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IBM Optimization Supply Chain Mgmt Technical Mastery Test v1
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Killexams : IBM Optimization Topics - BingNews https://killexams.com/pass4sure/exam-detail/P2050-006 Search results Killexams : IBM Optimization Topics - BingNews https://killexams.com/pass4sure/exam-detail/P2050-006 https://killexams.com/exam_list/IBM Killexams : How to save costs while moving to the cloud No result found, try new keyword!A perennial hot topic, even more so currently ... answer – especially if you don’t have a clear view of your pre-cloud spend Instead, the key is optimization through a combination of rightsizing, ... Sun, 17 Jul 2022 19:10:00 -0500 en-US text/html https://www.datacenterdynamics.com/en/opinions/how-to-save-costs-while-moving-to-the-cloud/ Killexams : IBM Unveils $1 Billion Platform-as-a-Service Investment No result found, try new keyword!IBM says its data and analytics optimization system Power Systems will soon begin running on the SoftLayer cloud infrastructure to support Watson Solutions. IBM invests more than $6 billion in R&D ... Fri, 22 Jul 2022 12:00:00 -0500 en-us text/html https://www.thestreet.com/technology/ibm-unveils-1-billion-platform-as-a-service-investment-12438325 Killexams : Code Watch: Learning machine learning

Machine learning is, regrettably, not one of the day-to-day chores assigned to most programmers. However, with data volumes exploding, and high-profile successes such as IBM’s Jeopardy-beating Watson and the recommendation engines of Amazon and Netflix, the odds are increasing that ML’s opportunity might knock on your door one day.

From the 1960s to the 1980s, the emphasis of artificial intelligence was in “top-down” approaches in which expertise from domain experts was somehow transcribed into a fixed set of rules and their relations. Often, these would be a series of small “if-then” rules, and the “magic sauce” of expert systems was that they could draw conclusions by automatically chaining together the execution of those rules whose “if” parameters were known. The technology for inferencing worked well enough, but it turned out that very large rulebases were hard to debug and maintain, while not very large rulebases didn’t produce many compelling applications (for instance, my expert system for identifying seabirds failed to make me a billionaire).

The late 1980s saw a shift toward algorithms influenced by biological processes, and the rebirth of artificial neural networks (which were actually developed in the early 1960s), genetic algorithms, and such things as Ant and flocking algorithms. There was a flurry of interest in fuzzy logic, which was particularly well suited for control systems, as they provided continuous response curves.

The 1990s saw increasingly sophisticated algorithms in all these areas and began the march toward today’s world of machine learning, with its emphasis on statistical techniques used against large datasets. Perhaps the most significant development was the invention of support vector machines, which provide a robust way to determine hyperplanes that effectively bisect high-dimensional solution spaces.

As that last sentence demonstrated, it doesn’t take long before the techniques of AI and ML flirt with becoming unintelligible. A sentence can often be a confusing mashup of mathematics, jargon from AI’s five-decade history, and flawed metaphor (artificial neural networks aren’t a great deal like real-world neurons, and genetic algorithms don’t have much in common with meiosis and DNA recombination). But while there is a temptation to use a technique as a black box, I strongly believe that sustained success requires gaining an intuition into the underlying technique. That intuition doesn’t need to be an academic-level understanding of the mathematics, but it does need to be at a level where you can make reasonable guesses as to what type and volume of data you need, why and what kind of preprocessing you might need, and what problems are likely to crop up during processing.

Neural nets and genetic algorithms were hot Topics when I was editing “AI Expert,” but 20 years later, the most common StackOverflow.com questions about these techniques treat them as black boxes and often reveal misguided use cases. Genetic algorithms, in particular, seem to be woefully misunderstood. If you’re thinking about solving a problem with a GA, please buy a copy of Goldberg’s “Genetic Algorithms in Search, Optimization, and Machine Learning” or Mitchell’s “An Introduction to Genetic Algorithms,” and spend two days practicing before you begin coding. I ensure your results will come faster than if you don’t understand the model.

I think it’s fair to say that support vector machines are the most complex of the techniques in standard AI/ML (whatever you want to call it). Peter Harrington’s accurate book “Machine Learning in Action” does a good job of promoting understanding and intuition while having a good deal of the cookbook-style format that has become popular. Of course it doesn’t start with SVMs, but it’s no coincidence that the techniques of the initial chapters introduce the terminology and domain (at the expense of some of the other techniques I’ve mentioned). The code is in Python, which is one of the clearest languages even if it’s not your day-to-day work language; no matter what language you program in, you can understand an algorithm written in Python, although you naturally lose access to powerful libraries such as NumPy and SciPy. (Python is increasingly popular among scientists, but that’s a subject for another column.)

The simple heuristics for choosing among the major AI algorithms is, if it’s a set of rules that change over time with many interdependencies, consider an expert system (but it’s probably easier just to write the code). If it’s finding the best parameters to a function, consider a genetic algorithm. If it’s finding a winning move in a complex sequential game, consider tree search with pruning (or the infuriatingly successful Monte Carlo Tree Search). If it’s pattern-recognition and classification, try an SVM or, if you’re feeling nostalgic, a neural network.

One way or the other, if you have the opportunity, seize it. It’s always a thrill to write a program that solves a user’s problem, but it is pure joy to write a program that solves new ones.

Larry O’Brien is a technology consultant, analyst and writer. Read his blog at www.knowing.net.

