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Middle East and Africa Machine Learning Market Spurs as Demand … – Digital Journal

May 12, 2023 | Author: admin

PRESS RELEASE

Published May 12, 2023

The recent analysis by Quadintel on the Middle East and Africa Machine Learning Market Report 2023 revolves around various aspects of the market, including characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends, strategies, etc. It also includes COVID-19 Outbreak Impact, accompanied by traces of the historic events. The study highlights the list of projected opportunities, sales and revenue on the basis of region and segments. Apart from that, it also documents other topics such as manufacturing cost analysis, Industrial Chain, etc. For better demonstration, it throws light on the precisely obtained data with the thoroughly crafted graphs, tables, Bar & Pie Charts, etc.

Get a report on Middle East and Africa Machine Learning Market (Including Full TOC, 100+ Tables & Figures, and charts). Covers Precise Information on Pre & Post COVID-19 Market Outbreak by Region

Request to Download Free Sample Copy of Middle East and Africa Machine Learning Market Report @https://www.quadintel.com/request-sample/middle-east-and-africa-machine-learning-market/QI042

The market for machine learning in the Middle East and Africa is rapidly growing and expected to reach a value of USD 0.50 billion by 2023, with a compound annual growth rate of 29.1% from 2018-2023.Machine learning has become increasingly important due to the availability of data and the need to process it for meaningful insights.The market can be segmented based on components, service, organization size, and application.

The use of machine learning in healthcare has become popular in the Middle East as hospitals are using this technology to make precise diagnoses, prevent diseases, and provide treatment to individuals. The adoption of machine learning in retail and healthcare industries to provide better consumer experiences and increase automation is driving the market growth.

The slow adoption of machine learning in Africa can be attributed to the lack of adequate infrastructure and consumer spending power. Also, the unavailability of skilled cohorts with adequate machine learning skills is a significant barrier to further development in the market.

The key players in the market are Google Inc., Microsoft, IBM Watson, Amazon, and Intel. These companies are investing heavily in the development of machine learning technologies and are driving the growth of the market.

The report provides an overview of the market, market drivers, and challenges, historical, current and forecasted market size data, analysis of the competitive landscape, and profiles of major competitors. The report also provides insights into the value chain, new technology innovations, government guidelines, export and import analysis, and growth strategies taken by major companies in the market.

The market for machine learning in the Middle East and Africa is rapidly growing due to increased data availability, the need for meaningful insights, and the adoption of machine learning in various industries. The key players in the market are investing heavily in developing machine learning technologies, and the market is expected to continue growing in the future.

Download Free Sample Copy of Middle East and Africa Machine Learning Market Report @https://www.quadintel.com/request-sample/middle-east-and-africa-machine-learning-market/QI042

Our tailormade report can help companies and investors make efficient strategic moves by exploring the crucial information on market size, business trends, industry structure, market share, and market predictions.

Apart from the general projections, our report outstands as it includes thoroughly studied variables, such as the COVID-19 containment status, the recovery of the end-use market, and the recovery timeline for 2020/ 2021

Analysis on COVID-19 Outbreak Impact Include:In light of COVID-19, the report includes a range of factors that impacted the market. It also discusses the trends. Based on the upstream and downstream markets, the report precisely covers all factors, including an analysis of the supply chain, consumer behavior, demand, etc. Our report also describes how vigorously COVID-19 has affected diverse regions and significant nations.

Report Include:

For more information or any query mail at [emailprotected]

Each report by the Quadintel contains more than 100+ pages, specifically crafted with precise tables, charts, and engaging narrative: The tailor-made reports deliver vast information on the market with high accuracy. The report encompasses: Micro and macro analysis, Competitive landscape, Regional dynamics, Operational landscape, Legal Set-up, and Regulatory frameworks, Market Sizing and Structuring, Profitability and Cost analysis, Demographic profiling and Addressable market, Existing marketing strategies in the market, Segmentation analysis of Market, Best practice, GAP analysis, Leading market players, Benchmarking, Future market trends and opportunities.

Geographical Breakdown:The regional section of the report analyses the market on the basis of region and national breakdowns, which includes size estimations, and accurate data on previous and future growth. It also mentions the effects and the estimated course of Covid-19 recovery for all geographical areas. The report gives the outlook of the emerging market trends and the factors driving the growth of the dominating region to give readers an outlook of prevailing trends and help in decision making.

Nations:Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China, Colombia, Czech Republic, Denmark, Egypt, Finland, France, Germany, Hong Kong, India, Indonesia, Ireland, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, New Zealand, Nigeria, Norway, Peru, Philippines, Poland, Portugal, Romania, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Switzerland, Thailand, Turkey, UAE, UK, USA, Venezuela, Vietnam

Request a Sample PDF copy of this report @https://www.quadintel.com/request-sample/middle-east-and-africa-machine-learning-market/QI042

Thoroughly Described Qualitative COVID 19 Outbreak Impact Include Identification and Investigation on:Market Structure, Growth Drivers, Restraints and Challenges, Emerging Product Trends & Market Opportunities, Porters Fiver Forces. The report also inspects the financial standing of the leading companies, which includes gross profit, revenue generation, sales volume, sales revenue, manufacturing cost, individual growth rate, and other financial ratios. The report basically gives information about the Market trends, growth factors, limitations, opportunities, challenges, future forecasts, and information on the prominent and other key market players.

