• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.341-350
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• 2023

The templated grain growth (TGG) method has gained significant attention for its ability to produce highly textured piezoelectric ceramics with significantly enhanced performance, making it a promising method for transducer and actuator applications. However, the texturing process using the TGG method requires the optimization of multiple steps, which can be challenging for beginners in this field. Therefore, in this tutorial, we provide an overview of the TGG method mainly based on our previous published works, including its various processing steps such as synthesizing anisotropic-shaped templates with size and size distribution control using the molten salt synthesis technique, tape casting, and identifying key factors for proper alignment of the templates in the target matrix system. Our goal is to provide a resource that can serve as a basic reference for researchers and engineers looking to improve their understanding and utilization of the TGG method for producing textured piezoelectric ceramics.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.359-365
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• 2023

In order to satisfy the requirements of dynamic X-ray imaging with high frame rate and low image lag, minimizing parasitic capacitance in photodiode and overlapped electrodes in pixels is critically required. This study presents duoPIX^TM dynamic X-ray imaging sensor composing of readout thin film transistor, reset thin film transistor and photodiode in a pixel. Furthermore, dynamic X-ray detector using duoPIX^TM imaging sensor was manufactured and evaluated its X-ray imaging performances such as frame rate, sensitivity, noise, MTF and image lag. duoPIX^TM dynamic X-ray detector has 150 × 150 mm² imaging area, 73 um pixel pitch, 2048 × 2048 matrix resolution(4.2M pixels) and maximum 50 frames per second. By means of comparison with conventional dynamic X-ray detector, duoPIX^TM dynamic X-ray detector showed overall better performances than conventional dynamic X-ray detector as shown in the previous study.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.420-429
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• 2023

GC-MS/MS using liquid-liquid extraction (LLE) and C18 cartridges was used to identify and quantify levels of chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin and permethrin in bulk raw milk. A calibration curve spanning 10 ng/mL to 200 ng/mL was obtained with a satisfactory correlation coefficient of 0.99. The limits of detection (LOD) and limits of quantitation (LOQ) for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in the matrix ranged from 0.06 to 1.81 ng/mL and 0.19 to 6.04 ng/mL, respectively. The recoveries of 5 pesticides from spiked samples at 37.5-125 ng/mL ranged from 86.1 to 102.1%. The measurement of uncertainty of the GC-MS/MS method for these five pesticides was developed based on the analytical process and quantification. An analysis method that is easier and faster than the method specified in the Korean food standards codes for analyzing these five pesticides in raw material milk was developed. Moreover, the analytical method for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in bulk raw milk by GC-MS/MS was established.

• Analytical Science and Technology
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• v.31 no.4
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• pp.161-170
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• 2018

The epidemic of disorders associated with synthetic stimulants, such as methamphetamine (MA) and amphetamine (AP), is a health, social, legal, and financial problem. Owing to the high potential of their abuse and addiction, reliable analytical methods are required to detect and identify MA, AP, and their metabolites in biological samples. Thus, a dilute-and-shoot liquid chromatography-tandem mass spectrophotometry (LC-MS/MS) was developed for simultaneous determination of MA, 4-hydroxymethamphetamine (4HMA), AP, and 4-hydroxyamphetamine (4HA) in urine. Urine sample ($100{\mu}L$) was mixed with $50{\mu}L$ of mobile phase consisting of 0.4 % formic acid and methanol and $50{\mu}L$ of working internal-standard solution. Aliquots of $8{\mu}L$ diluted urine was injected into the LC-MS/MS system. For all analytes, chromatographic separation was performed using a C18 reversed-phase column with gradient elution and a total run time of 5 min. The identification and quantification were performed by multiple reaction monitoring (MRM). Linear least-squares regression was conducted to generate a calibration curve, with $1/x^2$ as the weighting factor. The linear ranges were 2.0-200, 1.0-800, and 10-2500 ng/mL for 4HA and 4HMA, AP, and MA, respectively. The inter- and intraday precisions were within 6.6 %, whereas the inter- and intraday accuracies ranged from -14.9 to 11.3 %. The low limits of quantification were 2.0 ng/mL (4HA and 4HMA), 1.0 ng/mL (AP), and 10 ng/mL (MA). The proposed method exhibited satisfactory selectivity, dilution integrity, matrix effect, and stability, which are required for validation. Moreover, the purification efficiency of high-speed centrifugation was clearly higher than 6-15 % for QC samples (n=5), which was higher than that of the membrane-filtration method. The applicability of the proposed method was tested by forensic analysis of urine samples from drug abusers.

