• Archives of Plastic Surgery
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• v.35 no.5
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• pp.607-610
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• 2008

Purpose: Salivary duct carcinoma(SDC) is uncommon but high grade adenocarcinoma arising in the ductal epithelium of salivary glands. SDC is characterized by distinctive clinical and pathologic features. The most important histologic aspect of this neoplasm is its resemblance to ductal carcinoma of the breast. Clinically SDC is defined by cervical lymph node involvement and distant metastasis with a high rate of recurrence and mortality. We described some of the clinical and pathological features of SDC and the management using case report for our patient. Methods: We present a case of a 40-year-old male with 2-year history of a swelling arising in his left preauricular region. There was a single painless, firm and solid $2{\times}1.5cm$ mass in the left parotid area. Facial nerve function was intact and no cervical lymph node were palpable. In August 2005, we found out $1.7{\times}1.8cm$ sized cystic, nodular lesions that were located in the superficial lobe of left parotid gland through Computed tomography. And then superficial parotidectomy and postoperative radiation therapy were performed in Jan 2007. Results: Pathologically, the specimen were consisted of homogeneous, chondoid to myxoid type of tissues. It was yellow mass that has multiloculated cystic lesions. In postoperative PET(Positiron emission tomography) CT, there was no evidence of uptaking FDG(Fluorodeoxyglucose) into the deep layers of parotid gland and distant metastasis were not seen. Conclusion: Salivary duct carcinoma(SDC) is a rare but high grade adenocarcinoma related to pleomorphic adenocarcinoma. The prognosis of SDC can be different according to the type of tumor such as mucoepidermoid adenocarcinoma, adenoid duct carcinoma and acinar cell carcinoma. So we need to study more carefully for accurate diagnosis in early stage of diagnosis. Although radiotherapy has not yet proven to be a significant factor in overall survival, the combination of parotidectomy and postoperative radiation therapy can lead to more favorable results in treating of SDC.

• Korean Medical Education Review
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• v.17 no.1
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• pp.5-9
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• 2015

A teaching hospital is a place where both patient care and learning occur together. To identify the role of the teaching hospital in an effective clerkship, we first determined the features of workplace learning and the factors that affect learning in the workplace, and then we proposed a role for the teaching hospital in the clinical clerkship. Features of learning in a clerkship include learning in context, and learning from patients, supervising doctors, others in the team, and colleagues. During the clerkship, medical students learn in three-way learner-patient-teacher relationships, and students' participation in the tasks of patient care is crucial for learning. Factors that influence learning in the workplace are associated with tasks, context, and learner. Tying the three factors together, we proposed a role for the teaching hospital in the three categories: involvement in the tasks of patient care, engagement in the medical team, and engagement in the learning environment and system. Supervising doctors and team members in a teaching hospital support students' deep participation in patient care, while improving the learning environment through organizational guidelines and systems. Gathering both qualitative and quantitative data for the evaluation of a teaching hospital is important.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.38.1-38.1
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• 2008

Tides caused by the Galactic gravitational field affect the current dynamical structure of globular clusters in the Galaxy. Indeed, the observed feature of tidal tails stretching beyond globular clusters' tidal radii provides a key information of interaction with the gravitational field of the Galaxy and kinematical orbit of the clusters, which can be an evidence of the merging scenario of the Galaxy formation and evolution. To find such a tidal feature, we have studied spatial density distribution of stars around five globular clusters in the Galactic halo and one cluster in the Galactic bulge, for which we have used wide-field deep photometric data of gri and JHK bands obtained from the MegaCam and WIRCam of the CFHT. Applying the statistical contrast filtering of field stars in the color-magnitude plane of detected stars around five halo clusters, we have found features of tidal tails for four clusters M53, M15, NGC 5053, and NGC 5466. The detected over-density tidal features are well aligned with the cluster's orbits and stretched into the direction of the Galactic center. Statistical analysis indicate that these tidal tails are believed to be cluster stars that have escaped due to the tidal effects to the clusters. A similar tidal feature to that of halo clusters is also detected for the bulge cluster NGC 6626, while the over-density feature seems to be extended into the Galactic plane rather than into the orbital direction and the Galactic center. Conclusively, our result adds further observational evidence of the merging scenario of the Galaxy formation and evolution.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.465-481
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• 2004

