Responsibility in the age of autonomous machines

2016 ◽  
Author(s):  
Minao Kukita
Keyword(s):  
Autonomous Machines

The Dark Side of Artificial Intelligence: Challenges for the Legal System

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Willem Gravett
Keyword(s):  
Artificial Intelligence ◽  
Legal System ◽  
Indirect Effects ◽  
Current Trend ◽  
Dark Side ◽  
Work Practices ◽  
Direct And Indirect Effects ◽  
Autonomous Machines ◽  
State Surveillance

The development of artificial intelligence has the potential to transform lives and work practices, raise efficiency, savings and safety levels, and provide enhanced levels of services. However, the current trend towards developing smart and autonomous machines with the capacity to be trained and make decisions independently holds not only economic advantages, but also a variety of concerns regarding their direct and indirect effects on society as a whole. This article examines some of these concerns, specifically in the areas of privacy and autonomy, state surveillance, and bias and algorithmic transparency. It concludes with an analysis of the challenges that the legal system faces in regulating the burgeoning field of artificial intelligence.

scholarly journals A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1178
Author(s):  
Bo Sun ◽  
Bo Tan ◽  
Wenbo Wang ◽  
Elena Simona Lohan
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Time Estimation ◽  
Satellite System ◽  
Base Station ◽  
Rectangular Array ◽  
Single Station ◽  
5G Network ◽  
Autonomous Machines ◽  
3D Positioning

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.

Light-driven Ti3C2 MXene micromotors: self-propelled autonomous machines for photodegradation of nitroaromatic explosives

2021 ◽  
Author(s):  
Carmen C. Mayorga-Martinez ◽  
Jan Vyskočil ◽  
Filip Novotný ◽  
Martin Pumera
Keyword(s):  
High Energy ◽  
Nitroaromatic Explosives ◽  
2D Material ◽  
Autonomous Machines

Light powered self-propelled 2D-material MXene-based sandwitch micromachines degrade high-energy exposives on a go.

scholarly journals Engineering Education in the Age of Autonomous Machines

Computer ◽  
2021 ◽  
Vol 54 (4) ◽  
pp. 66-69
Author(s):  
Shaoshan Liu ◽  
Jean-Luc Gaudiot ◽  
Hironori Kasahara
Keyword(s):  
Engineering Education ◽  
Autonomous Machines

scholarly journals Approaches to the robotization of agricultural mobile machines

2018 ◽  
Vol 161 ◽  
pp. 03014 ◽  
Author(s):  
Vladimir Serebrenny ◽  
Madin Shereuzhev ◽  
Ivan Metasov
Keyword(s):  
High Precision ◽  
Modern Technology ◽  
The State ◽  
Agricultural Machinery ◽  
Factors Affecting ◽  
Technological Processes ◽  
Autonomous Machines ◽  
Autonomous Movement ◽  
Technical Solutions ◽  
Agricultural Machines

Agriculture is the extremely important and developing economic movement in all times. Automation of agricultural machines occurs by different ways. One way is through the creation of specialized technical solutions for the required technological processes, another way is the construction of automatic agricultural machines, including mobile ones. The state of modern technology allows to create autonomous machines. The agriculture robotization trends are the high precision and unmanned farming. The article considers the issues of robotization of agricultural machinery. Stages of robotization of agricultural mobile machines were analyzed. The factors affecting the autonomous movement of mobile agrorobots were shown.

scholarly journals Profiling NVIDIA Jetson Embedded GPU Devices for Autonomous Machines

2020 ◽  
Author(s):  
Yazhou Li ◽  
Yahong Rosa Zheng
Keyword(s):  
Effective Means ◽  
Field Testing ◽  
Operating Mode ◽  
Autonomous Driving ◽  
Robot Operating System ◽  
Race Car ◽  
Localization And Mapping ◽  
Autonomous Machines ◽  
Particle Filter Algorithm ◽  
Embedded Gpu

This paper presents two methods, tegrastats GUI version jtop and Nsight Systems, to profile NVIDIA Jetson embedded GPU devices on a model race car which is a great platform for prototyping and field testing autonomous driving algorithms. The two profilers analyze the power consumption, CPU/GPU utilization, and the run time of CUDA C threads of Jetson TX2 in five different working modes. The performance differences among the five modes are demonstrated using three example programs: vector add in C and CUDA C, a simple ROS (Robot Operating System) package of the wall follow algorithm in Python, and a complex ROS package of the particle filter algorithm for SLAM (Simultaneous Localization and Mapping). The results show that the tools are effective means for selecting operating mode of the embedded GPU devices.

A Zero-Trust Methodology for Security of Complex Systems With Machine Learning Components

2021 ◽  
Author(s):  
Britta Hale ◽  
Douglas L. Van Bossuyt ◽  
Nikolaos Papakonstantinou ◽  
Bryan O’Halloran
Keyword(s):  
Machine Learning ◽  
Security Threats ◽  
Training Algorithms ◽  
Technological Advances ◽  
Autonomous Machines ◽  
Complex Models ◽  
Aerial Vehicle ◽  
Very High ◽  
Testing Coverage

Abstract Fuelled by recent technological advances, Machine Learning (ML) is being introduced to safety and security-critical applications like defence systems, financial systems, and autonomous machines. ML components can be used either for processing input data and/or for decision making. The response time and success rate demands are very high and this means that the deployed training algorithms often produce complex models that are not readable and verifiable by humans (like multi layer neural networks). Due to the complexity of these models, achieving complete testing coverage is in most cases not realistically possible. This raises security threats related to the ML components presenting unpredictable behavior due to malicious manipulation (backdoor attacks). This paper proposes a methodology based on established security principles like Zero-Trust and defence-in-depth to help prevent and mitigate the consequences of security threats including ones emerging from ML-based components. The methodology is demonstrated on a case study of an Unmanned Aerial Vehicle (UAV) with a sophisticated Intelligence, Surveillance, and Reconnaissance (ISR) module.

Internet of Things and Nature-Inspired Intelligent Techniques for the Future of Biomedical Engineering

2018 ◽  
pp. 263-282
Author(s):  
Gur Emre Guraksin
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Biomedical Engineering ◽  
Scientific Community ◽  
Engineering Applications ◽  
Related Literature ◽  
Research Fields ◽  
The Future ◽  
Autonomous Machines ◽  
General Network

Along with the rise of artificial intelligence (AI), there are many different research fields gaining importance. Because of the growing amount of data and needs for immediate access to information for dealing with the problems, different types of research fields take place within the scientific community. Internet of things (IoT) is one of them, and it enables devices to communicate with each other in order to form a general network of physical, working devices. The objective of this chapter in this manner is to provide a general discussion of using nature-inspired techniques of AI to form the future of biomedical engineering over IoT. Because it is often thought that the medical services of the future will be based on autonomous machines supported with AI and IoT, discussing such a topic by considering biomedical engineering applications will be good for the related literature.

Sign in / Sign up

Export Citation Format

Share Document