• Clinical and Experimental Pediatrics
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• v.61 no.12
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• pp.403-406
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• 2018

Floating-Harbor syndrome is a rare autosomal dominant genetic disorder associated with SRCAP mutation. To date, approximately 50 cases of Floating-Harbor syndrome have been reported, but none have been reported in Korea yet. Floating-Harbor syndrome is characterized by delayed bony maturation, unique facial features, and language impairment. Here, we present a 6-year-old boy with a triangular face, deep-set protruding eyes, low-set ears, wide nose with narrow nasal bridge, short philtrum, long thin lips, clinodactyly, and developmental delay that was transferred to our pediatric clinic for genetic evaluation. He showed progressive delay in the area of language and cognition-adaption as he grew. He had previously undergone chromosomal analysis at another hospital due to his language delay, but his karyotype was normal. We performed targeted exome sequencing, considering several syndromes with similar phenotypes. Library preparation was performed with the TruSight One sequencing panel, which enriches the sample for about 4,800 genes of clinical relevance. Massively parallel sequencing was conducted with NextSeq. An identified variant was confirmed by Sanger sequencing of the patient and his parents. Finally, the patient was confirmed as the first Korean case of Floating-Harbor syndrome with a novel SRCAP (Snf2 related CREBBP activator protein) mutation (c.7732dupT, p.Ser2578Phefs*6), resulting in early termination of the protein; it was not found in either of his healthy parents or a control population. To our knowledge, this is the first study to describe a boy with Floating-Harbor syndrome with a novel SRCAP mutation diagnosed by targeted exome sequencing in Korea.

• Korean Journal of Heritage: History & Science
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• v.50 no.2
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• pp.4-25
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• 2017

The Hoeamsa Temple of Yangju City was established at least during the late Korea Dynasty. This temple was rebuilt several times with the support of the royal family from the late Korea Dynasty to the early Joseon Dynasty. It was continually rebuilt in association with JiGong monk, HyeKeun monk, and MuHak monk. Hoeamsa temple was leading the Buddhist culture as a Buddhist center of the Joseon Dynasty . It was destroyed in the late Joseon Period. This site has been excavated several times since 1997. Various roofing tiles were unearthed. Of these tiles the edge of eaves are the artifacts showing the best features of this era. In this temple site has been excavated a variety of Sanskrit roof tiles. These tiles were made using superior technique. On the roof tiles are engraved Sanskrit mantras with a variety of 1 to 9 words. The jeongbeopkkye mantra(oṃ raṃ) and six-word mantra(oṃ ma ṇi pa dme hūṃ) were discovered the most. These mantras were believe to expel several evils from the Buddhist temple. It must have been that the six-word mantra culture became prevalent and provided a turning point in the history of Korean Buddhism. We can clearly know when some of the Sanskrit roof tiles were first manufactured. These roof tiles are the absolute standard of the other Sanskrit roof tiles excavated from different Buddhist temples. The master craftsmen must have been very skilled, understood the mantra very well, and had deep faith in the Sanskrit mantra. Hoeamsa Temple is a milestone in studying the Sanskrit roof tiles. More studies on various aspects are expected to be followed.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.4
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• pp.40-48
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• 2011

Mt. Hee-yang is located in Mungyeong-si, Gyeongsangbuk-do, South Korea. Through the analysis and interpretations of twenty-two different ancient writings which covers Mt. Hee-yang, and three times of field studies, I tried to analyze the cognition of our ancestors in those days regarding Mt. Hee-yang. Since Mt. Hee-yang goes very deep in the mountain range, Mt. Hee-yang was recognized as appropriate place for seclusion or operating Byeolseo. From the era of Silla, in terms of Fengshui, Mt. Hee-yang was also interpreted as an image of either a phoenix flying into the sky(鳳凰登天) or a valley of a phoenix and dragon(鳳巖龍谷). This cognition comes from its formations of topographical features, and continued to the era of Joseon Dynasty. The purposes of excursion were to retrace the course of predecessors, to attain one's long-cherished desire to visit, or to enjoy holidays. From the analysis of Mt. Hee-yang's visitors, the average social status of them is lowered a lot around the end of Joseon Dynasty, compared with the early period of Joseon Dynasty. Studying the visitor's route of Mt. Hee-yang, I could see the places that are highly-recognized were the top of Mt. Hee-yang, Seonyudong(仙遊洞), Bakundae(白雲臺), Yayuam(夜遊岩). Mt. Hee-yang was recognized as Sun-kyung(仙境) where Sin-seon(a taoist hermit with miraculous powers; the sage of old) lives, and mostly it was main destination of visit while Bakundae(白雲臺) was perceived diversely on each visitor because of its strange scenery.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.5
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• pp.249-258
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• 2022

The specific muscular structure of the tongue greatly affects margin shrinkage and tumor invasion, making the optimal surgical margin controversial. This study investigated surgical margin correlated prognosis of TSCC (tongue squamous cell carcinoma) according to margin location and its value, and the histopathologic factors which are suggestive of tumor invasion. And we would like to propose defining of the surgical margin for TSCC via prognosis according to location and margin values. We reviewed 45 patients diagnosed with TSCC who visited Seoul National University Dental Hospital (SNUDH) (Seoul, Republic of Korea) from 2010 to 2019, who were managed by a single surgical team. Patient clinical and pathological data of patients were retrospectively reviewed, and in 36 out of 45 patients, the pathologic parameters including the worst pattern of invasion (WPOI) and tumor budding were investigated via diagnostic histopathology slide reading. When standardized with as 0.25 cm anterior margins, as 0.35 cm deep margin, there was no significant difference in disease specific survival (DSS) or loco-regional recurrence-free survival (LRFS). Additionally, there was a non-significant difference in DSS and LRFS at the nearest margin of 0.35 cm (P_DSS=0.276, P_LRFS=0.162). Aggressive WPOI and high tumor budding showed lower survival and recurrence-free survival, and there were significant differences in close margin and involved margin frequencies. In TSCC, the value and location of the surgical margin did not have a significant relationship with prognosis, but WPOI and tumor budding suggesting the pattern of muscle invasion affected survival and recurrence-free survival. WPOI and tumor budding should be considered when setting an optimal surgical margin.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.359-366
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• 2022

