• Korean Journal of Materials Research
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• v.29 no.5
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• pp.336-341
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• 2019

The gas adsorption isotherm requires accurate measurement for the analysis of porous materials and is used as an index of surface area, pore distribution, and adsorption amount of gas. Basically, adsorption isotherms of porous materials are measured conventionally at 77K and 87K using liquid nitrogen and liquid argon. The cold volume calibration in this conventional method is done simply by splitting a sample cell into two zones (cold and warm volumes) by controlling the level sensor in a Dewar filled with liquid nitrogen or argon. As a result, BET measurement for textural properties is mainly limited to liquefied gases (i.e. $N_2$ or Ar) at atmospheric pressure. In order to independently investigate other gases (e.g. hydrogen isotopes) at cryogenic temperature, a novel temperature control system in the sample cell is required, and consequently cold volume calibration at various temperatures becomes more important. In this study, a cryocooler system is installed in a commercially available BET device to control the sample cell temperature, and the automated cold volume calibration method of temperature variation is introduced. This developed calibration method presents a reliable and reproducible method of cryogenic measurement for hydrogen isotope separation in porous materials, and also provides large flexibility for evaluating various other gases at various temperature.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.47-53
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• 2021

The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.140-147
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• 2021

EEG(electroencephalogram) are measured to accurately determine the level of sleep in various sleep examinations. In general, measurements are more accurate as the number of sensor channels increases. EEG can interfere with sleep by attaching electrodes to the skin when measuring. It is necessary for self sleep care to select the minimum number of EEG channels that take into account both the user's discomfort and the accuracy of the measurement data. In this paper, we proposed a sleep stage analysis model based on machine learning and conducted experiments for using from one channel to four channels. We obtained estimation accuracy for sleep stage as following 82.28% for one channel, 85.77% for two channels, 80.33% for three channels and 68.87% for four channels. Although the measurement location is limited, the results of this study compare the accuracy according to the number of channels and provide information on the selection of channel numbers in the EEG sleep analysis.

• Animal Bioscience
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• v.34 no.10
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• pp.1717-1722
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• 2021

Objective: Stroking calves during the postnatal period could effectively improve human-calf relationships. The objective of this study is to examine how daily calf stroking frequency during the postnatal period affects the establishment of human-calf relationships. Methods: Six calves were stroked by a trainer for 6 minutes once daily for 5 days after birth (D1). Six calves were stroked by a trainer for 3 minutes twice daily for 5 days after birth (D2). A further four calves were stared at but not stroked as the control group. The overall stroking or staring duration was the same for all groups, at 6 min/d and 30 min over 5 days. The tests for reactions to the stationary trainer in an unfamiliar environment and avoidance distance measurements for an approaching trainer were conducted at 1 month and 3 months after the treatment. Results: Calves in both stroking groups approached significantly closer to the stationary trainer, vocalized less, and looked at the trainer shorter than the control group at 1 month. However, at 3 months, there was no significant difference between the D1 and the control group, whereas the D2 approached significantly closer to the trainer and vocalized less, and looked at the trainer for a shorter time than the control group. For the avoidance distance, the trainer could approach closer to both stroking groups than the control at 1 month, however, there was no difference among groups at 3 months. Conclusion: Our results suggested that the difference in the calf stroking procedure affected the established human-calf relationships, even though the total stroking duration was the same for all stroked calves. It is likely to be more effective to stroke more frequently than intensively when the aim is to establish better human-calf relationships within limited labor time.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.1-8
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• 2022

Elevators are the main means of transport in buildings. A malfunction of an elevator in operation may cause in convenience to users. Furthermore, fatal accidents, such as injuries and death, may occur to the passengers also. Therefore, it is important to prevent failure before accidents happen. In related studies, preventive measures are proposed through analyzing failures, and the lifespan of elevator components. However, these methods are limited to existing an elevator model and its surroundings, including operating conditions and installed environments. Vibration occurs when the elevator is operated. Experts have classified types of faults, which are symptoms for malfunctions (failures), via analyzing vibration. This study proposes an artificial intelligent model for classifying faults automatically with deep learning algorithms through elevator vibration data, hereby preventing failures before they occur. In this study, the vibration data of six elevators are collected. The proposed methodology in this paper removes "the measurement error data" with incorrect measurements and extracts operating sections from the input datasets for proceeding deep learning models. As a result of comparing the performance of training five deep learning models, the maximum performance indicates Accuracy 97% and F1 Score 97%, respectively. This paper presents an artificial intelligent model for detecting elevator fault automatically. The users' safety and convenience may increase by detecting fault prior to the fatal malfunctions. In addition, it is possible to reduce manpower and time by assisting experts who have previously classified faults.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.322-323
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• 2002

