Category Archives: Data Mining
Data Mining Software Market Size, Scope and Forecast | IBM, RapidMiner, Salford Systems, Oracle, GMDH, Apteco, SAS Institute, University of Ljubljana,…
New Jersey, United States TheData Mining Software Marketreport is the result of extensive and expert research into theData Mining Softwareindustry. TheData Mining SoftwareMarketreport explains what the market is all about, the market prognosis, several segmentations, and everything that falls under the markets umbrella. It also looks at major and secondary market drivers, market share, potential sales volume, regional analysis, and the markets key segments. The research also includes key variables that contribute to the markets growth as well as elements that might stifle the markets growth. The professionals at VM Reports applied precise research techniques and other analyses.
PESTLE analysis and SWOT analysis are two of the analyses utilized in theData Mining SoftwareMarketresearch, and they shed light on numerous internal and external variables that affect the market in every situation. It also includes a section that identifies strengths, weaknesses, opportunities, and threats, as well as Porters five forces model.
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There is also a section dedicated to significant actors and their plans, such as acquisitions, collaborations, and so on. The material in the Data Mining Software Market research was gathered mostly via expert opinions, interviews, and surveys. Verified Market Research experts have created a Data Mining Software Market research that is full of clarity, accuracy, and useful information. The data in the report is quite accurate and reliable, with no duplicates or mistakes.
Key Players Mentioned in the Data Mining Software Market Research Report:
IBM, RapidMiner, Salford Systems, Oracle, GMDH, Apteco, SAS Institute, University of Ljubljana, Salford Systems and Lexalytics.
Data Mining SoftwareMarket Segmentation:
Data Mining Software Market, By Deployment Type
Cloud-based On-Premise
Data Mining Software Market, By Component
Services Tools
Data Mining Software Market, By Application
Large enterprises SMEs
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Data Mining Software Market Report Scope
Key questions answered in the report:
1. Which are the five top players of the Data Mining Software market?
2. How will the Data Mining Software market change in the next five years?
3. Which product and application will take a lions share of the Data Mining Software market?
4. What are the drivers and restraints of the Data Mining Software market?
5. Which regional market will show the highest growth?
6. What will be the CAGR and size of the Data Mining Software market throughout the forecast period?
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Sheryl Sandbergs influence reaches all of us. But its a troubling legacy – The Guardian
If you are reading this, odds are that you are one of the 2.87 billion daily users of the products offered by Meta, the parent company of Facebook, Instagram, Facebook Messenger and WhatsApp. If you are not using any of these products, you are connected to people who do use them. And this connects you to Sheryl Sandberg, who resigned last week from her role as Metas chief operating officer.
Even if you have never met her, interacted directly with her or read her books on corporate feminism or bereavement, Sandberg has had an impact on your life. Shes not the only reason that our data is tracked online, whether we use Metas products or not. Many others have helped to create and exploit an entire industry that profits from our data. Whats more, lawmakers and regulators worldwide have done little to stop this, in no small part because companies like the ones Sandberg helped run spend millions of dollars every year lobbying to prevent or water down any attempts at regulation.
Still, as Shera Frenkel and Cecilia Kang write in An Ugly Truth: Inside Facebooks Battle for Domination, Sandberg pioneered a whole new level of tracking and led the creation of a new business of data mining at scale. Put simply, scale means to add revenue at a faster rate than costs. Sandberg once said that she felt she was put on this planet to scale organisations and she has the track record to back it up.
At Google, where she worked before joining Facebook, she led the transformation of the search engine into the worlds leading digital advertising business. After she took up her role at Facebook, its advertising sales exploded from $777m in 2009 to $117bn in 2021 the year Meta reached a market valuation of a trillion dollars. Along the way, the company acquired Instagram and WhatsApp, had a successful initial public offering (IPO) and expanded from 400 employees to more than 77,000 today. Meta is now the second leading digital advertising business behind Alphabet, Googles parent company.
Yet where Sandberg sees scale, others see something sinister. The Harvard emerita professor Shoshana Zuboff, author of The Age of Surveillance Capitalism, has described Sandberg as the Typhoid Mary of surveillance capitalism owing to her role in spreading Googles data-mining practices to Facebook. At the heart of data mining is an implicit agreement: the products are free in that we dont have to pay money to use them. Instead, we pay with our data, exchanging our online behaviour, preferences, social network and privacy for connection.
