• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.845-854
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• 2019

In IoT environment, an intelligent agent is an autonomous entity with computing power that interacts with various things for specific purposes without human intervention. Recently, as the development of Internet technology has increased the size of resources and services that intelligent agents can utilize, an environment where intelligent agents can collaborate with each other is needed. To effectively support these changes, a method is needed to provide workspaces where intelligent agents can form various groups and collaborate on them. In this paper, we present TSpace which is an Ethereum-based group workspace for effective collaboration among intelligent agents. In TSpace, intelligent agents in IoT environment can use group service based on the Ethereum blockchain through the developed CoAP/RESTful web service. TSpace also introduces a new mechanism for managing Ethereum wallets of agents accessing group services and for creating Ethereum transactions using them.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.387-394
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• 2019

Recently, the importance of big data has been increased, and demand for data analysis for the big data is also increased. R language is developed for data analysis, and users are analyzing data by using algorithms of various statistics, machine learning and data mining packages in R language. However, it is difficult to develop an application using R. Early study proposed a method to call R script through another language such as PHP, Java, and so on. However, it is troublesome to write such a development method in addition to R in combination with other languages. In this study, we introduce how to write API using only R language without using another language by using Plumber package. We also propose a solution for security issues related with R API. If we use propose technology for developing web application, we can expect high productivity, easy of use, and easy of maintenance.

• Knowledge Management Research
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• v.20 no.3
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• pp.173-193
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• 2019

Reward-based crowdfunding is a funding platform that allows funds to be raised to early operators who have lack of funds, and is seen as an outstanding infrastructure that is going to lead the fourth industrial revolution in that it is a field of realization of new technologies and creative ideas by start-ups. Reward-based crowdfunding has grown in line with the trend of the fourth industrial revolution, and funding success cases are taking place in various industries that culture/art to technology/IT, including as a new means of knowledge management in a rapidly changing industrial environment. The study focused on the fact that consumer's donation purposes may also vary depending on the category of projects classified as reward-based crowdfunding. Because consumer payment decisions and motivation of consumer purchasing behavior are classified according to the purpose of purchase, the previous papers that the goal gradient effect that the main motivation of consumer donation for reward-based crowdfunding introduced vary depending on project category of utilitarian and hedonic. In this study, consumer's daily donation data is collected by Indiegogo which is a leading reward-based crowdfunding company using web-crawling and the model was defined as propensity score matching (PSM) and random effect model. The results showed that the goal gradient effect occurred in utilitarian project category, but no goal gradient effect for the hedonic project category. Furthermore, this paper developed the study of motivation of consumer donation and contributes theoretical foundation by the results consumer donation may vary depending on the project category; also, this paper has implications for an effective marketing strategy depending on the project category leaves real meaning to the projector.

• Korean Medical Education Review
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• v.23 no.2
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• pp.80-89
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• 2021

Professional identity formation (PIF) is an essential concept in professional education. Many scholars have explored conceptual frameworks of PIF and conducted empirical studies to advance an understanding of the construct in medical education. Despite its importance, it is unclear what educational approaches and assessment practices are actually implemented in medical education settings. Therefore, we conducted a literature review of empirical studies reporting educational practices for medical learners' PIF. We searched the Web of Science database using keywords and chose 37 papers for analysis based on inclusion and exclusion criteria. Thematic analysis was conducted. Most empirical papers (92%) were from North America and Western Europe and used qualitative research methods, including mixed methods (99%). The papers reported the use of reflection activities and elective courses for specific purposes, such as art as an educational activity. Patient and healthcare experiences were also found to be a central theme in medical learners' PIF. Through an iterative analysis of the key themes that emerged from the PIF studies, we derived the following key concepts and implications: (1) the importance of creating informal and incidental learning environments, (2) ordinary yet authentic patient experiences, (3) a climate of psychosocial safety in a learning environment embracing individual learners' background and emotional development, and (4) the reconceptualization of PIF education and assessment. In conclusion, research on PIF should be diversified to include various cultural and social contexts. Theoretical frameworks should also be diversified and developed beyond Kegan's developmental framework to accommodate the nonlinear and dynamic nature of PIF.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• Smart Media Journal
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• v.11 no.10
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• pp.54-64
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• 2022

A big data-driven digital transformation is defined as a process that aims to innovate companies by triggering significant changes to their capabilities and designs through the use of big data and various technologies. For a successful big data-driven digital transformation, reviewing related literature, which enhances the understanding of research statuses and the identification of key research topics and relationships among key topics, is necessary. However, understanding and describing literature is challenging, considering its volume and variety. Establishing a common ground for central concepts is essential for science. To clarify key research topics on the big data-driven digital transformation, we carry out a comprehensive literature review by performing text mining of 439 articles. Text mining is applied to learn and identify specific topics, and the suggested key references are manually reviewed to develop a state-of-the-art overview. A total of 10 key research topics and relationships among the topics are identified. This study contributes to clarifying a systematized view of dispersed studies on big data-driven digital transformation across multiple disciplines and encourages further academic discussions and industrial transformation.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.265-276
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• 2017

Korean petroglyphs have been found over a lot of ruins through nation-wide regions including Daegok-ri Bangudae and Cheonjeon-ri in Ulsan. In this paper, we present an information system for Korean petroglyph ruins named KPetro which supports the dedicated camera application and the timeline service. The system provides the services for searching and updating information in various ways over the primary database constructed with the data on petroglyph ruins, which are collected by the Bangudae Petroglyph Institute. In addition, through the camera application developed for the system, users can easily add photos to the appropriate petroglyph ruin according to the GPS information of the location where those photos are taken. Also, the system provides the timeline service showing the photos for a specific petroglyph ruins in order of shooting time. To support both mobile and desktop environments, KPetro provides its functions in a web browser using the HTML5 standard technology and the JavaScript language, enabling the system to be adaptable to various user devices and extendable for its functionalities.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.35-44
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• 2016

MICE industry is emerging as a new growth engine recently. Most of the domestic MICE events are carried out at low cost on a small scale. The event organizers want to cut down on costs of prints such as brochures and other promotional printed materials, as well as the personnel costs for the simple guide job needed on site, which are generated repeatedly and wastefully. The existing mobile web has a defect that the participants can't easily earn the information in the fixed menu, but have to search by themselves wasting lots of time. Therefore, it is necessary to develop the solution enables providing information efficiently at low cost for short-term use during the events. In this study, we implemented specific total management system for exhibitions and convention using beacon. The information system for exhibitions and events using beacon can raise the management efficiency, and the digital brochure function based on CMS heightens the information retrieval ability and also reduces costs. Organizers can manage their event efficiently in a small exhibition and convention event by running an online website and operate a site management system by them selves.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.71-79
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• 2018

The Internet of Things is a technology that makes it possible for objects made up of hardware and software to exchange information with one another via the Internet, thereby facilitating the servitization of the objects. An IoT service, which is composed of an IoT device and a web service, has recently been applied to the marketing field and is being used as a means to meet customer needs. However, applying appropriate marketing elements to IoT services is not easy. Therefore, analysis tools are needed to properly apply marketing elements to IoT services. This study aims to construct an analysis model for marketing evaluation of IoT services. In this study, the technical elements and marketing elements of IoT were derived through a literature review, and the analysis model for marketing evaluation of IoT services was established by exploring the relationship between the elements based on a service blueprint. We also applied real cases to verify the analytical model. This study is expected to contribute to the development of tools for evaluating IoT services.