectors. According to the IBM Security Data Breach Report of 2022, an Indian enterprise, on average, can save Rs10 crore (approximately $1.2 million) if it can detect a cyber breach in less than 200 days compared to when it detects in more than 200 days.
Also read: The cyber-insurance vision is failing for ransomware attacks in India
1. To start, AI has the power to automate repeatable tasks, contributing to lesser fatigue of personnel/employees in enterprise security operation centres (ESOCs). This will result in enterprises' hedging' cyber-risks arising from the lack of focus of such personnel to identify important indicators of cyber-compromise. Moreover, as a related but significant benefit, AI will help enterprises precisely identify the root cause of a cyber-attack from several compromise indicator features something that is computationally infeasible for humans in ESOCs to routinely identify accurately and that too in the ever-increasing threat landscape. The last point is even more relevant today in the age of generative AI products such as ChatGPT that can create human-evading malware signatures on the fly.
2. In the process of generating effective true-positive cyber-attack alarms, AI has the power to dig out 'complex' statistical relationships not only between compromise indicator variables (for both internal and external enterprise cyber-threats) but also between incidents (that might have occurred far in the past) that might look un-related to the gut-feeling driven human eye.
3. Unlike human intelligence, AI can effectively parse the entire space of structured, unstructured, and noisy threat-related data to output crisp and concise information needed for ESOC personnel to evaluate and optimise cyber-resilience metrics such as Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR).
4. While points 1, 2, and 3 above showcase the accuracy of AI solutions, speed is the other critically important factor distinguishing AI from human (expert) intelligence. The power of AI can be leveraged at speed, especially on real-time cyber-threat data, to conduct (real-time) data mining and (un-)supervised learning for generating accurate threat intelligence at speed. On an overarching note, AI will guide ESOC personnel (analysts) to fast, precise and automated cyber-resilience, improving incident response spanning an enterprise's people, process, and technology spectrum.
The bottom line is that the Indian enterprise can save a lot more (probably a multi-fold of $1.2 million, as mentioned above) if it can leverage the power of AI to analyse and detect cyber threats accurately with low false alarms within a period much less than 200 days. This is simply because the existing cost estimates are conservative and exist only for reported threats, of which the reported quantity is far lesser than the actual number of threats reportable, and reducing reporting time is of essential financial value to an enterprise.
A very good real-world example of this is the use of AI in its cyber-security processes by Trellix (erstwhile McAfee Enterprises) since 2020 to alert its customers (via their software products) on cyber threats, predict their impact, and prescribe corrective action. Since the use of AI as a cyber-security strategy on their High-Velocity Sales (HVS) platform, Trellix has boosted its initial potential client interests 10-fold, had a 5 percent increase in renewal rates, and had a three-fold increase in the amount of time managers could afford to spend to coach their sales team members on boosting sales.
One might be inclined to believe (from the Trellix example) that the returns and competitive business risks of adopting and not adopting AI in cyber-security processes are quite high from a sales perspective. This point can be rationalised by seminal academic theory in the strategic management sciences. Based on insights from the widely popular Five Forces strategy model by Michael Porter of the Harvard Business School, the threat of new entrants (Trellix competitors), product substitutes (competitor products churned from AI-driven platforms like HVS), high bargaining power of customers (clients of Trellix-like products), and low bargaining power of suppliers (Trellix) should push enterprises to necessarily adopt AI as a cyber-security strategy to boost sales.
However, when it comes to enterprises (not necessarily only those having a cyber-security vision), it is not directly evident that incorporating AI as a cyber-resilience-improving strategy within business processes will boost salesespecially for small and medium businesses (SMBs). This is because
Second, the service-selling enterprise could be a hardware, software, and/or firmware supplier that has locked in a set of enterprises as customers (in a supply chain). One example of such an enterprise includes AWS, which provides a public cloud service as its business operation. Another example could include critical infrastructure enterprises reliant upon each other to sustain business continuity (e.g., a manufacturing company depending on a power grid and vice versa). In such cases, to prevent churn, remain profitable, and sustain market competition, the supplier enterprise must spend enough on AI to gather client environment data (applications, processes using supplied solutions) that 'minimises' the likelihood of business disrupting malicious intruder entry into (IT/OT) systems. Essentially, the supplier enterprise must ensure their systems remain securely online to prevent business disruptions for both their clients and them by ensuring there is no malicious entry from any endpoint. An example of such AI is a real-time system orchestrated AI solution such as ScadaShield (by Cyberbit), that performs continuous monitoring and detection across the entire attack surface for both IT and OT components and can be combined with ESOC automation to trigger workflows that accelerate cyber-attack root cause identification and mitigation.
Third, the enterprise selling services could primarily be a solution consultant that provides its clients (e.g., general IT and/or OT-driven enterprises) security software as a service (SSaaS/SECaaS), where the selling enterprise (e.g., CrowdStrike, Trellix) can make profits, both out of the software/firmware/hardware components and their integration. In such cases, the enterprise must spend on AI that collects and analyses information within the supplying enterprise's and client businesses' systems to prevent churn and remain competitively profitable in the market. The former protects the supplying enterprise from any malicious cyber intruders by analysing usage information and other data. In contrast, the latter protects the enterprise's clients by analysing the client's cyber posture information to generate effective alerts. The bottom line is that enterprises selling such products want to use AI to improve sales efficiency, improve customer relationships, and decrease costs. This requires the use of advanced AI tools to increase sales effectiveness. An example of such AI is that available on the XDR platform of Trellix that leverages AI, (real-time) machine learning, and advanced telemetry based on threat intelligence from more than one billion sensors across corporate and government enterprises to reduce malicious intruder probabilities and boost enterprise cyber-resilience significantly.
On top of everything, AI as a business strategy for the modern IT/OT-driven business ecosystems has the potential to adhere very well with certain elements of the seminal Eight-Fold strategy proposed by Michael Cusumano of the MIT Sloan School of Management for software-driven businessesespecially those offering pioneering solutions (cyber-security as a service). More specifically, enterprises providing cybersecurity-as-a-service
The authors would like to acknowledge Keri Pearlson of the MIT Sloan School of Management for her strategic insights from her research on cyber-security as a competitive business advantage.
Ranjan Pal (MIT Sloan School of Management, USA) Cynthia Zhang (EECS, Massachusetts Institute of Technology, USA) Bodhibrata Nag (Indian Institute of Management Calcutta, India)Michael Siegel (MIT Sloan School of Management, USA)
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Why AI in cybersecurity needs to be part of business strategy to boost resilience - Forbes India