• Korean Journal of Food Science and Technology
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• v.51 no.4
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• pp.316-323
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• 2019

It is difficult to analyze pymetrozine in citrus fruits using the hydromatrix method because of its low efficiency of purification and overlap of matrix and pymetrozine peaks. Liquid-liquid extraction can analyze pymetrozine in citrus fruits using dichloromethane. Since low pH interferes with the extraction of pymetrozine, the extracts of citrus fruits were maintained over pH 7.0 by adding borax buffer and 1 N NaOH in the improved method. According to the improved method, citrus fruits (such as lemon, lime, orange, tangerine, and grapefruit) were extracted and purified for HPLC-photo diode array analysis. The results of validation were as follows: $4.360{\mu}g/kg$ of limit of detection, $14.533{\mu}g/kg$ of limit of quantitation, and 0.007 mg/kg of method quantitative limit. Citrus fruits spiked with pymetrozine showed a recovery range from 71.8 to 83.7% and a coefficient of variation below 6%. Thus, the improved method can efficiently analyze pymetrozine in citrus fruits.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.235-241
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• 2019

An analytical method was developed for the determination of an antibiotic fungicide, kasugamycin, in agricultural products (hulled rice, potato, soybean, mandarin and green pepper) using liquid chromatographytandem mass spectrometry (LC-MS/MS). Samples were extracted with methanol adjusted to pH 13 using 1 N sodium hydroxide, and purified with a HLB (hydrophilic lipophilic balance) cartridge. Linearity of a matrix-matched calibration curve using seven concentration levels, from 0.001 to 0.1 mg/kg, was excellent with a correlation coefficient ($R^2$) of more than 0.9998. The limits of detection (LOD) and quantification (LOQ) of instrument were 0.0005 and $0.001{\mu}g/mL$, respectively, and the LOQ of analytical method calculated as 0.01 mg/kg. The average recoveries at three spiking levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) were in the range of 71.2~95.4% with relative standard deviation of less than 12.1%. The developed method was simple and all optimized results was satisfied with the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. The present study could be served as a reference for the establishment of maximum residue limits (MRL) of kasugamycin and be used as basic data for safety management relative to kasugamycin residues in imported and domestic agricultural products.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.242-250
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• 2019

An analytical method was developed for the determination of fenquinotrione, a triketone herbicide, in agricultural products. Fenquinotrione was metabolized to KIH-3653-M-2 in plants. Analyte extraction was conducted using 2% formic acid in acetonitrile and cleaned up using a hydrophillic-lipophillic balance (HLB) cartridge. The limits of detection (LOD) and quantification (LOQ) were 0.004 and 0.01 mg/kg, respectively. Matrix-matched calibration curves were linear over the calibration ranges ($0.001{\sim}0.1{\mu}g/mL$) into a blank extract with $r^2>0.99$. The recovery results for fenquinotrione and KIH-3653-M-2 ranged between 81.1 to 116.2% and 78.0 to 110.0% at different concentration levels (LOQ, $10{\times}LOQ$, $50{\times}LOQ$) with relative standard deviation (RSD) less than 4.6%. All values were corresponded with the criteria ranges requested in both the Codex (CAC/GL 40-1993, 2003) and MFDS guidelines (2016). Therefore, the proposed method can be used as an official analytical method for determination of fenquinotrione in the Republic of Korea.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.140-147
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• 2019

An analytical method was developed for the determination of quinoxyfen in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with 1% acetic acid in acetonitrile and water was removed by liquid-liquid partitioning with $MgSO_4$ (anhydrous magnesium sulfate) and sodium acetate. Dispersive solid-phase extraction (d-SPE) cleanup was carried out using $MgSO_4$, PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed by using LC-MS/MS in positive mode with MRM (multiple reaction monitoring). The matrix-matched calibration curves were constructed using six levels ($0.001-0.25{\mu}g/mL$) and the coefficient of determination ($R^2$) was above 0.99. Recovery results at three concentrations (LOQ, 10 LOQ, and 50 LOQ, n=5) were in the range of 73.5-86.7% with RSDs (relative standard deviations) of less than 8.9%. For inter-laboratory validation, the average recovery was 77.2-95.4% and the CV (coefficient of variation) was below 14.5%. All results were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for quinoxyfen determination in agricultural commodities. This study could be useful for the safe management of quinoxyfen residues in agricultural products.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.115-123
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• 2019