Fri, 15 Jul 2022 12:00:00 -0500 en-US text/html https://sdtimes.com/machine-learning/code-watch-learning-machine-learning/
Killexams : CIOReview Names Cobalt Iron Among 10 Most Promising IBM Solution Providers 2022

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

LAWRENCE, Kan.--(BUSINESS WIRE)--Jul 28, 2022--

Cobalt Iron Inc., a leading provider of SaaS-based enterprise data protection, today announced that the company has been deemed one of the 10 Most Promising IBM Solution Providers 2022 by CIOReview Magazine. The annual list of companies is selected by a panel of experts and members of CIOReview Magazine’s editorial board to recognize and promote innovation and entrepreneurship. A technology partner for IBM, Cobalt Iron earned the distinction based on its Compass ® enterprise SaaS backup platform for monitoring, managing, provisioning, and securing the entire enterprise backup landscape.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220728005043/en/

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

According to CIOReview, “Cobalt Iron has built a patented cyber-resilience technology in a SaaS model to alleviate the complexities of managing large, multivendor setups, providing an effectual humanless backup experience. This SaaS-based data protection platform, called Compass, leverages strong IBM technologies. For example, IBM Spectrum Protect is embedded into the platform from a data backup and recovery perspective. ... By combining IBM’s technologies and the intellectual property built by Cobalt Iron, the company delivers a secure, modernized approach to data protection, providing a ‘true’ software as a service.”

Through proprietary technology, the Compass data protection platform integrates with, automates, and optimizes best-of-breed technologies, including IBM Spectrum Protect, IBM FlashSystem, IBM Red Hat Linux, IBM Cloud, and IBM Cloud Object Storage. Compass enhances and extends IBM technologies by automating more than 80% of backup infrastructure operations, optimizing the backup landscape through analytics, and securing backup data, making it a valuable addition to IBM’s data protection offerings.

CIOReview also praised Compass for its simple and intuitive interface to display a consolidated view of data backups across an entire organization without logging in to every backup product instance to extract data. The machine learning-enabled platform also automates backup processes and infrastructure, and it uses open APIs to connect with ticket management systems to generate tickets automatically about any backups that need immediate attention.

To ensure the security of data backups, Cobalt Iron has developed an architecture and security feature set called Cyber Shield for 24/7 threat protection, detection, and analysis that improves ransomware responsiveness. Compass is also being enhanced to use several patented techniques that are specific to analytics and ransomware. For example, analytics-based cloud brokering of data protection operations helps enterprises make secure, efficient, and cost-effective use of their cloud infrastructures. Another patented technique — dynamic IT infrastructure optimization in response to cyberthreats — offers unique ransomware analytics and automated optimization that will enable Compass to reconfigure IT infrastructure automatically when it detects cyberthreats, such as a ransomware attack, and dynamically adjust access to backup infrastructure and data to reduce exposure.

Compass is part of IBM’s product portfolio through the IBM Passport Advantage program. Through Passport Advantage, IBM sellers, partners, and distributors around the world can sell Compass under IBM part numbers to any organizations, particularly complex enterprises, that greatly benefit from the automated data protection and anti-ransomware solutions Compass delivers.

CIOReview’s report concludes, “With such innovations, all eyes will be on Cobalt Iron for further advancements in humanless, secure data backup solutions. Cobalt Iron currently focuses on IP protection and continuous R&D to bring about additional cybersecurity-related innovations, promising a more secure future for an enterprise’s data.”

About Cobalt Iron

Cobalt Iron was founded in 2013 to bring about fundamental changes in the world’s approach to secure data protection, and today the company’s Compass ® is the world’s leading SaaS-based enterprise data protection system. Through analytics and automation, Compass enables enterprises to transform and optimize legacy backup solutions into a simple cloud-based architecture with built-in cybersecurity. Processing more than 8 million jobs a month for customers in 44 countries, Compass delivers modern data protection for enterprise customers around the world. www.cobaltiron.com

Product or service names mentioned herein are the trademarks of their respective owners.

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Photo Caption: Cobalt Iron Compass ® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection.

Follow Cobalt Iron

https://twitter.com/cobaltiron
https://www.linkedin.com/company/cobalt-iron/
https://www.youtube.com/user/CobaltIronLLC

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CONTACT: Agency Contact:

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Wall Street Communications

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Killexams : Breakthrough quantum algorithm

City College of New York physicist Pouyan Ghaemi and his research team are claiming significant progress in using quantum computers to study and predict how the state of a large number of interacting quantum particles evolves over time. This was done by developing a quantum algorithm that they run on an IBM quantum computer. "To the best of our knowledge, such particular quantum algorithm which can simulate how interacting quantum particles evolve over time has not been implemented before," said Ghaemi, associate professor in CCNY's Division of Science.

Entitled "Probing geometric excitations of fractional quantum Hall states on quantum computers," the study appears in the journal of Physical Review Letters.

"Quantum mechanics is known to be the underlying mechanism governing the properties of elementary particles such as electrons," said Ghaemi. "But unfortunately there is no easy way to use equations of quantum mechanics when we want to study the properties of large number of electrons that are also exerting force on each other due to their electric charge.

His team's discovery, however, changes this and raises other exciting possibilities.

"On the other front, recently, there has been extensive technological developments in building the so-called quantum computers. These new class of computers utilize the law of quantum mechanics to preform calculations which are not possible with classical computers."

We know that when electrons in material interact with each other strongly, interesting properties such as high-temperature superconductivity could emerge," Ghaemi noted. "Our quantum computing algorithm opens a new avenue to study the properties of materials resulting from strong electron-electron interactions. As a result it can potentially guide the search for useful materials such as high temperature superconductors."

He added that based on their results, they can now potentially look at using quantum computers to study many other phenomena that result from strong interaction between electrons in solids. "There are many experimentally observed phenomena that could be potentially understood using the development of quantum algorithms similar to the one we developed."

The research was done at CCNY -- and involved an interdisciplinary team from the physics and electrical engineering departments -- in collaboration with experts from Western Washington University, Leeds University in the UK; and Schlumberger-Doll Research Center in Cambridge, Massachusetts. The research was funded by the National Science Foundation and Britain's Engineering and Science Research Council.