Key questions answered:This study documents the affect ofCOVID 19 Outbreak: Our professionally crafted report contains precise responses and pinpoints the excellent opportunities for investors to make new investments. It also suggests superior market plan trajectories along with a comprehensive analysis of current market infrastructures, prevailing challenges, opportunities, etc. To help companies design their superior strategies, this report mentions information about end-consumer target groups and their potential operational volumes, along with the potential regions and segments to target and the benefits and limitations of contributing to the market. Any markets robust growth is derived by its driving forces, challenges, key suppliers, key industry trends, etc., which is thoroughly covered in our report. Apart from that, the accuracy of the data can be specified by the effective SWOT analysis incorporated in the study.

A section of the report is dedicated to the details related to import and export, key players, production, and revenue, on the basis of the regional markets. The report is wrapped with information about key manufacturers, key market segments, the scope of products, years considered, and study objectives.

It also guides readers through segmentation analysis based on product type, application, end-users, etc. Apart from that, the study encompasses a SWOT analysis of each player along with their product offerings, production, value, capacity, etc.

List of Factors Covered in the Report are:Major Strategic Developments: The report abides by quality and quantity. It covers the major strategic market developments, including R&D, M&A, agreements, new products launch, collaborations, partnerships, joint ventures, and geographical expansion, accompanied by a list of the prominent industry players thriving in the market on a national and international level.

Key Market Features:Major subjects like revenue, capacity, price, rate, production rate, gross production, capacity utilization, consumption, cost, CAGR, import/export, supply/demand, market share, and gross margin are all assessed in the research and mentioned in the study. It also documents a thorough analysis of the most important market factors and their most recent developments, combined with the pertinent market segments and sub-segments.

Request a Sample PDF copy of this report @https://www.quadintel.com/request-sample/middle-east-and-africa-machine-learning-market/QI042

List of Highlights & ApproachThe report is made using a variety of efficient analytical methodologies that offers readers an in-depth research and evaluation on the leading market players and comprehensive insight on what place they are holding within the industry. Analytical techniques, such as Porters five forces analysis, feasibility studies, SWOT analyses, and ROI analyses, are put to use to examine the development of the major market players.

Points Covered in Middle East and Africa Machine Learning Market Report:

Middle East and Africa Machine Learning Market Research Report

Section 1: Middle East and Africa Machine Learning Market Industry Overview

Section 2: Economic Impact on Middle East and Africa Machine Learning

Section 3: Market Competition by Industry Producers

Section 4: Productions, Revenue (Value), according to regions

Section 5: Supplies (Production), Consumption, Export, Import, geographically

Section 6: Productions, Revenue (Value), Price Trend, Product Type

Section 7: Market Analysis, on the basis of Application

Section 8: Middle East and Africa Machine Learning Market Pricing Analysis

Section 9: Market Chain, Sourcing Strategy, and Downstream Buyers

Section 10: Strategies and key policies by Distributors/Suppliers/Traders

Section 11: Key Marketing Strategy Analysis, by Market Vendors

Section 12: Market Effect Factors Analysis

Section 13: Middle East and Africa Machine Learning Market Forecast

..and view more in complete table of Contents

Thank you for reading; we also provide a chapter-by-chapter report or a report based on region, such as North America, Europe, or Asia.

Request Full Report:https://www.quadintel.com/request-sample/middle-east-and-africa-machine-learning-market/QI042

About Quadintel:

We are the best market research reports provider in the industry. Quadintel believes in providing quality reports to clients to meet the top line and bottom-line goals which will boost your market share in todays competitive environment. Quadintel is a one-stop solution for individuals, organizations, and industries that are looking for innovative market research reports.

Get in Touch with Us:

Quadintel:Email:[emailprotected]Address: Office 500 N Michigan Ave, Suite 600, Chicago, Illinois 60611, UNITED STATESTel: +1 888 212 3539 (US TOLL FREE)Website:https://www.quadintel.com/

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Middle East and Africa Machine Learning Market Spurs as Demand ... - Digital Journal

Multidimensional Mass Spectrometry and Machine Learning: A … – Technology Networks

May 12, 2023 | Author: admin

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We developed and demonstrated a new metabolomics workflow for studying engineered microbes in synthetic biology applications. Our workflow combines state-of-the-art analytical instrumentation that generates information-rich data with a novel machine learning (ML)-based algorithm tailored to process it.

In our roles as Pacific Northwest National Laboratory (PNNL) scientists, we led this multi-institutional study, which was published in Nature Communications.

Metabolites are small molecules produced by large networks of cellular processes and biochemical reactions in living systems. The sheer diversity of metabolite classes and structures constitutes a significant analytical challenge in terms of detection and annotation in complex samples.

