A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective

V Pereira, E Hadjielias, M Christofi, D Vrontis - Human Resource …, 2023 - Elsevier
Artificial intelligence (AI) can bring both opportunities and challenges to human resource
management (HRM). While scholars have been examining the impact of AI on workplace …

Machine learning-based virtual screening and its applications to Alzheimer's drug discovery: a review

KA Carpenter, X Huang - Current pharmaceutical design, 2018 - ingentaconnect.com
Background: Virtual Screening (VS) has emerged as an important tool in the drug
development process, as it conducts efficient in silico searches over millions of compounds …

A review of autonomous agricultural vehicles (The experience of Hokkaido University)

A Roshanianfard, N Noguchi, H Okamoto… - Journal of Terramechanics, 2020 - Elsevier
Robotic farming will play an undeniably significant role in future sustainable agriculture.
Autonomous agricultural vehicles for arable crops and their components are reviewed …

[HTML][HTML] An integrated route and path planning strategy for skid–steer mobile robots in assisted harvesting tasks with terrain traversability constraints

RP Urvina, CL Guevara, JP Vásconez, AJ Prado - Agriculture, 2024 - mdpi.com
This article presents a combined route and path planning strategy to guide Skid–Steer
Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with …

[HTML][HTML] A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights

S Beycimen, D Ignatyev, A Zolotas - Engineering Science and Technology …, 2023 - Elsevier
This article provides a detailed analysis of the assessment of unmanned ground vehicle
terrain traversability. The analysis is categorized into terrain classification, terrain map** …

Energy consumption prediction using machine learning; a review

A Mosavi, A Bahmani - 2019 - preprints.org
Abstract Machine learning (ML) methods has recently contributed very well in the
advancement of the prediction models used for energy consumption. Such models highly …

[HTML][HTML] On misbehaviour and fault tolerance in machine learning systems

L Myllyaho, M Raatikainen, T Männistö… - Journal of Systems and …, 2022 - Elsevier
Abstract Machine learning (ML) provides us with numerous opportunities, allowing ML
systems to adapt to new situations and contexts. At the same time, this adaptability raises …

Human-centered torque vectoring control for distributed drive electric vehicle considering driving characteristics

L Zhang, H Chen, Y Huang, P Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Most of the existing torque vectoring control (TVC) strategies are “vehicle-centered,” hence,
fail to consider how driving characteristics affect the vehicle's motion. To address this issue …

Advanced automation system for charging electric vehicles based on machine vision and finite element method

M Talaat, I Arafa, HMB Metwally - IET Electric Power …, 2020 - Wiley Online Library
Electric vehicle (EV) technology proposed itself as a great solution for the predictable
shortage in traditional energy sources. Using wireless power transfer (WPT) technology for …

A Comprehensive Overview of Control Algorithms, Sensors, Actuators, and Communication Tools of Autonomous All-Terrain Vehicles in Agriculture

H Etezadi, S Eshkabilov - Agriculture, 2024 - mdpi.com
This review paper discusses the development trends of agricultural autonomous all-terrain
vehicles (AATVs) from four cornerstones, such as (1) control strategy and algorithms,(2) …