Story Source:

Materials provided by City College of New York. Note: Content may be edited for style and length.

Tue, 26 Jul 2022 12:00:00 -0500 en text/html https://www.sciencedaily.com/releases/2022/07/220727110714.htm
Killexams : Dow Analyst Moves: IBM No result found, try new keyword!T he latest tally of analyst opinions from the major brokerage houses shows that among the 30 stocks making up the Dow Jones Industrial Average, International Business Machines is the #22 analyst pick ... Mon, 01 Aug 2022 03:46:00 -0500 text/html https://www.nasdaq.com/articles/dow-analyst-moves%3A-ibm-2 Killexams : Life Sciences Analytics Market 2022, Worth USD 27000 Mn by 2028 at CAGR of 6.2% – Report Spread across 110 Pages

The MarketWatch News Department was not involved in the creation of this content.

Aug 04, 2022 (The Expresswire) -- [110 Pages] "Life Sciences Analytics Market" Insights 2022 By Types (Services, Software), Applications (Clinical Research Institutions, Pharmaceutical and Biotechnology Companies, Medical Device Companies, Others), Regions and Forecast to 2028. The Life Sciences Analytics Market research includes an in-depth analysis of report detailed information on factors influencing demand, growth, opportunities, challenges, and restraints, and Analysis of Pre and Post COVID-19 Market. The global Life Sciences Analytics market size is projected to reach multi million by 2028, in comparison to 2022, with unexpected CAGR during the forecast period.

The Life Sciences Analytics market report provides a detailed analysis of global market size, regional and country-level market size, segmentation market growth, market share, competitive Landscape, sales analysis, impact of domestic and global market players, value chain optimization, trade regulations, accurate developments, opportunities analysis, strategic market growth analysis, product launches, area marketplace expanding, and technological innovations.

According to our (Global Info Research) latest study, due to COVID-19 pandemic, the global Life Sciences Analytics market size is estimated to be worth USD 17700 million in 2021 and is forecast to a readjusted size of USD 27000 million by 2028 with a CAGR of 6.2% during review period. Clinical Research Institutions accounting for % of the Life Sciences Analytics global market in 2021, is projected to value USD million by 2028, growing at a % CAGR in next six years. While Services segment is altered to a % CAGR between 2022 and 2028.

Global key companies of Life Sciences Analytics include Accenture, Cognizant, IBM Corporation, Oracle Corporation, and IQVIA, etc. In terms of revenue, the global top four players hold a share over % in 2021.

The Global Life Sciences Analytics market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2028. In 2021, the market is growing at a steady rate and with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon.

Final Report will add the analysis of the impact of COVID-19 on this industry.

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Moreover, it helps new businesses perform a positive assessment of their business plans because it covers a range of Topics market participants must be aware of to remain competitive.

Life Sciences Analytics Market Report identifies various key players in the market and sheds light on their strategies and collaborations to combat competition. The comprehensive report provides a two-dimensional picture of the market. By knowing the global revenue of manufacturers, the global price of manufacturers, and the production by manufacturers during the forecast period of 2022 to 2028, the reader can identify the footprints of manufacturers in the Life Sciences Analytics industry.

Get a demo PDF of report -https://www.marketgrowthreports.com/enquiry/request-sample/21008552

Life Sciences Analytics Market - Competitive and Segmentation Analysis:

As well as providing an overview of successful marketing strategies, market contributions, and accurate developments of leading companies, the report also offers a dashboard overview of leading companies' past and present performance. Several methodologies and analyses are used in the research report to provide in-depth and accurate information about the Life Sciences Analytics Market.

The Major players covered in the Life Sciences Analytics market report are:

The ● Accenture
● Cognizant
● IBM Corporation
● Oracle Corporation
● IQVIA
● SAS Institute
● SCIOInspire
● TAKE Solutions
● Wipro
● Genpact
● Tableau
● Veeva Systems
● SAP
● Medidata Solutions
● Microsoft
● Salesforce
● ArisGlobal

The current market dossier provides market growth potential, opportunities, drivers, industry-specific challenges and risks market share along with the growth rate of the global Life Sciences Analytics market. The report also covers monetary and exchange fluctuations, import-export trade, and global market

status in a smooth-tongued pattern. The SWOT analysis, compiled by industry experts, Industry Concentration Ratio and the latest developments for the global Life Sciences Analytics market share are covered in a statistical way in the form of tables and figures including graphs and charts for easy understanding.

Get a demo Copy of the Life Sciences Analytics Market Report 2022

A thorough evaluation of the restrains included in the report portrays the contrast to drivers and gives room for strategic planning. Factors that overshadow the market growth are pivotal as they can be understood to devise different bends for getting hold of the lucrative opportunities that are present in the ever-growing market. Additionally, insights into market expert’s opinions have been taken to understand the market better.

Report further studies the market development status and future Life Sciences Analytics Market trend across the world. Also, it splits Life Sciences Analytics market Segmentation by Type and by Applications to fully and deeply research and reveal market profile and prospects.