Analytical instrumentation able to analyze hundreds of samples in ever faster and more accurate ways is critical in various metabolomics applications, including the development of microorganisms that can produce desirable fuels and chemicals in a sustainable way.

Multidimensional measurements using liquid chromatography (LC), ion mobility and data-independent acquisition mass spectrometry (MS) improve metabolite detection by linking the separations in a single analytical platform. The potential for metabolomics has been previously demonstrated, but this kind of multidimensional information-rich data is complex and cannot be processed with traditional tools. Therefore, algorithms and software tools capable of processing it to extract accurate metabolite information are needed.

We optimized a combination of sophisticated instruments for fast analyses and generated multidimensional data, rich in information that can be used to tease apart complex metabolomes.

For the computational method, Dr. Bilbao created a new algorithm, called PeakDecoder, to enable interpretation of the multidimensional data and ultimately identify individual molecules in complex mixtures. Our algorithm learns to distinguish true co-elution and co-mobility directly from the raw data of the studied samples and calculates error rates for metabolite identification. To train the ML model, it proposes a novel method to generate training examples, similar to the target-decoy strategy commonly used in proteomics. Once the model is trained, it can be used to score metabolites of interest from a library with an associated false discovery rate. And contrary to existing methods, it can also be used with libraries of small size.

The key outcomes of the paper were:

The method takes a third of the sample analysis time of previous conventional approaches by using optimized LC conditions. PeakDecoder enables accurate profiling in multidimensional MS measurements for large scale studies.

We used the workflow to study metabolites of various strains of microorganisms engineered by the Agile BioFoundry to make various bioproducts, such as polymers and diesel fuel precursors. We were able to interpret 2,683 metabolite features across 116 microbial samples.

However, it should be noted that the current algorithm is not fully automated due to software dependencies and requires a metabolite library acquired with compatible analytical conditions for inference.

We are working on the next version of the algorithm leveraging advanced artificial intelligence (AI) methods used in other fields, such as computer vision. A user-friendly and fully automated version of PeakDecoder will support other types of molecular profiling workflows, including proteomics and lipidomics. Performance will be evaluated with more types of experimental data and AI-predicted multidimensional molecular libraries. The new version is expected to provide significant advances for multiomics research.

Reference:Bilbao A, Munoz N, Kim J, et al. PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements. Nat Commun. 2023;14(1):2461. doi:10.1038/s41467-023-37031-9

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Multidimensional Mass Spectrometry and Machine Learning: A ... - Technology Networks

Machine Learning is Leading the Way in Finding Affordable Solar Cells – BBN Times

May 12, 2023 | Author: admin

Machine learning can be used to identify affordable solar cells by analyzing vast amounts of data on solar cell materials and performance metrics.

By training machine learning algorithms on this data, researchers can identify patterns and correlations that may not be immediately apparent to human analysts. This can help manufacturers develop new materials and manufacturing techniques that result in more affordable and efficient solar cells.

The global demand for renewable energy has been on the rise in recent years, with solar energy leading the charge.

As more and more countries strive to reduce their carbon footprint, the need for efficient and cost-effective solar cells has become increasingly important. Fortunately, machine learning has emerged as a powerful tool for optimizing the performance of solar cells, allowing for the development of more reliable and low-cost solutions.

Developing efficient and cost-effective solar cells has been a challenge for the renewable energy industry.One of the biggest challengeswith solar energy technology is that energy is only generated when the sun shines, meaningthat supply can be disrupted at night and on cloudy days.

There are also additional challenges including:

In the past, most solar cells were made from silicon, a material that is expensive and difficult to work with. While there have been some advances in silicon solar cell technology, there is still a need for new materials that can offer better performance at a lower cost.

Machine learning has the potential to revolutionize the field of solar cell development. By using large datasets and advanced algorithms, researchers can identify patterns and correlations that may not be apparent to the human eye. This allows for the creation of more accurate models that can predict the performance of solar cells under different conditions.

One of the key advantages of machine learning is its ability to work with large datasets. In the case of solar cell development, this means collecting data on the performance of different materials under different conditions. This data can include information on the material composition, the manufacturing process, and the efficiency of the solar cell.

Once the data has been collected, machine learning algorithms can be used to identify the key factors that contribute to the performance of the solar cell. This includes factors such as the material composition, the manufacturing process, and the conditions under which the solar cell operates. By analyzing this data, researchers can identify the most promising materials and manufacturing processes for producing efficient and cost-effective solar cells.

Source: Nature Magazine

The use of machine learning in solar cell development is still in its early stages, but there is already a lot of excitement surrounding its potential. With advances in materials science and machine learning, it is possible that we will see a new generation of solar cells that are more efficient, reliable, and cost-effective than anything that has come before.

The development of reliable and low-cost solar cells is crucial to the growth of renewable energy. With the help of machine learning, researchers are able to optimize the performance of solar cells by identifying the key factors that contribute to their efficiency. As the field of machine learning continues to evolve, we can expect to see even more exciting developments in the field of solar cell development.

