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Monitoring of Protein and pH Levels in Human Biofluids using FD-SOI Silicon Nanowire Arrays

Medical research and technological advancements are heading towards tailored healthcare approaches that prioritize individual needs, allowing for more accurate diagnoses, more effective treatments, and better patient outcomes overall. One such approach is ...

EPFL2023

Probing proton diffusion as a guide to environmental stability in powder-engineered FAPbI3 and CsFAPbI3 perovskites

Mohammad Khaja Nazeeruddin, Jianxing Xia

Formamidinium lead iodide-based solar cells show promising device reliability. The grain imperfection can be further suppressed by developing powder methodology. The water uptake capability is critical for the stability of a-formamidinium lead triiodide (F ...

ELSEVIER2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

A Network Calculus Analysis of Asynchronous Mechanisms in Time-Sensitive Networks

Ehsan Mohammadpour

Time-sensitive networks provide worst-case guarantees for applications in domains such as the automobile, automation, avionics, and the space industries. A violation of these guarantees can cause considerable financial loss and serious damage to human live ...

EPFL2023

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Trung-Dung Hoang, Thanh Trung Huynh

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 ...

ELSEVIER2023

Risk of incorrect choices due to uncertainty in BPS evaluations of conceptual-stage neighbourhood-scale building designs

Marilyne Andersen, Luisa Pastore, Minu Agarwal

At the conceptual stage, building performance simulation (BPS) based evaluations are being increasingly used for tasks such as ranking of competing massing design proposals. However, such conceptual stage evaluations suffer from information deficiency in b ...

2023

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Jürg Alexander Schiffmann, Cyril Picard, Faez Ahmed

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

Amer Soc Mechanical Engineers2023

Out of their minds? Externalist challenges for using AI in forensic psychiatry

Marcello Ienca, Ambra D'imperio

Harnessing the power of machine learning (ML) and other Artificial Intelligence (AI) techniques promises substantial improvements across forensic psychiatry, supposedly offering more objective evaluations and predictions. However, AI-based predictions abou ...

FRONTIERS MEDIA SA2023

Data-driven optimization tool for the functional, economic, and environmental properties of blended cement concrete using supplementary cementitious materials

Hisham Tarek Mohamed Hafez

The need to produce more sustainable concrete is proving imminent given the rising environmental concerns facing the industry. Blended cement concrete, based on any of the prominent supplementary cementitious materials (SCMs) such as fly ash, ground granul ...

ELSEVIER2023

Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units

Olga Fink, Mina Montazeri

This paper proposes a safe reinforcement learning algorithm for generation bidding decisions and unit maintenance scheduling in a competitive electricity market environment. In this problem, each unit aims to find a bidding strategy that maximizes its reve ...

2023

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Data-driven optimization tool for the functional, economic, and environmental properties of blended cement concrete using supplementary cementitious materials

Hisham Tarek Mohamed Hafez

ELSEVIER2023

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Trung-Dung Hoang, Thanh Trung Huynh

ELSEVIER2023

Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units

Olga Fink, Mina Montazeri

2023