• Journal of Radiation Protection and Research
• /
• v.20 no.2
• /
• pp.129-136
• /
• 1995

In spite of the prescriptions on the reference X-ray fields given by the International Organization of Strandard(ISO) and American National Standard Institute(ANSI), the measurement of X-ray spectrum is not only time consuming but very difficult, paticularly when significant corrections have to be applied to the measured pulse-height distributions of the observed spectra. This paper describes the calculation method of ISO Narrow Series and ANSI X-ray filtered radiations by theoretical model which is modified framer's theory by target attenuation and backscatter correction. The X-ray spectra, average energies and conversion coefficients are calculated and compared with those obtained using the spectra prescribed by ISO and AMSI to assure good agreement.

• Korean Journal of Food Science and Technology
• /
• v.48 no.5
• /
• pp.418-423
• /
• 2016

This study was conducted to identify the geographical origin of soybeans in Cheonggukjang by analyzing its organic components and inorganic elements with Fourier transform near-infrared spectroscopy (FT-NIRS) and with energy dispersive X-ray fluorescence (ED-XRF) coupled with multivariate statistical analysis. For method development, 280 samples from various regions were collected and analyzed. The discriminant accuracy for the developed methods was 97.5% for FT-NIRS and 98.0% for ED-XRF with multivariate statistical analysis. A validation test confirmed the discriminant accuracy to be 96.3% for FT-NIRS and 95.0% for ED-XRF. Overall, the results showed that methods using FT-NIRS and ED-XRF could be used to identify the geographical origin of Cheonggukjang.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.35 no.3
• /
• pp.223-231
• /
• 2022

Spectroscopies are the most widely used for understanding the crystallographic, chemical, and physical aspects of materials; therefore, numerous commercial and non-commercial software have been introduced to help researchers better handling their spectroscopic data. However, not many researchers, especially early-stage ones, have a proper background knowledge on the choice of fitting functions and a technique for actual fitting, although the essence of such data analysis is peak fitting. In this regard, we present a practical guide for peak fitting for data analysis. We start with a basic-level theoretical background why and how a certain protocol for peak fitting works, followed by a step-by-step visualized demonstration how an actual fitting is performed. We expect that this contribution is sure to help many active researchers in the discipline of materials science better handle their spectroscopic data.

• Journal of the Korean Society of Radiology
• /
• v.16 no.3
• /
• pp.303-308
• /
• 2022

Mammography using X-rays is currently the most used for early diagnosis of breast cancer. As the frequency of use of X-ray devices increases, interest in radiation hazards caused by mammography is increasing. Therefore, in this study, in order to measure the exposure dose of the mammary gland in X-ray mammography that requires high contrast and high resolution, the international Atomic Energy Agency (IAEA) stipulates the international standards presented by IEC 62220-1-2: 2015. Based on the beam quality criteria of the recommendation, we tried to present a guideline for evaluating the average mammary gland dose. As a result, the average streamline dose value of the 4.5 cm PMMA phantom was 2.3 mGy at the maximum within the 30 kV range, and was evaluated to be 1.19 mGy based on 28 kV.

• Journal of the Korean Society of Radiology
• /
• v.85 no.4
• /
• pp.693-704
• /
• 2024

Artificial intelligence (AI) technology is actively being applied for the interpretation of medical imaging, such as chest X-rays. AI-based software medical devices, which automatically detect various types of abnormal findings in chest X-ray images to assist physicians in their interpretation, are actively being commercialized and clinically implemented in Korea. Several important issues need to be considered for AI-based detection assistant tools to be applied in clinical practice: the evaluation of performance and efficacy prior to implementation; the determination of the target application, range, and method of delivering results; and monitoring after implementation and legal liability issues. Appropriate decision making regarding these devices based on the situation in each institution is necessary. Radiologists must be engaged as medical assessment experts using the software for these devices as well as in medical image interpretation to ensure the safe and efficient implementation and operation of AI-based detection assistant tools.

