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TEHRAN- An Iranian oil ship that was illegally stolen by a foreign firm five years ago has been retaken by the Islamic Revolution Guards Corps (IRGC) Navy and Irans Intelligence Ministry in a joint operation.

The 10,000-ton oil tanker Purity has returned to Iranian territorial waters as a result of a court order and a joint operation by the IRGC Navy and Intelligence Ministry, according to Mojtaba Qahremani, head of the justice department in Irans southern province of Hormozgan, Tasnim reported on Friday.

The seized 10,000-ton oil tanker Purity had been illegally leased to a foreigner by falsifying documents since 2018 and its Iranian owners were deprived of the benefits of the oil tanker, Qahremani added.

The head of the Hormozgan Province Justice Department also said that it was recognized during investigations by security groups that the foreign corporation employed the vessel for fuel trafficking.

Qahremani went on to highlight, Following a judicial order and close cooperation between the IRGC Navy and Intelligence Ministry, the oil tanker was finally identified and confiscated in the Persian Gulf waters earlier this month.

The ship was said to have docked in Irans Assaluyeh Port on the Persian Gulfs westernmost coast to have its fuel consignments unloaded.

Late in October, forces from the IRGCs first naval zone captured a foreign tanker ship carrying 11 million gallons of illegal fuel in the Persian Gulf.

The Islamic Republic has said unequivocally that the Persian Gulf would never be a safe haven for smugglers.

As a result, several assaults on Iranian and international tankers have also been hindered by the IRGCs Navy over the last years.

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Iran recaptures oil tanker in joint operation by IRGC Navy ... - Tehran Times

WATCH TIME: 5 minutes

The enrollment of patients who are unlikely to show meaningful cognitive decline with placebo may make it more difficult to show the benefits of active treatment for cognition. Recent research used data from the placebo arm of 5 phase 3 trials, showing that predictive machine learning models can potentially increase sensitivity to effects from treatment and reduce the requirements for sample size in clinical trials.1

In total, 1982 patients were included in the pooled placebo analysis, with meaningful cognitive decline not observed in 42% to 58% of individuals at the end of trials. Using the predictive machine learning models, positive predictive values were approximately 12% to 25% higher than the sample rate of meaningful cognitive decline. Notably, negative predictive values of models were approximately 15% to 24% higher than the base rate of patients who had stable cognition at the end of trial.

Ali Ezzati, MD, assistant professor, department of neurology, at the Albert Einstein College of Medicine and Montefiore Medical Center, presented this study during the experimental therapeutics in dementia session at the 2023 American Academy of Neurology (AAN) Annual Meeting, April 22-27, in Boston, Massachusetts. During the meeting, Ezzati sat down with NeurologyLive in an interview to talk about the reason behind the difficulties and failures in clinical trials for Alzheimer disease (AD). He also spoke about the findings from his study that were presented, and the proposal to improve the design of trials using machine learning predictive models.

Click here for more coverage on AAN 2023.

Read more here:
Enhancing Alzheimer Disease Clinical Trials With Predictive ... - Neurology Live

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.

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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.

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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.

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Report Include:

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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.

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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

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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.

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

SAS is an organization dedicated to responsible innovation and using technology to ignite positive change. In line with its mission, SAS will apply crowd-driven artificial intelligence (AI) and machine learning to help protect endangered sea turtles. SAS is working with the UNC Center for Galapagos Studies (CGS) on this project and to further research in several initiatives on the Islands in general.

According to a release from SAS,1 an app called ConserVision, will allow citizen scientists to match images of turtles' facial markings to help train a SAS computer vision model. Once the model can accurately identify turtles individually, researchers will have valuable information more quickly to better track each turtle's health and migratory patterns over periods of time. The ultimate goal from there is to allow the model to perform facial recognition on any sea turtle image, whether it comes from a conservation group or a vacationing tourist.

SAS also eventually aims to have the app identify a health index regarding growth rates, health threats, and presence data. From there, researchers can better understand temporal and spatial movement patterns of these turtles and to identify health risks due to marine debris, boat strikes, diseases, etc.

"As our challenges as a global community get increasingly more complex, we need dynamic ways to access and use information to ramp up conservation efforts," said Sarah Hiser, MSc, principal technical architect at SAS, said in the release. "By using technology like analytics, AI and machine learning to quantify the natural world, we gain knowledge to help protect ecosystems and tackle climate change."1

"For over 10 years, the Galapagos Science Center has hosted exceptional scientists doing innovative research that increases our understanding of the environment and results in positive real-world outcomes," explained UNC-Chapel Hill interim vice chancellor for research, Penny Gordon-Larsen, PhD, in the release. "This innovative public-private partnership with SAS will enhance the center's capacity for analyzing data that will positively impact both the environment and the people who inhabit these magnificent islands."1

SAS will help UNC CGS with 3 projects focusing on marine life, including:

Reference

SAS seeks crowd-driven AI to protect endangered sea turtles in Galapagos. News release. SAS. Published May 9, 2023. Accessed May 12, 2023. https://prnmedia.prnewswire.com/news-releases/sas-seeks-crowd-driven-ai-to-protect-endangered-sea-turtles-in-galapagos-301819633.html

Read more from the original source:
Artificial intelligence used to protect sea turtles in the Galapagos - DVM 360

Irans Islamic Revolutionary Guard Corps (IRGC) on Wednesday opened a new airbase in Zahedan, the provincial capital of Sistan and Baluchestan, state media reported.

The Shahid Ali Arabi airbase will house and support IRGCs helicopter and drone fleet, Fars News Agency reported on May 10.

"IRGC combat engineers and domestic specialists equipped this base by drawing on the latest technical-engineering protocols and based on aviation standards, so that various types of attack, combat and support helicopters and drones could both land and take off," the report added.

IRGC Ground Force Commander Brig Gen Mohammad Pakpour said that the airbase will enhance the helicopter fleets capabilities for defense, rescue, logistics, and relief missions in the region.

Pakpour added the base would have the capacity to host dozens of helicopters, and to offer refuelling and repair facilities.

Speaking at the opening ceremony, IRGC Commander-in-Chief Maj Gen Hossein Salami said, "This base has been designed and created to play an important role in the lives and security of the inhabitants of the region".

Sistan-Baluchestan Province, which is situated on the borders with Afghanistan and Pakistan, is used by various militant groups and often serves as an entry point for smuggled drugs and arms.

In order to bolster Irans defense against enemy threats, the Army and the IRGC kicked off large-scale air defense exercises in a number of regions across the country on February 28.

The IRGC Air Force unveiled subterranean tunnels used for the storage of air defense missile systems. A series of air defense systems are kept in the underground tunnels, raised when needed, and returned to the earlier position later.

The Air Force unveiled its first underground military base on February 7. The tactical subterranean airbase named Oghab-44 (Eagle-44) can accommodate and prepare various aircraft including fighter jets, bombers, and unmanned aerial vehicles for missions.

This large underground base consists of various sections, such as an alert area, command post, warplane hangars, repair and maintenance center, navigation and airport equipment, and fuel tanks.

More:
IRGC Opens New Airbase in Southeast Iran - Caspian News