• Journal of Food Hygiene and Safety
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• v.21 no.2
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• pp.100-106
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• 2006

The use of underarm and body care cosmetics with oestrogenic chemical excipients (particularly the parabens) and the hypothesized association with breast cancer incidence, particularly in women. It is noted that the type of cosmetic product is irrelevant (e.g. antiperspirant/deodorant versus body lotion, moisturizers or sprays versus creams) and attention must focus on issues of actual exposure to chemicals through continued dermal application of body care products and the endocrine/hormonal activity and toxicity of the chemicals in the formulations. To evaluate the estrogenic activities of parabens such as ethylparaben, butylparaben, propylparaben, isobutylparaben and isopropylparaben, we used recombinant yeasts containing the human estrogen receptor [Saccharomyces cerevisiae ER+LYS 8127], human breast cancer MCF-7 cell lines and human estrogen receptor ${\alpha}\;and\;{\beta}$. In E-screen assays, isopropylparaben is the most estrogenic paraben, and in ER competition assay, isobutylparaben is the most estrogenic paraben. We evaluated isopropylparaben was most active in the recombinant yeast assay, followed by propylparaben, ethylparaben, isobutylparaben and butylparaben. Results from this study demonstrate that parabens are observed in human endocrine system. Therefore, we have shown that the parabens is induced the estrogenic activities similar to $17{\beta}$-estradiol and Bisphenol-A.

• Economic and Environmental Geology
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• v.45 no.6
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• pp.643-659
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• 2012

The Chungju Fe-REE deposit is located in the Kyemyeongsan Formation of the Ogcheon Group. The Kyemyeongsan Formation includes meta-volcanic rocks and pegmatite hosted REE deposit which show different kind of REE-containing minerals. The meta-volcanic rocks hosted REE deposits' main REE minerals are allanite, zircon, apatite, and sphene, whereas the pegmatite hosted REE deposits is mainly composed of fergusonite, and karnasurtite, zircon, thorite. The meta-volcanic rock hosted major REE mineral is allanite as the form of aggregation and contains 23.89-29.19 wt% TREO (Total Rare Earth Oxide), 4.71-9.92 wt% $La_2O_3$, 11.30-14.33 wt% $Ce_2O_3$, 0.11-0.29 wt% $Y_2O_3$, 0.15-0.94 wt% $ThO_2$, as a formula of (Ca, Y, REE, Th)$_{2.095}$(Mg, Al, Ti, Mn, $Fe^{3+})_{2.770}(SiO_4)_{2.975}(OH)$. Accompanying REE in a coupled substitution for $Ca^{2+}$ (M1 site) and $Al^{3+}-Fe^{2+}$ (M2 site) leads to a large chemical variety. Due to the allanite's high contents of Fe, it belongs to Ferrialanite. The pegmatite hosted deposit's domi-nant REE mineral is fergusonite as prismatic or subhedral grains associated with zircon, fluorite and karnasurtite. Geochemical composition of the fergusonite($YNbO_4$) suggests substitution of Y-REE and Y-Th in A-site, and Nb-Ta-Ti in B-site, furthermore the proportion of $Y_2O_3$ and $Nb_2O_5$ is oddly 1:1.5 comparing to the ideal ratio 1:1 and Nb is higher than Y, also A-site Y actively substitutes with REE. Karnasurtite in pegmatite variously ranges 9.16-22.88 wt% $Ce_2O_3$, 2.15-9.16 wt% and $La_2O_3$, 0.44-10.8 wt% $ThO_2$, as a calculated formula (Y, REE, Th, K, Na, Ca)$_{1.478}(Ti, Nb)_{1.304}$(Mg, Al, Mn, $Fe^{3+})_{0.988}$(Si, P)$_{1.431}O_7(OH)_4{\cdot}3H_2O$. Firstly the 870-860 Ma is the initial age of the supercontinent Rhodinia dispersal and subsequent A-1 type volcanism, which contains Fe, REE, and HFS(High Field Strength elements; Nb, Zr, Y etc.) elements in Fe-rich meta-volcanic rocks dominant Kyemyeongsan Formation, might mineralized allanite. Another synthesis is that regional metamorphism at late Paleozoic 300-280 Ma(Cho et al., 2002) might cause allanite mineralization. Also pegmatite REE mineralization highly related to the granite intrusion over the Chungju area in Jurassic(190 Ma; Koh et al., 2012). Otherwise above all, A-1 type volcanism at the same time of the Kyemyeongsan Formation development, regional metamorphism and pegmatite, might have caused REE mineralization. Although REE ore bodies display a close spatial association, each ore bodies display temporal distinction, different mineral assemblage and environment of ore formation.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Poultry Science
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• v.46 no.2
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• pp.65-75
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• 2019