In the early years of these companies, it might have been possible for us to be ignorant of the terms of this agreement or to minimise our complicity in it. However, since 2016 none of us could be in any doubt. We learned that Russia had manipulated Facebook to interfere in the US election. We learned, thanks to this newspapers investigations, that Facebook had improperly shared the data of 87 million users with Cambridge Analytica to facilitate targeted political advertising in the United States, the United Kingdom and elsewhere. We learned that supporters of the former president Donald Trump had used Facebook to organise the attack on the US Capitol on 6 January 2021. And we learned that Meta has known about and failed to fix its role in spreading misinformation and disinformation.
With each revelation, Sandbergs response, in lockstep with that of Metas CEO, Mark Zuckerberg, has been to deny, deflect, apologise and promise to do better. Yet while Meta has made many changes, the fundamental agreement remains the same we give them our data in exchange for their products, they translate it into billions of dollars in advertising revenues and terrible things sometimes happen along the way. If we dont like it, we are free to leave, as Meta explained in a recent update to its privacy policy. What was once implicit is now explicit. None of us can claim any more that we do not know what we are participating in.
In response, some users have deleted Facebook, quit Instagram and left Facebook Messenger or WhatsApp for Signal, a more privacy-preserving messaging app. However, the overwhelming majority of Metas users continue to use its products. Investors have been similarly unmoved; while Facebooks share price was volatile from 2018 to 2020, it resumed soaring thereafter, reversed only by a recent privacy-protecting move from Apple and Zuckerbergs costly and, so far unproved, pivot to the metaverse.
Concerns about our privacy, the integrity of our democracies or the safety of our children had little impact on the business model that Sandberg so finely honed. Nor did Facebooks role in facilitating genocide in Myanmar, which was condemned by the UN in 2018. Sandberg said she was devastated and promised to do better when testifying before the US Senate intelligence committee. However, as recently as March this year, the Associated Press reported it was still possible to pay for ads calling for the killing of Myanmars Rohingya Muslim community.
But failures of content moderation, one of Sandbergs other responsibilities as chief operating officer, will be part of her record and remain a challenge for Meta. As Bloomberg reported last month, it is still possible to sell and buy guns on Facebook Marketplace. Livestreaming of shootings, sex trafficking and the challenge of moderating hate speech versus freedom of expression remain unresolved.
Artificial intelligence alone cannot solve this and Meta has not hired anywhere near enough human content moderators, who suffer terrible damage to their mental health while cleaning up the platforms while enjoying none of the wealth. These are problems for other companies, of course, but because of its scale, its an even bigger problem for Meta.
Sandberg, who will remain on Metas board, she says, and spend more time on her philanthropy, will go down in history for her success in scaling Google and Facebook and her failure to deal with the costs of that success. That is her legacy. How we choose to respond to it will be ours.
Stephanie Hare is the author of Technology Is Not Neutral: A Short Guide to Technology Ethics
Do you have an opinion on the issues raised in this article? If you would like to submit a letter of up to 300 words to be considered for publication, email it to us at observer.letters@observer.co.uk
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Sheryl Sandbergs influence reaches all of us. But its a troubling legacy - The Guardian
The mining industry found it easier to fill digital media vacancies in Q1 2022 – Mining Technology
Digital media related jobs that were closed during Q1 2022 had been online for an average of 21 days when they were taken offline.
This was a decrease compared to the equivalent figure a year earlier, indicating that the required skillset for these roles has become easier to find in the past year.
Digital media is one of the topics that GlobalData, our parent company and from which the data for this article is taken, has identified as being a key disruptive technology force facing companies in the coming years. Companies that excel and invest in these areas now are thought to be better prepared for the future business landscape and better equipped to survive unforeseen challenges.
On a regional level, these roles were hardest to fill in Europe, with related jobs that were taken offline in Q1 2022 having been online for an average of 35 days.
The next most difficult place to fill these roles was found to be North America, while Asia-Pacific was in third place.
At the opposite end of the scale, jobs were filled fastest in the Middle East and Africa, with adverts taken offline after 6.5 days on average.
While the mining industry found it easier to fill these roles in the latest quarter, these companies also found it easier to recruit digital media jobs than the wider market, with ads online for 34.4% less time on average compared to similar jobs across the entire jobs market.
GlobalData's job analytics database tracks the daily hiring patterns of thousands of companies across the world, drawing in jobs as they're posted and tagging them with additional layers of data on everything from the seniority of each position to whether a job is linked to wider industry trends.