On the basis of product typethis report displays the production, revenue, price, market share and growth rate of each type, primarily split into:

● Services
● Software

On the basis of the end users/applicationsthis report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including:

● Clinical Research Institutions
● Pharmaceutical and Biotechnology Companies
● Medical Device Companies
● Others

Life Sciences Analytics Market - Regional Analysis:

Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Life Sciences Analytics in these regions, from 2015 to 2027, covering

● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Some of the key questions answered in this report:

● What is the global (North America, Europe, Asia-Pacific, South America, Middle East and Africa) sales value, production value, consumption value, import and export of Life Sciences Analytics? ● Who are the global key manufacturers of the Life Sciences Analytics Industry? How is their operating situation (capacity, production, sales, price, cost, gross, and revenue)? ● How the competition goes in the future related to Life Sciences Analytics? ● Which is the most leading country in the world? ● What are the Life Sciences Analytics market opportunities and threats faced by the vendors in the global Life Sciences Analytics Industry? ● Which application/end-user or product type may seek incremental growth prospects? What is the market share of each type and application? ● What focused approach and constraints are holding the Life Sciences Analytics market? ● What are the different sales, marketing, and distribution channels in the global industry? ● What are the upstream raw materials and manufacturing equipment of Life Sciences Analytics along with the manufacturing process of Acetonitrile? ● What are the key market trends impacting the growth of the Life Sciences Analytics market? ● Economic impact on the Life Sciences Analytics industry and development trend of the Life Sciences Analytics industry. ● What are the market opportunities, market risk, and market overview of the Life Sciences Analytics market? ● What are the key drivers, restraints, opportunities, and challenges of the Life Sciences Analytics market, and how they are expected to impact the market? ● What is the Life Sciences Analytics market size at the regional and country-level? ● How do you find your target audience?

Our research analysts will help you to get customized details for your report, which can be modified in terms of a specific region, application or any statistical details. In addition, we are always willing to comply with the study, which triangulated with your own data to make the market research more comprehensive in your perspective.

Inquire more and share questions if any before the purchase on this report at- https://www.marketgrowthreports.com/enquiry/pre-order-enquiry/21008552

With tables and figures helping analyse worldwide Global Life Sciences Analytics market trends, this research provides key statistics on the state of the industry and is a valuable source of guidance and direction for companies and individuals interested in the market.

Detailed TOC of Global Life Sciences Analytics Market Research Report 2022

1 Scope of the Report
1.1 Market Introduction
1.2 Years Considered
1.3 Research Objectives
1.4 Market Research Methodology
1.5 Research Process and Data Source
1.6 Economic Indicators
1.7 Currency Considered

2 Executive Summary
2.1 World Market Overview
2.1.1 Global Life Sciences Analytics Annual Sales 2017-2028
2.1.2 World Current and Future Analysis for Life Sciences Analytics by Geographic Region, 2017, 2022 and 2028
2.1.3 World Current and Future Analysis for Life Sciences Analytics by Country/Region, 2017, 2022 and 2028
2.2 Life Sciences Analytics Segment by Type
2.3 Life Sciences Analytics Sales by Type
2.3.1 Global Life Sciences Analytics Sales Market Share by Type (2017-2022)
2.3.2 Global Life Sciences Analytics Revenue and Market Share by Type (2017-2022)
2.3.3 Global Life Sciences Analytics Sale Price by Type (2017-2022)
2.4 Life Sciences Analytics Segment by Applications
2.5 Life Sciences Analytics Sales by Application
2.5.1 Global Life Sciences Analytics Sale Market Share by Application (2017-2022)
2.5.2 Global Life Sciences Analytics Revenue and Market Share by Application (2017-2022)
2.5.3 Global Life Sciences Analytics Sale Price by Application (2017-2022)

3 Global Life Sciences Analytics by Company
3.1 Global Life Sciences Analytics Breakdown Data by Company
3.1.1 Global Life Sciences Analytics Annual Sales by Company (2020-2022)
3.1.2 Global Life Sciences Analytics Sales Market Share by Company (2020-2022)
3.2 Global Life Sciences Analytics Annual Revenue by Company (2020-2022)
3.2.1 Global Life Sciences Analytics Revenue by Company (2020-2022)
3.2.2 Global Life Sciences Analytics Revenue Market Share by Company (2020-2022)
3.3 Global Life Sciences Analytics Sale Price by Company
3.4 Key Manufacturers Life Sciences Analytics Producing Area Distribution, Sales Area, Product Type
3.4.1 Key Manufacturers Life Sciences Analytics Product Location Distribution
3.4.2 Players Life Sciences Analytics Products Offered
3.5 Market Concentration Rate Analysis
3.5.1 Competition Landscape Analysis
3.5.2 Concentration Ratio (CR3, CR5 and CR10) and (2020-2022)
3.6 New Products and Potential Entrants
3.7 Mergers and Acquisitions, Expansion

4 World Historic Review for Life Sciences Analytics by Geographic Region
4.1 World Historic Life Sciences Analytics Market Size by Geographic Region (2017-2022)
4.1.1 Global Life Sciences Analytics Annual Sales by Geographic Region (2017-2022)
4.1.2 Global Life Sciences Analytics Annual Revenue by Geographic Region
4.2 World Historic Life Sciences Analytics Market Size by Country/Region (2017-2022)
4.2.1 Global Life Sciences Analytics Annual Sales by Country/Region (2017-2022)
4.2.2 Global Life Sciences Analytics Annual Revenue by Country/Region
4.3 Americas Life Sciences Analytics Sales Growth
4.4 APAC Life Sciences Analytics Sales Growth
4.5 Europe Life Sciences Analytics Sales Growth
4.6 Middle East and Africa Life Sciences Analytics Sales Growth

Get a demo Copy of the Life Sciences Analytics Market Report 2022

5 Americas
5.1 Americas Life Sciences Analytics Sales by Country
5.1.1 Americas Life Sciences Analytics Sales by Country (2017-2022)
5.1.2 Americas Life Sciences Analytics Revenue by Country (2017-2022)
5.2 Americas Life Sciences Analytics Sales by Type
5.3 Americas Life Sciences Analytics Sales by Application
5.4 United States
5.5 Canada
5.6 Mexico
5.7 Brazil

