• IMMUNE NETWORK
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• v.22 no.4
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• pp.30.1-30.3
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• 2022

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5095-5099
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• 2015

Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.

• Management & Information Systems Review
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• v.35 no.2
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• pp.221-254
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• 2016

With increasing interest of health due to population aging, medical device industry is highlighted as a promising industry. However, Korea medical device industry is not enough market competitiveness compared to global company due to a narrow domestic market and a small company structure. In order to retain the national competitiveness, it is necessary that we have to derive a central technology and its trend. This study has predicted a central technology for medical device industrial using patent network analysis. The central technology is defined as a key technology that is connected to most other technologies and that significantly affects them. For the empirical study, we conducted social network analysis using covariance and correlation coefficient between IPC codes extracted from medical device patents, introduced by Jun(2012). A social network is a social structure of diverse items as well as of human beings. In this study, we set each medical device as a node in an SNA and analyze the Degree values between them. Also, Korea health industrial statistics system are utilized for verification of selected central technology. As a result, we found that the central technology is located on the medical device items, which are listed higher the amount of production. The central technology selected through the proposed methodology will provide a inspiration for establishment of R&D policy.

• IMMUNE NETWORK
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• v.24 no.3
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• pp.22.1-22.1
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• 2024

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.73-81
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• 2011

The WBAN(Wireless Body Area Network) technology is a short distance wireless network which provides each device's interactive communication by connecting devices inside and outside of body located within 3 meters. Standardization on the physical layer, data link layer, network layer and application layer is in progress by IEEE 802.15.6 TG BAN. The The WBAN servides consists of both medical and non-medical applications. The medical application service uses the sensor that transfer the periodic traffic and have different data rates. It uses GTS method to guarantee QoS. In this paper, a new method is proposed, which are suitable design for MAC Protocol. Firstly, MAC frame structure and a primitive based on the WBAN are proposed. Secondly, we proposed the GTS algorithm improved the channel utilization based on the WFQ(Weighted Fair Queuing). The proposed scheduling method is improved channel utilization compared with i-Game(Round Robin scheduling method).

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.64-76
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• 2020

Scientometrics and social network analysis (SNA) measures were used to analyze the international scientific collaboration (ISC) of All India Institute of Medical Sciences (AIIMS) for a period of 10 years (2009-2018). The dataset consists of 19,622 records retrieved from the Scopus database. The mean degree of collaboration 0.95 implied that researchers of AIIMS tend to collaborate domestically (80.29%) and internationally (14.67%). The data exhibits a hyper authorship pattern, and a medium-size research team consists of 4 to 10 authors who contributed a maximum of 62.08% (12,182) publications. 71.97% of research findings are scattered in journal articles. The most preferred journals published 58.55% of medical literature. An undirected collaboration network is constructed in Pajek to study the ISC of AIIMS during the period 2009-2018 which consists of 179 vertices (Vn) and 11,938 edges. The degree centrality (Dc) identified that the United States of America (Dc - 54; CC - 0.99) and United Kingdom (Dc - 41; 0.98) are the most collaborative countries in the whole network as well as the most influential countries. The Louvain community detection method is used to detect influential research groups of AIIMS. The temporal evolution of ISC of AIIMS studied through scientometrics and SNA measures shed light on the structure and properties of ISC networks of AIIMS. It revealed that AIIMS, India has taken keen steps to enrich the quality of research by extending and encouraging the collaboration between institutions and industries at the international level.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2384-2392
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• 2015

The technical development and practical applications of big-data for health is one hot topic under the banner of big-data. Big-data medical image fusion is one of key problems. A new fusion approach with coding based on Spherical Coordinate Domain (SCD) in Wireless Sensor Network (WSN) for big-data medical image is proposed in this paper. In this approach, the three high-frequency coefficients in wavelet domain of medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on the multi-scale edge of medical image, it can be fused and reconstructed. Experimental results indicate the novel approach is effective and very useful for transmission of big-data medical image(especially, in the wireless environment).

• Nutrition Research and Practice
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• v.7 no.1
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• pp.9-14
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• 2013

Bamboo leaves (Phyllostachys pubescens Mazel ex J. Houz (Poacea)) have a long history of food and medical applications in Asia, including Japan and Korea. They have been used as a traditional medicine for centuries. We investigated the mechanism of anti-inflammatory activity of a bamboo leaf extract (BLE) on tumor necrosis factor-alpha (TNF-${\alpha}$)-induced monocyte adhesion in human umbilical vein endothelial cells (HUVECs). Exposure of HUVECs to BLE did not inhibit cell viability or cause morphological changes at concentrations ranging from 1 ${\mu}g/ml$ to 1 mg/ml. Treatment with 0.1 mg/ml BLE caused 63% inhibition of monocyte adhesion in TNF-${\alpha}$-activated HUVECs, which was associated with 38.4% suppression of vascular cell adhesion molecule-1 expression. Furthermore, TNF-${\alpha}$-induced reactive oxygen species generation was decreased to 47.9% in BLE treated TNF-${\alpha}$-activated HUVECs. BLE (0.05 mg/ml) also caused about 50% inhibition of interleukin-6 secretion from lipopolysaccharide-stimulated monocyte. The results indicate that BLE may be clinically useful as an anti-inflammatory or anti-oxidant for human cardiovascular disease including atherosclerosis.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.292-305
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• 2013

EPCglobal has proposed the EPC Sensor Network to efficiently integrate and interoperate the RFID and WSN technologies based on the international standard EPCglobal Network. However, it can not deal with the sensor data without EPS. Also, it does not provide enough management function for the sensor data only. This study proposes USN management system that can deal with these weaknesses of EPC Sensor Network. Not only that, it is suitable for the medical environment properly. In the medical environment, it is important for the medical information to be integrated and interconnected via the standard for medical data. This proposed USN management system is based on SIP-HL 7 and can send RFID and WSN data based on SIP(Session Initiation Protocol). It can be interconnected with the existing hospital information system and exchange the information. Also it can design and materialize SIP Interface based on HL7 that allows the medical information to be exchanged and sent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1955-1961
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• 2009

As a core technology realizing ubiquitous world, recent researches are being concentrated to wireless sensor network. However, most research results were focused to the sensor network technology itself, even though interworking between the sensor network and Internet is also one of primitive requirements for ubiquitous world. In this paper, we design the tiny TCP/IPv6 profile which makes it possible to inter-connect the sensor network device to IPv6 based Internet. To confirm operation of the designed profile, we experimentally implemented and evaluated minimum TCP/IPv6 based on TinyOS. The evaluation result shows that throughput of our tiny TCP/IPv6 is almost same as that of TinyOS component.