Predicting extreme events is essential to the preparation and protection of vulnerable regions, especially at a time of climate change. The city of Santos on the coast of São Paulo state (Brazil) is Latin America’s largest port and has been the focus for significant case studies, not least because of the storm surges that threaten its infrastructure and the local ecosystems.

An article reporting the results of a study that focused on a critical part of Santos and used advanced machine learning tools to optimize existing extreme event prediction systems has been published in Proceedings of the AAAI Conference on Artificial Intelligence.

It mobilized a large number of researchers and was coordinated by Anna Helena Reali Costa, full professor at the University of São Paulo’s Engineering School (POLI-USP). The first author is Marcel Barros, a researcher in POLI-USP’s Department of Computer Engineering and Digital Systems.

The models used to predict sea surface heights, high tides, wave heights and so on are based on differential equations comprising temporal and spatial information such as astronomic tide (determined by the relative positions of the sun, moon and Earth), wind regime, current velocity and salinity, among many others.

These models are successful in several areas but they are complex and depend on a number of simplifications and hypotheses. Moreover, new measurements and other data sources cannot always be integrated into them to make forecasts more reliable.

Although modelers are increasingly using machine learning methods capable of identifying patterns in data and extrapolating to new situations, a great many examples are required to train the algorithms that perform complex tasks such as those involved in weather forecasting and storm tide prediction.

“Our study combined the two worlds to develop a model based on machine learning that uses physical models as a starting point but refines them by adding measured data. This research field is known as physics-informed machine learning, or PIML,” Barros explained.

Harmonization of these two sources of information is fundamental to develop more precise and accurate forecasts. However, the use of sensor data faces significant technical challenges, owing especially to its irregular nature and problems such as missing data, temporal displacements, and variations in sampling frequencies. Sensors that fail can take days to be brought back online, but the mechanisms for predicting storm tides must be capable of operating continuously without the missing data.

“To address situations with highly irregular data, we developed an innovative technique to represent the passing of time in neural networks. This representation lets the model be told the position and size of the missing data windows, so that it considers them in its predictions of tide and wave heights,” Barros said.

The innovation permits better modeling of complex natural phenomena and can also be used to model other phenomena that involve irregular time series, such as health data, sensor networks in manufacturing, or financial indicators.

“Furthermore, our model combines different kinds of neural networks so as to integrate multimodal data, such as satellite images, tables and forecasts from numerical models, with possible future integration of other types of data, such as text and audio. This approach is an important step toward more robust and adaptable forecasting systems that can handle the complexity and variability of the data associated with extreme weather events,” Reali Costa said.

The model has three key virtues, she added, it combines physical and numerical models; it represents time in neural networks in a new way; and it works with data in different formats by means of multimodal architecture.

“The study offers a methodology that can improve the accuracy of predictions of extreme events, such as storm tides in Santos. At the same time, it highlights the challenges and potential solutions for the integration of physical models and sensor data in complex contexts,” she said.

European Union regulators on Monday leveled their first charges under the bloc’s new digital competition rulebook, accusing Apple of preventing app makers from pointing users to cheaper options outside its App Store.

The European Commission said that according to the preliminary findings of its investigation, the restrictions that the iPhone maker imposes on developers using its mobile App Store had breached the 27-nation bloc’s Digital Markets Act.

The rulebook, also known as the DMA, is a sweeping set of regulations aimed at preventing tech “gatekeepers” from cornering digital markets under threat of heavy financial penalties. The commission opened an initial round of investigations after it took effect in March, including a separate ongoing probe into whether Apple is doing enough to allow iPhone users to easily change web browsers, and other cases involving Google and Meta.

Apple has been facing pressure on both sides of the Atlantic to tear down some of the competitive barriers around its lucrative iPhone franchise. The U.S. Justice Department has filed a sweeping antitrust lawsuit against Apple this year, accusing it of illegally monopolizing the smartphone market and boxing out competitors, stifling innovation and keeping prices artificially high. App makers such as Spotify had complained for years about Apple’s requirement that subscriptions only be bought through iOS apps, allowing the company to take a commission of up to 30%.

Under the DMA’s provisions, app developers must be allowed to inform customers of cheaper purchasing options and direct them to those offers.

The commission, the bloc’s executive arm, said App Store rules “prevent app developers from freely steering consumers to alternative channels for offers and content.”

Apple now has a chance to respond to the findings. The commission must make a final decision on Apple’s compliance by March 2025. The company could face fines worth up to 10% of its global revenue, which could amount to billions of euros, or daily penalties.

The commission kept up the pressure on Apple, simultaneously opening a new investigation into contractual terms that it’s offering app developers.

Regulators zeroed in on a “core technology fee” of 50 euro cents (54 cents) that Apple is now charging developers for each time their apps are downloaded and installed from outside Apple’s App Store. The DMA’s provisions open the way for alternative app stores to give consumers more choice.

The commission said the the new terms are a “condition to access some of the new features enabled by the DMA.” Rivals had criticized the fee, saying it would deter many existing free apps, which don’t pay any fees, from jumping ship.

“We are concerned Apple’s new business model makes it too hard for app developers to operate as alternative marketplaces & reach their end users on iOS,” the European Commissioner for Competition, Margrethe Vestager, said on social media.

Apple Inc. said over the past several months, it “has made a number of changes to comply with the DMA in response to feedback from developers and the European Commission.”

“We are confident our plan complies with the law, and estimate more than 99% of developers would pay the same or less in fees to Apple under the new business terms we created,” the company said in a statement. “All developers doing business in the EU on the App Store have the opportunity to utilize the capabilities that we have introduced, including the ability to direct app users to the web to complete purchases at a very competitive rate.”

The company said it will “continue to listen and engage” with the commission.

The EU had been carrying out a similar investigation since 2020 into whether Apple’s in-app purchasing system and restrictions violated Brussels’ antitrust rules. But “to avoid multiple investigations into the very same conduct,” that probe is being shut down to focus on the investigation under the DMA, which clearly spells out what Apple can’t do, the commission said Monday.

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