6 APAC
6.1 APAC Life Sciences Analytics Sales by Region
6.1.1 APAC Life Sciences Analytics Sales by Region (2017-2022)
6.1.2 APAC Life Sciences Analytics Revenue by Region (2017-2022)
6.2 APAC Life Sciences Analytics Sales by Type
6.3 APAC Life Sciences Analytics Sales by Application
6.4 China
6.5 Japan
6.6 South Korea
6.7 Southeast Asia
6.8 India
6.9 Australia
6.10 China Taiwan

7 Europe
7.1 Europe Life Sciences Analytics by Country
7.1.1 Europe Life Sciences Analytics Sales by Country (2017-2022)
7.1.2 Europe Life Sciences Analytics Revenue by Country (2017-2022)
7.2 Europe Life Sciences Analytics Sales by Type
7.3 Europe Life Sciences Analytics Sales by Application
7.4 Germany
7.5 France
7.6 UK
7.7 Italy
7.8 Russia

8 Middle East and Africa
8.1 Middle East and Africa Life Sciences Analytics by Country
8.1.1 Middle East and Africa Life Sciences Analytics Sales by Country (2017-2022)
8.1.2 Middle East and Africa Life Sciences Analytics Revenue by Country (2017-2022)
8.2 Middle East and Africa Life Sciences Analytics Sales by Type
8.3 Middle East and Africa Life Sciences Analytics Sales by Application
8.4 Egypt
8.5 South Africa
8.6 Israel
8.7 Turkey
8.8 GCC Countries

9 Market Drivers, Challenges and Trends
9.1 Market Drivers and Growth Opportunities
9.2 Market Challenges and Risks
9.3 Industry Trends

10 Manufacturing Cost Structure Analysis
10.1 Raw Material and Suppliers
10.2 Manufacturing Cost Structure Analysis of Life Sciences Analytics
10.3 Manufacturing Process Analysis of Life Sciences Analytics
10.4 Industry Chain Structure of Life Sciences Analytics

11 Marketing, Distributors and Customer
11.1 Sales Channel
11.1.1 Direct Channels
11.1.2 Indirect Channels
11.2 Life Sciences Analytics Distributors
11.3 Life Sciences Analytics Customer

12 World Forecast Review for Life Sciences Analytics by Geographic Region
12.1 Global Life Sciences Analytics Market Size Forecast by Region
12.1.1 Global Life Sciences Analytics Forecast by Region (2023-2028)
12.1.2 Global Life Sciences Analytics Annual Revenue Forecast by Region (2023-2028)
12.2 Americas Forecast by Country
12.3 APAC Forecast by Region
12.4 Europe Forecast by Country
12.5 Middle East and Africa Forecast by Country
12.6 Global Life Sciences Analytics Forecast by Type
12.7 Global Life Sciences Analytics Forecast by Application

13 Key Players Analysis
13.1.1 Company Information
13.1.2 Life Sciences Analytics Product Offered
13.1.3 Life Sciences Analytics Sales, Revenue, Price and Gross Margin (2020-2022)
13.1.4 Main Business Overview
13.1.5 Latest Developments

14 Research Findings and Conclusion

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Killexams : Aviation IoT Market 2022, Worth USD 1443.3 Mn by 2028 at CAGR of 16.9% – Report Spread across 86 Pages

The MarketWatch News Department was not involved in the creation of this content.

Jul 22, 2022 (The Expresswire) -- [86 Pages] "Aviation IoT Market" Insights 2022 By Types (Passengers Aviation IoT, Aircraft Operations Aviation IoT, Other), Applications (Military, Civilian), Regions and Forecast to 2028. The Aviation IoT Market research includes an in-depth analysis of report detailed information on factors influencing demand, growth, opportunities, challenges, and restraints, and Analysis of Pre and Post COVID-19 Market. The global Aviation IoT market size is projected to reach multi million by 2028, in comparison to 2022, with unexpected CAGR during the forecast period.

The Aviation IoT market report provides a detailed analysis of global market size, regional and country-level market size, segmentation market growth, market share, competitive Landscape, sales analysis, impact of domestic and global market players, value chain optimization, trade regulations, accurate developments, opportunities analysis, strategic market growth analysis, product launches, area marketplace expanding, and technological innovations.

According to our (Global Info Research) latest study, due to COVID-19 pandemic, the global Aviation IoT market size is estimated to be worth USD 482.7 million in 2021 and is forecast to a readjusted size of USD 1443.3 million by 2028 with a CAGR of 16.9% during review period. Military accounting for % of the Aviation IoT global market in 2021, is projected to value USD million by 2028, growing at a % CAGR in next six years. While Passengers Aviation IoT segment is altered to a % CAGR between 2022 and 2028.

Global key companies of Aviation IoT include IBM, Cisco Systems, Microsoft, Wind River, and Accenture, etc. In terms of revenue, the global top four players hold a share over % in 2021.

The Global Aviation IoT market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2028. In 2021, the market is growing at a steady rate and with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon.

Final Report will add the analysis of the impact of COVID-19 on this industry.

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Moreover, it helps new businesses perform a positive assessment of their business plans because it covers a range of Topics market participants must be aware of to remain competitive.

Aviation IoT Market Report identifies various key players in the market and sheds light on their strategies and collaborations to combat competition. The comprehensive report provides a two-dimensional picture of the market. By knowing the global revenue of manufacturers, the global price of manufacturers, and the production by manufacturers during the forecast period of 2022 to 2028, the reader can identify the footprints of manufacturers in the Aviation IoT industry.

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Aviation IoT Market - Competitive and Segmentation Analysis:

As well as providing an overview of successful marketing strategies, market contributions, and accurate developments of leading companies, the report also offers a dashboard overview of leading companies' past and present performance. Several methodologies and analyses are used in the research report to provide in-depth and accurate information about the Aviation IoT Market.

