• Journal of Digital Contents Society
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• v.9 no.4
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• pp.759-769
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• 2008

Convergence technology stimulating participation sharing openness to the public of web 2.0 such as Open-API, Mash-Up, Syndication gives diversity to education field. The convergence in education field means the revolution toward education 2.0 and new education reflecting web 2.0 stream is called 'education 2.0'. Education environment can be the space of social network intimately linked between learners, educators and educational organization. Network technology developed in ontology language makes it possible to educate semantically which understands privatized education service and connection. Especially, filtering system by the reputation system of Amazon and the collective intelligence of Wikipedia are the best samples. Education area can adopt actively because learners as educational main body can broaden their role of participation and communicate bilaterally in the equal position. In this paper, new network architecture in contents linkage is introduced and researched for utilization and analysis of the architecture for web 2.0 technology and educational contents are to be converged. Education 2.0 service utilizing convergence technology and network architecture for realizing education 2.0 is introduced and analyzed so that the research could be a preceding research to the education 2.0 platform foundation.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.81-87
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• 2015

This study will show the digital forensic model which fights against cyber-crimes to prepare various cyber-crimes. The digital forensic model will be more useful about the investigation of cyber-crimes and arresting criminals after researching the uses of the digital forensic model and cyber-crime rates in South Korea. This model conduct the standardized data with various languages by the language support system through the digital forensic analyzer. This model will send the data to law enforcement reviewing whether or not we ought to prove criminal charges. Moreover, law enforcement can access the file system to find out admissibility of evidence. And this model simplifies lawful investigation about additional investigation. The data, which is conducted and saved by the digital forensic system, will be helpful to protect against the future crimes because of the data.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.117-121
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• 2008

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Therefore, the energy consumption is important in the routing design, otherwise cluster schemes are efficient in energy conserving. For the above reasons, an Energy conserving Context aware Clustering algorithm (ECC) is proposed to establish the network clustering structure, and a routing algorithm is introduced to choose the Optimal Energy Routing Protocol (OERP) path in this paper. Because in ad hoc network, the topology, nodes residual energy and energy consuming rate are dynamic changing. The network system should react continuously and rapidly to the changing conditions, and make corresponding action according different conditions. So we use the context aware computing to actualize the cluster head node, the routing path choosing. In this paper, we consider a novel routing protocol using the cluster schemes to find the optimal energy routing path based on a special topology structure of Resilient Ontology Multicasting Routing Protocol (RODMRP). The RODMRP is one of the hierarchical ad hoc network structure which combines the advantage of the tree based and the mesh based network. This scheme divides the nodes in different level found on the node energy condition, and the clustering is established based on the levels. This protocol considered the residual energy of the nodes and the total consuming energy ratio on the routing path to get the energy efficiently routing. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.295-304
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• 2011

To effectively manage research information in the field of national defense, metadata about the information should be managed systematically, and an integrated system to help convergence and management of the information should be implemented based on the metadata. In addition, the system should provide the users with effective integrated search services in a mobile environment, because searching via the use of mobile devices is increasing. The objective of this paper is to suggest a MSISS (Mobile Semantic Integrated Search System), which satisfies the requirements for effective management of the national defense research information. Specifically, we defined national defense research ontologies and national defense research rules after analyzing the Dublin Core metadata and database information of the major military research institutions. We implemented a prototype system for MSISS to demonstrate the use of the ontologies and rules for semantic integrated searching of the military research information. We also presented a triple-based search service to support semantic integrated search in a mobile environment and suggested future mobile semantic integrated search services.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.666-675
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• 2019

Background: Korean Red Ginseng (KRG) has been widely used as an herbal medicine to normalize and strengthen body functions. Although many researchers have focused on the biological effects of KRG, more studies on the action mechanism of red ginseng are still needed. Previously, we investigated the proteomic changes of the rat spleen while searching for molecular signatures and the action mechanism of KRG. The proteomic analysis revealed that differentially expressed proteins (DEPs) were involved in the increased immune response and phagocytosis. The aim of this study was to evaluate the biological activities of KRG, especially the immune-enhancing response of KRG. Methods: Rats were divided into 4 groups: 0 (control group), 500, 1000, and 2000 mg/kg administration of KRG powder for 6 weeks, respectively. Isobaric tags for relative and absolute quantitation was performed with Q-Exactive LC-MS/MS to compare associated proteins between the groups. The putative DEPs were identified by a current UniProt rat protein database search and by the Gene Ontology annotations. Results: The DEPs appear to increase the innate and acquired immunity as well as immune cell movement. These results suggest that KRG can stimulate immune responses. This analysis refined our targets of interest to include the potential functions of KRG. Furthermore, we validated the potential molecular targets of the functions, representatively LCN2, CRAMP, and HLA-DQB1, by Western blotting. Conclusion: These results may provide molecular signature candidates to elucidate the mechanisms of the immune response by KRG. Here, we demonstrate a strategy of tissue proteomics for the discovery of the molecular function of KRG.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1144-1172
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• 2022

