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We present a cost-effective electro-optic frequency comb generation and equalization method using a single phase modulator inserted in a Sagnac interferometer layout. The equalization relies on the interference of comb lines generated in both clockwise and ...

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While the introduction of practical deep learning has driven progress across scientific fields, recent research highlighted that the requirement of deep learning for ever-increasing computational resources and data has potential negative impacts on the sci ...

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Short-term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements

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Headwater streams often experience intermittent flow. Consequently, the flowing drainage network expands and contracts and the flowing drainage density (DD) varies over time. Monitoring the DD dynamics is essential to understand the processes controlling i ...

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Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information

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We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

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Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

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Recently, we published an article [1] presenting how the Power Electronics course at the bachelor level is organized by the Power Electronics Laboratory and taught at Ecole Polytechnique Fédérale de Lausanne, EPFL, Switzerland. For those avid readers who m ...

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Decision support for the design of integrated biorefineries

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A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

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The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

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Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

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In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

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