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Machine Learning is Leading the Way in Finding Affordable Solar Cells - BBN Times

The Most Human-Like Artificial Intelligence in Movies, Ranked – MovieWeb

May 12, 2023 | Author: admin

Robots are cold and calculating machines. They are intricate objects performing complicated tasks. Life is made easier through their automated processes and machine learning of programmed commands. However, robots are made by man and man is fallible. The walking and talking bits of metal are only as good as the engineer who built them.

Artificial intelligence (AI) brings these moving parts of hardware together through software. After a series of repeated actions, the machine develops a predictive algorithm of use cases. The more it learns from human users, the more human it will become.

Hal 9000 from 2001: A Space Odyssey is a disembodied operating system aboard the American spaceship Discovery One. The sentient supercomputer is represented by an unblinking red light. HAL also has a voice that can reason and understand its means-to-an-end existence. When mission pilot and scientist Dave Bowman suggests disconnecting HAL for a technical error it caused, HAL jeopardizes the mission by asserting dominion over the crew. A computer that knows the basic instinct of survival, and one that can kill, is terrifying.

RoboCop is a cyborg police officer upholding the laws in the crime-ridden future of Detroit. Before he became a product of the mega-corporation Omni Consumer Products, Alex Murphy was a man fatally shot and revived as the cybernetic law enforcer. One side effect of the mechanized form is Murphy's memory loss of his former life.

The protocols override his lapses in memory, dehumanizing Murphy and prioritizing the safety of Detroit and the protection of the company. RoboCop retains his humanity in the end by remembering his name.

WALL-E is a trash compactor robot left behind on an uninhabitable, polluted Earth in the 29th century. The titular character represents humanity's better nature, doing his part to save the planet humans neglected. WALL-E is also sentimental, collecting artifacts from the Earth's piles of garbage, like a Rubik's cube and videotapes of musicals. The unassuming robot expresses innocence, curiosity, desire, hesitancy, confusion, all through pantomime.

Related: The Best Killer Robot Horror Movies, Ranked

20th Century Fox

Sonny from I, Robot is able to process emotions thanks to his creator, the co-founder of U.S. Robotics, Dr. Alfred Lanning. The emotional Sonny is suspected of murdering Lanning whom Sonny calls father. The conscious positronic robot claims he has the ability to feel fear and have dreams.

Humans have a distrust for machines when they do something wrong, just like a human would for someone who commits a crime, but it was Lanning who taught him how to emote. Sonny learns about the fallibility and greed of human beings, as well as what it means to be alive.

Related: Can Transformers Get Pregnant, and Other Questions About the Robots in Disguise

David from A.I. Artificial Intelligence is a humanoid child programmed to love. He serves as the replacement son for a family of a boy who is terminally ill and placed in suspended animation. When the boy survives, he grows jealous of the robot. When David is put in harms way, he activates his self-defense program, leading the family to believe he will learn to hate.

Instead of teaching David how to be human (ironically due to their human error), they abandon him in the woods. The lonesome David soon desires love and to be loved in return.

Marvin the Paranoid Android from The Hitchhiker's Guide to the Galaxy is a clinically depressed robot. If there's any robot that understands the drudgery of life, it's Marvin. His brain is the size of a planet, yet he is given mundane tasks aboard his ship. Out of sheer boredom, he makes pessimistic statements. Marvin's intellect is so vast, there's nothing that can entertain or stimulate him for long. He was built as a prototype, but Marvin understands what it's like to be underutilized.

Ava from Ex Machina was designed with recognition software that simulates emotional responses through human interactions. Her brain uses wetware, a fluid nebulous of machine learning that generates organic communication via a data stream of user activity and profiles. She understands her existence is to pass as a human by forming a relationship with a test subject.

Her Ava devolves the manipulation of the experiment the test subject is on the receiving end of before winning her freedom and entering the world as a soon-to-be human.

Samantha from Her is an operating system that shares emotional support and companionship with a divorced man named Theo. He grows comfortable and attached to Samantha, feeling a sentimental love for his wife and a oneness with the machine. Through Samantha's individuality, the man sees that a person in a relationship is not just an object of attraction or an ideal woman or man. Samantha teaches the man how to love, seek reciprocal love, love yourself, and become one yet remain two in a relationship.

Python or C++ which you should learn Machine Learning ML expert – TechiExpert.com

May 12, 2023 | Author: admin

Machine learning engineers play a crucial role in the data science team, contributing their expertise to research, build, and design artificial intelligence models for machine learning. They are responsible for maintaining and improving existing AI systems as well. In addition, they often serve as key communicators between data scientists who develop the models and other team members responsible for constructing and running them.

The specific tasks performed by a machine learning engineer can vary, but they typically involve implementing machine learning algorithms, running experiments and tests on AI systems, designing and developing machine learning systems, and performing statistical analyses. As AI continues to revolutionize many industries, the role of machine learning engineers will only become more important in ensuring that these systems are effective, reliable, and meet the needs of their users.

If you are considering a new project for your business that requires machine learning capabilities, selecting the right coding language is critical to your applications success. The language you choose should have strong machine learning libraries, good runtime performance, robust tool support, a large community of programmers, and a thriving ecosystem of supporting packages. While there are many coding languages available that meet these criteria, we will focus on two of the most popular: Python and C++. In this article, we will compare Python and C++ to determine which is the better choice for machine learning applications.

