Modular Reconfigurable Robotics

2019 ◽  
Vol 2 (1) ◽  
pp. 63-88 ◽  
Author(s):  
Jungwon Seo ◽  
Jamie Paik ◽  
Mark Yim
Keyword(s):  
State Of The Art ◽  
Low Cost ◽  
Future Research ◽  
Research Directions ◽  
Current State ◽  
Robot Systems ◽  
Technical Issues ◽  
Future Research Directions ◽  
Reconfigurable Robot ◽  
High Level

This article reviews the current state of the art in the development of modular reconfigurable robot (MRR) systems and suggests promising future research directions. A wide variety of MRR systems have been presented to date, and these robots promise to be versatile, robust, and low cost compared with other conventional robot systems. MRR systems thus have the potential to outperform traditional systems with a fixed morphology when carrying out tasks that require a high level of flexibility. We begin by introducing the taxonomy of MRRs based on their hardware architecture. We then examine recent progress in the hardware and the software technologies for MRRs, along with remaining technical issues. We conclude with a discussion of open challenges and future research directions.

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.

scholarly journals Designing a solver competition: the QBFEVAL'10 case study

10.29007/cv3b ◽  
2018 ◽  
Author(s):  
Claudia Peschiera ◽  
Luca Pulina ◽  
Armando Tacchella
Keyword(s):  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Quantified Boolean Formulas ◽  
Current State ◽  
Boolean Formulas ◽  
Future Research Directions

In this paper we report about QBFEVAL'10, the seventh in a series of events established with the aim of assessing the advancements in reasoning about quantified Boolean formulas (QBFs). The paper discusses the results obtained and the evaluation setup, from the criteria used to select QBF instances down to the hardware infrastructure. We also discuss the current state-of-the-art in light of past challenges and we envision future research directions that are motivated by the results of QBFEVAL'10.

Emotional networks: The heart of brain design

2000 ◽  
Vol 23 (2) ◽  
pp. 198-199
Author(s):  
John C. Fentress
Keyword(s):  
Neural Networks ◽  
Single Unit ◽  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Behavioral Issues ◽  
Current State ◽  
Adaptive Action ◽  
Future Research Directions

The concept of emotion as defined by Rolls is based upon reinforcement mechanisms and their underlying neural networks. He shows how these networks process signals at many levels, through both separate and convergent pathways essential for adaptive action. While many behavioral issues related to emotion are omitted from his review, he succeeds admirably in summarizing both the “current state of the art” in single unit analyses and in pointing out how future research directions may be crafted.

scholarly journals On the Security and Privacy Challenges of Virtual Assistants

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2312
Author(s):  
Tom Bolton ◽  
Tooska Dargahi ◽  
Sana Belguith ◽  
Mabrook S. Al-Rakhami ◽  
Ali Hassan Sodhro
Keyword(s):  
Language Processing ◽  
State Of The Art ◽  
Security And Privacy ◽  
Future Research ◽  
Research Directions ◽  
Privacy Concerns ◽  
Current Trends ◽  
Current State ◽  
Future Research Directions ◽  
Privacy Issues

Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtual assistants (VAs) have grown in number and popularity. The sophisticated natural language processing and speech recognition employed by VAs enables users to interact with them conversationally, almost as they would with another human. To service user voice requests, VAs transmit large amounts of data to their vendors; these data are processed and stored in the Cloud. The potential data security and privacy issues involved in this process provided the motivation to examine the current state of the art in VA research. In this study, we identify peer-reviewed literature that focuses on security and privacy concerns surrounding these assistants, including current trends in addressing how voice assistants are vulnerable to malicious attacks and worries that the VA is recording without the user’s knowledge or consent. The findings show that not only are these worries manifold, but there is a gap in the current state of the art, and no current literature reviews on the topic exist. This review sheds light on future research directions, such as providing solutions to perform voice authentication without an external device, and the compliance of VAs with privacy regulations.

Probabilistic Rule Learning Systems

2021 ◽  
Vol 54 (4) ◽  
pp. 1-16
Author(s):  
Abdus Salam ◽  
Rolf Schwitter ◽  
Mehmet A. Orgun
Keyword(s):  
Probability Theory ◽  
Rule Learning ◽  
Background Knowledge ◽  
Learning Systems ◽  
Future Research ◽  
Research Directions ◽  
System Architectures ◽  
Probabilistic Rule ◽  
Future Research Directions ◽  
High Level

This survey provides an overview of rule learning systems that can learn the structure of probabilistic rules for uncertain domains. These systems are very useful in such domains because they can be trained with a small amount of positive and negative examples, use declarative representations of background knowledge, and combine efficient high-level reasoning with the probability theory. The output of these systems are probabilistic rules that are easy to understand by humans, since the conditions for consequences lead to predictions that become transparent and interpretable. This survey focuses on representational approaches and system architectures, and suggests future research directions.

Life cycle assessment of carbon capture and storage/utilization: From current state to future research directions and opportunities

2021 ◽  
Vol 108 ◽  
pp. 103309
Author(s):  
Tatiane Tobias da Cruz ◽  
José A. Perrella Balestieri ◽  
João M. de Toledo Silva ◽  
Mateus R.N. Vilanova ◽  
Otávio J. Oliveira ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Carbon Capture ◽  
Carbon Capture And Storage ◽  
Future Research ◽  
Research Directions ◽  
Current State ◽  
Future Research Directions ◽  
And Storage

scholarly journals Social commerce—state-of-the-art and future research directions

2016 ◽  
Vol 26 (3) ◽  
pp. 269-290 ◽  
Author(s):  
Catherine Baethge ◽  
Julia Klier ◽  
Mathias Klier
Keyword(s):  
State Of The Art ◽  
Future Research ◽  
Social Commerce ◽  
Research Directions ◽  
Future Research Directions
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