• The Korean Journal of Food And Nutrition
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• v.31 no.4
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• pp.495-501
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• 2018

Ultraviolet B (UVB) exposure is a risk factor for skin damage resulting in oxidative stress, inflammation, and cell death. The purpose of this study was to investigate the physicochemical properties of Platycodon grandiflorum (PG) to improve its biological activities using a three-step steaming process. We investigated the protective effects of PG and steamed PG extracts on human dermal fibroblasts (HDFs) against UVB radiation-induced oxidative stress and inflammation as well as the underlying mechanisms. The antioxidant potential of the PG extracts was evaluated by measuring the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS) scavenging activity. ABTS and DPPH were shown by the 0, 30, and 70% ethanol extracts of 2S-PG and 3S-PG ($IC_{50}$, 28~45 and $27{\sim}30{\mu}g/mL$, respectively). Treatment of UVB-irradiated cells with steamed PG ($25{\sim}400{\mu}g/mL$) did not affect their viability. The streamed PG extract suppressed UVB-induced generation of reactive oxygen species (ROS). In addition, streamed PG extract reduced cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) protein expression in UVB-irradiated HDF, regulating nuclear factor $(NF)-{\kappa}B$ expression. These findings suggest that steamed PG extract may be potentially effective against inflammation associated with UVB-induced oxidation stress.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.4
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• pp.141-146
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• 2015

Data have been increased enormously due to the development of IT technology such as recent smart equipments, social network services and streaming services. To meet these environments the technologies that can treat mass data have received attention, and the typical one is Hadoop. Hadoop is on the basis of open source, and it has been designed to be used at general purpose computers on the basis of Linux. To initial Hadoop nearly no security was introduced, but as the number of users increased data that need security increased and there appeared new version that introduced Kerberos and Token system in 2009. But in this method there was a problem that only one secret key can be used and access permission to blocks cannot be authenticated to each user, and there were weak points that replay attack and spoofing attack were possible. Hence, to supplement these weak points and to maintain efficiency a protocol on the basis of group key, in which users are authenticated in logical group and then this is reflected to token, is proposed in this paper. The result shows that it has solved the weak points and there is no big overhead in terms of efficiency.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.6
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• pp.950-955
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• 2010

In this study, we prepared CheonJeongKiBo-Dan(7 oriental medicinal plants, 7OMP: Astragalus Membranaceus root, Panax Ginseng root, Glycyrrhiza Glabra (licorice) root, Schizandra Chinensis fruit, Polygonatum Odoratum, Rehmannia Glutinosa root, Paeonia Albiflora root) by extracting them in one reactor and studied its efficacies on skin. UV irradiation has been suggested as a major cause of photoaging in skin. In order to investigate protective effects against UV-B induced cellular damage, 7OMP was extracted with 70% ethanol and dissolved in DMSO. The protective effect was detected by MTT assay, reactive oxygen species (ROS) generation, phosphorylation of ATR and p53 in human dermal fibroblast cell system after UV-B irradiation. 7OMP reduced UV-B-induced cellular damage in HDFs cells, and inhibited ROS generation. UV-B-induced toxicity accompanying ROS production and the resultant DNA damage are responsible for activation of ATR, p53 and Bad. In this study, 7OMP hampered phosphorylations of ATR and p53 in human dermal fibroblasts. Therefore, 7OMP may be protective against UV-induced skin photoaging.

• Journal of Pharmacopuncture
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• v.20 no.3
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• pp.213-219
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• 2017

