• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.31 no.5
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• pp.379-389
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• 2005

Obstructive adenitis of the salivary gland following salivary stone or infectious disease of the gland and surrounding tissues is a common disease. It is often difficult to decide whether to perform total excision of the gland or to consider conservative treatment. The present study was designed to investigate histological, histochemical changes of submandibular gland after ligating the excretory duct for identifying the results of gland duct obstruction. A group of 40 rat of Sprague-Dawley weighing about $200{\sim}220gm$ were used in the present study. 30 rats had ligation of the main excretory ducts of submandibular glands just at the exit from the glands. For controls, 10 rats had a sham operation without duct ligation. They were inducted into euthanagia state by intracardial Ketamine injection in 1, 2, 3, 5, 7, 14, 21, 28, 35 and 42 days after the ligation. In each ligation period, 3 animals were used for ligation and one animal was for control. The submandibular glands were dissected out at sacrifice and stained with H&E, PAS, mucicarmine stain and histological examination were carried out under the light microscope. After examination and comparison of all specimens, the results were as follows: 1. In the features of H&E stain, acini disappeared by degrees after the ligation of the excretary duct and interstitial cells were displaced into fibrous connective tissue. Salivary gland had been atrophied with enlarging ducts and proliferating ductal cells. 2. Through total experimental period, a lot of vessels were observed and the atrophy of serous gland was severer than that of mucous gland. 3. The deep portion of submandibular glands showed severe degeneration rather than superficial portion of them after the ligation. 4. The changes which had enlarged ducts and proliferating ductal cells were observed in entire gland and more prominent in serous gland than mucous gland after the ligation. 5. Although PAS and mucicarmine reactions were decreased gradually after the ligation with the lapse of time, since 2 to 3 weeks they were strong positive reactions on entire gland, especially on duct-like structure. So, we can suggest that salivary gland will be atrophied but, survived acini will be redistributed around the ducts.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.32 no.5
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• pp.401-409
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• 2006

Infections of the oral and maxillofacial region are one of the most common conditions for which a patient presents to a maxillofacial surgeons. Although these infections can arise from a variety of source, dental disease is the most common etiology. So, odontogenic infection are frequently encountered in the practice of oral and maxillofacial surgery. These infections often respond to antimicrobial chemotherapy or surgical intervention, such as extraction of teeth, incision and drainage through clinical features. But, odontogenic infections have the potential to spread via the fascial spaces in the head and neck region, and, they spread to cavernous sinus, deep musculofascial space and other vital structure. We have undertaken clinical studies on infections in the oral and maxillofacial regions by analyzing retrospectively hospitalized patients in the Dept. of Oral and Maxillofacial Surgery, Chonbuk National University Hospital past 5 years from 2000 to 2004. And, the patients' age, sex, medical history, causes of the infection, surgical intervention, and other clinical parameters were reviewed. The obtained results were as follows : 1. The most frequent cause of oral and maxillofacial infection was odontogenic. And in the odontogenic cause, dental caries was the most common cause (47.2%). 2. The most common fascial space involved was the submandibular space (15.7%), followed by the buccal space (14.8%). 3. 60.4% of all patients required surgical drainage of the abscess, endodontic treatment or tooth extraction or periodontal treatment with drainage. 4. The most causative organism isolated from the pus culture were streptococcus viridans (53.9%). 5. Underlying medical problems were found in 136 patients (41.9%), the most common being hypertension (27.9%) and diabetes (14.7%).

• Tuberculosis and Respiratory Diseases
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• v.45 no.3
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• pp.596-603
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• 1998

Lambert Eaton myasthenic syndrome(LEMS) is a paraneoplastic syndrome caused by defects in the secretion of acetylcholine from the presynaptic membrane of nerve terminals and is strongly associated with small cell lung carcinoma. The pathogenesis of LEMS is the destruction of voltage gated calcium channels by an autoimmune process resulting in clinical manifestations consisting of lower extremity weakness. decreased deep tendon reflexes and autonomic dysfunctions. The diagnosis can be confirmed by the characteristic clinical features and repetitive nerve stimulation. The neurological symptoms and signs of LEMS may manifest themselves months before the clinical manifestation of the underlying malignancy. Therefore early diagnosis and treatment of the primary malignancy may become possible through the diagnosis of this rare paraneoplastic syndrome. We report a case of a patient diagnosed with LEMS who upon further evaluation for an underlying malignancy was found to have a 0.2 cm sized nodular and infiltrative mass lesion at the bifurcation of the left apicoposterior segmental and anterior segmental bronchi by bronchoscopy. Although repeated bronchoscopic biopsies of the lesion was not able to disclose malignancy, under strong clinical suspicion left upper lobectomy was performed and subsequently the diagnosis of small cell carcinoma of the lung was confirmed. Muscle weakness began to improve starting from a week after the surgery, then reached a plateau 2 weeks later. Muscle weakness improved further after the trial of anticancer chemotherapy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1119-1127
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• 2018

