The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).
The study is to develop specific strategies to prevent adolescents' depression, early detection and intervention services. This study was a descriptive research study with the purpose of predictors of protective factors for depression in adolescent using decision making tree analysis. The subjects for the study were 485 student in G city. This study collected data between September 23, 2013 and September 26, 2013 and analyzed them with frequency analysis, percentage, the mean and standard deviation, ${\chi}^2$-test, t-test, and a decision-making tree by using SPSS 20.0 program. From the data analysis, the predictive model for protective factors related to depression in adolescent with 4 pathways, 12 nodes. The common predicting variables of depression in adolescent were characteristics, family cohesion, parent adolescent communication, peer communication. The specialty of training data and test data was 76.0% and 65.4%. The sensitivity of training data was 78.2% and 63.7%. As for the classification accuracy, training data and test data explained 70.1% and 69.7%. Parent adolescent communication and peer communication to decrease depression of Korean middle and high school students are necessary. This study should contribute as baseline data for intervention strategies and planning ability of depression prevention in adolescents.
Kim, Eun-Sook;Lee, Ji-Sun;Park, Go-Eun;Lim, Jong-Hwan
Journal of Korean Society of Forest Science
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v.108
no.1
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pp.10-20
/
2019
The purpose of this study is to identify the long-term area changes in the subalpine coniferous forests in Korea in order to understand the changes in the subalpine forest ecosystems vulnerable to climate change. We analyzed 20 years of time-series Landsat satellite images (mid 1990s, mid 2010s) for change detection of coniferous forests and compared with the long term changes of climate information to identify their relationship in the study area. As a result, the area of coniferous forests in the study region decreased by 25% over 20 years. The regions with largest changes are Seoraksan, Baegunsan-Hambaeksan-Jangsan, Jirisan, and Hallasan. The region with the largest decrease in area was Baegunsan (reduced area: 542 ha), and the region with large decrease in area and the largest rate of decrease was Hallasan (rate of decrease: 33.3%). As the Jeju region has the most rapid temperature rise, it is projected that Hallasan is the most vulnerable forest ecosystem affected by climate change. The result of this study shows that from a long-term perspective the overall coniferous forests in the subalpine region are declining, but the trend varies in each region. This national and long-term information on the change of coniferous forests in the subalpine region can be utilized as baseline data for the detailed survey of endangered subalpine coniferous trees in the future.
As coastal erosion of the east coast is accelerating, the need for scientific and quantitative coastal erosion monitoring technology for a wide area increases. The traditional method for observing changes in the coast was precision monitoring based on field surveys, but it can only be applied to a small area. The airborne bathymetric Light Detection And Ranging (LiDAR) system is a technology that enables economical surveying of coastal and seabed topography in a wide area. In particular, it has the advantage of constructing topographical data for the intertidal zone, which is a major area of interest for coastal erosion monitoring. In this study, time series analysis of coastal seabed topography acquired in Aug, 2021 and Mar. 2022 on the littoral cell GW36 in Gangwon was performed using the Seahawk Airborne Bathymetric LiDAR (ABL) system. We quantitatively monitored the topographical changes by measuring the baseline length, shoreline and Digital Terrain Model (DTM) changes. Through this, the effectiveness of the ABL surveying technique was confirmed in coastal erosion monitoring.
This study performed a trichlorfon (TCF) residue and pharmacokinetic analysis with Japanese eels, Anguilla japonica, to obtain baseline data to establish the maximum residue level (MRL) of TCF in A. japonica. After dipping A. japonica in 30 ppm and 150 ppm of TCF at 28℃ and 18℃, drug residue in the body was analyzed with LC-MS/MS, and these results were further analyzed with the PK solver program to obtain the pharmacokinetic parameters of TCF in the serum, muscles, and liver. The maximum concentrations (Cmax) in the serum, muscles, and liver were 25.87-357.42, 129.91-1043.73, and 40.47-375.20, respectively, and the time to maximum concentration (Tmax) was 0.13-1.32h, 1.17-3.34h, and 0.14-5.40h, respectively. The terminal elimination half-life (T1/2) was 2.13-3.92h, 5.30-10.35h, and 0.65-13.81h, respectively. In the 30 mg/L concentration group, TCF was not detected in the serum of eels 96 hours after bathing, and was below the detection limit after 336 hours in muscle and liver. On the other hand, in the 150 mg/L concentration group, TCF was not detected in the serum of eels 336 hours after bathing, but was detected in muscle and liver at 336 hours. In conclusion, the results of this study would be useful in establishing the MRL of TCF in farmed A. japonica.
International conference on construction engineering and project management
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2009.05a
/
pp.30-31
/
2009
Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.
