The mobile revolution – Machine intelligence for autonomous vehicles

2015 ◽  
Vol 57 (3) ◽  
Author(s):  
Markus Enzweiler
Keyword(s):  
Autonomous Vehicles ◽  
Large Scale ◽  
State Of The Art ◽  
Machine Intelligence ◽  
Open Problems ◽  
Research Directions ◽  
Current State ◽  
Transportation Behavior ◽  
Open Issues

AbstractWhat started as a distant vision just a few decades ago is quickly becoming reality. Autonomous vehicles are about to be deployed on a large scale and will fundamentally change our transportation behavior. In this particular application, extreme demands on reliability and quality give rise to numerous problems and open issues that need to be jointly identified and addressed by both academia and industry. In this article, we present an overview of the current state-of-the-art in the field of intelligent autonomous vehicles. We further discuss open problems and current research directions.

scholarly journals Using plants to remediate or manage metal-polluted soils: an overview on the current state of phytotechnologies

2021 ◽  
Vol 43 ◽  
pp. e58283
Author(s):  
Clístenes Williams Araújo do Nascimento ◽  
Caroline Miranda Biondi ◽  
Fernando Bruno Vieira da Silva ◽  
Luiz Henrique Vieira Lima
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Cost Effective ◽  
Time Frame ◽  
Contaminated Site ◽  
Polluted Soils ◽  
Mining Sites ◽  
Current State ◽  
Remedial Actions ◽  
The Tropics

Soil contamination by metals threatens both the environment and human health and hence requires remedial actions. The conventional approach of removing polluted soils and replacing them with clean soils (excavation) is very costly for low-value sites and not feasible on a large scale. In this scenario, phytoremediation emerged as a promising cost-effective and environmentally-friendly technology to render metals less bioavailable (phytostabilization) or clean up metal-polluted soils (phytoextraction). Phytostabilization has demonstrable successes in mining sites and brownfields. On the other hand, phytoextraction still has few examples of successful applications. Either by using hyperaccumulating plants or high biomass plants induced to accumulate metals through chelator addition to the soil, major phytoextraction bottlenecks remain, mainly the extended time frame to remediation and lack of revenue from the land during the process. Due to these drawbacks, phytomanagement has been proposed to provide economic, environmental, and social benefits until the contaminated site returns to productive usage. Here, we review the evolution, promises, and limitations of these phytotechnologies. Despite the lack of commercial phytoextraction operations, there have been significant advances in understanding phytotechnologies' main constraints. Further investigation on new plant species, especially in the tropics, and soil amendments can potentially provide the basis to transform phytoextraction into an operational metal clean-up technology in the future. However, at the current state of the art, phytotechnology is moving the focus from remediation technologies to pollution attenuation and palliative cares.

scholarly journals An Overview of Lidar Imaging Systems for Autonomous Vehicles

2019 ◽  
Vol 9 (19) ◽  
pp. 4093 ◽  
Author(s):  
Santiago Royo ◽  
Maria Ballesta-Garcia
Keyword(s):  
Autonomous Vehicles ◽  
State Of The Art ◽  
Autonomous Vehicle ◽  
Single Point ◽  
Imaging Systems ◽  
Light Sources ◽  
Final Solution ◽  
Large Uncertainty ◽  
Current State ◽  
The Subject

Lidar imaging systems are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a race dedicated to deciding the final solution to be implemented. However, the diversity of state-of-the-art approaches to the solution brings a large uncertainty on the decision of the dominant final solution. Furthermore, the performance data of each approach often arise from different manufacturers and developers, which usually have some interest in the dispute. Within this paper, we intend to overcome the situation by providing an introductory, neutral overview of the technology linked to lidar imaging systems for autonomous vehicles, and its current state of development. We start with the main single-point measurement principles utilized, which then are combined with different imaging strategies, also described in the paper. An overview of the features of the light sources and photodetectors specific to lidar imaging systems most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development in autonomous vehicles has been included, in order to present some of the problems which still need to be solved before implementation may be considered as final. The reader is provided with a detailed bibliography containing both relevant books and state-of-the-art papers for further progress in the subject.

scholarly journals A state of the art review of hydroforming technology

2019 ◽  
Vol 13 (5) ◽  
pp. 789-828 ◽  
Author(s):  
Colin Bell ◽  
Jonathan Corney ◽  
Nicola Zuelli ◽  
David Savings
Keyword(s):  
Metal Forming ◽  
State Of The Art ◽  
Technology Readiness ◽  
Forming Process ◽  
Research Directions ◽  
Cold Forming ◽  
Technology Readiness Level ◽  
Current State ◽  
Readiness Level ◽  
Metal Forming Process

AbstractHydroforming is a relatively new metal forming process with many advantages over traditional cold forming processes including the ability to create more complicated components with fewer operations. For certain geometries, hydroforming technology permits the creation of parts that are lighter weight, have stiffer properties, are cheaper to produce and can be manufactured from fewer blanks which produces less material waste. This paper provides a detailed survey of the hydroforming literature of both established and emerging processes in a single taxonomy. Recently reported innovations in hydroforming processes (which are incorporated in the taxonomy) are also detailed and classified in terms of “technology readiness level”. The paper concludes with a discussion on the future of hydroforming including the current state of the art techniques, the research directions, and the process advantages to make predictions about emerging hydroforming technologies.