Salmonella enterica serovar Typhimurium isolate HJL777 is a virulent bacterial strain in pigs. The high rate of salmonella infection are at high risk of non-typhoidal salmonella gastroenteritis development. Salmonellosis is most common in young pigs. We investigated changes in gut microbiota and biological function in piglets infected with salmonella via analysis of rectal fecal metagenome and intestinal transcriptome using 16S rRNA and RNA sequencing. We identified a decrease in Bacteroides and increase in harmful bacteria such as Spirochaetes and Proteobacteria by microbial community analysis. We predicted that reduction of Bacteroides by salmonella infection causes proliferation of salmonella and harmful bacteria that can cause an intestinal inflammatory response. Functional profiling of microbial communities in piglets with salmonella infection showed increasing lipid metabolism associated with proliferation of harmful bacteria and inflammatory responses. Transcriptome analysis identified 31 differentially expressed genes. Using gene ontology and Innate Immune Database analysis, we identified that BGN, DCN, ZFPM2 and BPI genes were involved in extracellular and immune mechanisms, specifically salmonella adhesion to host cells and inflammatory responses during infection. We confirmed alterations in gut microbiota and biological function during salmonella infection in piglets. Our findings will help prevent disease and improve productivity in the swine industry.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.37-43
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• 2023

In today's business landscape, collaboration and interoperability are crucial for organizational success and profitability. However, integrating operations across multiple organizations is challenging due to differing roles and policies in Identity and Access Management (IAM). User-centric identity (UCI) adopts a personalized approach to digital identity management, centering on the end-user for authentication and access control. It provides a decentralized system that ensures secure and customized access for each user. UCI aims to address complex security challenges by aligning access privileges with individual user requirements. This research delves into UCI's ability to streamline resource access amidst conflicting IAM roles and protocols across various organizations. The study presents a UCI-based multi-domain access control (MDAC) framework, which encompasses an ontology, a unified method for articulating access roles and policies across domains, and software services melding with UCI infrastructure. The goal is to enhance organizational resource management and decision-making by offering clear guidelines on access roles and policy management across diverse domains, ultimately boosting companies' return on investment.

• Journal of Life Science
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• v.34 no.7
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• pp.465-475
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• 2024

Lactiplantibacillus plantarum K9 is a probiotic strain that can be utilized from various bioactive substances isolated from Protaetia brevitarsis seulensis larvae. In this study, a genetic analysis of L. plantarum K9 revealed the existence of a bacterial chromosome and three plasmids. The glycolysis pathway and pentose phosphate pathway were examined for their normal functioning via an analysis of the core metabolic pathways of L. plantarum K9. Since the key enzymes, fluctose-1,6-bisphospatase (EC: 3.1.3.11) and 6-phosphogluconate dehydratase (EC: 4.2.1.12)/2-keto-deoxy-6-phosphogluconate (KDPG) aldolase (EC: 4.2.1.55), of gluconeogenesis and the ED pathway were not identified from the L. plantarum K9 genome, we suggest that gluconeogenesis and the ED pathway are not performed in L. plantarum K9. Additionally, while some enzymes, related to fumarate and malate biosyntheses, involved in the TCA cycle were identified from L. plantarum K9, the enzymes associated with the remaining TCA cycle were absent, indicating that the TCA cycle cannot proceed. Meanwhile, based on our findings, we propose that the oxidative electron transport system performs class IIB-type (bd-type) electron transfer. In summary, we assert that L. plantarum K9 performs homolactic fermentation, executes gluconeogenesis and the pentose phosphate pathway, and carries out energy metabolism through the class IIB-type oxidative electron transport system. Therefore, we suggest that L. plantarum K9 has relatively high lactic acid production, and that it has excellent antibacterial activity, as a result, compared to other lactic acid bacterial strains. Moreover, we speculate that L. plantarum K9 has an oxidative electron transport capability, indicating that it is highly resistant to oxygen and suggesting that it has fine cultivation characteristics, which collectively make it highly suitable for use as a probiotic.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.