A number of Korean native chicken(KNC) populations were registered in FAO (Food and Agriculture Organization) DAD-IS (Domestic Animal Diversity Information Systems, http://www.fao.org/dad-is). But there is a lack of scientific basis to prove that they are unique population of Korea. For this reason, this study was conducted to prove KNC's uniqueness using 25 Microsatellite markers. A total of 548 chickens from 11 KNC populations (KNG, KNB, KNR, KNW, KNY, KNO, HIC, HYD, HBC, JJC, LTC) and 7 introduced populations (ARA: Araucana, RRC and RRD: Rhode Island Red C and D, LGF and LGK: White Leghorn F and K, COS and COH: Cornish brown and Cornish black) were used. Allele size per locus was decided using GeneMapper Software (v 5.0). A total of 195 alleles were observed and the range was 3 to 14 per locus. The MNA, $H_{\exp}$, $H_{obs}$, PIC value within population were the highest in KNY (4.60, 0.627, 0.648, 0.563 respectively) and the lowest in HYD (1.84, 0.297, 0.286, 0.236 respectively). The results of genetic uniformity analysis suggested 15 cluster (${\Delta}K=66.22$). Excluding JJC, the others were grouped in certain cluster with high genetic uniformity. JJC was not grouped in certain cluster but grouped in cluster 2 (44.3%), cluster 3 (17.7%) and cluster8 (19.1%). As a results of this study, we can secure a scientific basis about KNC's uniqueness and these results can be use to basic data for the genetic evaluation and management of KNC breeds.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Journal of the Korean Chemical Society
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• v.55 no.3
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• pp.418-429
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• 2011

Novel chromium(III), manganese(II), iron(III), cobalt(II), nickel(II), copper(II), ruthenium(III), and zirconyl(II) complexes of $N^1,N^2$-bis(3-((3-hydroxynaphthalen-2-yl)methylene-amino)propyl)phthalamide ($H_4L$, 1) have been synthesized and characterized by elemental, physical, and spectral analyses. The spectral data showed that the ligand behaves as either neutral tridentate ligand as in complexes 2-5 with the general formula $[H_4LMX_2(H_2O)]{\cdot}nH_2O$ (M=Cu(II), Ni(II), Co(II), X = Cl or $NO_3$), neutral hexadentate ligand as in complexes 10-12 with the general formula $[H_4LM_2Cl_6]{\cdot}nH_2O$ (M=Fe(III), Cr(III) or Ru(III)), or dibasic hexadentate ligand as in complexes 6-9 with the general formula $[H_2LM_2Cl_2(H_2O)_4]{\cdot}nH_2O$ (M = Cu(II), Ni(II), Co(II) or Mn(II), and 13 with general formula $[H_4L(ZrO)_2Cl_2]{\cdot}8H_2O$. Molar conductance in DMF solution indicated the non-ionic nature of the complexes. The ESR spectra of solid copper(II) complexes 2, 5, and 6 showed $g_{\parallel}$ >g> $g_e$, indicating distorted octahedral structure and the presence of the unpaired electron in the $N^1,N^2$ orbital with significant covalent bond character. For the dimeric copper(II) complex $[H_2LCu_2Cl_2(H_2O)_4]{\cdot}3H_2O$ (6), the distance between the two copper centers was calculated using field zero splitting parameter for the parallel component that was estimated from the ESR spectrum. The antibacterial and antifungal activities of the compounds showed that, some of metal complexes exhibited a greater inhibitory effect than standard drug as tetracycline (bacteria) and Amphotricene B (fungi).