• Journal of the Korean Society of Radiology
• /
• v.11 no.7
• /
• pp.547-553
• /
• 2017

In the current medical field, lead is widely used as a radiation shield. However, the lead weight is very heavy, so wearing protective clothing such as apron is difficult to wear for long periods of time and there is a problem with the danger of lethal toxicity in humans. Recently, many studies have been conducted to develop substitute materials of lead to resolve these problems. As a substitute materials for lead, barium(Ba) and iodine(I) have excellent shielding ability. But, It has characteristics emitting characteristic X-rays from the energy area near 30 keV. For patients or radiation workers, shielding materials is often made into contact with the human body. Therefore, the characteristic X-rays generated by the shielding material are directly exposured in the human body, which increases the risk of increasing radiation absorbed dose. In this study, we have developed the FLUKA transport code, one of the most suitable elements of radiation transport codes, to remove the characteristic X-rays generated by barium or iodine. We have verified the reliability of the shielding fraction of the structure of the structure shielding by comparing with the MCPDX simulations conducted as a prior study. Using the MCNPX and FLUKA, the double layer shielding structures with the various thickness combination consisting of barium sulphate ($BaSO_4$) and bismuth oxide($Bi_2O_3$) are designed. The accuracy of the type shown in IEC 61331-1 was geometrically identical to the simulation. In addition, the transmission spectrum and absorbed dose of the shielding material for the successive x-rays of 120 kVp spectra were compared with lead. In results, $0.3mm-BaSO_4/0.3mm-Bi_2O_3$ and $0.1mm-BaSO_4/0.5mm-Bi_2O_3$ structures have been absorbed in both 33 keV and 37 keV characteristic X-rays. In addition, for high-energy X-rays greater than 90 keV, the shielding efficiency was shown close to lead. Also, the transport code of the FLUKA's photon transport code was showed cut-off on low-energy X-rays(below 33keV) and is limited to computerized X-rays of the low-energy X-rays. But, In high-energy areas above 40 keV, the relative error with MCNPX was found to be highly reliable within 6 %.

• Journal of the Korean Society of Radiology
• /
• v.14 no.6
• /
• pp.773-780
• /
• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.71-77
• /
• 2005

On contraction of the muscles, marked changes in X-ray reflections are observed, suggesting that conformational changes of contractile molecules and the movement of myosin heads during muscle contraction. It was found that the successive twitches decreased not only the time needed to the peak tension after the onset of stimulation but also the time needed to the maximum change of the X-ray intensity. However, the difference of the time between the peak tension and the maximum intensity change$(T_i-I_i)$ is nearly the same at any twitch.

• Journal of Energy Engineering
• /
• v.23 no.3
• /
• pp.13-16
• /
• 2014

We have surveyed on significant progress in recent developments of accelerator-based pulsed X-ray sources has offered the opportunity for time-resolved studies on fast structure dynamics on the nanometer scale. The required and currently available techniques for time resolved X-ray diffraction measurements using the third-generation synchrotron radiation sources are summarized. Ultrafast X-ray experimental techniques are discussed for femtosecond studies at future synchrotron radiation sources.

• Journal of the Korean Chemical Society
• /
• v.42 no.6
• /
• pp.638-645
• /
• 1998

By using the spray pyrolysis method, zinc oxide(ZnO) was produced from zinc acetate, the surface morphology of the prepared films was investigated by using scanning electron microscopy. The thickness of ZnO thin film was increased up to 460$^{\circ}C$ and it was 833 nm. The maximum wavelength of absorption was obtained at 365 nm, and the maximum peak of fluorescence at 475 nm and 505 nm. ZnO film have been characterized by XPS, XRD, and SEM. XRD results show that all the films are preferred orientation along the (002) plane which is depend on the substrate temperature. The optimal temperature to produce ZnO was determined at around 460$^{\circ}C$ from measurements of XPS, XRD and photocurrent. It was also shown that the homogeneous particles had the higher photocurrent.