• Parasites, Hosts and Diseases
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• v.23 no.2
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• pp.203-213
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• 1985

The in situ posture of anterior body of Metagonimus yokogawai was observed in experimental metagonimiasis of dog. The metacercariae were collected from naturally infected sweetfish by peptic digestion; a total of 8 dogs was orally infected with 10,000 metacercariae respectively. Two dogs were killed on 3 days, 9 days, 4 weeks and 10 weeks after the infection. The postures of worms in histological section of small intestine and of whole worms collected from the fixed intestinal mucosa were examined by light and scanning electron microscope. The results were summarized as follows: 1. The recovery rates of worms were 42.6% on 3 days, 55.0% on 9 days, 33.2% on 4 weeks and 9. 8% on 10 weeks after the infection respectively. 2. In histological sections of small intestine, most of worms were found at intervillous spaces as ovoid sections of posterior body. However, many worms, especially in 3 day-old worms, revealed protruded anterior body in glandular lumens of crypt. Some sections of anterior body were bifurcated or sacculated. 3. The worms collected from fixed intestinal mucosa under dissecting microscope exhibited a variety of postures. Many worms showed flat shapes with a concavity or curvatures. However, in many worms, the anterior body made a single or multiple protrusions. 4. By SEM observation of protruded anterior body, a longitudinal groove was found. 5. The frequency of worms with protruded anterior body decreased in 9 days, 4 weeks and 10 weeks than in 3 day-old worms. The above findings indicated that the anterior body of juvenile and adult M. yokogawai protruded to lumens of glandular crypt by folding their lateral portions to make a reversible tubelike structure. Frequent multiple protrusions were considered to be made to adapt the microniche of glandular crypts of dog intestine.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.429-444
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• 1988

Considering the recent trent toward the development of multiple-use of forest trees, investigations for comprehensive information on these young stands of Hinoki cypress are necessary for rational forest management. From this point of view, 83 sample trees were selected and cut down from 23-ear old stands of Hinoki cypress at Changsung-gun, Chonnam-do. Various stem growth factors of felled trees were measured and canonical correlaton analysis, principal component analysis and factor analysis were applied to investigate the stem growth characteristics, relationships among stem growth factors, and to get potential information and comprehensive information. The results are as follows ; Canonical correlation coefficient between stem volume and quality growth factor was 0.9877. Coefficient of canonical variates showed that DBH among diameter growth factors and height among height growth factors had important effects on stem volume. From the analysis of relationship between stem-volume and canonical variates, which were linearly combined DBH with height as one set, DBH had greater influence on volume growth than height. The 1st-2nd principal components here adopted to fit the effective value of 85% from the pincipal component analysis for 12 stem growth factors. The result showed that the 1st-2nd principal component had cumulative contribution rate of 88.10%. The 1st and the 2nd principal components were interpreted as "size factor" and "shape factor", respectively. From summed proportion of the efficient principal component fur each variate, information of variates except crown diameter, clear length and form height explained more than 87%. Two common factors were set by the eigen value obtained from SMC (squared multiple correlation) of diagonal elements of canonical matrix. There were 2 latent factors, $f_1$ and $f_2$. The former way interpreted as nature of diameter growth system. In inherent phenomenon of 12 growth factor, communalities except clear length and crown diameter had great explanatory poorer of 78.62-98.30%. Eighty three sample trees could he classified into 5 stem types as follows ; medium type within a radius of ${\pm}1$ standard deviation of factor scores, uniformity type in diameter and height growth in the 1st quadrant, slim type in the 2nd quadrant, dwarfish type in the 3rd quadrant, and fall-holed type in the 4 th quadrant.

• Explosives and Blasting
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• v.9 no.1
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• pp.3-13
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• 1991

The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.

• Tuberculosis and Respiratory Diseases
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• v.51 no.3
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• pp.211-223
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• 2001

Background : Rhinovirus infection of the airways results in increased permeability of the airway vascular endothelium with the influx of plasma proteins, including lipids such as LDL. In vitro studies on the effect of oxLDL on leukocytes has shown many pro inflammatory effects on multiple leukocytes. We hypothesized that oxLDL is one mechanism for recruiting granulocytes to the airways during a RV infection. Therefore, chemotaxis and transendothelial migration, in response to nLDL, was determined for these granulocytes. Methods : nLDL was oxidized with 5mM Cu2S04 for 20-24 hours. 3-5 105 cells were loaded into the Transwell filter while the chemotatic agonists were placed in the lower well for chemotaxis. Confluent monolayers on HPMEC were grown on Transwell filters for transendothelial migration. The filters were washed and eosinophils and neutrophils loaded on to the filter with the chemotatic agonist was were placed in the lower well. The wells were incubated for 3 hours. The number of migrating cells was counted on a hemocytometer. Results : OxLDL, but not nLDL, is chemotatic for eosinophils and neutrophils. The level of granulocytes chemotaxis was dependent on both the concentration of LDL and its degree of oxidation. OxLDL stimulates eosinophil and neutrophils migration across HPMEC monolayers (+/-IL-$1{\beta}$ preactivation) in a dose dependent manner. Conclusion : Increased vascular permeability during a RV infection may lead to the influx and oxidation of LDL. The resulting oxLDL. is one possible mechanism for the recruitment of neutrophils and eosinophils to the airway interstitial matrix. Once in the airways, granulocytes can further interact with oxLDL to promote airway inflammation.