Partial volume averaging effect of PET data influences on the accuracy of quantitative measurements of regional brain metabolism because spatial resolution of PET is limited. The purpose of this study was to evaluate the accuracy of partial volume correction carried out on $^{18}$ F-PET images using Hoffman brain phantom. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices of the same phantom. All the MR slices of the phantom were then segmented to be binary images. Each of these binary images was convolved in 2 dimensions with the spatial resolution of the PET. The original PET images were then divided by the smoothed binary images in slice-by-slice, voxel-by-voxel basis resulting in larger PET image volume in size. This enlarged partial volume corrected PET image volume was multiplied by original binary image volume to exclude extracortical region. The evaluation of partial volume corrected PET image volume was performed by region of interests (ROI) analysis applying ROIs, which were drawn on cortical regions of the original MR image slices, to corrected and original PET image volume. From the ROI analysis, range of regional mean values increases of partial volume corrected PET images was 4 to 14%, and average increase for all the ROIs was about 10% in this phantom study. Hoffman brain phantom study was useful for the objective evaluation of the partial volume correction method. This MR-based correction method would be applicable to patients in the. quantitative analysis of FDG-PET studies.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.2
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• pp.68-74
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• 2023

Objectives: Drug holidays are suggested to reduce the formation of osteonecrosis in patients under intravenous (IV) bisphosphonates (BPs) therapy. The objectives of this study are to evaluate the incidence of medication-related osteonecrosis of the jaw (MRONJ) following tooth extraction in cancer patients using IV BP, and to assess the effect of drug holiday on the development of MRONJ. Patients and Methods: A manuel search of the patient folders of Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Hacettepe University was undertaken to identify cancer patients who used IV BPs and had at least one tooth extraction between 2012 and 2022. Patents' age, sex, systemic condition, the type of BP used, duration of BP used, number of tooth extraction, duration of drug holiday, localization of tooth extraction and incidence of MRONJ were recorded. Results: One hundred nine teeth were removed from 57 jaws in 51 patients. All tooth extractions were performed under perioperative antibiotic prophylaxis and with primary wound closure. The incidence of MRONJ was 5.3%. Stage 1 MRONJ developed in 3 patients (only one had a drug holiday). The median duration of drug holiday was 2 months. No significant difference between the patients with and without a drug holiday and MRONJ development was found (P=0.315). The mean age of patients developed MRONJ was 40.33±8.08 years. A statistically significant difference was found between age and MRONJ development (P=0.002). Conclusion: The effect of a short-term drug holiday on the development of MRONJ may be limited because BPs remain in bone tissue for a long time. Drug holidays should be applied with the approval of an oncologist with other preventive measurements.

• Korean Journal of Community Nutrition
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• v.28 no.2
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• pp.141-159
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• 2023

Objectives: This study aimed to determine whether a mobile health (mhealth) intervention is effective in reducing weight and changing dietary behavior among employees with overweight and obesity. The study also investigated whether engagement with the intervention affected its effectiveness. Methods: The intervention involved the use of a dietary coaching app, a wearable device for monitoring physical activity and body composition, and a messenger app for communicating with participants and an intervention manager. A total of 235 employees were recruited for a 12-week intervention from eight workplaces in Korea. Questionnaire surveys, anthropometric measurements, and 24-h dietary recalls were conducted at baseline and after the intervention. Results: After the intervention, significant decreases in the mean body weight, body mass index, body fat percentage, and waist circumference were observed. Furthermore, the consumption frequencies of multigrain rice and legumes significantly increased, whereas those of pork belly, instant noodles, processed meat, carbonated beverages, and fast food significantly decreased compared with those at baseline. The mean dietary intake of energy and most nutrients also decreased after the intervention. When the participants were categorized into three groups according to their engagement level, significant differences in anthropometric data, dietary behaviors, and energy intake were observed following the intervention, although there were no differences at baseline, indicating that higher engagement level led to greater improvements in weight loss and dietary behavior. Conclusions: The intervention had positive effects on weight loss and dietary behavior changes, particularly among employees with higher engagement levels. These results indicate the importance of increasing the level of engagement in the intervention to enhance its effectiveness. The mhealth intervention is a promising model for health promotion for busy workers with limited time.

• Journal of Korean Public Health Nursing
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• v.37 no.1
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• pp.5-24
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• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.