Check engineering papers: citations, claims and retractions

Effects of regional temperature on electric vehicle efficiency, range, and emissions in the United States

Yuksel, T., & Michalek, J. J. (2015) · Environmental Science & Technology

Electric Vehicles and InfrastructureElectric and Hybrid Vehicle Technologies

Cited by 380

Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes

Zhao, M., Kang, M., Tang, B., & Pecht, M. (2018) · IEEE Transactions on Industrial Electronics

Machine Fault Diagnosis TechniquesGear and Bearing Dynamics Analysis

Cited by 380

Durability Performance of Geopolymer Concrete: A Review

Wong, L. S. (2022) · Polymers

Concrete and Cement Materials ResearchMicrobial Applications in Construction Materials

Cited by 380

A New Generation of Ai: A Review and Perspective on Machine Learning Technologies Applied to Smart Energy and Electric Power Systems

Cheng, L., & Yu, T. (2019) · International Journal of Energy Research

Smart Grid and Power SystemsSmart Grid Energy Management

Cited by 380

Lithium-ion battery thermal management using heat pipe and phase change material during discharge–charge cycle: A comprehensive numerical study

Jiang, Z. Y., & Qu, Z. G. (2019) · Applied Energy

Battery Modeling and ManagementHeat Transfer and Boiling Studies

Cited by 380

Biomechanical energy harvesting from human motion: theory, state of the art, design guidelines, and future directions

Riemer, R., & Shapiro, A. (2011) · Journal of NeuroEngineering and Rehabilitation

Innovative Energy Harvesting TechnologiesAdvanced Sensor and Energy Harvesting Materials

Cited by 379

Digital transformation success under Industry 4.0: a strategic guideline for manufacturing SMEs

Ghobakhloo, M., & Iranmanesh, M. (2021) · Journal of Manufacturing Technology Management

Digital Transformation in IndustryDigital Innovation in Industries

Cited by 379

A longitudinal study of ammonia, acetone and propanol in the exhaled breath of 30 subjects using selected ion flow tube mass spectrometry, SIFT-MS

Turner, C., Španěl, P., & Smith, D. (2006) · Physiological Measurement

Advanced Chemical Sensor TechnologiesMass Spectrometry Techniques and Applications

Cited by 379

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

Charlton, P. H., Birrenkott, D. A., Bonnici, T., Pimentel, M. A. F., Johnson, A. E. W., Alastruey, J., Tarassenko, L., Watkinson, P. J., Beale, R., & Clifton, D. A. (2018) · IEEE Reviews in Biomedical Engineering

Non-Invasive Vital Sign MonitoringECG Monitoring and Analysis

Cited by 379

An adaptive multi-sensor data fusion method based on deep convolutional neural networks for fault diagnosis of planetary gearbox

Jing, L., Wang, T., Zhao, M., & Wang, P. (2017) · Sensors

Machine Fault Diagnosis TechniquesGear and Bearing Dynamics Analysis

Cited by 379

Cobots: Robots for Collaboration With Human Operators

Colgate, J. E., Wannasuphoprasit, W., & Peshkin, M. A. (1996) · Dynamic Systems and Control

Teleoperation and Haptic SystemsRobot Manipulation and Learning

Cited by 379

Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning

Isele, D., Rahimi, R., Cosgun, A., Subramanian, K., & Fujimura, K. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Autonomous Vehicle Technology and SafetyReinforcement Learning in Robotics

Cited by 379

The Curious Case of Fluorination of Conjugated Polymers for Solar Cells

Zhang, Q., Kelly, M. A., Bauer, N., & You, W. (2017) · Accounts of Chemical Research

Organic Electronics and PhotovoltaicsOrganic Light-Emitting Diodes Research

Cited by 379

Transfer learning with neural networks for bearing fault diagnosis in changing working conditions

Zhang, R., Tao, H., Wu, L., & Guan, Y. (2017) · IEEE Access

Machine Fault Diagnosis TechniquesFault Detection and Control Systems

Cited by 378

Mega-scale fabrication by Contour Crafting

Khoshnevis, B., Hwang, D., Yao, K. T., & Yeh, Z. (2006) · International Journal of Industrial and Systems Engineering

Innovations in Concrete and Construction MaterialsAdditive Manufacturing and 3D Printing Technologies

Cited by 378

Data-driven state of charge estimation of lithium-ion batteries: Algorithms, implementation factors, limitations and future trends

Hossain Lipu, M. S., Hannan, M. A., Hussain, A., Ayob, A., Saad, M. H. M., Karim, T. F., & How, D. N. T. (2020) · Journal of Cleaner Production

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 378

Passive structural control of offshore wind turbines

Lackner, M. A., & Rotea, M. A. (2011) · Wind Energy

Vibration Control and Rheological FluidsAeroelasticity and Vibration Control

Cited by 378

Silver nanowire-embedded PDMS with a multiscale structure for a highly sensitive and robust flexible pressure sensor

Joo, Y., Byun, J., Seong, N., Ha, J., Kim, H., Kim, S., Kim, T., Im, H., Kim, D., & Hong, Y. (2015) · Nanoscale

Advanced Sensor and Energy Harvesting MaterialsNanomaterials and Printing Technologies

Cited by 378

Toward Wearable Self‐Charging Power Systems: The Integration of Energy‐Harvesting and Storage Devices

Pu, X., Hu, W., & Wang, Z. L. (2018) · Small

Advanced Sensor and Energy Harvesting MaterialsInnovative Energy Harvesting Technologies

Cited by 378

The soft x-ray free-electron laser FLASH at DESY: beamlines, diagnostics and end-stations

Tiedtke, K., Azima, A., von Bargen, N., Bittner, L., Bonfigt, S., Düsterer, S., Faatz, B., Frühling, U., Gensch, M., Gerth, C., et al. (2009) · New Journal of Physics

Particle Accelerators and Free-Electron LasersLaser-Matter Interactions and Applications

Cited by 378

Wearable flexible sweat sensors for healthcare monitoring: a review

Chung, M., Fortunato, G., & Radacsi, N. (2019) · Journal of The Royal Society Interface

Advanced Sensor and Energy Harvesting MaterialsElectrochemical sensors and biosensors

Cited by 378

Differences between young adults and elderly in thermal comfort, productivity, and thermal physiology in response to a moderate temperature drift and a steady-state condition

Schellen, L., Van Marken Lichtenbelt, W. D., Loomans, M. G. L. C., Toftum, J., & De Wit, M. H. (2010) · Indoor Air

Building Energy and Comfort OptimizationThermoregulation and physiological responses

Cited by 377

Lithium-ion battery data and where to find it

dos Reis, G., Strange, C., Yadav, M., & Li, S. (2021) · Energy and AI

Battery Modeling and ManagementAdvancements in Battery Materials

Cited by 377

Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits

Bayat, F. M., Prezioso, M., Chakrabarti, B., Nili, H., Kataeva, I., & Strukov, D. (2018) · Nature Communications

Advanced Memory and Neural ComputingNeural Networks and Applications

Cited by 377