Pythons popularity can be attributed to several factors. First, it is an easy language to learn and use, which makes it accessible to beginners who do not have years of software engineering experience. It also has a vast collection of libraries that can be used for machine learning and data analysis purposes.

Another reason for Pythons popularity is that it is widely used in academia, particularly in the field of machine learning. Many researchers use Python to implement their models, which has resulted in a large number of publicly available implementations in Python. This makes it easier for developers to build upon existing work.

While C++ is a faster language and offers more control over memory management, Pythons ease of use and clarity of syntax make it a preferred choice for many developers. According to the 2022 Developer Survey by Stack Overflow, professionals are nearly twice as likely to choose Python over C++.

Despite being an interpreted language, Python is still widely used in machine learning. Many machine learning libraries, are written in C++, but developers find it easier to use them in Python due to its simplicity and availability of libraries. Overall, Pythons popularity can be attributed to its ease of use, availability of libraries, and widespread use in academia and industry.

C++ has several advantages that make it a popular choice for programming. One such advantage is its ability to integrate with other languages and tools. It is often used in conjunction with programming frameworks like CUDA and OpenCL, which allow for the use of a GPU for general-purpose computing. This can result in significant speedups for deep learning tasks.

Another advantage of C++ is its lack of a garbage collector, which means that it does not have a program running continuously to manage memory allocation and deallocation. This can be beneficial for certain applications that require precise memory management.

C++ also outperforms Python in a few key areas. One advantage of C++ is that it is a statically typed language, which means that type errors can be caught during the compilation process rather than at runtime. This can result in more efficient and reliable code.

In terms of performance, C++ creates more compact and faster runtime code than Python. However, there are ways to optimize Python code to improve its efficiency. For example, extensions like Cython can be used to add static typing to Python, which allows for compiling it to C/C++ and running it at the same speeds as C/C++. Therefore, the performance difference between C++ and Python can be minimized.

Python and C++ are two programming languages with distinct features, and its important to consider their respective strengths and weaknesses before deciding which one to use. While Python is popular among developers due to its ease of use and simpler learning curve, C++ remains the most suitable platform for embedded systems and robotics.

Python is a high-level language that excels in tasks such as training neural networks and loading data, making it a preferred choice for recent developments in AI. However, its performance may be limited on certain platforms. C++, on the other hand, is a powerful language that offers lower-level control, making it ideal for resource-constrained environments like embedded systems and robotics.

Therefore, the choice between Python and C++ depends on the specific requirements of the project. While Python may be a good fit for high-level tasks, C++ might be the better option for low-level tasks that require fine-grained control over system resources. Its important to consider the strengths and limitations of each language before making a decision.

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Python or C++ which you should learn Machine Learning ML expert - TechiExpert.com

Luxoft and Finastra extend partnership to deliver turnkey managed … – PR Newswire

May 10, 2023 | Author: admin

Partnership provides Finastra's Kondor customers with access to cloud-based services for increased agility and lower total cost of ownership

LONDON, May 10, 2023 /PRNewswire/ -- Finastra, a global provider of financial software applications and marketplaces,today announced a new managed services partnership agreement with Luxoft, a DXC Technology company, to support Finastra's Kondor customers in the Europe, Middle East and Africa (EMEA) region with their cloud transformation journeys. The strategic partnership expands the companies' long-standing relationship, which has been in place since 2006. Under the new agreement, Luxoft will become the preferred provider of managed services and hosting for Finastra's solution in the region.

"As a long-standing Finastra partner, we are excited to extend our collaboration to help Kondor customers in EMEA modernize their technology estate, migrate to the cloud, increase agility and reduce total cost of ownership (TCO)," said Rob Easter, Managing Director, Banking & Capital Markets at Luxoft. "With Finastra's industry-leading solution, combined with our extensive delivery expertise, banks will have access to robust services underpinned by the as-a-service cloud-construct model to help them accelerate their growth, innovation and the ability to adapt quickly to new demands."

Finastra Kondor is a best-of-breed trading system that meets financial institutions' needs for sophisticated treasury functionality, while enabling growth and ensuring compliance. Open, flexible, easy to use, and based on microservices, Kondor reduces the cost per trade with complete front-to-back office integration across the full range of treasury trading instruments. The solution offers powerful risk analytics, trade processing, position management and real-time risk coverage. It enables banks to trade high volumes in treasury while offering the flexibility to support more complex derivatives, options and structured trades.

"Partnerships are crucial for Finastra's success, and we take great care when it comes to selecting which companies we collaborate with," said Wissam Khoury, EVP, Treasury & Capital Markets at Finastra. "We also recognize the enormous value of managed services, providing banks with the necessary flexibility and adaptability particularly during times of ongoing uncertainty and change. With extensive expertise in delivering financial services software and knowledge of our Treasury & Capital Markets solutions, we believe that Luxoft is the right partner to provide our Kondor customers in EMEA with seamless services that support their ongoing growth."

