• Korean Journal of Community Nutrition
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• v.14 no.2
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• pp.229-235
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• 2009

This study was carried out to determine whether a short-term zinc supplementation could improve the zinc status without adverse changes in copper status among type 2 diabetic patients. Seventy-six diabetic subjects and 72 normal adults participated in this study. Subjects were randomly divided into supplemented and control groups. Forty-four diabetic patients and 34 normal subjects were supplemented with 50 mg zinc gluconate daily for 4 weeks. Dietary intakes of participants were measured for two non-consecutive days by 24-hour recall method. Nutritional status of zinc and copper were also evaluated by biochemical measurement of fasting plasma samples and spot urinary collection. At baseline, diabetic patients showed significantly lower levels of dietary zinc intake and higher urinary zinc excretion than the normal adult group(p<0.05, p<0.0001). Plasma level of zinc was not significantly different between diabetic and normal adults at baseline. However, plasma zinc level increased significantly in both diabetic patients and normal adults after zinc supplementation. The changes in plasma copper levels following zinc supplementation were not statistically significant in diabetic subjects as well as in normal adults. These results indicated that four weeks of zinc supplementation did not influence Cu status and that it may contribute to improving the zinc status. Therefore, we suggest that Zn supplementation for a short-term period may improve marginal zinc status of diabetic patients without interfering with their copper status

• Korean Journal of Chemical Engineering
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• v.35 no.12
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• pp.2496-2503
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• 2018

The short-term stability of high efficiency polymer : nonfullerene solar cells was investigated by employing a quick (ten cycles) current density-voltage (J-V) cycling method. Polymer : nonfullerene solar cells with initial power conversion efficiency (PCE) of >10% were fabricated using bulk heterojunction (BHJ) films of poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)-benzo[1,2-b:4,5b']dithiophene))-alt-(5,5-(1',3'-di-2-thienyl-5,7'-bis(2-ethylhexyl)benzo[1',2'-c:4',5'-c']dithiophene-4,8-dione))] (PBDB-T) and 3,9-bis(2-methylene-((3-(1,1-dicyanomethylene)-6/7-methyl)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (IT-M). One set of the BHJ (PBDB-T : IT-M) films was thermally annealed at $160^{\circ}C$ for 30min, while another set was used without any thermal treatment after spin-coating. The quick J-V scan (cycling) measurement disclosed that the PCE decay was relatively slower for the annealed BHJ layers than the unannealed (as-cast) BHJ layers. As a result, after ten cycles, the annealed BHJ layers delivered higher PCE than the unannealed BHJ layers due to higher and more stable trend in fill factor. The present quick J-V cycling method is simple but expected to be useful for the prediction of short-term stability in organic solar cells.

• Safety and Health at Work
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• v.13 no.2
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• pp.227-234
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• 2022

Background and Purpose: In 2021, lung cancer in school food workers was first recognized as an occupational cancer. The classification of the carcinogenicity of cooking fumes by International Agency for Research on Cancer (IARC) was based on Chinese epidemiological data. This study aimed to determine the hazard levels of school cooking fumes in Korea. Materials and Methods: Based on public school cafeterias in one area, 25 locations were selected for the survey according to the number per school type, ventilation states, and environmental pre-assessments of cafeterias. Two inside cooking areas using a heat source and one outside cooking area were selected as control measurement points. Measurements of CO, CO₂, polycyclic aromatic hydrocarbons (PAHs), and total volatile organic compounds (TVOCs), including benzene, formaldehyde, and particulate matter (PM10, PM2.5, PM1, respectively), were taken. The concentrations and patterns of each substance in the kitchens were compared with the outdoor air quality. Result: Known carcinogens, such as the concentrations of PAHs, formaldehyde, TVOC (benzene), and particulate matter in school cooking fumes, were all detected at similar or slightly higher levels than those found outside. Additionally, substances were detected at relatively low concentrations compared to the Chinese cooking fumes reported in the literature. However, the short-term exposure to high concentrations of CO (or composite exposure with CO₂) and PM2.5 in this study were shown. Conclusion: The school cooking fumes in South Korea was a relatively less harmful than Chinese cooking fumes, however short-term, high exposure of toxic substances can cause a critical health effect.

