Data-Driven Multiscale Science for Tire Compounding: Methods and Future Directions

2020 ◽  
pp. 281-312
Author(s):  
Hongyi Xu ◽  
Richard J. Sheridan ◽  
L. Catherine Brinson ◽  
Wei Chen ◽  
Bing Jiang ◽  
...  
Keyword(s):  
Data Driven ◽  
Future Directions

scholarly journals COVID-19 Contact Tracing: Challenges and Future Directions

2020 ◽  
Author(s):  
Mohammad Jabed Morshed Chowdhury ◽  
Md Sadek Ferdous ◽  
Kamanashis Biswas ◽  
Niaz Chowdhury ◽  
Vallipuram Muthukkumarasamy
Keyword(s):  
Personal Data ◽  
Human Memory ◽  
Data Driven ◽  
Contact Tracing ◽  
Future Directions ◽  
Significant Challenge ◽  
Innovative Solution ◽  
Public Health Officials ◽  
Novel Coronavirus ◽  
High Level

Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.

scholarly journals When Intelligent Transportation Systems Sensing Meets Edge Computing: Vision and Challenges

2021 ◽  
Vol 11 (20) ◽  
pp. 9680
Author(s):  
Xuan Zhou ◽  
Ruimin Ke ◽  
Hao Yang ◽  
Chenxi Liu
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Research Community ◽  
Edge Computing ◽  
Data Driven ◽  
Future Directions ◽  
Critical Part ◽  
Modern Cities ◽  
Computing Vision

The widespread use of mobile devices and sensors has motivated data-driven applications that can leverage the power of big data to benefit many aspects of our daily life, such as health, transportation, economy, and environment. Under the context of smart city, intelligent transportation systems (ITS), such as a main building block of modern cities and edge computing (EC), as an emerging computing service that targets addressing the limitations of cloud computing, have attracted increasing attention in the research community in recent years. It is well believed that the application of EC in ITS will have considerable benefits to transportation systems regarding efficiency, safety, and sustainability. Despite the growing trend in ITS and EC research, a big gap in the existing literature is identified: the intersection between these two promising directions has been far from well explored. In this paper, we focus on a critical part of ITS, i.e., sensing, and conducting a review on the recent advances in ITS sensing and EC applications in this field. The key challenges in ITS sensing and future directions with the integration of edge computing are discussed.

scholarly journals Data-driven methods for building control — A review and promising future directions

2020 ◽  
Vol 95 ◽  
pp. 104211 ◽  
Author(s):  
Emilio T. Maddalena ◽  
Yingzhao Lian ◽  
Colin N. Jones
Keyword(s):  
Data Driven ◽  
Future Directions ◽  
Building Control

scholarly journals Future Directions for Electric Propulsion Research

Aerospace ◽  
2020 ◽  
Vol 7 (9) ◽  
pp. 120 ◽  
Author(s):  
Ethan Dale ◽  
Benjamin Jorns ◽  
Alec Gallimore
Keyword(s):  
Power Systems ◽  
Electric Propulsion ◽  
Large Scale ◽  
Data Driven ◽  
Hall Thrusters ◽  
Future Directions ◽  
Ion Thrusters ◽  
Open Questions ◽  
S Curve ◽  
Near Future

The research challenges for electric propulsion technologies are examined in the context of s-curve development cycles. It is shown that the need for research is driven both by the application as well as relative maturity of the technology. For flight qualified systems such as moderately-powered Hall thrusters and gridded ion thrusters, there are open questions related to testing fidelity and predictive modeling. For less developed technologies like large-scale electrospray arrays and pulsed inductive thrusters, the challenges include scalability and realizing theoretical performance. Strategies are discussed to address the challenges of both mature and developed technologies. With the aid of targeted numerical and experimental facility effects studies, the application of data-driven analyses, and the development of advanced power systems, many of these hurdles can be overcome in the near future.

Adaptive Control Approaches for Nonlinear Systems: Retrospect and Prospects

2015 ◽  
Vol 719-720 ◽  
pp. 336-345
Author(s):  
Hong Liang Rao
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Data Driven ◽  
Research Progress ◽  
New Classification ◽  
Future Directions ◽  
Main Research ◽  
Model Driven ◽  
Classification Framework ◽  
State Of Art

This paper discusses the state-of-art of adaptive control approaches for nonlinear systems to date and presents a new classification framework, in which the existing adaptive control approaches can be broadly classified into two categories: model-driven methods and data-driven methods. The principle, main research progress, and inherent problems of these methods are reviewed. Finally, some practical considerations and future directions are also briefly explored and discussed.

scholarly journals The Lyme and Tickborne Disease Dashboard: A map-based resource to promote public health awareness and research collaboration

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260122
Author(s):  
Frank C. Curriero ◽  
Cara Wychgram ◽  
Alison W. Rebman ◽  
Anne E. Corrigan ◽  
Anton Kvit ◽  
...  
Keyword(s):  
Public Health ◽  
Spatial Data ◽  
Scientific Collaboration ◽  
One Health ◽  
Research Collaboration ◽  
Data Driven ◽  
Data Sets ◽  
Future Directions ◽  
The Us ◽  
Spatial Data Sets

With the incidence of Lyme and other tickborne diseases on the rise in the US and globally, there is a critical need for data-driven tools that communicate the magnitude of this problem and help guide public health responses. We present the Johns Hopkins Lyme and Tickborne Disease Dashboard (https://www.hopkinslymetracker.org/), a new tool that harnesses the power of geography to raise awareness and fuel research and scientific collaboration. The dashboard is unique in applying a geographic lens to tickborne diseases, aiming not only to become a global tracker of tickborne diseases but also to contextualize their complicated geography with a comprehensive set of maps and spatial data sets representing a One Health approach. We share our experience designing and implementing the dashboard, describe the main features, and discuss current limitations and future directions.

Agricultural Robotics

2019 ◽  
Vol 2 (1) ◽  
pp. 365-392 ◽  
Author(s):  
Stavros G. Vougioukas
Keyword(s):  
Data Driven ◽  
Farm Labor ◽  
Data Sets ◽  
Future Directions ◽  
Agricultural Robots ◽  
Benchmark Data ◽  
Labor Inputs ◽  
Sustainable Fashion ◽  
And Performance ◽  
Physical And Chemical

A key goal of contemporary agriculture is to dramatically increase production of food, feed, fiber, and biofuel products in a sustainable fashion, facing the pressure of diminishing farm labor supply. Agricultural robots can accelerate plant breeding and advance data-driven precision farming with significantly reduced labor inputs by providing task-appropriate sensing and actuation at fine spatiotemporal resolutions. This article highlights the distinctive challenges imposed on ground robots by agricultural environments, which are characterized by wide variations in environmental conditions, diversity and complexity of plant canopy structures, and intraspecies biological variation of physical and chemical characteristics and responses to the environment. Existing approaches to address these challenges are presented, along with their limitations; possible future directions are also discussed. Two key observations are that biology (breeding) and horticultural practices can reduce variabilities at the source and that publicly available benchmark data sets are needed to increase perception robustness and performance despite variability.

scholarly journals Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sameer Sayyad ◽  
Satish Kumar ◽  
Arunkumar Bongale ◽  
Pooja Kamat ◽  
Shruti Patil ◽  
...  
Keyword(s):  
Milling Process ◽  
Remaining Useful Life ◽  
Data Driven ◽  
Future Directions ◽  
Life Estimation ◽  
Useful Life
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