We determined Asian dust days by constructing the standard of Asian dust using PM$_{10}$ concentrations ($\geq$150 $\mu\textrm{g}$m$^{-3}$ , 24-hr average) and TOMS aerosol index ($\geq$0.7) for 5 years (1998-2002), and grouped Into long-lasted cases (LLCs, $\geq$4 days) and short-lasted cases (SLCs, $\leq$2 days) concerning the mean lasting time (about 3 days) of Asian dust. Further we performed the specific analyses associated with concentration variations and synoptic conditions by using PM$_{10}$ and TOMS data, weather maps during the dusty cases (LLCs and SLCs). As a result, the LLCs (9 cates) had large variations of PM$_{10}$ concentration as the mean of 131.1$\mu\textrm{g}$m$^{-3}$ and the maximum mean of 379.8$\mu\textrm{g}$m$^{-3}$ , and showed dominant features the continuous passage of deep trough caused by blocking effect and weak trough (56%, 5 cases) over Korea. The SLCs (11 cases) had relatively small variations of PM$_{10}$ concentration as the mean of 133.3$\mu\textrm{g}$m$^{-3}$ and the maximum mean of 247.2$\mu\textrm{g}$m$^{-3}$ , and showed passage of one weak trough (64%, 7 cases) over Korea. Thereafter, the case studies (April 7-13, 2002 of LLC and March 23-24, 2000 of SLC) performed by the simulation of MM5 with meteorological variables of the horizontal wind, potential temperature, isentropic potential vorticity, and helped to better understand the features of synoptic conditions in connection with the concentration variations for each case.

• Journal of the Korean Wood Science and Technology
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• v.45 no.6
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• pp.797-808
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• 2017

Automatic wood species identification systems have enabled fast and accurate identification of wood species outside of specialized laboratories with well-trained experts on wood species identification. Conventional automatic wood species identification systems consist of two major parts: a feature extractor and a classifier. Feature extractors require hand-engineering to obtain optimal features to quantify the content of an image. A Convolutional Neural Network (CNN), which is one of the Deep Learning methods, trained for wood species can extract intrinsic feature representations and classify them correctly. It usually outperforms classifiers built on top of extracted features with a hand-tuning process. We developed an automatic wood species identification system utilizing CNN models such as LeNet, MiniVGGNet, and their variants. A smartphone camera was used for obtaining macroscopic images of rough sawn surfaces from cross sections of woods. Five Korean softwood species (cedar, cypress, Korean pine, Korean red pine, and larch) were under classification by the CNN models. The highest and most stable CNN model was LeNet3 that is two additional layers added to the original LeNet architecture. The accuracy of species identification by LeNet3 architecture for the five Korean softwood species was 99.3%. The result showed the automatic wood species identification system is sufficiently fast and accurate as well as small to be deployed to a mobile device such as a smartphone.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.203-214
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• 2020

It is necessary to classify technical documents such as patents, R&D project reports in order to understand the trends of technology convergence and interdisciplinary joint research, technology development and so on. Text mining techniques have been mainly used to classify these technical documents. However, in the case of classifying technical documents by text mining algorithms, there is a disadvantage that the features representing technical documents must be directly extracted. In this study, we propose a BERT-based document classification model to automatically extract document features from text information of national R&D projects and to classify them. Then, we verify the applicability and performance of the proposed model for classifying documents.