• Journal of the Microelectronics and Packaging Society
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• v.24 no.4
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• pp.23-29
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• 2017

The packaged optical fiber Bragg grating sensors which were networked by multiplexing the Bragg grating sensors with WDM technology were investigated in application for the structural health monitoring of the marine trestle structure transporting the ship. The optical fiber Bragg grating sensor was packaged in a cylindrical shape made of aluminum tubes. Furthermore, after the packaged optical fiber sensor was inserted in polymeric tube, the epoxy was filled inside the tube so that the sensor has resistance and durability against sea water. The packaged optical fiber sensor component was investigated under 0.2 MPa of hydraulic pressure and was found to be robust. The number and location of Bragg gratings attached at the trestle were determined where the trestle was subject to high displacement obtained by the finite element simulation. Strain of the part in the trestle being subjected to the maximum load was analyzed to be ${\sim}1000{\mu}{\varepsilon}$ and thus shift in Bragg wavelength of the sensor caused by the maximum load of the trestle was found to be ~1,200 pm. According to results of the finite element analysis, the Bragg wavelength spacings of the sensors were determined to have 3~5 nm without overlapping of grating wavelengths between sensors when the trestle was under loads and thus 50 of the grating sensors with each module consisting of 5 sensors could be networked within 150 nm optical window at 1550 nm wavelength of the Bragg wavelength interrogator. Shifts in Bragg wavelength of the 5 packaged optical fiber sensors attached at the mock trestle unit were well interrogated by the grating interrogator which used the optical fiber loop mirror, and the maximum strain rate was measured to be about $235.650{\mu}{\varepsilon}$. The modelling result of the sensor packaging and networking was in good agreements with experimental result each other.

• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.161-170
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• 2009

Purpose : A parallel imaging method provides us to improve temporal resolution to obtain three-dimensional (3D) MR images. The objective of this study was to optimize three 3D MRI techniques by adjusting 2D SESNE factors of the parallel imaging method in phantom and human brain. Materials and Methods : With a 3 Tesla MRI system and an 8-channel phase-array sensitivity-encoding (SENSE) coil, three 3D MRI techniques of 3D T1-weighted imaging (3D T1WI), 3D T2-weighted imaging (3D T2WI) and 3D fluid attenuated inversion recovery (3D FLAIR) imaging were optimized with adjusting SESNE factors in a water phantom and three human brains. The 2D SENSE factor was applied on the phase-encoding and the slice-encoding directions. Signal-to-noise ratio(SNR), percent signal reduction rate(%R), and contrast-to-noise ratio(CNR) were calculated by using signal intensities obtained in specific regions-of-interest (ROI). Results : In the phantom study, SENSE factor = 3 was provided in 0.2% reduction of signals against without using SENSE with imaging within 5 minutes for 3D T1WI. SENSE factor = 2 was provided in 0.98% signal reduction against without using SENSE with imaging within 5 minutes for 3D T2WI. SENSE factor = 4 was provided in 0.2% signal reduction against without using SENSE with imaging around 6 minutes for 3D FLAIR. In the human brain study, SNR and CNR were higher with SENSE factors = 3 than 4 for all three imaging techniques. Conclusion : This study was performed to optimize 2D SENSE factors in the three 3D MRI techniques that can be scanned in clinical time limitations with minimizing SNR reductions. Without compromising SNR and CNR, the optimum 2D SENSE factors were 3 and 4, yielding the scan time of about 5 to 6 minutes. Further studies are necessary to optimize 3D MRI techniques in other areas in human body.

• Archives of design research
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• v.20 no.3 s.71
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• pp.299-314
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• 2007

For the past 20 years, the growth and development of university-design-educational institutes contributed to the industrial development of our country. Due to the technological fluctuation and changes in the industrial structure in the latter half of the 20th century, the enterprise is demanding professionally-oriented design manpower. The principle which appears from instances of the advanced nations is to accommodate the demands in social changes and apply them to educational design programs. In order to respond promptly to the industrial demand especially, the advanced nations adopted "multidisciplinary design education programs" to lead innovation in the area of design globally. The objective of the research consequently is to suggest an educational system and a program through which the designer can be educated to obtain complex knowledge and the technique demanded by the industry and enterprise. Nowadays in order to adapt to a new business environment, designers specially should have both the knowledge and techniques in engineering and business administration. We suggest that the IPDI, a multidisciplinary design educational system and program is made up of the coordinated operation of major classes, on-the-job training connection, educational system for research base creation, renovation design development program for the application and the synthesis of alternative proposals about the training facility joint ownership by connecting with the education of design, business administration and engineering.