AN APPLICATION CONCEPT OF THE FIBRE-OPTICAL TECHNOLOGY IN GEODETIC MONITORING OF ENGINEERING OBJECTS

2017 ◽  
Vol 166 (46) ◽  
pp. 60-74
Author(s):  
Krzysztof Karsznia ◽  
Konrad Podawca
Keyword(s):  
Risk Management ◽  
Large Scale ◽  
State Of The Art ◽  
Monitoring Systems ◽  
Management Approach ◽  
Engineering Structures ◽  
Geoinformation Systems ◽  
Current State ◽  
Modern Engineering ◽  
Integrated Risk

Monitoring of structures and other different field objects undoubtedly belongs to the main issues of modern engineering. The use of technologies making it possible to implement structural monitoring makes it possible to build an integrated risk management approach combining instrumental solutions with geoinformation systems. In the studies of engineering structures, there is physical monitoring mainly used for examining the physical state of the object - so-called SHM ("Structural Health Monitoring"). However, very important role is also played by geodetic monitoring systems (GMS). The progress observed in the field of IT and automatics has opened new possibilities of using integrated systems on other, often large-scale objects. Based on the current state-of-the-art, the article presents the concept of integration approaches of physical and geodetic monitoring systems in order to develop useful guidelines for further construction of an expert risk management system.

Real Time Simulation for High Fidelity Multibody Dynamics and Mechatronic Systems

2014 ◽  
Author(s):  
William Prescott
Keyword(s):  
Real Time ◽  
Multibody Dynamics ◽  
Large Scale ◽  
State Of The Art ◽  
High Fidelity ◽  
Implicit Integration ◽  
Mechatronic Systems ◽  
Vehicle Simulation ◽  
Current State ◽  
Time Simulation

This paper will investigate the use of large scale multibody dynamics (MBD) models for real-time vehicle simulation. Current state of the art in the real-time solution of vehicle uses 15 degree of freedom models, but there is a need for higher-fidelity systems. To increase the fidelity of models uses this paper will propose the use of the following techniques: implicit integration, parallel processing and co-simulation in a real-time environment.

scholarly journals Sustainability in Heritage Wood Conservation: Challenges and Directions for Future Research

Forests ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 18
Author(s):  
Zarah Walsh-Korb
Keyword(s):  
Sustainable Development Goals ◽  
State Of The Art ◽  
Heritage Conservation ◽  
Future Research ◽  
Research Directions ◽  
Current State ◽  
The Future ◽  
Development Goals ◽  
Sustainable Conservation ◽  
New Research

Conserving the world’s cultural and natural heritage is considered a key contributor to achieving the targets set out in the United Nation’s Sustainable Development Goals, yet how much attention do we pay to the methods we use to conserve and protect this heritage? With a specific focus on wooden objects of cultural heritage, this review discusses the current state-of-the-art in heritage conservation in terms of sustainability, sustainable alternatives to currently used consolidants, and new research directions that could lead to more sustainable consolidants in the future. Within each stage a thorough discussion of the synthesis mechanisms and/or extraction protocols, particularly for bio-based resources is provided, evaluating resource usage and environmental impact. This is intended to give the reader a better understanding of the overall sustainability of each different approach and better evaluate consolidant choices for a more sustainable approach. The challenges facing the development of sustainable consolidants and recent research that is likely to lead to highly sustainable new consolidant strategies in the future are also discussed. This review aims to contribute to the ongoing discussion of sustainable conservation and highlight the role that consolidants play in truly sustainable heritage conservation.

scholarly journals Crop Rotation Modeling for Deep Learning-Based Parcel Classification from Satellite Time Series

2021 ◽  
Vol 13 (22) ◽  
pp. 4599
Author(s):  
Félix Quinton ◽  
Loic Landrieu
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Crop Rotation ◽  
Large Scale ◽  
State Of The Art ◽  
Crop Rotations ◽  
Learning Approach ◽  
Type Mapping ◽  
Current State ◽  
Crop Type

While annual crop rotations play a crucial role for agricultural optimization, they have been largely ignored for automated crop type mapping. In this paper, we take advantage of the increasing quantity of annotated satellite data to propose to model simultaneously the inter- and intra-annual agricultural dynamics of yearly parcel classification with a deep learning approach. Along with simple training adjustments, our model provides an improvement of over 6.3% mIoU over the current state-of-the-art of crop classification, and a reduction of over 21% of the error rate. Furthermore, we release the first large-scale multi-year agricultural dataset with over 300,000 annotated parcels.

scholarly journals Compressing Large-Scale Transformer-Based Models: A Case Study on BERT

2021 ◽  
Vol 9 ◽  
pp. 1061-1080
Author(s):  
Prakhar Ganesh ◽  
Yao Chen ◽  
Xin Lou ◽  
Mohammad Ali Khan ◽  
Yin Yang ◽  
...  
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Research Attention ◽  
Model Compression ◽  
Future Research Directions ◽  
Or Applications

Abstract Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks. However, these models often have billions of parameters, and thus are too resource- hungry and computation-intensive to suit low- capability devices or applications with strict latency requirements. One potential remedy for this is model compression, which has attracted considerable research attention. Here, we summarize the research in compressing Transformers, focusing on the especially popular BERT model. In particular, we survey the state of the art in compression for BERT, we clarify the current best practices for compressing large-scale Transformer models, and we provide insights into the workings of various methods. Our categorization and analysis also shed light on promising future research directions for achieving lightweight, accurate, and generic NLP models.

scholarly journals A Review of the State of the Art in Non-Contact Sensing for COVID-19

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5665
Author(s):  
William Taylor ◽  
Qammer H. Abbasi ◽  
Kia Dashtipour ◽  
Shuja Ansari ◽  
Syed Aziz Shah ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Current State ◽  
Global Pandemic ◽  
Future Research Directions ◽  
Contact Sensing

COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic.

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