• Korean Journal of Ichthyology
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• v.26 no.4
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• pp.274-280
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• 2014

The spermatozoa of Platichthys stellatus is relatively simple cells composed of a spherical head, a short midpiece, and a tail, as in most Pleuronectiformes. The ultrastructure is characterized by the following features: a round nucleus with a deep nuclear fossa, the centriolar complex located at a right angle to each other, a short midpiece, a tail with paired lateral ribbon and no acrosome. However there are some minor morphological differences, including the appearance and number of the mitochondria, the shape and size of the nuclear fossa and the structure of the basal body. Especially the basal body structure consisting of a basal foot, a rootlet and nine alar sheets structures varies considerably in different species. It can be used as indicator of relationships in Pleuronectiformes because minute morphological differences might have functional and evolutionary significance. In conclusion, the spermatozoa of P. stellatus show a certain structural homogeneity and provide support for the concept that ultrastructural features of spermatozoa can be useful in taxonomic studies of Pleuronectiformes.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1024-1034
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• 2019

Preference for music is determined by a variety of factors, and identifying characteristics that reflect specific factors is important for music recommendations. In this paper, we propose a method to extract the singing voice related music features reflecting various musical characteristics by using a model learned for singer identification. The model can be trained using a music source containing a background accompaniment, but it may provide degraded singer identification performance. In order to mitigate this problem, this study performs a preliminary work to separate the background accompaniment, and creates a data set composed of separated vocals by using the proven model structure that appeared in SiSEC, Signal Separation and Evaluation Campaign. Finally, we use the separated vocals to discover the singing voice related music features that reflect the singer's voice. We compare the effects of source separation against existing methods that use music source without source separation.

• Convergence Security Journal
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• v.21 no.3
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• pp.57-66
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• 2021

As the detection performance using deep learning and machine learning of the intrusion detection field has been verified, the cases of using it are increasing day by day. However, it is difficult to collect the data required for learning, and it is difficult to apply the machine learning performance to reality due to the imbalance of the collected data. Therefore, in this paper, A mixed sampling technique using t-SNE visualization for imbalanced data processing is proposed as a solution to this problem. To do this, separate fields according to characteristics for intrusion detection events, including payload. Extracts TF-IDF-based features for separated fields. After applying the mixed sampling technique based on the extracted features, a data set optimized for intrusion detection with imbalanced data is obtained through data visualization using t-SNE. Nine sampling techniques were applied through the open intrusion detection dataset CSIC2012, and it was verified that the proposed sampling technique improves detection performance through F-score and G-mean evaluation indicators.

• Journal of Genetic Medicine
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• v.18 no.2
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• pp.127-131
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• 2021

Autosomal recessive spinocerebellar ataxia 20 (SCAR20; OMIM #616354) is a recently described disorder that is characterized by ataxia, intellectual disability, cerebellar atrophy, macrocephaly, coarse face, and absent speech. It is caused by loss-of-function mutations in SNX14. To date, all cases with homozygous pathogenic variants have been identified in consanguineous families. This report describes the first Korean cases of SCAR20 family caused by homozygous variants in SNX14. Two siblings were referred to our clinic because of severe global developmental delay. They presented similar facial features, including a high forehead, long philtrum, thick lips, telecanthus, depressed nasal bridge, and broad base of the nose. Because the older sibling was unable to walk and newly developed ataxia, repeated brain magnetic resonance imaging (MRI) was performed at the age of 4 years, revealing progressive cerebellar atrophy compared with MRI performed at the age of 2 years. The younger sibling's MRI revealed a normal cerebellum at the age of 2 years. Whole-exome sequencing was performed, and homozygous variants, such as c.2746-2A>G, were identified in SNX14 from the older sibling. Sanger sequencing confirmed homozygous SNX14 variants in the two siblings as well as a heterozygous variant in both parents. This report extends our knowledge of the phenotypic and mutational spectrum of SCAR20. We also highlight the importance of deep phenotyping for the diagnosis of SCAR20 in individuals with developmental delay, ataxia, cerebellar atrophy, and distinct facial features.