An analytical method was developed for the determination of fenpropimorph, a morpholine fungicide, in hulled rice, potato, soybean, mandarin and green pepper using QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) sample preparation and LC-MS/MS (liquid chromatography-tandem mass spectrometry). The QuEChERS extraction was performed with acetonitrile followed by addition of anhydrous magnesium sulfate and sodium chloride. After centrifugation, d-SPE (dispersive solid phase extraction) cleanup was conducted using anhydrous magnesium sulfate, primary secondary amine sorbents and graphitized carbon black. The matrix-matched calibration curves were constructed using seven concentration levels, from 0.0025 to 0.25 mg/kg, and their correlation coefficient ($R^2$) of five agricultural products were higher than 0.9899. The limits of detection (LOD) and quantification (LOQ) were 0.001 and 0.0025 mg/kg, respectively, and the limits of quantification for the analytical method were 0.01 mg/kg. Average recoveries spiked at three levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n=5) and were in the range of 90.9~110.5% with associated relative standard deviation values less than 5.7%. As a result of the inter-laboratory validation, the average recoveries between the two laboratories were 88.6~101.4% and the coefficient of variation was also below 15%. All optimized results were satisfied the criteria ranges requested in the Codex guidelines and Food Safety Evaluation Department guidelines. This study could serve as a reference for safety management relative to fenpropimorph residues in imported and domestic agricultural products.

• 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 the Korean Society of Radiology
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• v.13 no.5
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• pp.801-809
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• 2019

Existing Gamma Knife Radiosurgery(GKRS) for large lesions is often conducted in stages with volume or dose partitions. Often in case of volume division the target used to be divided into sub-volumes which are irradiated under the determined prescription dose in multi-sessions separated by a day or two, 3~6 months. For the entire course of treatment, treatment informations of the previous stages needs to be reflected to subsequent sessions on the newly mounted stereotactic frame through coordinate transformation between sessions. However, it is practically difficult to implement the previous dose distributions with existing Gamma Knife system except in the same stereotactic space. The treatment area is expanding because it is possible to perform the multistage treatment using the latest Gamma Knife Platform(GKP). The purpose of this study is to introduce the image-coregistration based on the stereotactic spaces and the strategy of multistage GKRS such as the determination of prescription dose at each stage using new GKP. Usually in image-coregistration either surgically-embedded fiducials or internal anatomical landmarks are used to determine the transformation relationship. Author compared the accuracy of coordinate transformation between multi-sessions using four or six anatomical landmarks as an example using internal anatomical landmarks. Transformation matrix between two stereotactic spaces was determined using PseudoInverse or Singular Value Decomposition to minimize the discrepancy between measured and calculated coordinates. To evaluate the transformation accuracy, the difference between measured and transformed coordinates, i.e., ${\Delta}r$, was calculated using 10 landmarks. Four or six points among 10 landmarks were used to determine the coordinate transformation, and the rest were used to evaluate the approaching method. Each of the values of ${\Delta}r$ in two approaching methods ranged from 0.6 mm to 2.4 mm, from 0.17 mm to 0.57 mm. In addition, a method of determining the prescription dose to give the same effect as the treatment of the total lesion once in case of lesion splitting was suggested. The strategy of multistage treatment in the same stereotactic space is to design the treatment for the whole lesion first, and the whole treatment design shots are divided into shots of each stage treatment to construct shots of each stage and determine the appropriate prescription dose at each stage. In conclusion, author confirmed the accuracy of prescribing dose determination as a multistage treatment strategy and found that using as many internal landmarks as possible than using small landmarks to determine coordinate transformation between multi-sessions yielded better results. In the future, the proposed multistage treatment strategy will be a great contributor to the frameless fractionated treatment of several Gamma Knife Centers.

• Cross-Cultural Studies
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• v.40
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• pp.111-131
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• 2015

