Task Planning with Manual Intervention Using Improved JSHOP2 Planner

The Effects of the Manual Intervention and Self Corrective Exercise Models of General Coordinative Manipulation on the Distorsional Leg

Journal of The Korean Society of Integrative Medicine ◽

10.15268/ksim.2015.3.1.029 ◽

2015 ◽

Vol 3 (1) ◽

pp. 29-39

Author(s):

Yunseo Kim ◽

Sangeun Moon

Keyword(s):

Manual Intervention

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Disturbance Analysis in the Classification of Objects Obtained from Urban LiDAR Point Clouds with Convolutional Neural Networks

Remote Sensing ◽

10.3390/rs13112135 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2135

Author(s):

Jesús Balado ◽

Pedro Arias ◽

Henrique Lorenzo ◽

Adrián Meijide-Rodríguez

Keyword(s):

Laser Scanning ◽

Ambient Noise ◽

Point Clouds ◽

Density Variation ◽

Density Reduction ◽

Manual Intervention ◽

Point Density ◽

Disturbance Analysis ◽

Street Furniture

Mobile Laser Scanning (MLS) systems have proven their usefulness in the rapid and accurate acquisition of the urban environment. From the generated point clouds, street furniture can be extracted and classified without manual intervention. However, this process of acquisition and classification is not error-free, caused mainly by disturbances. This paper analyses the effect of three disturbances (point density variation, ambient noise, and occlusions) on the classification of urban objects in point clouds. From point clouds acquired in real case studies, synthetic disturbances are generated and added. The point density reduction is generated by downsampling in a voxel-wise distribution. The ambient noise is generated as random points within the bounding box of the object, and the occlusion is generated by eliminating points contained in a sphere. Samples with disturbances are classified by a pre-trained Convolutional Neural Network (CNN). The results showed different behaviours for each disturbance: density reduction affected objects depending on the object shape and dimensions, ambient noise depending on the volume of the object, while occlusions depended on their size and location. Finally, the CNN was re-trained with a percentage of synthetic samples with disturbances. An improvement in the performance of 10–40% was reported except for occlusions with a radius larger than 1 m.

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DeComplex: Task planning from complex natural instructions by a collocating robot

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros45743.2020.9341289 ◽

2020 ◽

Author(s):

Pradip Pramanick ◽

Hrishav Bakul Barua ◽

Chayan Sarkar

Keyword(s):

Task Planning

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Autonomous task planning and situation awareness in robotic surgery*

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros45743.2020.9341382 ◽

2020 ◽

Cited By ~ 1

Author(s):

Michele Ginesi ◽

Daniele Meli ◽

Andrea Roberti ◽

Nicola Sansonetto ◽

Paolo Fiorini

Keyword(s):

Robotic Surgery ◽

Situation Awareness ◽

Task Planning

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A Survey on Security and Privacy Issues in Modern Healthcare Systems

ACM Transactions on Computing for Healthcare ◽

10.1145/3453176 ◽

2021 ◽

Vol 2 (3) ◽

pp. 1-44

Author(s):

Akm Iqtidar Newaz ◽

Amit Kumar Sikder ◽

Mohammad Ashiqur Rahman ◽

A. Selcuk Uluagac

Keyword(s):

Healthcare Systems ◽

Security And Privacy ◽

Health Conditions ◽

Future Research ◽

Security Measures ◽

Implantable Medical Devices ◽

Manual Intervention ◽

Security Challenges ◽

Future Research Directions ◽

Privacy Violation

Recent advancements in computing systems and wireless communications have made healthcare systems more efficient than before. Modern healthcare devices can monitor and manage different health conditions of patients automatically without any manual intervention from medical professionals. Additionally, the use of implantable medical devices, body area networks, and Internet of Things technologies in healthcare systems improve the overall patient monitoring and treatment process. However, these systems are complex in software and hardware, and optimizing between security, privacy, and treatment is crucial for healthcare systems because any security or privacy violation can lead to severe effects on patients’ treatments and overall health conditions. Indeed, the healthcare domain is increasingly facing security challenges and threats due to numerous design flaws and the lack of proper security measures in healthcare devices and applications. In this article, we explore various security and privacy threats to healthcare systems and discuss the consequences of these threats. We present a detailed survey of different potential attacks and discuss their impacts. Furthermore, we review the existing security measures proposed for healthcare systems and discuss their limitations. Finally, we conclude the article with future research directions toward securing healthcare systems against common vulnerabilities.

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High-Speed Imaging to Study an Auto-Oscillating Vocal Fold Replica for Different Initial Conditions

International Journal of Applied Mechanics ◽

10.1142/s1758825117500648 ◽

2017 ◽

Vol 09 (05) ◽

pp. 1750064 ◽

Cited By ~ 2

Author(s):

A. Van Hirtum ◽

X. Pelorson

Keyword(s):

Vocal Fold ◽

High Speed ◽

Initial Conditions ◽

Vocal Folds ◽

High Speed Imaging ◽

Human Voice ◽

Manual Intervention ◽

Geometrical Features ◽

Upstream Pressure

Experiments on mechanical deformable vocal folds replicas are important in physical studies of human voice production to understand the underlying fluid–structure interaction. At current date, most experiments are performed for constant initial conditions with respect to structural as well as geometrical features. Varying those conditions requires manual intervention, which might affect reproducibility and hence the quality of experimental results. In this work, a setup is described which allows setting elastic and geometrical initial conditions in an automated way for a deformable vocal fold replica. High-speed imaging is integrated in the setup in order to decorrelate elastic and geometrical features. This way, reproducible, accurate and systematic measurements can be performed for prescribed initial conditions of glottal area, mean upstream pressure and vocal fold elasticity. Moreover, quantification of geometrical features during auto-oscillation is shown to contribute to the experimental characterization and understanding.

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