• Journal of Veterinary Clinics
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• v.32 no.2
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• pp.187-190
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• 2015

An 18-month-old female spayed domestic short-haired cat, weighing 4.1 kg, was presented as an emergency case after it suffered a gunshot injury. Physical examination of the cat revealed paraplegia, with loss of deep nociception. A bullet (diameter, 3 mm) lodged in the left epaxial muscle at the level of the first lumbar (L1) was observed on radiographic examination, and a hyperattenuating spot in the spinal canal was confirmed using computed tomography. Exploratory laminectomy was performed, and an incomplete fracture of the right caudal articular process of L1 and a necrotizing spinal cord lesion were found. The animal was euthanized and necropsy was performed, which revealed a crack on the left pedicle of L1. This case report presents the first detailed clinical description of a gunshot injury to the spinal cord in a cat.

• Journal of Chest Surgery
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• v.41 no.1
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• pp.141-144
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• 2008

Low grade fibromyxoid sarcoma (LGFM) is a rare, deep soft-tissue malignant tumor. Although its histologic features are benign, the clinical course is malignant. The usual tumor locations are the lower extremity and chest wall. LGFM originating from the visceral pleura is extremely rare. We report here on a 37 year old man with a LGFM of the visceral pleura. Thirty three months after surgery, the patient is alive without any sign of local recurrence or distant metastasis.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.26-30
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• 2018

Planetary global localization is necessary for long-range rover missions in which communication with command center operator is throttled due to the long distance. There has been number of researches that address this problem by exploiting and matching rover surroundings with global digital elevation maps (DEM). Using conventional methods for matching, however, is challenging due to artifacts in both DEM rendered images, and/or rover 2D images caused by DEM low resolution, rover image illumination variations and small terrain features. In this work, we use train CNN discriminator to match rover 2D image with DEM rendered images using conditional Generative Adversarial Network architecture (cGAN). We then use this discriminator to search an uncertainty bound given by visual odometry (VO) error bound to estimate rover optimal location and orientation. We demonstrate our network capability to learn to translate rover image into DEM simulated image and match them using Devon Island dataset. The experimental results show that our proposed approach achieves ~74% mean average precision.

• Analytical Science and Technology
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• v.33 no.2
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.55-63
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• 2017

One of the purposes of Information Technology (IT) is to support human response to natural and social problems such as natural disasters and spread of disease, and to improve the quality of human life. Recent climate change has happened worldwide, natural disasters threaten the quality of life, and human safety is no longer guaranteed. IT must be able to support tasks related to disaster response, and more importantly, it should be used to predict and minimize future damage. In South Korea, the data related to the damage is checked out by each local government and then federal government aggregates it. This data is included in disaster reports that the federal government discloses by disaster case, but it is difficult to obtain raw data of the damage even for research purposes. In order to obtain data, information extraction may be applied to disaster reports. In the field of information extraction, most of the extraction targets are web documents, commercial reports, SNS text, and so on. There is little research on information extraction for government disaster reports. They are mostly text, but the structure of each sentence is very different from that of news articles and commercial reports. The features of the government disaster report should be carefully considered. In this paper, information extraction method for South Korea government reports in the word format is presented. This method is based on patterns and dictionaries and provides some additional ideas for tokenizing the damage representation of the text. The experiment result is F1 score of 80.2 on the test set. This is close to cutting-edge information extraction performance before applying the recent deep learning algorithms.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.1
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• pp.80-84
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• 2000

Tumors of the parotid gland are the most frequently encountered salivary gland tumors. Knowledge of the histology and anatomy of the salivary gland is important when considering the histiogenesis of salivary gland tumors, requiring close cooperation between the pathologist and the surgeon. Most tumors are benign epithelial formations. Pleomorphic adenomas predominate. Superficial lobectomy is adequate treatment. When the tumor involves a deep lobe, total parotidectomy is indicated. Treatment of malignant tumors depends on the histology, its TNM stage and other factors. Total parotidectomy with lymph adectomy and radiotherapy are needed in case of high grade malignancy. In children, vascular neoplasias are the most frequent, followed by malignant tumors. Their histological features and treatment are the same as for adults. We reviewed 64 cases of the parotid tumors at Department of surgery, Dong-A University Hospital from July. 1990 to Jan. 1999 for the purpose of apprehension of parotid gland tumor by the clinical study and review. Over all sex ratio was 1：1.13(M:F), mean age was 38.9 years, mean size was 3.53cm. According to histologic findings of 64 cases, pleomorphic adenoma was 55(85.9%), Warthin's tumor was 3(4.7%), mucoepidermoid carcinoma was 3(4.7%), squamous cell carcinoma was 2(3.1%), acinic cell carcinoma was 1(1,6%). Post op. facial nerve palsy 16(25%), Frey's syndrome 11(17.2%) cases were happened. Hence, the clinical manifestation of pain, tenderness, facial N. palsy suggest malignant tumors.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.69.1-69.1
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• 2011

While the Virgo Cluster Catalog (VCC) is well established catalog from deep photographic plate survey, with available survey data recently released (e.g., SDSS), it can be further updated concerning the membership and morphology of galaxies. While membership and morphology of galaxies included in the VCC are based on the single band imaging data, thanks to the multi-color imaging and spectroscopic observations of SDSS, we are able to revise the membership and morphology of sample galaxies in the fields of the Virgo cluster. We present a new catalog of galaxies in the Virgo cluster using SDSS DR7 data, the extended Virgo cluster catalog. Using SDSS imaging and spectroscopic data, we introduce two kinds of galaxy classifications which are complementary each other. In addition to traditional morphological classification by visual inspection of the images ("Primary Classification"), we also attempt to classify galaxies with the spectroscopic features ("Secondary Classification"). The primary classification is basically based on the scheme of galaxy morphological classification of VCC. The secondary classification relies on the SED shape and presence of emission/absorption lines returned from SDSS. Our morphological classifications allow to study the evolution and associated star formation histories of galaxies in the Virgo cluster.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.93-96
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• 2008

We analyze a precise seabed feature around the Hupo Bank by using Multi-beam echosounder. Multi-beam echosounder system can observe the topography undulation according to the navigation of the survey ship by shooting wide beam. It is possible to embody a precision seabed feature because it can be make high density of incompletion depth sounding between survey lines. Through this survey, there is the Hupo Bank which is 84 km long, 1-15 km wide, 5.3-160 m deep in the center, at the west is moat, at the east is scarp and submarine canyon. The top of the Hupo Bank is the Wangdol reef that has 5.3 m in depth of water at least. Moat in survey area is 30 m long, and 30-40 m wide and has a depressed channel. The gap of depth of water in scarp is approximately 60 m and shows a characteristic of cuttig plane. Submarine canyon is 3.5 - 13.5 km wide.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.447-453
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• 2020

In this paper, we propose a system to extract effective speaker representations from a speech signal using a deep learning method. Based on the fact that speech signal contains identity unrelated information such as text content, emotion, background noise, and so on, we perform a training such that the extracted features only represent speaker-related information but do not represent speaker-unrelated information. Specifically, we propose an auto-encoder based disentanglement method that outputs both speaker-related and speaker-unrelated embeddings using effective loss functions. To further improve the reconstruction performance in the decoding process, we also introduce a discriminator popularly used in Generative Adversarial Network (GAN) structure. Since improving the decoding capability is helpful for preserving speaker information and disentanglement, it results in the improvement of speaker verification performance. Experimental results demonstrate the effectiveness of our proposed method by improving Equal Error Rate (EER) on benchmark dataset, Voxceleb1.