Most of the cyber attacks are caused by malicious codes. The damage caused by cyber attacks are gradually expanded to IoT and CPS, which is not limited to cyberspace but a serious threat to real life. Accordingly, various malicious code analysis techniques have been appeared. Dynamic analysis have been widely used to easily identify the resulting malicious behavior, but are struggling with an increase in Anti-VM malware that is not working in VM environment detection. On the other hand, static analysis has difficulties in analysis due to various packing techniques. In this paper, we proposed malware classification techniques regardless of known packers or unknown packers through the proposed model. To do this, we designed a model of supervised learning and unsupervised learning for the features that can be used in the PE structure, and conducted the results verification through 98,000 samples. It is expected that accurate analysis will be possible through customized analysis technology for each class.

• Journal of KIISE
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• v.42 no.3
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• pp.367-378
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• 2015

This study was directed at the design of a hybrid algorithm for competition relation extraction. Previous works on relation extraction have relied on various lexical and deep parsing indicators and mostly utilize only the machine learning method. We present a new algorithm integrating machine learning with various filtering methods. Some simple but useful features for competition relation extraction are also introduced, and an optimum feature set is proposed. The goal of this paper was to increase the precision of competition relation extraction by combining supervised learning with various filtering methods. Filtering methods were employed for classifying compete relation occurrence, using distance restriction for the filtering of feature pairs, and classifying whether or not the candidate entity pair is spam. For evaluation, a test set consisting of 2,565 sentences was examined. The proposed method was compared with the rule-based method and general relation extraction method. As a result, the rule-based method achieved positive precision of 0.812 and accuracy of 0.568, while the general relation extraction method achieved 0.612 and 0.563, respectively. The proposed system obtained positive precision of 0.922 and accuracy of 0.713. These results demonstrate that the developed method is effective for competition relation extraction.

• The Journal of Korean Medicine
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• v.32 no.6
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• pp.10-17
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• 2011

Background: Vibration response imaging (VRI) is a new technology that records energy generated by airflow during the respiration cycle. Analysis of lung sound using VRI may overcome the limitations of auscultation. Objectives: To set a VRI standard for healthy Koreans, we conducted a clinical assessment to evaluate breath sound images and quantification in healthy subjects and compared the findings with reported breath sound characteristics. Methods: Recordings were performed using the VRIxp. Eighty subjects took a deep breath four times during a 12-second interval while sitting upright. The quantitative aspect was analyzed using the VRI quantitative lung data (QLD) for total left lung, total right lung and for six lung regions: left upper lung (LUL), left middle lung (LML), left lower lung (LLL), right upper lung (RUL), right middle lung (RML), right lower lung (RLL). The qualitative aspect was provided through image assessments by three reviewers. Results: In all regions the left lung had significantly higher QLD than the right lung (P<0.005, paired t-test). The inter-rater agreement was 0.78. 84% of the images were found normal by the final assessment. Among the 16% (n=13) of images with abnormal final assessment, the most common flawed features were dynamic image (77%, n=10) and maximum energy frame (MEF) shape (77%, n=10). No significant differences were found between males and females for QLD but there were significant differences in qualitative aspects including dynamic images, MEF shape, and missing LLL. Conclusion: The characteristics of healthy Koreans are similar to those of Western subjects reported previously. VRI is easy to use and objective, and so is helpful to diagnose patients with respiratory diseases and to monitor the progress of diseases after medical treatments.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.351-360
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• 2018

Human emotion recognition is a research topic that is receiving continuous attention in computer vision and artificial intelligence domains. This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, and audio in a wild environment. The proposed method has the following features. First, the learning performance of the image-based network is greatly improved by employing both multi-task learning and semi-supervised learning using the spatio-temporal characteristic of videos. Second, a model for converting 1-dimensional (1D) landmark information of face into two-dimensional (2D) images, is newly proposed, and a CNN-LSTM network based on the model is proposed for better emotion recognition. Third, based on an observation that audio signals are often very effective for specific emotions, we propose an audio deep learning mechanism robust to the specific emotions. Finally, so-called emotion adaptive fusion is applied to enable synergy of multiple networks. The proposed network improves emotion classification performance by appropriately integrating existing supervised learning and semi-supervised learning networks. In the fifth attempt on the given test set in the EmotiW2017 challenge, the proposed method achieved a classification accuracy of 57.12%.

