arXiv subjects

Seonghyeok Jang

Publications and source records attributed to Seonghyeok Jang.

3 recordsLinked to original sources

arXiv2024

νOscillation: a software package for computation and simulation of neutrino propagation and interaction

The behavior of neutrinos is the only phenomenon that cannot be explained by the standard model of particle physics. Because of these mysterious neutrino interactions observed in nature, at present, there is growing interest in this field and ongoing or planned neutrino experiments are seeking solutions to this mystery very actively. The design of neutrino experiments and the analysis of neutrino data rely on precise computations of neutrino oscillations and scattering processes in general. Motivated by this, we developed a software package that calculates neutrino production and oscillation in nuclear reactors, neutrino-electron scattering of solar neutrinos, and the oscillation of neutrinos from radioactive isotopes for the search of sterile neutrinos. This software package is validated by reproducing the result of calculations and observations in other publications. We also demonstrate the feasibility of this package by calculating the sensitivity of a liquid scintillator detector, currently in planning, to the sterile neutrinos. This work is expected to be used in designs of future neutrino experiments.

hep-ex↗

arXiv2024

SAM: Semi-Active Mechanism for Extensible Continuum Manipulator and Real-time Hysteresis Compensation Control Algorithm

Cable-Driven Continuum Manipulators (CDCMs) enable scar-free procedures but face limitations in workspace and control accuracy due to hysteresis. We introduce an extensible CDCM with a Semi-active Mechanism (SAM) and develop a real-time hysteresis compensation control algorithm using a Temporal Convolutional Network (TCN) based on data collected from fiducial markers and RGBD sensing. Performance validation shows the proposed controller significantly reduces hysteresis by up to 69.5% in random trajectory tracking test and approximately 26% in the box pointing task. The SAM mechanism enables access to various lesions without damaging surrounding tissues. The proposed controller with TCN-based compensation effectively predicts hysteresis behavior and minimizes position and joint angle errors in real-time, which has the potential to enhance surgical task performance.

cs.RO↗

arXiv2024

Hysteresis Compensation of Flexible Continuum Manipulator using RGBD Sensing and Temporal Convolutional Network

Flexible continuum manipulators are valued for minimally invasive surgery, offering access to confined spaces through nonlinear paths. However, cable-driven manipulators face control difficulties due to hysteresis from cabling effects such as friction, elongation, and coupling. These effects are difficult to model due to nonlinearity and the difficulties become even more evident when dealing with long and coupled, multi-segmented manipulator. This paper proposes a data-driven approach based on Deep Neural Networks (DNN) to capture these nonlinear and previous states-dependent characteristics of cable actuation. We collect physical joint configurations according to command joint configurations using RGBD sensing and 7 fiducial markers to model the hysteresis of the proposed manipulator. Result on a study comparing the estimation performance of four DNN models show that the Temporal Convolution Network (TCN) demonstrates the highest predictive capability. Leveraging trained TCNs, we build a control algorithm to compensate for hysteresis. Tracking tests in task space using unseen trajectories show that the proposed control algorithm reduces the average position and orientation error by 61.39% (from 13.7mm to 5.29 mm) and 64.04% (from 31.17° to 11.21°), respectively. This result implies that the proposed calibrated controller effectively reaches the desired configurations by estimating the hysteresis of the manipulator. Applying this method in real surgical scenarios has the potential to enhance control precision and improve surgical performance.

cs.RO↗