You can keep track of the latest data from this database as it emerges by visiting our live dashboard here.
Process Instrumentation Systems and Bulk Solids Sensors for the Mining Sector
Milled and Atomised Dense-Media Ferrosilicon
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The mining industry found it easier to fill digital media vacancies in Q1 2022 - Mining Technology
Partnerships increased in the mining industry in H2 2021 – Mining Technology
In the second half of 2021, the number of partnerships increased by 11.1% from the same period in 2020.
This marks an acceleration in growth from the 14.3% decrease in deals that occurred in H1 2021, relative to the same period a year earlier.
During second half of 2021, partnerships accounted for 5% of all deals taking place in the sector. This represents a decrease from the figure of 5.5% in second half of 2020.
GlobalData's deals database is a comprehensive repository that looks at mergers, acquisitions, venture financing, equity offerings, asset transactions, partnerships, and debt offerings taking place daily between thousands of companies across the world.
The database details key deal information, such as deal summary, deal rationale, deal financials, parties involved, advisors, and deal payment modes.
By tracking the proportion of various types of deals in each sector we can gauge which sectors are seeing growth and where others are struggling.
Process Instrumentation Systems and Bulk Solids Sensors for the Mining Sector
Milled and Atomised Dense-Media Ferrosilicon
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Partnerships increased in the mining industry in H2 2021 - Mining Technology
Hut 8 Mining Production and Operations Update – PR Newswire
7,078 self-mined Bitcoin in reserve after 309 were generated in May
Testing complete at North Bay, Ontario site; mining began on June 2
TORONTO, June 6, 2022 /PRNewswire/ - Hut 8 Mining Corp. (Nasdaq:HUT) (TSX: HUT) ("Hut 8" or "the Company"), one ofNorth America'slargest, innovation-focused digital asset mining pioneers, supporting open and decentralized systems since 2018, advanced its Bitcoin holdings in the period ending May 31 and began operations at its North Bay site on June 2.
Production highlights for May 2022:
Additional updates:
"We are thrilled that our most powerful and efficient machines are now mining Bitcoin at our North Bay site," said Jaime Leverton, CEO of Hut 8. "Over the next several weeks, our team will continue to install and bring miners online in real-time, complementing production at our facilities in Medicine Hat and Drumheller."
About Hut 8
Hut 8 is one of North America's largest innovation-focused digital asset miners, led by a team of business-building technologists, bullish on bitcoin, blockchain, Web 3.0 and bridging the nascent and traditional high performance computing worlds. With two digital asset mining sites located in Southern Alberta and a third site in North Bay, Ontario, all located in Canada, Hut 8 has one of the highest capacity rates in the industry and one of the highest inventories of self-mined Bitcoin of any crypto miner or publicly-traded company globally. With 36,000 square feet of geo-diverse data centre space and cloud capacity connected to electrical grids powered by significant renewables and emission-free resources, Hut 8 is revolutionizing conventional assets to create the first hybrid data centre model that serves both the traditional high performance compute (Web 2.0) and nascent digital asset computing sectors, blockchain gaming, and Web 3.0. Hut 8 was the first Canadian digital asset miner to list on the Nasdaq Global Select composite index and the first blockchain company to be added to the S&P/TSX Composite Index in 2021. Through innovation, imagination, and passion, Hut 8 is helping to define the digital asset revolution to create value and positive impacts for its shareholders and generations to come.
Cautionary Note Regarding ForwardLooking Information
Thispress release includes "forward-looking information" and "forward-looking statements" within the meaning of Canadian securities laws and United States securities laws, respectively (collectively, "forward-looking information"). All information, other than statements of historical facts, included in this press release that address activities, events or developments that the Company expects or anticipates will or may occur in the future, including such things as future business strategy, competitive strengths, goals, expansion and growth of the Company's businesses, operations, plans and other such matters is forward-looking information. Forward-looking information is often identified by the words "may", "would", "could", "should", "will", "intend", "plan", "anticipate", "allow", "believe", "estimate", "expect", "predict", "can", "might", "potential", "predict", "is designed to", "likely" or similar expressions. In addition, any statements in this press release that refer to expectations, projections or other characterizations of future events or circumstances contain forward-looking information and include, among others, statements regarding: Bitcoin and Ethereum network dynamics; the Company's ability to advance its HODL and growth strategies;the Company's ability to produce additional Bitcoin and maintain existing rates of productivity; the Company's ability to install and bring additional miners online as well as increase the power supply at its North Bay site; the anticipated measurable impact the Company's North Bay site will have on its production results; the Company's ability to limit costs associated with mining digital assets; and the Company's ability to increase its overall efficiency and hashrate through the expected production contributions from all miners online at each of the Company's three sites.
