• Journal of radiological science and technology
• /
• v.40 no.4
• /
• pp.533-542
• /
• 2017

In diagnostic radiology, the imaging system has been changed from film/screen to digital system. However, the method for removing scatter radiation such as anti-scatter grid has not kept pace with this change. Therefore, authors have devised the indirect flat panel detector (FPD) system with net-like lead in substrate layer which can remove the scattered radiation. In clinical context, there are many radiographic examinations with angulated incident X-ray. However, our proposed FPD has net-like lead foil so the vertical lead foil to the angulate incident X-ray would have bad effect on its performance. In this study, we identified the effect of vertical/horizontal lead foil component on the novel system's performance and improved the structure of novel system for clinical usage with angulated incident X-ray. Grid exposure factor and image contrast were calculated to investigate various structure of novel system using Monte Carlo simulation software when the incident X-ray was tilted ($0^{\circ}$, $15^{\circ}$, and $30^{\circ}$ from the detector plane). More photons were needed to obtain same image quality in the novel system with vertical lead foil only then the system with horizontal lead foil only. An optimal structure of novel system having different heights of its vertical and horizontal lead foil component showed improved performance compared with the novel system in a previous study. Therefore, the novel system will be useful in a clinical context with the angulated incident X-ray if the height and direction of lead foil in the substrate layer are optimized as the condition of conventional radiography.

• Journal of the Korean Vacuum Society
• /
• v.14 no.4
• /
• pp.252-257
• /
• 2005

A high-brightness electron beam source for a microfocus X-ray tube has been fabricated using a carbon-nanotube (CNT) field emitter. The electron source consists of cathode that includes a CNT field emitter, a beam-extracting grid, and an anode that accelerates that electron beam. The microfocus X-ray tube requires an electron beam with the diameter of less than 5 $\mu$m and beam current of higher than 30 $\mu$A at the position of the X-ray target. To satisfy the requirements, the geometries of the field emitter tips and the electrodes of the gun was optimized by calculating the electron trajectories and beam spatial profile with EGUN code. The CNT tips were fabricated with successive steps: a tungsten wire with the diameter of 200 $\mu$m was chemically etched and was subsequently coated with CNTs by chemical vapor deposition. The experiments of electron emission at the fabricated CNT tips were performed. The design characteristics and basic experimental results of the electron source are reported.

• Journal of the Korea Convergence Society
• /
• v.12 no.6
• /
• pp.9-16
• /
• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.