In this paper, we present the Korean menu-ordering Sentence Text-to-Speech (TTS) system using conformer-based FastSpeech2. Conformer is the convolution-augmented transformer, which was originally proposed in Speech Recognition. Combining two different structures, the Conformer extracts better local and global features. It comprises two half Feed Forward module at the front and the end, sandwiching the Multi-Head Self-Attention module and Convolution module. We introduce the Conformer in Korean TTS, as we know it works well in Korean Speech Recognition. For comparison between transformer-based TTS model and Conformer-based one, we train FastSpeech2 and Conformer-based FastSpeech2. We collected a phoneme-balanced data set and used this for training our models. This corpus comprises not only general conversation, but also menu-ordering conversation consisting mainly of loanwords. This data set is the solution to the current Korean TTS model's degradation in loanwords. As a result of generating a synthesized sound using ParallelWave Gan, the Conformer-based FastSpeech2 achieved superior performance of MOS 4.04. We confirm that the model performance improved when the same structure was changed from transformer to Conformer in the Korean TTS.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.35-56
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• 2023

With the development of information and communication technology, numerous reviews are continuously posted on websites, which causes information overload problems. Therefore, users face difficulty in exploring reviews for their decision-making. To solve such a problem, many studies on review helpfulness prediction have been actively conducted to provide users with helpful and reliable reviews. Existing studies predict review helpfulness mainly based on the features included in the review. However, such studies disable providing the reason why predicted reviews are helpful. Therefore, this study aims to propose a methodology for applying eXplainable Artificial Intelligence (XAI) techniques in review helpfulness prediction to address such a limitation. This study uses restaurant reviews collected from Yelp.com to compare the prediction performance of six models widely used in previous studies. Next, we propose an explainable review helpfulness prediction model by applying the XAI technique to the model with the best prediction performance. Therefore, the methodology proposed in this study can recommend helpful reviews in the user's purchasing decision-making process and provide the interpretation of why such predicted reviews are helpful.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.435-452
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• 2023

This study experimented with automatic classification of subject headings using BERT-based transfer learning model, and analyzed its performance. This study analyzed the classification performance according to the main class of KDC classification and the category type of subject headings. Six datasets were constructed from Korean national bibliographies based on the frequency of the assignments of subject headings, and titles were used as classification features. As a result, classification performance showed values of 0.6059 and 0.5626 on the micro F1 and macro F1 score, respectively, in the dataset (1,539,076 records) containing 3,506 subject headings. In addition, classification performance by the main class of KDC classification showed good performance in the class General works, Natural science, Technology and Language, and low performance in Religion and Arts. As for the performance by the category type of the subject headings, the categories of plant, legal name and product name showed high performance, whereas national treasure/treasure category showed low performance. In a large dataset, the ratio of subject headings that cannot be assigned increases, resulting in a decrease in final performance, and improvement is needed to increase classification performance for low-frequency subject headings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.273-275
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• 2022

The use of drugs by pregnant women poses a potential risk to the fetus. Therefore, it is essential to classify drugs that pregnant women should prohibit. However, the fetal toxicity of most drugs has not been identified. This takes a lot of time and cost. In silico approaches, such as virtual screening, can identify compounds that may present a high risk to the fetus for a wide range of compounds at the low cost and time. We collected class information of each drug from the hazard classification lists for prescribing drugs in pregnancy by the government of Korea and Australia. Using the structural and chemical features of each drug, various machine learning models were constructed to predict fetal toxicity of drugs. For all models, the quantitative performance evaluation was performed. Based on the attention algorithm, important molecular substructures of compounds were identified in the process of predicting the fetal toxicity of the drug by the proposed model. From the results, we confirmed that drugs with a high risk of fetal toxicity can be predicted for a wide range of compounds by machine learning. This study can be used as a pre-screening tool for fetal toxicity predictions, as it provides key molecular substructures associated with the fetal toxicity of compounds.

• Journal of Digestive Cancer Research
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• v.1 no.1
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• pp.48-51
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• 2013

We report an unusual case of postoperative early gastric cancer with liver metastasis mimicking pancreaticobiliary carcinoma. A 73-year-old man with early gastric cancer was transferred for endoscopic treatment. The patient underwent endoscopic submucosal dissection for the treatment of the early gastric cancer. The pathological diagnosis was adenocarcinoma with extension to the deep submucosa and some lymphatic invasion. Therefore, subsequent a subtotal gastrectomy was performed. The histological results demonstrated residual adenocarcinoma confined to the mucosa. The resection margin and lymph node metastasis were negative. Thus, he was closely monitored for recurrence every 6 months. After 2 years, he was suddenly suspected of developing liver metastasis and local recurrence. He received a liver biopsy, and the pathological result was poorly differentiated adenocarcinoma. Immunohistochemical staining suggested pancreaticobiliary carcinoma rather than metastatic adenocarcinoma from the stomach or colon, but primary focus was not found. We were sure that the recurrent stomach cancer metastasized to the liver because stomach cancer can show heterogeneous cytokeratin (CK) expression pattern with various histological features. Therefore, no single CK expression pattern has diagnostic value for distinguishing gastric carcinoma. The patient underwent chemotherapy for metastatic stomach cancer.