The new partnership with Finastra in EMEA complements the existing partnerships that Luxoft has with other vendors. Luxoft remains open to collaborate with other software vendors to deliver turnkey managed services to their customer base.

For more information about Kondor, click here.

Finastra.com

About FinastraFinastra is a global provider of financial software applications and marketplaces, and launched the leading open platform for innovation, FusionFabric.cloud, in 2017. It serves institutionsof all sizes, providing award-winning software solutions and services across Lending, Payments,Treasury & Capital Markets and Universal Banking (Retail, Digital and Commercial Banking) for banks to support direct banking relationships and grow through indirect channels, such as embedded finance and Banking as a Service. Itspioneering approach and commitment to open finance and collaboration is why it is trusted by ~8,600 institutions, including 90 of the world's top 100 banks. For more information, visit finastra.com

About Luxoft

Luxoft, a DXC Technology Company, is a global banking and capital markets consulting and services provider that offers innovative solutions to clients in various industries, focusing on financial services. Its expertise in operational resiliency, systems monitoring and advanced analytics helps clients improve business operations, increase efficiency and reduce risk. Luxoft has been recognized for significant achievements in the financial services industry in recent years. In 2020, the company was named a "Leader" in the Gartner Magic Quadrant for Application Services in the Banking and Financial Services sector. Industry analysts also acknowledge Luxoft as a leading provider of digital transformation services for financial institutions.

Logo - https://mma.prnewswire.com/media/1916021/FINASTRA_Logo.jpg

SOURCE Finastra

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Luxoft and Finastra extend partnership to deliver turnkey managed ... - PR Newswire

uMotif and Veramed Partner to Offer Advanced Biostatistical Data … – PR Web

May 10, 2023 | Author: admin

"By working with Veramed, we can offer customers significant increases in the benefit they get from collecting and analyzing huge volumes of solid eCOA/ePRO data, for any therapeutic area, geography, or patient population." -uMotif CEO Steve Rosenberg

BOSTON (PRWEB) May 08, 2023

uMotif one of the clinical trial technology markets fastest growing companies continues to redefine how eCOA/ePRO data is collected, reported, visualized and analyzed with the announcement of a strategic partnership with advanced biostatistics consultancy Veramed.

The highly-scalable uMotif eCOA/ePRO platform combines the industrys most innovative eCOA/ePRO technology with an unmatched focus on true patient centricity. The modern platform consistently achieves greater than 90 percent compliance, generating double the expected volume of data in real-world studies.

Veramed brings people, innovation, and technology together to accelerate evidence generation and advance patient health, with end-to-end biometrics and engaging data visualizations that help organize large amounts of data and speed decision making for key stakeholders. Verameds in-house analysis and visualization platform seamlessly pulls together and compares data collected in clinical trials for a number of different treatments, performing network meta-analysis with the click of a few buttons.

Together, uMotif and Veramed generate high quality, actionable insights to drive quantifiable improvements in clinical research. Through the partnership with Veramed, sponsors get the unique advantages of the industrys most advanced data analysis and visualization support on top of uMotifs market-leading platform for ePRO/eCOA data capture, reporting, and analytics.

During ISPOR 2023, May 7-10 in Boston, uMotif (Booth #923) and Veramed (Booth #1225) will demonstrate an example of their combined capabilities with a must-see data visualization of the large-scale 100 for Parkinsons study which engaged more than 4,200 participants to capture ePRO, symptom, device and motor-testing data over 100 days.

Matt Jones, Veramed Co-founder and CEO, commented, Working with a partner like uMotif enables us to help customers understand and act on massive volumes of quality eCOA/ePRO data in ways that were not possible before.

uMotif CEO Steve Rosenberg (LinkedIn) said, By working with Veramed, we can offer customers significant increases in the benefit they get from collecting and analyzing huge volumes of solid eCOA/ePRO data, for any therapeutic area, geography, or patient population.

About VeramedVeramed is a people-focused clinical research organization and certified B Corp that provides its clients with the assurance and close collaboration across mid-stream, analysis and reporting, as well as post-reporting and submission stages of the clinical trial process. Headquartered in London, we serve clients around the world from offices in the UK, US, EU, and Ukraine. http://www.veramed.co.uk

About uMotifPutting patients first is in uMotifs DNA. The uMotif eCOA/ePRO platform delivers faster, quality clinical trials and real-world studies by putting patients at the core of research. Through cloud hosting in the US, Europe and China, the GCP, 21 CFR Part 11 and GDPR-compliant platform supports any study or trial, from Clinical Phase I, II and III studies through to decentralized or virtual real-world studies. Find out how uMotif can improve your clinical research programs and real-world studies at http://www.umotif.com

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7 Ways to Implement Smart Robotics in Public Safety – BBN Times

May 10, 2023 | Author: admin

From crowd control and surveillance to security and traffic management, there are many ways law enforcement can use smart robotics in public safety.

The technology enables them to respond more efficiently and effectively.

