• The Journal of Korea Assosiation for Disability and Oral Health
• /
• v.15 no.1
• /
• pp.50-54
• /
• 2019

Muscular dystrophy (MD) is a heterogeneous group of inherited neuromuscular disorders, characterized by progressive muscle weakness. Severity of the disease ranges from mild to severe, and the disease is mostly caused by mutations in a number of genes. These genetic mutations cause lack of proteins which are essential for muscle cell stability. Muscle fibers are gradually replaced by fat and fibrous tissue. The muscles of the head and neck are affected in several types of MD that manifest as altered craniofacial morphology and dental malocclusion. A 3-year-10-month old, 15.0 kg boy with MD presented to Seoul National University Dental Hospital, Seoul, South Korea because of extensive carious teeth. A number of dental caries in primary dentition were identified during clinical oral examination. Due to dental anxiety and underlying systemic disease, general anesthesia was considered. General anesthesia was induced and maintained with intravenous anesthetics, propofol and remifentanil. Caries treatments - resin restoration, pulpectomy, zirconia crown restoration, stainless steel crown restoration - were performed. Under general anesthesia, successful dental procedure was done. Total intravenous anesthesia (TIVA) was performed instead of inhalation anesthesia in order to avoid risk of complications such as malignant hyperthermia and life-threatening rhabdomyolysis. With decreasing muscle function, plaque control becomes more difficult and leads to gingivitis. Especially, the open-mouth posture worsens gingivitis and can leads to malocclusions and problems in swallowing. Regular and periodic dental care is essential for maintaining oral health for patients with MD.

• Journal of Life Science
• /
• v.29 no.5
• /
• pp.530-536
• /
• 2019

Glioblastoma (GBM) is the most incurable brain cancer derived from the transformed glial cells. Standard anti-GBM treatment, including surgery and chemoradiotherapy, does not ensure good prognosis for the patients with GBM, because successful therapy is often impeded by presence of glioma stem cells (GSCs). GSCs, which is generally divided into proneural (PN) and mesenchymal (MES) subtype, are understood as subpopulation of cancer cells responsible for GBM initiation, progression and recurrence after standard treatments. In the present study, we demonstrate that PN subtype GSCs differentially transit to MES subtype GSCs by specific cytokines. The expression of CD44, a marker of MES subtype GSCs, was observed when GSC11 PN subtype GSCs were exposed to tumor necrosis factor alpha ($TNF-{\alpha}$) cytokine and GSC23 PN subtype GSCs were treated to transforming growth factor beta 1 ($TGF-{\beta}1$) cytokine. Ivy glioblastoma atlas project (Ivy GAP) bioinformatics database showed that $TNF-{\alpha}$ and $TGF-{\beta}1$ were highly expressed in necrotic region and perivascular region, respectively. In addition, $TNF-{\alpha}$ signaling was relatively upregulated in necrotic region, while $TGF-{\beta}$ signaling was increased in perivascular region. Taken together, our observations suggest that MES subtype GSCs can be derived from various PN subtype GSCs by multimodal cytokine stimuli provided by neighboring tumor microenvironment.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.10
• /
• pp.285-290
• /
• 2021

In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.

• Journal of the Korean Society of Radiology
• /
• v.79 no.6
• /
• pp.340-347
• /
• 2018

Purpose: To evaluate value of image subtraction for identifying hepatocellular carcinoma (HCC) capsule on gadoxetic acid-enhanced MR images. Materials and Methods: This study involved 108 patients at risk of HCC preoperatively examined using gadoxetic acid-enhanced MRI with hepatic resection between May 2015 and February 2017. We evaluated qualities of subtraction images and presence of capsular appearance on portal venous or transitional phases conventional and subtraction images. We assessed effect of capsular appearance on subtraction images on HCC. Results: After excluding 1 patient who had treated by transarterial chemoembolization prior to surgery and 33 patients with unsatisfactory subtraction image qualities, 82 focal hepatic lesions (73 HCC, 5 non-HCC malignancies, and 4 benign) from 74 patients were analyzed. Regarding detection of capsules, sensitivity, accuracy, and area under the receiver operating characteristic curve (AUC) on subtraction images were significantly higher than those on conventional images (95.4%, 89.0%, and 0.80, respectively; p < 0.001), though specificities were same (64.7%). For diagnosis of HCC, sensitivity, accuracy, and AUC on subtraction images were significantly higher than on conventional images (82.2%, 79.3%, and 0.69, respectively; p = 0.011), though specificities were identical (55.6%). Conclusion: Portal venous or transitional phase gadoxetic acid-enhanced MRI subtraction images could improve detection of HCC capsule.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.20 no.6
• /
• pp.183-194
• /
• 2010

A company's private network protected by a firewall and NAT(Network Address Translation) is not accessible directly through an external internet. However, as Reverse Connection technology used by NetCat extends to the technologies such as SSH Tunnel or HTTP Tunnel, now anyone can easily access a private network of corporation protected by a firewall and NAT. Furthermore, while these kinds of technologies are commercially stretching out to various services such as a remote control and HTTP Tunnel, security managers in a company or general users are confused under the circumstances of inner or outer regulation which is not allowed to access to an internal system with a remote control. What is more serious is to make a covert channel invading a company's private network through a malicious code and all that technologies. By the way, what matters is that a given security system such as a firewall cannot shield from these perceived dangers. So, we analyze the indirect access of technological methods and the status quo about a company's internal network and find a solution to get rid of the related dangers.