Statements containing forward-looking information are not historical facts, but instead represent management's expectations, estimates and projections regarding future events based on certain material factors and assumptions at the time the statement was made. While considered reasonable by Hut 8 as of the date of this press release, such statements are subject to known and unknown risks, uncertainties, assumptions and other factors that may cause the actual results, level of activity, performance or achievements to be materially different from those expressed or implied by such forward-looking information, including but not limited to, security and cybersecurity threats and hacks, malicious actors or botnet obtaining control of processing power on the Bitcoin or Ethereum network, further development and acceptance of Bitcoin and Ethereum networks, changes to Bitcoin or Ethereum mining difficulty, loss or destruction of private keys, increases in fees for recording transactions in the Blockchain, erroneous transactions, reliance on a limited number of key employees, reliance on third party mining pool service providers, regulatory changes, classification and tax changes, momentum pricing risk, fraud and failure related to cryptocurrency exchanges, difficulty in obtaining banking services and financing, difficulty in obtaining insurance, permits and licenses, internet and power disruptions, geopolitical events, uncertainty in the development of cryptographic and algorithmic protocols, uncertainty about the acceptance or widespread use of cryptocurrency, failure to anticipate technology innovations, the COVID19 pandemic, climate change, currency risk, lending risk and recovery of potential losses, litigation risk, business integration risk, changes in market demand, changes in network and infrastructure, system interruption, changes in leasing arrangements, and other risks related to the cryptocurrency and data centre business. For a complete list of the factors that could affect the Company, please see the "Risk Factors" section of the Company's Annual Information Form dated March 17, 2022, and Hut 8's other continuous disclosure documents which are available on http://www.sedar.com.
These factors are not intended to represent a complete list of the factors that could affect Hut 8; however, these factors should be considered carefully. There can be no assurance that such estimates and assumptions will prove to be correct. Should one or more of these risks or uncertainties materialize, or should assumptions underlying the forward-looking statements prove incorrect, actual results may vary materially from those described in this press release as intended, planned, anticipated, believed, sought, proposed, estimated, forecasted, expected, projected or targeted and such forward-looking statements included in this press release should not be unduly relied upon. The impact of any one assumption, risk, uncertainty, or other factor on a particular forward-looking statement cannot be determined with certainty because they are interdependent and Hut 8's future decisions and actions will depend on management's assessment of all information at the relevant time. The forward-looking statements contained in this press release are made as of the date of this press release, and Hut 8 expressly disclaims any obligation to update or alter statements containing any forward-looking information, or the factors or assumptions underlying them, whether as a result of new information, future events or otherwise, except as required by law.
SOURCE Hut 8 Mining Corp
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Digitalization in mining starts with right network – Ericsson
The smart mine is the mine of the future.
The global mining equipment market is expected to grow to $125.7 billion by 2025, growing at a compound annual growth rate (CAGR) of 5% from 2021-2025, driven by increased adoption of smart technologies like automation and remote-controlled machinery. Thats a sign that companies know digitalization in mining is the future.
But all the new use cases and exciting smart technologies have one thing in common they need to be powered by fast, reliable, and secure connectivity solutions. And it wont be enough to simply connect these devices to wireless (or fixed) broadband. The right kind of connectivity, and the right kind of network, purpose-built for a rugged environment like mining, is critical to achieving the efficiency and safety results a smart mine can bring. In addition, mining companies are being squeezed by some of the labor and supply chain issues facing nearly every industry today, creating pressure to cut costs and get more ore from existing mines.
Mining companies are justifiably excited about technologies like automation, mixed reality, digital twinning, and more. They have the potential to create operational efficiencies, save money and time on repairs by making maintenance smarter, and increase safety by taking human workers out of dangerous situations. But all this cutting-edge technology wont help if its not connected by the right kind of network.
Demand for things like the rare minerals needed to make todays high-tech devices is fueling the growth of whats already a $500 billion global industry in mining.