An unusual success engendering loyalty among cult fans in the United States, Mamoru Oshii's 1995 cyberpunk anime, Ghost in the Shell (GITS) revolves around a female cyborg assassin named Motoko Kusanagi, a.k.a. "the Major." When the news came out last year that Scarlett Johansson was offered 10 million dollars for the role of the Major in the live action remake of GITS, the frustrated fans accused DreamWorks of "whitewashing" the classic Japanimation and turning it into a PG-13 film. While it would be premature to judge a film yet to be released, it appears timely to revisit the core achievement of Oshii's film untranslatable into the Hollywood formula. That is, unlike ultimately heteronormative and humanist sci-fi films produced in Hollywood, such as the Matrix trilogy or Cloud Atlas, GITS defies a Hollywoodization by evoking much bafflement in relation to its queer, posthuman characters and settings. This essay homes in on Major Kusanagi's body in order to update prior criticism from the perspectives of posthumanism and queer theory. If the Major's voluptuous cyborg body has been read as a liberating or as a commodified feminine body, latest critical work of posthumanism and queer theory causes us to move beyond the moralistic binaries of human/non-human and male/female. This deconstruction of binaries leads to a radical rethinking of "reality" and "identity" in an image-saturated, hypermediated age. Viewed from this perspective, Major Kusanagi's body can be better understood less as a reflection of "real" women than as an embodiment of our anxieties on the loss of self and interiority in the SNS-dominated society. As is warned by many posthumanist and queer critics, queer and posthuman components are too often used to reinforce the human. I argue that the Major's hybrid body is neither a mere amalgam of human and machine nor a superficial postmodern blurring of boundaries. Rather, the compelling combination of individuality, animality, and technology embodied in the Major redefines the human as always, already posthuman. This ethical act of revision-its shifting focus from oppressive humanism to a queer coexistence-evinces the lasting power of GITS.

• Journal of Food Hygiene and Safety
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• v.36 no.3
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• pp.228-238
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• 2021

The aim of this research was to develop a rapid and easy multi-residue method for determining dimethipin, omethoate, dimethipin, chlorfenvinphos and azinphos-methyl in agricultural products (hulled rice, potato, soybean, mandarin and green pepper). Samples were prepared using QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) and analyzed using gas chromatography-tandem mass spectrometry (GC-MS/MS). Residual pesticides were extracted with 1% acetic acid in acetonitrile followed by addition of anhydrous magnesium sulfate (MgSO₄) and anhydrous sodium acetate. The extracts were cleaned up using MgSO₄, primary secondary amine (PSA) and octadecyl (C₁₈). The linearity of the calibration curves, which waas excellent by matrix-matched standards, ranged from 0.005 mg/kg to 0.3 mg/kg and yielded the coefficients of determination (R²) ≥ 0.9934 for all analytes. Average recoveries spiked at three levels (0.01, 0.1, 0.5 mg/kg) and were in the range of 74.2-119.3%, while standard deviation values were less than 14.6%, which is below the Codex guideline (CODEX CAC/GL 40).

• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.48-67
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• 2021

Plant species exhibit current characteristics as a result of interactions with environmental conditions. The plants of Viola sp. have selected chasmogamous flowers with vigorous vegetative propagation or development of cleistogamous flowers as an adaptation strategy. Viola websteri is distributed on the Korean peninsula and the eastern part of Jilin Province, China. The center and edge of the distribution are expected to exhibit different population-dynamics. It is necessary to investigate the cause of its current limited distribution even though V. websteri has a mixed-mating strategy. Firstly, We examined the vegetation environment of habitats and evaluated its characteristics. Growth characteristics were examined through plant phenology. We then evaluated the population structure, characteristics of chasmogamous flowers, and productivity of cleistogamous flowers. Moreover, we compared population sizes between 2014 and 2018. Most habitats were located in deciduous broadleaf mixed forests adjacent to valleys. V. websteri produced chasmogamous flowers with self-incompatibility in April-May and cleistogamous flowers in June-September. The cleistogamous flower production is a strategy ensuring seed production under uncertain environmental fluctuations; these were approximately twice as numerous as chasmogamous flowers. The population structure was distinguished into stable and very unstable regions. There were sites where the population experienced a sharp decline in the 2018 compared to that of 2014. This large decline was found in the edge populations. The habitats had different microsites depending on the natural disturbances of drought and the matrix constituting the habitat, thus supporting various plants. Ensuring the production of seeds through cleistogamous flowers, it was determined that rapid seedling re-establishment and population replenishment were possible when the natural disturbance factor was removed. Environmental factors did not equally affect all populations or individuals. Therefore, it was expected that it would be able to persisted in a long time, despite the rapid decrease in the number of individuals in the population regionally. Local extinction and re-establishment are likely to repeat according to environmental change. We propose the additional population investigation based on this works are required. We also suggest a need to assess the long-term population dynamics and the genetic characteristics of chasmogamous flowers and cleistogamous flowers to establish and implement effective conservation strategies.