• Ocean and Polar Research
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• v.24 no.4
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• pp.345-357
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• 2002

Ecological characteristics on habitats and morphological features of the seagrass Zostera caulescens Miki in Korea were examined. The biogeographical distribution of Z. caulescens was confirmed in the south coast of the Korea. Zostera caulescens usually inhabits at the inner bay, where is sheltered from wave action and 3.0 to 6.5 m deep. The sediment in habitats is composed of very fine muddy sand or sandy mud. In morphology, Z. caulescens is easily distinguished from other species of the genus by the formation of vegetative canopy on the top of reproductive stems. The number of longitudinal ribs in testa was 24 revealed by scanning electron microscope (SEM) while the number of ribs in Z. marina has been often reported to be 16-20. Purplish anthocyanin spots were displayed on the surface when the testa was removed. We found that the size and shape of leaf epidermal cells in Z. caulescens were very different from those of Z. marina when the leaf cuticles were removed by maceration which could be useful characters for identifying Zostera species. The leaf of Z. caulescens displays two different casts of color when the fresh plant is closely observed. The margins of leaves appear brighter than the center of leaves due to the thickening by the development of paralleled venation in the middle of leaves. The comparison of two populations of Z. caulescens in Korea showed that they were considerably different in their shoot density and biomass. The shoot density and biomass at Gabae population was $367.3 m^{-2}\;and\;725.7g$ dry wt $m^P{-2}$ respectively, while those at Jukrim population were $112.5m^{-2}\;and\;392.0g\;dry\;wt\;m^{-2}$, respectively.

• Cartoon and Animation Studies
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• s.40
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• pp.423-442
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• 2015

In a digital environment that is keep in change content from smart phones to tablet PC are a social network service is holding deep place in our lives. Social networking applications has building a network and communication with others than other application, it means that Social networking applications are sharing not only personal purpose in that trend of variety and competition of these social networks can be expected to trend and be developed thru analysis of user certification. this study of social network service application is proposed to developing of application thru analyze the two-effective application which is high ranked in google store. the theoretical foundation was set based on the seven elements of the social network service of the information structures designed by Jean Smith. This study proceeded analysis is for the functional elements of Facebook and Instagram, and the advantages and disadvantages through survey research. As a result of the empirical analysis to user of Instagram and face book of communication, identity, satisfaction for the group are equally. Instagram is about the presence, reputation, and Facebook has had a high level of satisfaction for each sharing and relationship. Facebook got high satisfaction from sharing features, but user feel of discomfort in the randomly showing advertising content. Instagram is not showing off advertise on common page of content, it is good point to be complementary to facebook. And, Instagram hashtag is good for convenience, but satisfaction is high with Facebook. in order to increase the satisfaction of Instagram, it is necessary to consider the main advantage of the communication and the functional aspects of the share from facebook.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.387-396
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• 2018

Stock price prediction has been a difficult problem to solve. There have been many studies to predict stock price scientifically, but it is still impossible to predict the exact price. Recently, a variety of types of cryptocurrency has been developed, beginning with Bitcoin, which is technically implemented as the concept of distributed ledger. Various approaches have been attempted to predict the price of cryptocurrency. Especially, it is various from attempts to stock prediction techniques in traditional stock market, to attempts to apply deep learning and reinforcement learning. Since the market for cryptocurrency has many new features that are not present in the existing traditional stock market, there is a growing demand for new analytical techniques suitable for the cryptocurrency market. In this study, we first collect and process seven cryptocurrency price data through Bithumb's API. Then, we use the gradient boosting model, which is a data-driven learning based machine learning model, and let the model learn the price data change of cryptocurrency. We also find the most optimal model parameters in the verification step, and finally evaluate the prediction performance of the cryptocurrency price trends.