To meet these needs, mining operators need a cellular network built specifically for their use cases of today and tomorrow. A commercial LTE network, designed for consumer traffic that consists mainly of video and data download, doesnt have the same high security, flexibility, and upstream traffic needs to handle the demands of an industrial environment like a mine. A few examples:
All of these factors will be important considerations for mine operators as they bring connectivity to more aspects of the mine and introduce new technologies to make operations smarter, safer and more efficient. Its an exciting time for the industry, but this digitalization in mining needs to rest on the bedrock of a robust and reliable connectivity solution. The connected mine of the future needs more than a connectivity platform thats good enough. An industrial LTE network, purpose-built for the needs of a mine, can be the enabler for a productive and valuable digital transformation.
At the Boliden Aitik mine, private networks enable automation
How smart, sustainable mining is reshaping the industry
Accelerating mining safety and smart mines with limitless connectivity
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Digitalization in mining starts with right network - Ericsson
Cloud Analytics Market Assessment, Business Solutions, New Trends and Opportunities Analysis by 2027 | Vmware Inc., Qlik Tchnologies Inc., Pivotlink -…
1. Executive Summary1.1. Market Snapshot1.2. Global & Segmental Market Estimates & Forecasts, 2018-2028 (USD Billion)1.2.1.Cloud Analytics Market, by Region, 2018-2028 (USD Billion)1.2.2.Cloud Analytics Market, by Type, 2018-2028 (USD Billion)1.2.3.Cloud Analytics Market, by Application, 2018-2028 (USD Billion)1.2.4.Cloud Analytics Market, by Verticles, 2018-2028 (USD Billion)1.3. Key Trends1.4. Estimation Methodology1.5. Research Assumption
2. GlobalCloud Analytics Market Definition and Scope2.1. Objective of the Study2.2. Market Definition & Scope2.2.1. Scope of the Study2.2.2. Industry Evolution2.3. Years Considered for the Study2.4. Currency Conversion Rates
3. GlobalCloud Analytics Market Dynamics3.1.Cloud Analytics Market Impact Analysis (2018-2028)3.1.1. Market Drivers3.1.2. Market Challenges3.1.3. Market Opportunities
4. GlobalCloud Analytics Market Industry Analysis4.1. Porters 5 Force Model4.1.1. Bargaining Power of Suppliers4.1.2. Bargaining Power of Buyers4.1.3. Threat of New Entrants4.1.4. Threat of Substitutes4.1.5. Competitive Rivalry4.1.6. Futuristic Approach to Porters 5 Force Model (2018-2028)4.2. PEST Analysis4.2.1. Political4.2.2. Economical4.2.3. Social4.2.4. Technological4.3. Investment Adoption Model4.4. Analyst Recommendation & Conclusion
5. GlobalCloud Analytics Market, by Type5.1. Market Snapshot5.2. GlobalCloud Analytics Market by Type, Performance Potential Analysis5.3. GlobalCloud Analytics Market Estimates & Forecasts by Type 2018-2028 (USD Billion)5.4.Cloud Analytics Market, Sub Segment Analysis
6. GlobalCloud Analytics Market, byApplication6.1. Market Snapshot6.2. GlobalCloud Analytics Market by Application, Performance Potential Analysis6.3. GlobalCloud Analytics Market Estimates & Forecasts by Application 2018-2028 (USD Billion)6.4.Cloud Analytics Market, Sub Segment Analysis6.4.1. Others
7. GlobalCloud Analytics Market, byVerticles7.1. Market Snapshot7.2. GlobalCloud Analytics Market by Verticles, Performance Potential Analysis7.3. GlobalCloud Analytics Market Estimates & Forecasts by Verticles 2018-2028 (USD Billion)7.4.Cloud Analytics Market, Sub Segment Analysis
8. GlobalCloud Analytics Market, Regional Analysis8.1.Cloud Analytics Market, Regional Market Snapshot8.2. North AmericaCloud Analytics Market8.3. EuropeCloud Analytics Market Snapshot8.4. Asia-PacificCloud Analytics Market Snapshot8.5. Latin AmericaCloud Analytics Market Snapshot8.6. Rest of The WorldCloud Analytics Market
9. Competitive Intelligence9.1. Top Market Strategies9.2. Company Profiles9.2.1.Keyplayer19.2.1.1. Key InDurationation9.2.1.2. Overview9.2.1.3. Financial (Subject to Data Availability)9.2.1.4. Product Summary9.2.1.5. Recent Developments
10. Research Process10.1. Research Process10.1.1. Data Mining10.1.2. Analysis10.1.3. Market Estimation10.1.4. Validation10.1.5. Publishing10.2. Research Attributes
.