The Major players covered in the Aviation IoT market report are:

The ● IBM
● Cisco Systems
● Microsoft
● Wind River
● Accenture
● Apple
● Living PlanIT
● Sitaonair

The current market dossier provides market growth potential, opportunities, drivers, industry-specific challenges and risks market share along with the growth rate of the global Aviation IoT market. The report also covers monetary and exchange fluctuations, import-export trade, and global market

status in a smooth-tongued pattern. The SWOT analysis, compiled by industry experts, Industry Concentration Ratio and the latest developments for the global Aviation IoT market share are covered in a statistical way in the form of tables and figures including graphs and charts for easy understanding.

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A thorough evaluation of the restrains included in the report portrays the contrast to drivers and gives room for strategic planning. Factors that overshadow the market growth are pivotal as they can be understood to devise different bends for getting hold of the lucrative opportunities that are present in the ever-growing market. Additionally, insights into market expert’s opinions have been taken to understand the market better.

Report further studies the market development status and future Aviation IoT Market trend across the world. Also, it splits Aviation IoT market Segmentation by Type and by Applications to fully and deeply research and reveal market profile and prospects.

On the basis of product typethis report displays the production, revenue, price, market share and growth rate of each type, primarily split into:

● Passengers Aviation IoT
● Aircraft Operations Aviation IoT
● Other

On the basis of the end users/applicationsthis report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including:

● Military
● Civilian

Aviation IoT Market - Regional Analysis:

Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Aviation IoT in these regions, from 2015 to 2027, covering

● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Some of the key questions answered in this report:

● What is the global (North America, Europe, Asia-Pacific, South America, Middle East and Africa) sales value, production value, consumption value, import and export of Aviation IoT? ● Who are the global key manufacturers of the Aviation IoT Industry? How is their operating situation (capacity, production, sales, price, cost, gross, and revenue)? ● How the competition goes in the future related to Aviation IoT? ● Which is the most leading country in the world? ● What are the Aviation IoT market opportunities and threats faced by the vendors in the global Aviation IoT Industry? ● Which application/end-user or product type may seek incremental growth prospects? What is the market share of each type and application? ● What focused approach and constraints are holding the Aviation IoT market? ● What are the different sales, marketing, and distribution channels in the global industry? ● What are the upstream raw materials and manufacturing equipment of Aviation IoT along with the manufacturing process of Acetonitrile? ● What are the key market trends impacting the growth of the Aviation IoT market? ● Economic impact on the Aviation IoT industry and development trend of the Aviation IoT industry. ● What are the market opportunities, market risk, and market overview of the Aviation IoT market? ● What are the key drivers, restraints, opportunities, and challenges of the Aviation IoT market, and how they are expected to impact the market? ● What is the Aviation IoT market size at the regional and country-level? ● How do you find your target audience?

Our research analysts will help you to get customized details for your report, which can be modified in terms of a specific region, application or any statistical details. In addition, we are always willing to comply with the study, which triangulated with your own data to make the market research more comprehensive in your perspective.

Inquire more and share questions if any before the purchase on this report at- https://www.marketgrowthreports.com/enquiry/pre-order-enquiry/21053420

With tables and figures helping analyse worldwide Global Aviation IoT market trends, this research provides key statistics on the state of the industry and is a valuable source of guidance and direction for companies and individuals interested in the market.

Detailed TOC of Global Aviation IoT Market Research Report 2022

1 Scope of the Report
1.1 Market Introduction
1.2 Years Considered
1.3 Research Objectives
1.4 Market Research Methodology
1.5 Research Process and Data Source
1.6 Economic Indicators
1.7 Currency Considered

2 Executive Summary
2.1 World Market Overview
2.1.1 Global Aviation IoT Annual Sales 2017-2028
2.1.2 World Current and Future Analysis for Aviation IoT by Geographic Region, 2017, 2022 and 2028
2.1.3 World Current and Future Analysis for Aviation IoT by Country/Region, 2017, 2022 and 2028
2.2 Aviation IoT Segment by Type
2.3 Aviation IoT Sales by Type
2.3.1 Global Aviation IoT Sales Market Share by Type (2017-2022)
2.3.2 Global Aviation IoT Revenue and Market Share by Type (2017-2022)
2.3.3 Global Aviation IoT Sale Price by Type (2017-2022)
2.4 Aviation IoT Segment by Applications
2.5 Aviation IoT Sales by Application
2.5.1 Global Aviation IoT Sale Market Share by Application (2017-2022)
2.5.2 Global Aviation IoT Revenue and Market Share by Application (2017-2022)
2.5.3 Global Aviation IoT Sale Price by Application (2017-2022)

3 Global Aviation IoT by Company
3.1 Global Aviation IoT Breakdown Data by Company
3.1.1 Global Aviation IoT Annual Sales by Company (2020-2022)
3.1.2 Global Aviation IoT Sales Market Share by Company (2020-2022)
3.2 Global Aviation IoT Annual Revenue by Company (2020-2022)
3.2.1 Global Aviation IoT Revenue by Company (2020-2022)
3.2.2 Global Aviation IoT Revenue Market Share by Company (2020-2022)
3.3 Global Aviation IoT Sale Price by Company
3.4 Key Manufacturers Aviation IoT Producing Area Distribution, Sales Area, Product Type
3.4.1 Key Manufacturers Aviation IoT Product Location Distribution
3.4.2 Players Aviation IoT Products Offered
3.5 Market Concentration Rate Analysis
3.5.1 Competition Landscape Analysis
3.5.2 Concentration Ratio (CR3, CR5 and CR10) and (2020-2022)
3.6 New Products and Potential Entrants
3.7 Mergers and Acquisitions, Expansion

