Point Cloud Quality Assessment Metric Based on Angular Similarity

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Arctic warming by abundant fine sea salt aerosols from blowing snow

Xin Yang, Jian Wang, Julia Schmale, Nora Bergner, Markus Frey

The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. Howe ...

2023

The thermodynamic and life-cycle assessments of a novel charging station for electric vehicles in dynamic and steady-state conditions

Jan Van Herle, Hossein Pourrahmani, Chengzhang Xu

The current study performs the thermodynamic and life-cycle assessments (LCA) of a novel charging station in two system designs. The goal is to design an efficient charging station for electric vehicles with high efficiencies and low environmental impacts ...

Nature Portfolio2023

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

SPIE2022

Organic Rankine Cycle as the Waste Heat Recovery Unit of Solid Oxide Fuel Cell: A Novel System Design for the Electric Vehicle Charging Stations Using Batteries as a Backup/Storage Unit

Jan Van Herle, Hossein Pourrahmani, Chengzhang Xu

The novelty of this study is to suggest a novel design for electric vehicle charging stations using fuel cell technology. The proposed system benefits from the Organic Rankine Cycle (ORC) to utilize the exhaust energy of the Solid Oxide Fuel Cell (SOFC) st ...

MDPI2022

The Application of Fuel-Cell and Battery Technologies in Unmanned Aerial Vehicles (UAVs): A Dynamic Study

Jan Van Herle, Claire Marie Isabelle Bernier, Hossein Pourrahmani

The harmful impacts of fossil-fuel-based engines on the environment have resulted in the development of other alternatives for different types of vehicles. Currently, batteries and fuel cells are being used in the automotive industry, while promising progr ...

MDPI2022

AI-based telepresence for broadcast applications

Touradj Ebrahimi, Rayan Daod Nathoo, Laurent Deillon, Henrique Piñeiro Monteagudo

In this paper, we introduce a new solution and underlying architecture that allows remote participants to interact with hosts in a broadcast scenario. To achieve this, background extraction is first applied to video received from remote participants to ext ...

SPIE2022

Two novel cogeneration charging stations for electric vehicles: Energy, exergy, economic, environment, and dynamic characterizations

Jan Van Herle, Hossein Pourrahmani, Chengzhang Xu

This paper suggests two novel designs for the electric vehicle charging stations using LiMn2O4 Lithium-ion battery and based on a Solid Oxide Fuel Cell (SOFC) and absorption refrigeration cycle (ARC) technologies to provide electricity and cooling, respect ...

Elsevier2022

The applications of Internet of Things in the automotive industry: A review of the batteries, fuel cells, and engines

Jan Van Herle, Hossein Pourrahmani

The current advances in the integration of devices through the internet of things (IoT) have encouraged researchers to focus on the applications of IoT in the automotive industry. Although different achievements in the in-vehicle network analysis and traff ...

ELSEVIER2022

Compressed natural gas (cng) power system with co2 emissions capture and storage

François Maréchal, Shivom Sharma

CNG power system (1) comprising a storage tank (6) connected fluidically to a fuel conversion system (2) via an energy transfer system (4), the fuel conversion system (2) comprising a power unit using CNG as fuel and generating gas emissions comprising C02 ...

2022

Incompleteness of graph neural networks for points clouds in three dimensions

Michele Ceriotti, Sergey Pozdnyakov

Graph neural networks (GNN) are very popular methods in machine learning and have been applied very successfully to the prediction of the properties of molecules and materials. First-order GNNs are well known to be incomplete, i.e. there exist graphs that ...

IOP Publishing Ltd2022

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