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EXPLORATION OP-ED: Up to R100bn in new mining ventures held up by delays in implementing mining cadastre – Daily Maverick
South Africas mining industry was once world-leading but now only accounts for around 4% of mining production worldwide. This decline in output is coupled with significant declines and volatility in global investment in the South African mining sector. This has led to South Africa being declared one of the most unattractive mining investment countries.
Despite this, South Africas economy still largely relies on its mining industry for much of its economic output and exports. However, recent and long-run data highlights the South African mining sectors struggles to grow and attract investment despite some bright spots. All signs are pointing towards mining becoming a sunset industry.
Most of these issues are being levelled at the feet of the South African Mineral Resources Administration System (Samrad), which has been labelled dysfunctional and opaque. Given these persistent problems, the Department of Minerals, Resources, and Energy (DMRE) has, as part of efforts to reignite and strengthen the ever-weakening mining sector, hailed its latest initiative, a mining cadastre (considered a gold standard in the industry), as the silver bullet designed to stop the seemingly unending corruption linked to the awarding of mining licences in the hopes of clawing in much-needed investment.
A mining cadastre is an online portal that provides pertinent information and data to the public, such as a countrys geological data, mining jurisdictions, the issuance of mining permits, expiry dates on already-issued licences, and available mining and prospecting rights, among others.
The move toward an online cadastre for the South African mining sector is heralded to bring about necessary transparency and reduce opportunities for corruption while also acting as a crucial missing piece in South Africas mining exploration puzzle.
The only problem is that since the announcement of the mining cadastre system by Minister Gwede Mantashe, no such system is in place or developed, with the minister himself citing the delays in the cadastre as one of the DMREs biggest headaches. Yet, at the recent Mining Indaba held in Cape Town, the minister and others within the DMRE told the participants that the delay in the delivery of the cadastre system was due to problems with the tender process designed to appoint developers for the system.
In the background, 4,500 mining applications (amounting to approximately R100-billion) remain unauthorised, according to Roger Baxter, CEO of the SA Minerals Council.
This backlog of mining licences is not just bad news for prospective exploration projects forced to wait in the wings while the DMRE gets its act together. It also spells bad news for the entire mining value chain because the mining industry comprises several different stages (e.g., from exploration to refining). All of these different stages of a mines lifecycle employ a broad spectrum of machinery and equipment, whose manufacturers are being unnecessarily stifled in their efforts to supply goods and services to these 4,500 unauthorised licensees while the cadastre system is looking like it is dead in the water.
Research conducted by the Centre for Competition, Regulation and Economic Development (CCRED) at the University of Johannesburg into the mining machinery and equipment value chain has pointed to the importance of the machinery and equipment sector as an industry that can assist in structurally transforming the mining sector and the broader economy given its linkages to other industries.
For example, the original equipment manufacturers (OEMs) supplying equipment to the mining industry have critical backward linkages to modular and major assembly suppliers, sub-assembly and parts suppliers, specialist component suppliers, and raw material suppliers.
In addition, the machinery and equipment sector is considered a root industry in the Fourth Industrial Revolution, which is becoming a more significant potential threat as the global mining value chain is fast becoming more complex and concentrated around large multinational OEMs who control competitive niches in the market.
To become competitive, South Africas machinery and equipment sector requires comprehensive and well-structured strategies to turn the industry around, given its poor performance over the past few years. Continued delays in the mining cadastre wont help this poor performance.
However, reviving the ailing mining industry is not as simple as getting the mining cadastre up and running. More steps need to be taken. For instance, South Africas machinery and equipment value chain has established some critical capabilities, with islands of competitiveness, that can be leveraged to create more technologically-sophisticated capabilities.
However, these islands of competitiveness are coming under threat, reflected in South Africas declining market shares in the SADC region (considered a key growth opportunity for South Africas exports) and deep-sea markets.
CCREDs research, which was one of the inputs into the Department of Trade, Industry and Competitions Steel Masterplan, emphasised the need to increase national industrial capabilities built on the back of national champions, increase exports, and accelerate transformation in the machinery and equipment cluster. These are essential targets for the sector if it and its sub-sectors like mining are to effectively compete against influential multinational firms and break ground on new opportunities in the future.