• Smart Media Journal
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• v.12 no.11
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• pp.134-144
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• 2023

Nowadays, Deep Learning (DL) technology is being used in several government departments. South Korea imports a lot of seafood. If the demand for fishery products is not accurately predicted, then there will be a shortage of fishery products and the price of the fishery product may rise sharply. So, South Korea's Ministry of Ocean and Fisheries is attempting to accurately predict seafood imports using deep learning. This paper introduces the solution for the fish import prediction in South Korea using the Long Short-Term Memory (LSTM) method. It was found that there was a huge gap between the sum of consumption and export against the sum of production especially in the case of two species that are Hairtail and Pollock. An import prediction is suggested in this research to fill the gap with some advanced Deep Learning methods. This research focuses on import prediction using Machine Learning (ML) and Deep Learning methods to predict the import amount more precisely. For the prediction, two Deep Learning methods were chosen which are Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). Moreover, the Machine Learning method was also selected for the comparison between the DL and ML. Root Mean Square Error (RMSE) was selected for the error measurement which shows the difference between the predicted and actual values. The results obtained were compared with the average RMSE scores and in terms of percentage. It was found that the LSTM has the lowest RMSE score which showed the prediction with higher accuracy. Meanwhile, ML's RMSE score was higher which shows lower accuracy in prediction. Moreover, Google Trend Search data was used as a new feature to find its impact on prediction outcomes. It was found that it had a positive impact on results as the RMSE values were lowered, increasing the accuracy of the prediction.

• Journal of Dental Anesthesia and Pain Medicine
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• v.22 no.2
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• pp.129-143
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• 2022

Background: Patient-controlled analgesia (PCA) has been widely used as an effective medical treatment for pain and for postoperative analgesia. However, improper dose errors in intravenous (IV) administration of narcotic analgesics from a PCA infusion pump can cause patient harm. Furthermore, opioid overdose is considered one of the highest risk factors for patients receiving pain medications. Therefore, accurate delivery of opioid analgesics is a critical function of PCA infusion pumps. Methods: We designed a microbalance method that consisted of a closed acrylic chamber containing a layer and an oil layer with an electronic balance. A commercially available infusion analyzer (IDA-5, Fluke Co., Everett, WA, USA) was used to measure the accuracy of the infusion flow rate from a commercially available smart PCA infusion pump (PS-1000, UNIMEDICS, Co., Ltd., Seoul, Korea) and compared with the results of the microbalance method. We evaluated the uncertainty of the flow rate measurement using the ISO guide (GUM:1995 part3). The battery life, delay time of the occlusion alarm, and bolus function of the PCA pump were also tested. Results: The microbalance method was good in the short-term 2 h measurement, and IDA-5 was good in the long-term 24 h measurement. The two measurement systems can complement each other in the case of the measurement time. Regarding battery performance, PS-1000 lasted approximately 5 days in a 1 ml/hr flow rate condition without recharging the battery. The occlusion pressure alarm delays of PS-1000 satisfied the conventional alarm threshold of occlusion pressure (300-800 mmHg). Average accuracy bolus volume was measured as 63%, 95%, and 98.5% with 0.1 ml, 1 ml, and 2 ml bolus volume presets, respectively. A 1 ml/hr flow rate measurement was evaluated as 2.08% of expanded uncertainty, with a 95% confidence level. Conclusion: PS-1000 showed a flow accuracy to be within the infusion pump standard, which is ± 5% of flow accuracy. Occlusion alarm of PS-1000 was quickly transmitted, resulting in better safety for patients receiving IV infusion of opioids. PS-1000 is sufficient for a portable smart PCA infusion pump.