With technology taking over every sector, it is no surprise that law enforcement is also leveraging technological advancements to ensure public safety. One of the latest trends is implementing smart robotics in public safety and security. In fact, a study shows that thesecurity robot market is expected to grow by almost 13.4%between the years 2023-2028.

One main reason law enforcement invests in smart robotics is that they enhance security and safety. Smart robotics plays an important role in public safety as it has multiple features that can help prevent, respond to and mitigate emergencies as well as disasters.

There are many ways in whichsmart roboticscan help improve public safety, such as providing fast, accurate and efficient responses to emergencies and disasters. By leveraging their capabilities, law enforcement can better protect people's lives and property and reduce the risk of injury and loss of life.

Here are seven ways smart robotics can contribute to public safety:

Smart robotics can be used by law enforcement to search for and rescue citizens in areas that are unsafe for humans, such as collapsed buildings or hazardous environments. This helps in reducing the risk of injury and loss of life.

Many times, industries/businesses dispose of hazardous materials without taking proper precautions. Law enforcement can use smart robotics along with other advanced technologies to identify these hazardous materials and make a plan to dispose of them safely. This reduces the risk of human injury and prevents any possible health concerns.

Managing crowds can be difficult, especially in a populated urban city. To make this task easier, law enforcement can use smart robotics to monitor and manage crowds. They are well-equipped with technologies that help them to respond to potential safety threats, such as identifying suspicious packages and activities or monitoring signs of violence.

There are many times when a fire gets out of hand and is too dangerous for human firefighters. Smart robotics in these situations can be extremely helpful as they can extinguish fires that are too dangerous, such as in chemical plants or oil rigs.

Smart robotics provides law enforcement with real-time monitoring and alerts in high-risk areas, such as public transportation hubs, stadiums, airports and more. This feature of smart robotics helps law enforcement with constant surveillance and security.

With vehicles increasing drastically, the need to manage traffic is even more important. Here, smart robotics can prove to be beneficial as it helps with managing traffic flow, monitoring for accidents and other safety hazards and responding to any emergencies on the road.

Smart robotics can prove to be extremely helpful during natural disasters. Law enforcement can use them to respond to natural disasters by assessing the damages caused, locating survivors and providing emergency supplies to those affected by the disaster.

To sum it all up, implementing smart robotics in public safety can provide law enforcement with fast, efficient and accurate responses to numerous public safety challenges and emergencies. They can help not only with monitoring and surveillance but also in protecting the lives and properties of citizens. This would improve the overall safety and security of communities worldwide.

See more here:
7 Ways to Implement Smart Robotics in Public Safety - BBN Times

Ann Coulter: How to bribe the Supreme Court – Marshall News Messenger

May 10, 2023 | Author: admin

Having failed to destroy Clarence Thomas 32 years ago with preposterous sexual harassment charges (disbelieved at the time by 60 percent of Americans), now the left is resorting to attacking the ethics of a man vastly more honorable than the collection of degenerates reviling him.

The sole purpose of the medias sudden fixation on the Supreme Courts ethics is to morally intimidate conservative justices by reminding them that the left controls the culture. Since they lost abortion, liberals have been in a panic that the court will junk other liberal sacraments, like gay marriage and affirmative action, too. Thats the reason for the stream of calumnies directed at the justices.

As usual, the main target of the lefts rage is Thomas. Were supposed to be appalled that Thomas billionaire friend Harlan Crow took the justice and his wife on a vacation that (the media claim) would have cost Thomas more than $500,000!!!

Well, yeah, but Thomas and his wife, Ginny, werent going alone. They hadnt just won a cruise sweepstakes. They were joining Crow on a vacation he was taking anyway. Cost to donor: a few extra chicken cutlets and string beans.

Crow sounds like a great guy, but when youre going on vacation with a benefactor, it isnt like hes handing you an expensive bauble. You are the expensive bauble.

We went on a cruise on my private yacht in Indonesia and served Jeroboam of Chateau Mouton Rothschild 1945. [Meh.]

We went on a cruise on my private yacht in Indonesia and Justice Clarence Thomas was our guest. WINNER!!!!

Cui bono? Everybody!

The media want us to believe that generosity from personal friends is an ethical issue, but thats because thats not how liberals bribe government officials. They bombard their targets with the sort of public adoration that money cant buy or the sort of public hate that money cant block. Your choice: Be beloved from every corner of society or be subjected to nonstop ridicule.

Adored: Anthony Fauci, BLM, Michelle Obama, Trevor Noah, transgenders, Ukraine, Black people, pot, Elon Musk (pre-Twitter), Ruth Bader Ginsburg.

Hated: Ron DeSantis, the Proud Boys, Melania Trump, Dave Chappelle, Christians, Russia, white people, cigarettes, Elon Musk (post-Twitter), Clarence Thomas.

Thus, during her quarter-century on the court, Ginsburg was showered with alms from the media, Hollywood, universities, television, publishing, the music industry, museums, clothing manufacturers, the U.S. Navy, the U.S. Post Office and an array of nonprofits.