Crucially too, other barriers to entry and structural problems must be rectified to assist the sector in becoming more competitive to regain its market share losses in the SADC region.
However, the story is clear-cut. For South Africa to achieve its larger industrial policy agenda, industry and government must first overcome more minor hurdles. Therefore, the DMRE must hold itself accountable for its failure to deliver the mining cadastre and work on expediting its development to unlock the R100-billion embodied in those 4,500 licences, indirectly paving the way for the machinery and equipment value chain to flourish as an additional benefit.
This is not a panacea for South Africas economic and social woes, but it is a move in the right direction. DM
Economist Jason F Bell is a researcher at the Centre for Competition Regulation and Economic Development (CCRED) at the College of Business and Economics, University of Johannesburg.
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Age, sex, residence, and region-specific differences in prevalence and patterns of multimorbidity among older Chinese: evidence from Chinese…
Data source and study population
Data came from the CLHLS, a widely representative cohort survey conducted by the center for healthy ageing and family studies at Peking University and the Chinese center for disease control and prevention (http://opendata.pku.edu.cn/dataverse/CHADS). This survey was first instituted in 1998 and is conducted at roughly three-year intervals to gather information on health status, socioeconomic characteristics, lifestyle, psychological attitudes, and the accessibility of healthcare service. All information was obtained through face-to-face interviews by specially trained interviewers from the local centers for disease prevention and control. In cases where participants were unable to answer questions, a proxy respondent (usually a spouse or a close relative) was interviewed, but questions about mood were answered by the participants themselves. The CLHLS study was approved by the Research Ethics Committee of Peking University (IRB0000105213074), and all participants or their proxy respondents provided written informed consent.
The samples were selected from 23 of 34 provinces in China. Detailed sampling procedures are available in elsewhere [18]. The most recent survey (2018) was used to explore the multimorbidity patterns in this study and involved interviews with 15,874 participants. After excluding 599 of these participants because they were under the age of 65, multiple imputation was used to deal with missing data, a valid sample of 15,275 were analyzed in this study.
Eighteen chronic noncommunicable diseases or conditions in CLHLS (see Table S1 in Additional file 1) and two affective disorders were included in our study. Most chronic diseases or conditions listed in the CLHLS are determined by answering the question: Are you currently suffering from any of the following chronic diseases? For the purpose of our analysis, heart disease and stroke/CVD were merged into cardiovascular disease; bronchitis, emphysema, pneumonia, and asthma were merged into respiratory disease; cataract and glaucoma were merged into vision impairment; Parkinsons disease, dementia, and epilepsy were merged into nervous system disease; arthritis and rheumatism/rheumatoid disease were merged into rheumatoid arthritis; and cholecystitis and cholelithiasis were merged into biliary disease.
Participants were identified as having an affective disorder if they had an anxiety disorder and/or depression. The Generalized Anxiety Disorder Scale (GAD-7) was used to assess anxiety symptoms and consists of seven negative-oriented questions. All responses were coded on four scales ranging from none (coded as 0), a few days (coded as 1), more than half the time (coded as 2), and almost every day (coded as 3). Total scores ranged from 0 to 21, with >4 being diagnosed as having anxiety disorder [20]. Depression disorder was accessed by the 10-item Center for Epidemiologic Studies Depression (CES-D) scale [21], which includes eight negative-oriented questions and two positive-oriented questions. We recoded all responses in a four-scale metric, ranging from always (coded as 0), often (coded as 1), sometimes (coded as 2), and seldom or never (coded as 3). Furthermore, the positive-oriented questions, including are you full of hope for future life? and do you feel as happy as you were when you are young? were reverse coded before the summary (seldom or never coded as 0, sometimes coded as 1, often coded as 2, and always coded as 3). The depression score ranges from 0 to 30, with a higher score suggesting a greater degree of depressive symptoms. A cutoff of 10 was defined as diagnosed with depression disorder. Multimorbidity was defined as an individual who has two or more chronic diseases or conditions and was divided into two types for analysis: 2 (MM2+) and3 (MM3+).
Personal information was collected about the respondents, including age, sex, and region. Age was classified into three categories: 6579years, 8089years, and90years. Residences were divided into urban (city and town) and rural on the basis of their geographical location. We categorized the regions into East (Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, and Shandong), West (Chongqing, Sichuan, and Shaanxi), South (Guangdong, Guangxi, and Hainan), North (Beijing, Tianjin, Hebei, Shanxi, Liaoning, Jilin, and Heilongjiang) and Central (Henan, Hubei, and Hunan).
