• Journal of Information Management
• /
• v.37 no.2
• /
• pp.1-20
• /
• 2006

It has lately been recognized that the sharing and exchanging of the research results information is the critical factor to improve the research productivity. So many institutions are planning or developing the information systems which provide the research information services for researcher. But it has very difficulty in integrating the research resources information due to the dispersion and heterogeneity in data sources, and semantic and structural difference in describing data. We propose the semantic web based methodology and conceptual framework for raising the interoperability of metadata about research results information, which will support the integration of the distributed research data for information services in the end. We first introduce the ontology which is developed based on Standard Metadata of Research Results Information published by STISC. Then to show the applicability in real-world environment, we express the metadata of research information in RDF/RDFS according to ontology. Finally we proposed the conceptual architecture of research information service system which shows the main components, the functional requirements, and the principal and design direction at implementing the system.

• The KIPS Transactions:PartD
• /
• v.11D no.5
• /
• pp.1063-1072
• /
• 2004

In the ASP(Application Service Provider) business, applications using database sometimes require some data from clients' databases. These days such data are extracted from client database using manual database operations as an EXCEL file and the ASP, once receiving this file, transfers it into the application's database using manual database operations. This paper describes how to deal with data transmitting between the client database and ASP database on the web without using database manual operations for data extraction and insertion. We propose a framework which enables to transmit client data in a systematical way, to match different attribute names of each database for sharing same attribute values, and to avoid exposing information about the network path of client database to the ASP. This approach consists of two steps of data processing. The first is extracting data from client database as XML format by using a downloaded client program from ASP site, the second is uploading and storing the XML file into the ASP database. The implemented prototype system shows the suggested data integration paradigm is valid and ASP business needing integration of client database can be activated using it.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.6
• /
• pp.309-314
• /
• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Korean Medicine Rehabilitation
• /
• v.34 no.1
• /
• pp.65-81
• /
• 2024

Objectives This study aimed to understand the general research trends, applicated disease, and methodology of transcutaneous/percutaneous vagus nerve stimulation, contemplating its clinical use in traditional Korean medicine and future research directions. Methods A scoping review was conducted following Arksey and O'Malley Framework Stage and adhering to the PRISMA extension for scoping reviews: checklist and explanation. Papers published until October 30, 2023, were investigated across 10 databases (PubMed, Embase, Scopus, Web of Science, China National Knowledge Infrastructure, Oriental Medicine Advanced Searching Integrated System, Korean Studies Information Service System, KMbase, Science ON, Research Information Sharing Service. The search terms used were 'Transcutaneous/Percutaneous vagus nerve stimulation'. Results Since 2021, the application of transcutaneous/percutaneous vagus nerve stimulation for musculoskeletal symptoms has been actively researched, predominantly in Asia (37%), Europe (37%), and North America (21%). All 19 papers were part of clinical studies. Chronic pain was noted that most applied disease, it also was found to potentially aid in acute post-surgical pain relief. Major assessment tools include not only simple pain metrics but also pain perception, vagal nerve tension, quality of life, and inflammatory markers. Most procedures were carried out through the ear, which offers a favorable site for therapeutic stimulation without notable side effects. And parameter analysis, frequencies typically ranged around 25 Hz to 30 Hz, while pulse widths were commonly set at 250 ㎲ or 300 ㎲. Conclusions Transcutaneous/percutaneous vagus nerve stimulation is easily accessible through acupuncture in Korean medicine. Therefore, if future studies establish parameters and clinical significance, it could be utilized as a therapeutic modality.

• The KIPS Transactions:PartD
• /
• v.11D no.1
• /
• pp.133-142
• /
• 2004

The next generation of web applications will need to be larger, more complex, and flexible Agent-oriented systems have great potential for these e-commerce applications. Agents can dynamically discover and compose e-services and mediate interactions. Development of software agents with CBD (Component Based Development) has proved to be successful in increasing speed to market of development Projects, lowering the development cost and providing better qualify. In this thesis, we propose a systemic development process for software agents using component and UML (Unified Modeling Language). We suggest a etA (e-business Agent) CBD reference architecture for layer the related components through identification and classification of general agent and e-business agent. We also propose the ebA-CBD process that is a guideline to consider the best features of existing agent oriented software engineering methodologies, while grounding agent-oriented concepts in the same underlying semantic framework used by UML. We first developed the agent components specification and modeled it with Goal, Role, Interaction, and Architecture Model. Based on this, we developed e-CPIMAS (e-Commerce Product Information Mailing Agent System) as a case study that provides the product information's mailing service according to proposed process formality. We finally describe how these concepts may assist in increasing the efficiency reusability, productivity and quality to develop the business application and e-business agent.