4 World Historic Review for Aviation IoT by Geographic Region
4.1 World Historic Aviation IoT Market Size by Geographic Region (2017-2022)
4.1.1 Global Aviation IoT Annual Sales by Geographic Region (2017-2022)
4.1.2 Global Aviation IoT Annual Revenue by Geographic Region
4.2 World Historic Aviation IoT Market Size by Country/Region (2017-2022)
4.2.1 Global Aviation IoT Annual Sales by Country/Region (2017-2022)
4.2.2 Global Aviation IoT Annual Revenue by Country/Region
4.3 Americas Aviation IoT Sales Growth
4.4 APAC Aviation IoT Sales Growth
4.5 Europe Aviation IoT Sales Growth
4.6 Middle East and Africa Aviation IoT Sales Growth

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5 Americas
5.1 Americas Aviation IoT Sales by Country
5.1.1 Americas Aviation IoT Sales by Country (2017-2022)
5.1.2 Americas Aviation IoT Revenue by Country (2017-2022)
5.2 Americas Aviation IoT Sales by Type
5.3 Americas Aviation IoT Sales by Application
5.4 United States
5.5 Canada
5.6 Mexico
5.7 Brazil

6 APAC
6.1 APAC Aviation IoT Sales by Region
6.1.1 APAC Aviation IoT Sales by Region (2017-2022)
6.1.2 APAC Aviation IoT Revenue by Region (2017-2022)
6.2 APAC Aviation IoT Sales by Type
6.3 APAC Aviation IoT Sales by Application
6.4 China
6.5 Japan
6.6 South Korea
6.7 Southeast Asia
6.8 India
6.9 Australia
6.10 China Taiwan

7 Europe
7.1 Europe Aviation IoT by Country
7.1.1 Europe Aviation IoT Sales by Country (2017-2022)
7.1.2 Europe Aviation IoT Revenue by Country (2017-2022)
7.2 Europe Aviation IoT Sales by Type
7.3 Europe Aviation IoT Sales by Application
7.4 Germany
7.5 France
7.6 UK
7.7 Italy
7.8 Russia

8 Middle East and Africa
8.1 Middle East and Africa Aviation IoT by Country
8.1.1 Middle East and Africa Aviation IoT Sales by Country (2017-2022)
8.1.2 Middle East and Africa Aviation IoT Revenue by Country (2017-2022)
8.2 Middle East and Africa Aviation IoT Sales by Type
8.3 Middle East and Africa Aviation IoT Sales by Application
8.4 Egypt
8.5 South Africa
8.6 Israel
8.7 Turkey
8.8 GCC Countries

9 Market Drivers, Challenges and Trends
9.1 Market Drivers and Growth Opportunities
9.2 Market Challenges and Risks
9.3 Industry Trends

10 Manufacturing Cost Structure Analysis
10.1 Raw Material and Suppliers
10.2 Manufacturing Cost Structure Analysis of Aviation IoT
10.3 Manufacturing Process Analysis of Aviation IoT
10.4 Industry Chain Structure of Aviation IoT

11 Marketing, Distributors and Customer
11.1 Sales Channel
11.1.1 Direct Channels
11.1.2 Indirect Channels
11.2 Aviation IoT Distributors
11.3 Aviation IoT Customer

12 World Forecast Review for Aviation IoT by Geographic Region
12.1 Global Aviation IoT Market Size Forecast by Region
12.1.1 Global Aviation IoT Forecast by Region (2023-2028)
12.1.2 Global Aviation IoT Annual Revenue Forecast by Region (2023-2028)
12.2 Americas Forecast by Country
12.3 APAC Forecast by Region
12.4 Europe Forecast by Country
12.5 Middle East and Africa Forecast by Country
12.6 Global Aviation IoT Forecast by Type
12.7 Global Aviation IoT Forecast by Application

13 Key Players Analysis
13.1.1 Company Information
13.1.2 Aviation IoT Product Offered
13.1.3 Aviation IoT Sales, Revenue, Price and Gross Margin (2020-2022)
13.1.4 Main Business Overview
13.1.5 Latest Developments

14 Research Findings and Conclusion

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Killexams : Privacy & Security

More than half of respondents to a new survey say their healthcare organizations experienced one or more cyberattacks in the past 24 months involving connected medical devices.

He's concerned that the acquisition would "provide Amazon with access to enormous tranches of patient data."

The companies are shaping their future plans for cybersecurity risk management, patient safety data and other health IT use cases.

The latest IBM X-Force Cost of a Data Breach Report also shows healthcare organizations have the longest breach cycle of any industry, requiring nearly 11 months to identify and contain security incidents.

 More than 92% of patients believe privacy is a right, and their health data should not be available for purchase, survey shows.

The draft publication 800-66 focuses on helping inform the industry about security issues around electronic protected health information.

Health systems in Kansas and Colorado had made sizable bitcoin payments after ransomware attacks. That money has now been recovered by the FBI and will be returned.

An expert in distributed ledger technology dives deep into how blockchain can best be used in healthcare – and dispels some stubborn misconceptions that might be hindering its wider acceptance.

"It should not take a federal investigation before a HIPAA-covered entity provides patients, or their personal representatives, with access to their medical records," said OCR Director Lisa J. Pino.

Strategies for protecting clinicians across the industry.

Mon, 01 Aug 2022 12:00:00 -0500 en text/html https://www.healthcareitnews.com/category/resource-topic/privacy-security
Killexams : Oncology Information System Market Report 2022: Consulting & Optimization Services Present Opportunities

DUBLIN, July 12, 2022 /PRNewswire/ -- The "Oncology Information System Market by Product and Service, Application, End User (Hospitals & diagnostic imaging centers, Ablation & Cancer Care Centers, Government Institutions and Research Facilities) - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

Research and Markets Logo

Oncology information systems manage data from various treatment schedules, treatment plans, and treatment delivery for each patient. Focus on laying a framework for standardization in OIS is further advancing the level of care for each cancer patient through a multidisciplinary approach.