Park, Hye-Suk;Kim, Hee-Joung;Lee, Chang-Lae;Cho, Hyo-Min;Yu, A-Ram
Progress in Medical Physics
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v.20
no.1
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pp.21-29
/
2009
Breast cancer is the most common form of cancer among korean woman. Therefore, the early detection activities of breast cancer such as breast self-examinations, clinical breast examinations, mammography are important. A yearly mammography examination has been recommended for women aged 40 and older for the early detection of breast cancer in asymptomatic periods. However, the glandular tissue of breast is the most radiation-sensitive tissue, and the determination of average glandular dose (AGD) forms an important part of the quality control of the mammographic systems. Because of the difficulty of estimating AGD directly, it is often estimated from the measurements of the incident air kerma and by applying the appropriate conversion factors. The primary objective of this study was to standardize the method of measuring AGD. The secondary objective was to evaluate the relationships between AGD per various composition and thickness of the breast using Monte Carlo simulations. As a result, we standardized the method of measuring AGD according to International Atomic Energy Agency (IAEA) guidelines (CoP: an international code of practice). Overall, AGD for mammographic practice in Korea was less than 3.0 mGy recommended by the Korea Food and Drug Adminstration (KFDA) protocol, and Korean Institute for Accreditation of Medical Image (KIAMI). The measured and simulated AGD for a given condition were calculated as 1.7 and 1.6 mGy, respectively. For the AGDs obtained, there was no significant difference between them. The simulated AGD was dependent on the fraction of glandular tissue of the breast. The AGD increases with increasing of the breast glandularity due to increasing absorption of low energy photons. The AGD also increases as a function of breast thickness. In conclusion, the results of this study could be used as a baseline to establish a reference level of radiation dose in mammography.
Kim, Dae-Hyun;Yoo, Jung-Ah;Suh, Myung-Rang;Bae, Jin-Ho;Jeong, Shin-Young;Ahn, Byeong-Cheol;Lee, Kyu-Bo;Lee, Jae-Tae
The Korean Journal of Nuclear Medicine
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v.38
no.1
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pp.85-98
/
2004
Purpose: Cellular uptake of $^{99}mTc$-sestamibi (MIBI) and $^{99}mTc$-tetrofosmin (TF) is low in cancer cells expressing multidrug resistance(MDR) by p-glycoprotein(Pgp) or multidrug related protein(MRP). Verapamil is known to increase cellular uptake of MIBI in MDR cancer cells, but is recently reported to have different effects on tracer uptake in certain cancer cells. This study was prepared to evaluate effects of verapamil on cellular uptake of MIBI and TF in several cancer cells. Materials and Methods: Celluar uptakes of Tc-99m MIBI and TF were measured in erythroleukermia K562 cell, breast cancer MCF7 cell, and human ovarian cancer SK-OV-3 cells, and data were compared with those of doxorubicin-resistant K562(Ad) cells. RT-PCR and Western blot analysis were used for the detection of mdr1 mRNA and Pgp expression, and to observe changes in isotypes of PKC enzyme. Effects of verapamil on MIBI and TF uptake were evaluated at different concentrations upto $200{\mu}M\;at\;1{\times}10^6\;cells/ml\;at\;37^{\circ}C$. Radioactivity in supernatant and pellet was measured with gamma counter to calculate cellular uptake ratio. Toxicity of verapamil was measured with MTT assay. Results: Cellular uptakes of MIBI and TF were increased by time in four cancer cells studied. Co-incubation with verapamil resulted in an increase in uptake of MIBI and TF in K562(Adr) cell at a concentration of $100{\mu}M$ and the maximal increase at $50{\mu}M$ was 10-times to baseline. In contrast, uptakes of MIBI and TF in K562, MCF7, SK-OV3 cells were decreased with verapamil treatment at a concentration over $1{\mu}M$. With a concentration of $200{\mu}M$ verapamil, MIBI and TF uptakes un K562 cells were decreased to 1.5 % and 2.7% of those without verapamil, respectively. Cellular uptakes of MIBI and TF in MCF7 and SK-OV-3 cells were not changed with $10{\mu}M$, but were also decreased with verapamil higher than $10{\mu}M$, resulting 40% and 5% of baseline at $50{\mu}M$. MTT assay of four cells revealed that K562, MCF7, SK-OV3 were not damaged with verapamil at $200{\mu}M$. Conclusion: Although verapamil increases uptake of MIBI and TF in MDR cancer cells, cellular uptakes were further decreased with verapamil in certain cancer cells, which is not related to cytotoxicity of drug. These results suggest that cellular uptakes of both tracers might differ among different cells, and interpretation of changes in tracer uptake with verapamil in vitro should be different when different cell lines are used.
This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.
Kim, Ha-Na;Baik, Byeong-Ju;Kim, Jae-Gon;Yang, Yeon-Mi;Park, Jeong-Yeol
Journal of the korean academy of Pediatric Dentistry
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v.35
no.1
/
pp.65-72
/
2008
Pulse oximeter to monitor oxygen saturation during pediatric dental sedations enables early detection of hypoxemia. The purpose of this study was to monitor the hemoglobin oxygen saturation level and pulse rate of nonmedicated pediatric patients during routine restorative procedures to study the effect of procedure and treated jaw. We obtained data from 53 children treated at the Department of Pediatric Dentistry, Chonbuk national university hospital. Pulse rate and oxygen saturation were measured and recorded using pulse oximetry at each step of treatment. The results are as follows: 1. In non-anesthesia group, steep increase of pulse rate was observed during rubber dam application in the maxilla and during cavity preparation in the mandible. 2. In anesthesia group, pulse rate started to decrease after the rubber dam application in the maxilla, while its decrease observed since cavity preparation step in the mandible. 3. In non-anesthesia group, oxygen saturation level was relatively constant during all steps in the maxilla, but in mandible, it was higher during operation compared to its pre and post operation baseline. 4. In anesthesia group, oxygen saturation level was observed at 99% level through all steps in both jaw groups, and there was no statistical significance between the maxilla and the mandible groups(p>0.05). The purpose of this study was to evaluate the effect of routine dental treatment on the pulse rate and oxygen saturation level in nonmedicated pediatric patients during routine restorative procedures in the maxilla and mandible.
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