• Journal of the Korean Geographical Society
• /
• v.41 no.5 s.116
• /
• pp.582-599
• /
• 2006

Due to the growing popularity of mobile information technology, more people, especially in the general public, have access to computerized geospatial information systems for wayfinding tasks or urban navigation. One of the problems with the current services is that, whether the users are exploring or navigating, whether they are travelers who are totally new to a region or long-term residents who have a fair amount of regional knowledge, the same method is applied and the direction are given in the same way. However, spatial knowledge for a given urban region expands in proportion to residency. Urban navigation is highly dependent on cognitive mental images, which is developed through spatial experience and social communication. Thus, the wayfinding service for a regional community can be highly supported, using well-known regional places. This research is to develop the framework for urban navigation within a regional community. The concept of communal ontology is proposed to aid in urban regional navigation. The experimental work was implemented with case study to collect regional landmarks, develop the ontological model and represent it with formal structure. The final product of this study will provide the geographical information of a region to the other agent and be the fundamental information structure for cognitive urban regional navigation.

• KIISE Transactions on Computing Practices
• /
• v.21 no.2
• /
• pp.101-108
• /
• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• Asia pacific journal of information systems
• /
• v.18 no.1
• /
• pp.117-144
• /
• 2008

Lots of virtual communities and online businesses presently derive their primary sources of revenues through advertising, but nevertheless are plagued with marginal profitability though they might possess a significant user base. In the light of the need for an efficacious business model, there have been recent insights of an online community in particular reaping profits through an innovative and lucrative revenue generation method that earns by selling digital items. There have been some obvious evidences (e.g., Cyworld, SecondLife, Habo Hotel, etc.) that online communities can be profitable through their unique business model of selling digital items. However, there is lack of understanding about the motivation of purchasing digital items. This study tries to identify the main motivators of digital item purchases based on social/individual identity theory and self-presentation theory. "Digital items", otherwise known as "virtual assets", may include online avatars, accessories for the avatars, decorative ornaments like furniture, digital wallpapers, skins, background music and virtual weapons used for Internet games. These digital items are employed by users for representation and articulation in the online space, especially to create and enhance their online profiles in web pages and games. Prices for digital items typically range from a few cents to a few dollars each. Based on the theoretical framework like social identity theory and self-presentation theory, we developed the research model and proposed seven hypotheses. An analysis of 225 members of Cyworld found that digital item purchase intention in virtual world is affected by both members' need for self-presentation and need for affiliation. We also found that the need for self-presentation is significantly increased by innovativeness of members, community group norm, and community involvement. We concluded that the need for self-presentation could be a key variable for profitable business model in online community service industry. However, neither individual self-efficacy nor the need for affiliation significantly influenced the need for self-presentation which triggers purchase intention of digital items. In term of the theoretical and practical contribution, this study can be a pioneering empirical research that investigates the purchase intention of digital items based on social identity theory and self-presentation theory in the online context. Also, the findings of our study are valuable and practical for practitioners in the market who wish to adopt or improve the business model of selling digital items in an online community. From the findings, it can be seen that innovativeness of users, community group norm, and community involvement are three significant factors that influence need for self-presentation of users which ultimately leads to their intentions to buy digital items. These findings put forth that virtual community providers and online businesses selling digital items should prioritize their efforts and focus on these three factors if they want to increase the sales of these digital items and generate greater revenues. This study provides important implications for academic researchers and practitioners to understand why the community members pay money for their digital items in virtual world and how the practitioners can increase the sales of digital items in an online community. A couple of limitations of the study and future research directions are also discussed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.10B
• /
• pp.1222-1232
• /
• 2011

RFID/USN core technologies for ubiquitous computing, It is possible to use variety of sensors, direct processors, and wireless network technology that easily collect the actual physical environment and can monitor information remotely. Especially the healthcare industry and services combined with U-Healthcare that have international competitiveness in the medical field. But the USN, standard management system of RFID such as EPCglobal architecture framework, the lack of interoperability issues and the global sensor network implementation. In this paper, a system for managing sensor nodes of the USN, USN of SIP-based management system (UMS) is proposed. UMS support Session Initiation Protocol (SIP), provide session management and mobility capabilities, that is based on Internet standard protocol. UMS architecture of the existing SIP architecture, added USN User Agent (UUA) and the USN Name Server (UNS) that the location of sensor nodes should be possible to trace. UUA on behalf of the limited capacity of the location of the sensor nodes to perform the registration process, UNS to track the location of the sensor nodes to provide name resolution services. The proposed management system has the advantage of internet applications such as Web services interoperability and easy to recycle existing resources with other SIP-based because it uses the Internet standard protocol SIP. In this paper we propose is based on the UMS blood temperature management system is verified through the scenario.

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