Factors such as the increasing adoption of OIS solutions to curtail the increasing cost of care and growing cases of cancer are expected to witness strong growth during the forecasted period. For instance, as per National Cancer Institute, by 2040, the new cancer cases will rise by 29.5 million and the number of cancer-related deaths to 16.4 million per year. Moreover, the development of a wide range of novel technologies will bring significant opportunities for the oncology information system market during the forecast period.

The Software segment held the largest share during the forecast period

The software segment accounted for 83.6% of the oncology information system market for products and services in 2021. Software is a non-tangible component used to run a system or perform primary tasks, which include maintaining patient records and performing treatment planning in any healthcare organization or hospital. It is an integral part of the HCIT market and works as an interface between the database and end-users. Healthcare organizations are moving from on-premise models to the web- and cloud-based models, which fuels the growth of this segment during the forecast period.

Radiation oncology segment held the largest share during the forecast period

In 2021, the radiation oncology segment accounted for 53.8% of the oncology information system market for application. Radiation oncology specializes in treating cancer with radiation - delivering a high radiation dose directly to the tumor to kill cancer cells with minimum exposure to healthy tissue that surrounds the tumor. This limits complications, side effects, and secondary effects to healthy tissues, which is driving advancements in radiation oncology. Some of the novel radiation oncology therapies that are widely used include external beam radiation therapy (EBRT), internal beam radiation therapy (IBRT), intraoperative radiation therapy (IORT), and brachytherapy. Integration of the radiotherapy system with OIS enables clinicians to accelerate radiation dose calculation speed and Excellerate the overall treatment planning efficiency.

 Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Increasing Prevalence of Cancer to Drive Market Growth
4.2 Consulting & Optimization Services to Register Highest Growth During Forecast Period
4.3 Radiation Oncology Segment Accounted for Largest Market Share in 2021
4.4 Developing Markets to Register Higher Growth During Forecast Period
4.5 China to Witness Highest Growth from 2022 to 2027

5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Need to Curtail Oncology Care Costs
5.2.1.2 Growing Adoption of EHRS and Other Oncology Healthcare IT Solutions to Excellerate Care Quality
5.2.1.3 Increasing Incidence and Prevalence of Cancer
5.2.1.4 Favorable Government Mandates and Support for Oncology Information Systems
5.2.1.5 Potential Benefits of and Technological Advancements in Oncology Information Systems
5.2.2 Restraints
5.2.2.1 Interoperability Issues
5.2.2.2 Dearth of Skilled It Professionals in Healthcare Industry
5.2.3 Opportunities
5.2.3.1 Growing Healthcare IT Industry
5.2.3.2 Integration of EMR with Treatment Planning Systems
5.2.4 Challenges
5.2.4.1 Concerns Regarding Data Privacy

6 Industry Insights
6.1 Introduction
6.2 Technology Analysis: Oncology Information Systems
6.2.1 Artificial Intelligence
6.2.2 Machine Learning
6.2.3 Internet of Things
6.2.4 Blockchain
6.3 Pricing Analysis: Oncology Information Systems
6.4 Ecosystem Landscape: Oncology Information Systems Market
6.5 Regulatory Analysis
6.5.1 North America
6.5.2 Europe
6.5.3 Asia-Pacific
6.5.4 Middle East & Africa
6.5.5 Latin America
6.6 Regulatory Bodies, Government Agencies, and Other Organizations
6.7 Porter's Five Forces Analysis
6.8 Key Stakeholders & Buying Criteria
6.9 Key Buying Criteria by End-Users
6.10 Patent Analysis
6.11 Key Conferences & Events in 2022-2023

7 Oncology Information Systems Market, by Product & Service
7.1 Introduction
7.2 Software
7.3 Professional Services

8 Oncology Information Systems Market, by Application
8.1 Introduction
8.2 Radiation Oncology
8.3 Medical Oncology
8.4 Surgical Oncology

9 Oncology Information Systems Market, by End-User
9.1 Introduction
9.2 Hospitals & Diagnostic Imaging Centers
9.3 Ablation & Cancer Care Centers
9.4 Government Institutes
9.5 Research Facilities

10 Oncology Information Systems Market, by Region

11 Competitive Landscape
11.1 Overview
11.2 Key Developments by Leading Players in Oncology Information Systems Market, January 2018-April 2022
11.3 Key Player Strategies/Right to Win
11.4 Revenue Share Analysis of Top Market Players
11.5 Market Ranking Analysis
11.6 Competitive Leadership Mapping
11.7 Competitive Leadership Mapping for Start-Ups/Smes
11.8 Competitive Benchmarking
11.9 Competitive Benchmarking for Startups/Smes
11.10 Oncology Information Systems Market: R&D Expenditure
11.11 Product and Regional Footprint Analysis of Top Players
11.12 Company Regional Footprint
11.13 Competitive Situation and Trends
11.13.1 Product Launches
11.13.2 Deals
11.13.3 Other Developments

 Companies Mentioned

  • Accuray Incorporated

  • Advanced Data Systems

  • Allscripts Healthcare, LLC

  • Altai Oncology, LLC

  • Bogardus Medical Systems, Inc.

  • Cerner Corporation

  • Curemd Healthcare

  • Elekta

  • Endosoft LLC

  • Epic Systems Corporation

  • F. Hoffmann-La Roche Ag

  • GE Healthcare

  • IBM

  • Koninklijke Philips N.V.

  • McKesson Corporation

  • Mica Information Systems, Inc.

  • MIM Software Inc.

  • Optum (Unitedhealth Group)

  • Raysearch Laboratories

  • Siemens Healthineers

For more information about this report visit https://www.researchandmarkets.com/r/3x9h4r

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