Objectives: Based on data from Chinese and Indian traditional herbal medicines, gum resin of Ferula assa-foetida (sometimes referred to asafetida or asafoetida) has several therapeutic applications. The authors of various studies have claimed that asafetida has cytotoxic, antiulcer, anti-neoplasm, anti-cancer, and anti-oxidative effects. In present study, the anti-aging effect of asafetida on senescent human dermal fibroblasts was evaluated. Methods: Senescence was induced in in vitro cultured human dermal fibroblasts (HDFs) through exposure to $H_2O_2$, and the incidence of senescence was recognized by using cytochemical staining for the activity of ${\beta}$-galactosidase. Then, treatment with oleo gum resin of asafetida was started to evaluate its rejuvenating effect. The survival rate of fibroblasts was evaluated by using methyl tetrazolium bromide (MTT) assays. Real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blot assays were performed to evaluate the expressions of apoptotic and anti-apoptotic markers. Results: Our experiments show that asafetida in concentrations ranging from $5{\times}10^{-8}$ to $10^{-7}g/mL$ has revitalizing effects on senescent fibroblasts and significantly reduces the ${\beta}$-galactosidase activity in these cells (P < 0.05). Likewise, treatment at these concentrations increases the proliferation rate of normal fibroblasts (P < 0.05). However, at concentrations higher than $5{\times}10^{-7}g/mL$, asafetida is toxic for cells and induces cell death. Conclusion: The results of this study indicate that asafetida at low concentrations has a rejuvenating effect on senescent fibroblasts whereas at higher concentrations, it has the opposite effect of facilitating cellular apoptosis and death.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1431-1438
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• 2014

We analyzed the articles from "Kukje Shinmun" and "Busan Ilbo", which are two local newpapers of Busan Metropolitan City. The articles cover from January 1, 2013 to December 31, 2013. Meaningful pattern inherent in 2889 articles of which the title includes "Busan" and "Traffic" and related data was analyzed. Textmining method, which is a part of datamining, was used for the social network analysis (SNA). HDFS and MapReduce (from Hadoop ecosystem), which is open-source framework based on JAVA, were used with Linux environment (Uubntu-12.04LTS) for the construction of unstructured data and the storage, process and the analysis of big data. We implemented new algorithm that shows better visualization compared with the default one from R package, by providing the color and thickness based on the weight from each node and line connecting the nodes.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.989-1009
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• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• Journal of KIISE
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• v.43 no.7
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• pp.736-743
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• 2016

Several studies have reported the impact of core affinity on the network I/O performance of multi-core systems. As the network bandwidth increases significantly, it becomes more important to determine the effective core affinity. Although a framework for dynamic core affinity that considers both network and disk I/O has been suggested, the multiple queues provided by high-speed I/O devices are not properly supported. In this paper, we extend the existing framework of dynamic core affinity to efficiently support the multiple queues of high-speed I/O devices, such as 40 Gigabit Ethernet and NVM Express. Our experimental results show that the extended framework can improve the HDFS file upload throughput by up to 32%, and can provide improved scalability in terms of the number of cores. In addition, we analyze the impact of the assignment policy of multiple I/O queues across a number of cores.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.45-51
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• 2021

In accordance with the rapid non-face-to-face environment and mobile first strategy, the explosive increase and creation of many structured/unstructured data every year demands new decision making and services using big data in all fields. However, there have been few reference cases of using the Hadoop Ecosystem, which uses the rapidly increasing big data every year to collect and load big data into a standard platform that can be applied in a practical environment, and then store and process well-established big data in a relational database. Therefore, in this study, after collecting unstructured data searched by keywords from social network services based on Hadoop 2.0 through three virtual machine servers in the Spring Framework environment, the collected unstructured data is loaded into Hadoop Distributed File System and HBase based on the loaded unstructured data, it was designed and implemented to store standardized big data in a relational database using a morpheme analyzer. In the future, research on clustering and classification and analysis using machine learning using Hive or Mahout for deep data analysis should be continued.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1544-1553
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• 2018

Recently internal information leakage in industries is severely increasing in spite of industry security policy. Thus, it is essential to prepare an information leakage prevention measure by industries. Most of the leaks result from the insiders, not from external attacks. In this paper, a real-time internal information leakage prevention system via both storage and network is implemented in order to protect confidential file leakage. In addition, a Hadoop-based user behavior analysis and statistics system is designed and implemented for storing and analyzing information log data in industries. The proposed system stores a large volume of data in HDFS and improves data processing capability using RHive, consequently helps the administrator recognize and prepare the confidential file leak trials. The implemented audit system would be contributed to reducing the damage caused by leakage of confidential files inside of the industries via both portable data media and networks.