Repository Community: null
http://hdl.handle.net/20.500.11750/201
2024-03-29T06:00:16Z
2024-03-29T06:00:16Z
An Adaptive Gain Dynamics for Time Delay Control Improves Accuracy and Robustness to Significant Payload Changes for Robots
Lee Junyoung
Chang, Pyung Hun
Jin Maolin
http://hdl.handle.net/20.500.11750/11403
2021-06-21T20:07:07Z
2020-03-31T15:00:00Z
Title: An Adaptive Gain Dynamics for Time Delay Control Improves Accuracy and Robustness to Significant Payload Changes for Robots
Author(s): Lee Junyoung; Chang, Pyung Hun; Jin Maolin
Abstract: Time delay control (TDC) is a promising technique for robot manipulators because it is model-free, efficient, and yet, robust. Nevertheless, when a robot operates under significant payload changes, it is difficult to achieve satisfactory performance with a constant gain. To cope with this problem, several adaptive rules have already been proposed thus far, but they are less effective to significant payload changes, and parameter tuning procedures are too complicated. In this paper, we propose an adaptive gain dynamics that is more effective in payload changes and yet simpler to implement. Through simulations using a one-link arm and experiments using a whole arm manipulator with payload changes, the proposed dynamics was compared with the conventional TDC and two other existing methods. Simulation results show that the proposed algorithm can adapt to significant payload changes, achieving better accuracy than the conventional TDC. Experimental results show that the proposed method has consistently better adaptation capability than other methods, achieving significantly better accuracy. In addition, the proposed method is simpler to implement, having only one tuning parameter, whereas the existing methods require four or five such tuning parameters.
2020-03-31T15:00:00Z
Mechano-neuromodulation of autonomic pelvic nerve for underactive bladder: A triboelectric neurostimulator integrated with flexible neural clip interface
Lee, SangHoon
Wang, Hao
Peh, Wendy Yen Xian
He, Tianyiyi
Yen, Shih-Cheng
Thakor, Nitish, V
Lee, Chengkuo
http://hdl.handle.net/20.500.11750/9742
2020-01-23T09:52:26Z
2019-05-31T15:00:00Z
Title: Mechano-neuromodulation of autonomic pelvic nerve for underactive bladder: A triboelectric neurostimulator integrated with flexible neural clip interface
Author(s): Lee, SangHoon; Wang, Hao; Peh, Wendy Yen Xian; He, Tianyiyi; Yen, Shih-Cheng; Thakor, Nitish, V; Lee, Chengkuo
Abstract: Mechano-neuromodulation of autonomic pelvic nerves was demonstrated for the first time using a triboelectric neurostimulator integrated with flexible neural clip interface. The detailed stimulation parameters such as current, pulse width, and charges generated by the proposed TENG were investigated for the stimulation of autonomic pelvic nerve. In in vivo experiments, different beats per minute (BPM) were delivered to the nerves to investigate the effect of stimulation frequency on mechano-neurostimulation while monitoring changes in bladder pressure and the occurrence of micturition. Furthermore, different numbers of pulses were applied to stimulate the pelvic nerve. The bladder contractions with micturition were observed when applying more than 50 BPM as well as one pulse. Comparison of stimulation was performed using a commercial stimulator with the similar long-pulse widths as generated by TENGs. In addition, chronic implantation of flexible clip interface was demonstrated with functionality test of the interface. The results demonstrate that this technology may potentially be used for self-powered mechano-neuromodulation for bladder function in the future. © 2019
2019-05-31T15:00:00Z
Secure Image-authentication Schemes with Hidden Double Random-phase Encoding
Yi, Faliu
Kim, Youhyun
Moon, Inkyu
http://hdl.handle.net/20.500.11750/9459
2024-03-07T18:01:23Z
2018-10-31T15:00:00Z
Title: Secure Image-authentication Schemes with Hidden Double Random-phase Encoding
Author(s): Yi, Faliu; Kim, Youhyun; Moon, Inkyu
Abstract: We present a new image-authentication algorithm based on binary-quantified double random-phase encoding (DRPE) and a discrete cosine transformation (DCT) domain watermarking scheme. The image is encrypted using a DRPE scheme, in which only the phase part of the encoded image is preserved. Then, this phase image is quantified to become a binary image by giving 0 to these phase values that are less than 0 and setting others to 1. Then, the quantified binary image is secretly inserted into a host image with a DCT-domain watermarking algorithm. During image authentication, the receiver gets the binary image from the watermarked image using an inverse DCT operation and codes 0 values as -pi and values of 1 as pi to create a phase image. Finally, the input image is decoded from the retrieved phase image based on a double random phase decryption technique and is further authenticated using a nonlinear cross-correlation method. The present image-authentication algorithm offers an additional layer of system security because the hidden binary image reveals no information that is from the original image. Moreover, the image decrypted from the retrieved phase image cannot be easily recognized with naked eyes. However, it can be successfully authenticated by nonlinear cross-correlation, even in the face of attacks including noise attacks, filtering attacks, partial occlusion attacks, or geometric transformation attacks to the watermarked image. Our simulation results demonstrated the capability of the proposed image-authentication technique.
2018-10-31T15:00:00Z
Perspective pinhole model with planar source for augmented reality surgical navigation based on C-arm imaging
Ha, Ho-Gun
Jeon, Sangseo
Lee, Seongpung
Choi, Hyunseok
Hong, Jaesung
http://hdl.handle.net/20.500.11750/9379
2022-11-16T11:10:13Z
2018-09-30T15:00:00Z
Title: Perspective pinhole model with planar source for augmented reality surgical navigation based on C-arm imaging
Author(s): Ha, Ho-Gun; Jeon, Sangseo; Lee, Seongpung; Choi, Hyunseok; Hong, Jaesung
Abstract: Purpose: For augmented reality surgical navigation based on C-arm imaging, accuracy of the overlaid augmented reality onto the X-ray image is imperative. However, overlay displacement is generated when a conventional pinhole model describing a geometric relationship of a normal camera is adopted for C-arm calibration. Thus, a modified model for C-arm calibration is proposed to reduce this displacement, which is essential for accurate surgical navigation. Method: Based on the analysis of displacement pattern generated for three-dimensional objects, we assumed that displacement originated by moving the X-ray source position according to the depth. In the proposed method, X-ray source movement was modeled as variable intrinsic parameters and represented in the pinhole model by replacing the point source with a planar source. Results: The improvement which represents a reduced displacement was verified by comparing overlay accuracy for augmented reality surgical navigation between the conventional and proposed methods. The proposed method achieved more accurate overlay on the X-ray image in spatial position as well as depth of the object volume. Conclusion: We validated that intrinsic parameters that describe the source position were dependent on depth for a three-dimensional object and showed that displacement can be reduced and become independent of depth by using the proposed planar source model. © 2018, CARS.
2018-09-30T15:00:00Z