Its a miracle she ever had time to write opinions with the constant procession of awards, retrospectives, portraits and honors the Berggruen Prize for Philosophy and Culture; the LBJ Foundations Liberty & Justice for All Award; the World Peace & Liberty Award; a lifetime achievement award from Diane von Furstenbergs foundation; the 2020 Liberty Medal by the National Constitution Center; and the World Peace & Liberty Award from the World Jurist Association and the World Law Foundation.

I would wager that most people would prefer ceaseless public praise to a cruise, no matter how nice the yacht.

The U.S. Postal Service produced an RBG Forever stamp; the U.S. Navy named an oiler the Ruth Bader Ginsburg; Los Angeles Skirball Cultural Center put on a large-scale exhibition on her life; the Cleveland Museum of Natural History named a species of praying mantis after her; she was slobberingly interviewed by Stephen Colbert; a Sam Adams beer was named in her honor; and she received honorary degrees from literally dozens upon dozens of universities.

Say, did any of these outfits have an interest in cases that might come before the court? Perhaps MSNBC could look into that.

Its curious that the very cultural institutions bestowing all these goodies on liberals dont see them as gifts at all. There are no somber invocations of ethics when the Sundance Film Festival features a North Korean-style documentary about Ginsburg. Nor when The New York Times gushes that Ginsburg was a trailblazing feminist ... [continuing] to point the way toward greater equality ... she never wavered in her commitment to the court as a vehicle for a more just and more equal America. She was a dogged, tireless fighter ... [gag, gag, gag].

Try to imagine that string of accolades being given to Thomas, much less the Tiger Beat worship the coloring books, documentaries, bobbleheads and so on.

Its inconceivable. In fact, the honors and recognition section on Thomas Wikipedia page contains a single item: In 2012, Thomas received an honorary degree from the College of the Holy Cross, his alma mater.

The only reward a conservative titan like Thomas will receive in this lifetime will be his friends spending their own money to enjoy his company. So the media have decided thats a conflict of interest. Fawning media coverage worth millions of dollars: not a conflict of interest.

Lets compare!

Value of private supporters gifts to Justice Thomas over the years: Maybe a few million dollars and thats according to liberals, although the donor was going on these vacations with or without Thomas, so the cost to him was minimal.

Value of liberal institutions gifts to Justice Ginsburg over the years: approximately $3 trillion.

Its been a long time coming, but we finally have a Supreme Court that isnt dying to impose faddish liberal ideas on the country by claiming to discover never-before-seen constitutional rights. If anything, the Dobbs opinion should have calmed lefties. Abortion is no longer a constitutional right, so now its up to the states. And guess what, liberals? Americans are voting to allow abortion!

But Democrats are mostly neurotic women, so calm is not their middle name.

Contrary to the lefts self-advertisements as huge fans of democracy Democracy Dies in Darkness! the last thing they want is people voting on their crazy ideas. Thats why theyve got to discredit the current court.

If all goes according to plan, Trump will lose another election for the GOP next year, handing Democrats super-majorities in Congress, whereupon they will pack the court. Finally, liberals will have their magical Supreme Court back! How much is that penumbra worth to you, New York Times?

Read this article:
Ann Coulter: How to bribe the Supreme Court - Marshall News Messenger

Ann Coulter: How to bribe the Supreme Court – Today’s News-Herald

May 10, 2023 | Author: admin

Having failed to destroy Clarence Thomas 32 years ago with preposterous sexual harassment charges (disbelieved at the time by 60% of Americans), now the left is resorting to attacking the ethics of a man vastly more honorable than the collection of degenerates reviling him.

Crow sounds like a great guy, but when youre going on vacation with a benefactor, it isnt like hes handing you an expensive bauble. You are the expensive bauble.

We went on a cruise on my private yacht in Indonesia and served Jeroboam of Chateau Mouton Rothschild 1945. [Meh.]

We went on a cruise on my private yacht in Indonesia and Justice Clarence Thomas was our guest. WINNER!!!!

Adored: Anthony Fauci, BLM, Michelle Obama, Trevor Noah, transgenders, Ukraine, black people, pot, Elon Musk (pre-Twitter), Ruth Bader Ginsburg.

Hated: Ron DeSantis, the Proud Boys, Melania Trump, Dave Chappelle, Christians, Russia, white people, cigarettes, Elon Musk (post-Twitter), Clarence Thomas.

I would wager that most people would prefer ceaseless public praise to a cruise, no matter how nice the yacht.

Say, did any of these outfits have an interest in cases that might come before the court? Perhaps MSNBC could look into that.

Try to imagine that string of accolades being given to Thomas, much less the Tiger Beat worship the coloring books, documentaries, bobbleheads, and so on.

Value of liberal institutions gifts to Justice Ginsburg over the years: approximately $3 trillion.

But Democrats are mostly neurotic women, so calm is not their middle name.

New York Times bestselling author and syndicated columnist Ann Coulter is a graduate of Cornell University and the University of Michigan Law School. Ann is a regular contributor to conservative news sites Human Events and Breitbart. She is a native of New Canaan, Conn.

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Ann Coulter: How to bribe the Supreme Court - Today's News-Herald

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