• Journal of Internet Computing and Services
• /
• v.21 no.6
• /
• pp.13-21
• /
• 2020

The Android author identification study can be interpreted as a method for revealing the source in a narrow range, but if viewed in a wide range, it can be interpreted as a study to gain insight to identify similar works through known works. The problem found in the Android author identification study is that it is an important code on the Android system, but it is difficult to find the important feature of the author due to the meaningless codes. Due to this, legitimate codes or behaviors were also incorrectly defined as malicious codes. To solve this, we introduced the concept of survival network to solve the problem by removing the features found in various Android apps and surviving unique features defined by authors. We conducted an experiment comparing the proposed framework with a previous study. From the results of experiments on 440 authors' identified apps, we obtained a classification accuracy of up to 92.10%, and showed a difference of up to 3.47% from the previous study. It used a small amount of learning data, but because it used unique features without duplicate features for each author, it was considered that there was a difference from previous studies. In addition, even in comparative experiments with previous studies according to the feature definition method, the same accuracy can be shown with a small number of features, and this can be seen that continuously overlapping meaningless features can be managed through the concept of a survival network.

• Journal of Internet Computing and Services
• /
• v.22 no.3
• /
• pp.27-35
• /
• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.449-455
• /
• 2020

Inventory management is one of the important business functions for manufacturing companies to determine market responsiveness. Customers' needs are diversifying, and the life cycle of products is decreasing, thus increasing the importance of inventory management. However, for small-scale manufacturing companies, investing in an IT system for inventory management is practically difficult. In this study, we introduce an inventory and warehouse management model that can be applied simply and quickly in small-scale manufacturing companies. Firstly, we introduce the concept of the properties of inventory and provide an analytical methodology based on the age and quantity of the inventory. Secondly, in accordance with the properties of the inventory, we introduce location management rules for warehouse operation. To apply the proposed model, we studied a wallpaper manufacturing company and verified the applicability of the proposed methods in the field. The proposed model can be applied immediately as part of on-site improvement activities by small-scale manufacturing companies, and inventory management activities are expected to reduce bad long-term inventory and further secure storage capacity for warehouses.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.197-207
• /
• 2021

Relationship between bone mineral density (BMD) and type 2 diabetes is still inconsistent. Recently, many epidemiologic data show that fracture risk is increased in type 2 diabetic patients regardless of BMD status. In this study, we used nation-wide data from 2008 to 2011 Korea National Health and Nutrition Examination Survey (KNHANES) to analyze the BMD status in patients with type 2 diabetes compared to non-diabetics. We included subjects aged 50 years or older in men (N=2,959, 2,430 without diabetes, 529 with type 2 diabetes) and postmenopausal women (N=2,902, 2,479 without diabetes, 423 with type 2 diabetes). Subjects with history of medication for osteoporosis or with illness or malignancy affecting bone metabolism were excluded. Data of anthropometric measurements and demographic characteristics were collected by trained examiner. Serum was separated from peripheral venous blood samples obtained after 8 hours of fasting. BMD was measured at lumbar spine and femur using dual-energy X-ray absorptiometry (DXA). There was a significant positive association between lumbar spine BMD and type 2 diabetes after adjusting age, gender, body mass index, monthly house income, education level, physical activity, daily calcium intake and vitamin D concentration by multiple regression analysis in all subjects. In the subgroup analysis by gender, this association was maintained both in male and female after adjusting those confounding factors. However, femur BMD was not different between type 2 diabetic and non-diabetic subjects. In conclusion, lumbar spine BMD was significantly higher in type 2 diabetic patients aged 50 years or more in men and postmenopausal women compared to non-diabetic subjects.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.209-220
• /
• 2021

The effect of body composition such as lean mass and fat mass on bone mineral density (BMD) is complex and still controversial. In this study, we investigated the relationship between body composition and bone mineral density using nation-wide data from 2008 to 2011 Korea National Health and Nutrition Examination Survey (KNHANES) in 2,139 men and 2,193 postmenopausal women aged 50 years or older. Subjects with history of medication for osteoporosis or with diseases or malignancy affecting bone metabolism were excluded. Data of anthropometric measurements and demographic characteristics were collected by trained examiner. Fasting blood sample was obtained for blood chemistry analysis. BMD of the lumbar spine, total femur, and femoral neck, and body composition such as total lean mass (TLM), total fat mass (TFM), truncal fat mass (TrFM) were measured using dual-energy X-ray absorptiometry (DXA). There were significant positive correlations between body composition indices such as lean mass and fat mass with BMD. In multiple regression analysis, TLM was positively associated with BMD after adjusting age, body mass index, monthly house income, education level, physical activity, daily calcium intake and vitamin D concentration in both men and postmenopausal women. BMD at lumbar spine and femur in lowest quartile of TLM was significantly lower than other quartiles after adjusting those confounding factors in both gender. TrFM was negatively associated with total femur BMD in male and femur neck BMD in postmenopausal women after adjusting confounding factors. In conclusion, TLM is very important factor in maintaining BMD in subjects aged 50 years or older in men and postmenopausal women.