A team of researchers from the University of La Rochelle in France have converted albatrosses into de facto surveillance drones as part of a project to gather data on illegal fishing boats in the South Pacific and Indian Ocean. The team traveled to popular albatross nesting locations at Amsterdam Island and Kerguelen Island in the Indian Ocean north of Antarctica, and attached small sensors to 169 albatrosses in a procedure that took about 10 minutes per bird. The sensors weigh 65 grams, or around a seventh of a pound, and were equipped with a GPS receiver, a radar antenna, and a satellite communications monitor to track various boat communication systems. The devices were each powered by a small lithium battery that maintains a charge through a small solar panel, according to a report from ArsTechnica. The albatrosses covered more than 18 million square miles between East Africa and New Zealand, gathering data from more than 600,000 GPS locations.

Many classification applications require accurate probability estimates in addition to good class separation but often classifiers are designed focusing only on the latter. Calibration is the process of improving probability estimates by post-processing but commonly used calibration algorithms work poorly on small data sets and assume the classification task to be binary. Both of these restrictions limit their real-world applicability. Previously introduced Data Generation and Grouping algorithm alleviates the problem posed by small data sets and in this article, we will demonstrate that its application to multi-class problems is also possible which solves the other limitation. Our experiments show that calibration error can be decreased using the proposed approach and the additional computational cost is acceptable.

The UAE continues to places great importance to protecting the environment and promoting a green economy, placing sustainability at the forefront of its strategic priorities. This is in line with the UAE Vision 2021, which aims to build a sustainable environment, and a diversified and sustainable competitive economy that ensures a secure future for generations to come. Under the guidance of its wise leadership, the UAE has made great progress towards sustainability, driven by significant achievements in the adoption of advanced technologies to create a new reality and to build a leading global model for sustainable development. The UAE has recognised the importance of Artificial Intelligence (AI) as the cornerstone for achieving sustainability goals, at a time when this advanced technology is expected to contribute to the growth of the country's GDP by 35% until 2031, while also reducing government expenditures by 50% annually, cutting down the number of paper transactions and saving millions of work hours annually. The aim of the UAE Strategy for Artificial Intelligence 2031 is to improve government performance, accelerate the pace of achievements, and to create innovative and productive work environments that ensure high levels of productivity.

Researchers in Japan and The Netherlands have, for the first time, used machine learning techniques, in particular artificial neural networks (ANNs), to predict the Indian Ocean Dipole (IOD), a positive phase of which has affected weather and climate in India and Australia in a spectacular fashion so far in 2019-20. The IOD has both positive and negative phases, and signals large socio-economic impacts on many countries and hence predicting the IOD well in advance will benefit the affected societies, note authors JV Ratnam and Swadhin K Behera (Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama) and HA Dijkstra (Institute for Marine and Atmospheric Research Utrecht, Utrecht University in The Netherlands) in a paper published by Nature. The IOD is a mode of climate variability observed in the Indian Ocean sea surface temperature anomalies with one pole in Sumatra (Indonesia) and the other near East Africa. Therefore, the IOD is represented by an index derived from the gradient between the western equatorial Indian Ocean and the south-eastern equatorial Indian Ocean. It starts sometime in May-June, peaks in September-October and ends in November (2019's rather strong positive phase of the IOD lasted into early January of 2020).

Learning rates in stochastic neural network training are currently determined a priori to training, using expensive manual or automated iterative tuning. This study proposes gradient-only line searches to resolve the learning rate for neural network training algorithms. Stochastic sub-sampling during training decreases computational cost and allows the optimization algorithms to progress over local minima. However, it also results in discontinuous cost functions. Minimization line searches are not effective in this context, as they use a vanishing derivative (first order optimality condition), which often do not exist in a discontinuous cost function and therefore converge to discontinuities as opposed to minima from the data trends. Instead, we base candidate solutions along a search direction purely on gradient information, in particular by a directional derivative sign change from negative to positive (a Non-negative Associative Gradient Projection Point (NN- GPP)). Only considering a sign change from negative to positive always indicates a minimum, thus NN-GPPs contain second order information. Conversely, a vanishing gradient is purely a first order condition, which may indicate a minimum, maximum or saddle point. This insight allows the learning rate of an algorithm to be reliably resolved as the step size along a search direction, increasing convergence performance and eliminating an otherwise expensive hyperparameter.

DUBAI, UNITED ARAB EMIRATES – A flurry of diplomatic visits and meetings crisscrossing the Persian Gulf have driven urgent efforts in recent days to defuse the possibility of all-out war after the U.S. killed Iran's top military commander. Global leaders and top diplomats are repeating the mantra of "de-escalation" and "dialog," yet none has publicly laid out a path to achieving either. The United States and Iran have said they do not want war, but fears have grown that the crisis could spin out of Tehran's or Washington's control. Tensions have careened from one crisis to another since President Donald Trump withdrew the U.S. from Iran's nuclear deal with world powers. The U.S. drone strike that killed Revolutionary Guard Gen. Qassem Soleimani and a senior Iraqi militia leader in Baghdad on Jan. 3 was seen as a major provocation.

DUBAI, UNITED ARAB EMIRATES – Iran's acknowledgement that it shot down a Ukrainian airliner, killing 176 people, raises new challenges for the Islamic Republic both externally amid tensions with the U.S. and internally as it deals with growing discontent from its people. The country did itself no favors by having its air-crash investigators, government officials and diplomats deny for days that a missile downed the flight, though a commander said Saturday that he had raised that possibility to his superiors as early as Wednesday, the day of the crash. While its paramilitary Revolutionary Guard took responsibility, the same commander claimed it warned Tehran to close off its airspace amid fears of U.S. retaliation over Iran launching ballistic missiles at Iraqi bases housing U.S. forces. That retaliation never came, but the worries proved to be enough to allegedly scare a missile battery into opening fire on the Boeing 737 operated by Ukrainian International Airlines. Wider tensions between Iran and the U.S., inflamed after Iran's top general was killed in Iraq by a U.S. drone strike on Jan. 3, have for the moment calmed. However, President Donald Trump vowed to impose new sanctions on Tehran and on Friday, his administration targeted Iran's metals industry, a major employer.

WASHINGTON – U.S. officials said Thursday it was "highly likely" that an Iranian anti-aircraft missile downed a Ukrainian jetliner late Tuesday, killing all 176 people on board. They suggested it could well have been a mistake. The crash came just a few hours after Iran launched a ballistic missile attack against Iraqi military bases housing U.S. troops amid a confrontation with Washington over the U.S. drone strike that killed an Iranian Revolutionary Guard general last week. Two U.S. officials, speaking on the condition of anonymity to discuss sensitive intelligence, said they had no certain knowledge of Iranian intent. But they said the airliner could have been mistaken for a threat.

DUBAI, UNITED ARAB EMIRATES – Iran's launching of more than a dozen missiles at American-led forces in Iraq on Wednesday came after years of preparing for a confrontation with its superpower foe, whose forces are vastly larger and more advanced. The Persian Gulf country has more than 500,000 active-duty personnel, including 125,000 members of its elite Revolutionary Guard, according to a report last year by the International Institute for Strategic Studies. But international sanctions and restrictions on arms imports have made it hard for Iran to develop or buy more sophisticated weaponry. To compensate for the imbalance, Iran has developed "asymmetric" responses -- ballistic missiles, deadly drones and a web of militia allies in Iraq, Syria, Lebanon and Yemen, among other things -- with the aim of being able to inflict pain while avoiding the traditional battlefield. "From a conventional military perspective, they would get absolutely hammered," said a British former military commander who asked not to be identified because of the sensitivity of the matter.