• Journal of the korean society of oceanography
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• v.37 no.4
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• pp.224-231
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• 2002

Vertical distributions of coprostanol (5$\beta$-cholestan-3$\beta$-ol) and other sterols were investigated in the intertidal sediment of Shinbul island in the Han River estuary to estimate the short-term variations of fecal contamination in association with reclamation activity which caused a construction of tidal barrier and emigration of residents from the island. Quantitative contributions of coprostanol in total sterol (9.87-15.84%) and in total organic carbon (82.0-157.7 $\mu\textrm{g}$ g$^{-1}$ OC) implied that a substantial amount of organic matter associated with fecal pollutants was introduced into the sediment. The highest contribution of coprostanol to organic carbon that was observed between 0.3-0.9 cm depth seemed to be associated with increased human activities for the reclamation project of the island. The ratio of coprostanol to organic carbon decreased within 0.3 cm depth, which indicated decreased fecal contamination after the emigration of residents from the island. The results suggested that measurement of coprostanol could relevantly reflect short-term fluctuation of fecal contamination in the sediment of the Han River estuary.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.291-296
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• 2016

The ideal chemical sensor must show the similar result under the same condition for accurate measurement of gases regardless of time. However, the actual responses of chemical sensors have been shown the lacks of repeatability and reproducibility because of the drift which has been caused by aging and pollution of the sensor and the environment change such as temperature and humidity. If the problems are not properly taken into considerations, the stability and reliability of the system using chemical sensors would be decreased. In this paper, we analyzed the sensor's drift and applied the three different compensation methods(DWT( Discrete Wavelets Transform), Baseline Manipulation, Internal Normalization) for reducing the effects of the drift in order to improve the stability and the reliability of short term of the chemical sensors. And in order to compare the results of the methods, the standard deviation was used as a criterion. The sensor drift was analyzed by a trend line graph. We applied the three methods to the successive data measured for three days and compared the results. As a result of comparison, the standard deviation of DWT showed lowest value. (Before compensation: 7.1219, DWT: 1.3644, Baseline Manipulation: 2.5209, Internal Normalization: 3.1425).

• Journal of Korean Academy of Nursing
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• v.42 no.7
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• pp.1062-1069
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• 2012

Purpose: Meager research has been carried out to determine the effectiveness of the token economy among patients behaving violently in mental hospitals. The purpose of this study was to examine the effectiveness of the Short-Term Token Economy (STTE) on violent behavior among chronic psychiatric in-patients. Methods: A nonequivalent control group design method was utilized. Participants in an experimental group (n=22) and control group (n=22) took part in this study from January to April, 2008. Observation on aggressive behavior among male in-patients in one hospital as a baseline was made during the week before the behavior modification program and measurement of aggressive behavior was done using the Overt Aggression Scale (OAS), which includes verbal attacks, property damage and physical attacks. Results: The aggressive behavior scores of the experimental group decreased, those of the control group, scores showed an increase after the eight-week behavior modification program utilizing STTE. Conclusion: The results of the study indicate that STTE is effective in reducing the incidence of aggressive behavior among male in-patients in psychiatric hospitals. The outcome of this study should be helpful in reducing the use of coercive measures or psychoactive medication in controlling the violent behavior among in-patients in hospitals.

• Fibers and Polymers
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• v.6 no.1
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• pp.66-71
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• 2005

The surface evenness and texture are closely related with the irregularity of yam thickness. Besides, yam thickness variation has an important role to influence the yam performance and the textile process efficiency. Thus, the information not only on the yam thickness, but also on the short- term irregular characteristics that have not been known before is required for enhancing the qualities of textile products. This paper reports the results of a study about the yam thickness and its variation for various types of yam on the basis of a new measurement system applying a laser slit beam as a light source. The new method delivers effective information on the irregularity. The analysis of the measured signal confirms that the visual shade created by the yam doubling and twisting can be measured and the yam thickness characteristics can be represented by corre­lograms. Depending on yam types, correlograms have different shapes and can be approximated to an exponentially decaying function with or without fluctuating magnitude. In addition, the effective information on the yam irregularity can be influ­enced by the sampling length interval of the measuring device used for tests.

• Smart Structures and Systems
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• v.29 no.4
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• pp.599-616
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• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.