ARM is the process of exploring associations between data items. Frequent itemset and association rules are mined according to the Apriori algorithm approach to discover combinations of variables that are associated in large databases [22, 23]. ARM consists of two steps: first, it involves listing all high-frequency items in the set; second, it generates frequent association rules based on the high-frequency items [24]. In the Apriori algorithm, Support, Confidence, and Lift are the measures of the degree of association. An association rule is an implication of the form {X}{Y}, where {X} and {Y} are disjointed, non-empty sets of codes. Code sets of {X} and {Y} are the antecedents and the consequents, respectively. The strength of an association rule {X}{Y} can be measured by Support (the prevalence of both X and Y co-occurring.) and Confidence (the probability that Y occurs given that X is already present.). Lift refers to the deviation of the support parameter from what would be expected if X and Y were independent; Lift (XY)=P(X, Y) / P(X)P(Y). When the Lift value is >1, it implies X and Y are positively correlated. A higher Lift value indicates a stronger association between X and Y.
Considering the CLHLS dataset, for example, we used the rule hypertension, rheumatoid arthritis=>vision impairment. This is expressed as follows: if a participant has both hypertension and rheumatoid arthritis (antecedent), this will lead to vision impairment (consequent). To simplify the analysis, the following minimum thresholds were used to define the degree of interest: support 3.0% and confidence >30.0%, lift >1. This means that for all association rules shown here ({X}{Y}), the joint set {X, Y} emerges more frequently than would be expected under statistical independence, the consequent ({Y}) occurring in at least 30% of all cases that show the morbidity in the antecedent ({X}).
In this study, missing data existed for all chronic disease variables at random, ranging from 653 in hypertension to 1097 in cancer. Direct deletion of missing data cases may cause a significant information loss, we performed multiple imputation by chained equations (MICE), using the mi package developed by Gelman in R studio [25]. Descriptive statistics were used to show sociodemographic characteristics. Analyses were stratified by age, sex, residence, and region. Categorical variables were expressed as frequencies. Frequency and percentages were reported for qualitative variables and assessed by the Chi-square test or Fishers exact test, as deemed appropriate. Findings at corrected P-values of <0.05 were considered significant. To visualize the epidemiological trends of multimorbidity, the distribution of the study population, the prevalence of MM2+ and MM3+ was mapped using ArcMap. We also plotted percentage stacked bar charts to reflect multimorbidity. Finally, we use the arules package in R studio for ARM to identify multiple patterns of chronic diseases. Sensitive analyses were conducted for association between ADL disability and chronic conditions. Statistical analyses were conducted using SPSS, version 22 for Windows (SPSS Inc., Chicago, IL, USA), R studio, version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria), and ArcGIS, version 10.3 (ArcMap, ESRI Inc., Redlands, CA, USA).
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Democrats ask Apple, Google to prohibit apps from using data mining to target people seeking abortions – The Hill
A group of Senate Democrats asked Apple and Google to prohibit apps available in their app stores from using data mining practices to target people seeking abortion services in letters sent to the tech giants Friday.
The senators, led by Sen. Ed Markey (Mass.), asked the companies to review and update their app store policies and practices as necessary to address concerns around allowing apps to engage in data practices that may victimize individuals who seek or have sought abortion services.
The Democrats said they are concerned that anti-abortion prosecutors or other actors will try to access and leverage personal information, such as data about locations, online activity, health and biometrics, in ways that threaten the well being of those exercising their right to choose.
The senators underscored the need for the updates following the leak of a draft majority opinion indicating the Supreme Court is poised to overturn Roe v. Wade, which could make abortion illegal in states across the country with restrictive laws.
The senators said information about app users fertility, browser histories indicating interest in contraception or location information showing a user visited a gynecologist could become a data trove for actors who are intent on targeting, intimidating, and harming individuals who seek abortions or individuals who simply take steps to promote their reproductive health.
The letters were also signed by Sens. Elizabeth Warren (D-Mass.), Ron Wyden (D-Ore.), Bernie Sanders (I-Vt.) and Cory Booker (D-N.J.).
Spokespeople for Apple and Google did not immediately respond to requests for comment.
The letters follow one sent by more than 40 Congressional Democrats to Google earlier this week urging the company to stop collecting and storing location data over concerns that it could be obtained by prosecutors to target individuals seeking abortion care.
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