• Fashion & Textile Research Journal
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• v.26 no.2
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• pp.166-178
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• 2024

Second-hand trading platforms have emerged as a major transaction method among people, and are particularly quite popular with the MZ Generation (Millennial + Generation Z). These generations are more open to transactions through such platforms. Understanding and analyzing these platforms from the perspective of their primary users can help businesses establish effective marketing strategies and attract new customers. This study examines the effect of second-hand trading platforms on usage intention by dividing the benefits into functional, economic, environmental, social, and hedonic categories for MZ generation consumers who have traded fashion products on such platforms. In addition, it explores how differences in fashion leadership affect the relationship between platform benefits, trust, and attitude. A total of 400 participants were analyzed using IBM SPSS Statistics 26.0 and IBM AMOS 24.0. The results indicate that the benefits of second-hand trading platforms have a significant impact on trust in and attitude toward these platforms. Furthermore, the effect of platform benefits on consumer responses varied based on the extent of fashion leadership. This study provides practical insights for developing marketing strategies for second-hand transaction platforms and underscores the academic significance of studying consumer behavior in a second-hand fashion markets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.985-992
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• 2020

Edge computing is a technology that can prepare for a new era of cloud computing. Edge computing is not a remote data center where data is processed and computed, but low-latency/high-speed computing is realized by adding computing power and data processing power to the edge side close to an access point such as a terminal device or a gateway. It is possible. The types of edge computing include mobile edge computing, fog computing, and cloudlet computing. In this article, we describes existing open source platforms for implementing edge computing nodes. By presenting and comparing the structure, features of open source edge platforms, it is possible to acquire knowledge required to select the best edge platform for industrial engineers who want to build an edge node using an actual open source edge computing platform.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.745-754
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• 2019

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.724-740
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• 2016

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.479-486
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• 2017

Recently, GPGPU has been able to increase the degradation of computer performance, and it is now possible to run physically based real-time simulations on PCs that require high computational complexity. Physical calculations applied in physics simulation can be performed by parallel processing, and can be efficiently performed using parallel computation using Compute shader recently supported by OpenGL 4.3 and Unity 4.0. In this paper, we measure and compare the number of performance in real - time physics simulation in OpenGL running on various platforms and Unity, a content creation tool supporting various platforms. Particle simulation experiments show that particle simulation using Unity performs faster than 136.04%. It is expected that it will be able to select better development tools for future multi - platform support.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.110-113
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• 2003

The development of an open LBS platform makes it easy to use of the location information between telecommunication companies which have different platforms and to develop various LBS solutions using position information. This paper proposes a mobile webservice solution providing public transportation services to the mobile subscribers working together open LBS platform.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.267-272
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• 2007

A business is an organized. profit-seeking activity that provides goods and service designed to satisfy customer' needs. For years, Internet users have been dream of intelligent software agents that automatically prowl the online world and bring back high-quality information. In the era of web2.0, Internet users can communicate each other on open platforms(e-mail, Naver Knowledge-In. Cyworld, Wikipedia, and blog etc.). The author investigate the impact of web2.0 user's perceived value. affective commitment. brand equity on loyalty intention. The results suggest that excellent service quality will be alternative solving in web2.0 business environment.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.1033-1048
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• 2018

This paper proposes an integrated lighting enabler system (ILES) based on standard machine-to-machine (M2M) platforms. This system provides common services of end-to-and M2M communication for smart lighting system. It is divided into two sub-systems, namely end-device system and server system. On the server side, the M2M platform OpenMTC is used to receive data from the sensors and send response for activating actuators. At the end-device system, a programmable smart lighting device is connected to the actuators and sensors for communicating their data to the server. Some experiments have been done to prove the system concept. The experiment results show that the proposed integrated lighting enabler system is effective to reduce the power consumption by 25.22% (in average). The proving of significance effect in reducing power consumption is measured by the Wilcoxon method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5634-5653
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• 2018

Internet of things (IoT) is based on a global dynamic information network with cloud services where a great number of devices (things) exchange data to provide added-value services and products. There are several commercial and open source IoT platforms available in the market to connect devices to internet; however, they have cost and operational constraints that make them not suitable for academic projects. In this work, an IoT platform, known as Novus-io, is introduced in order to support academic projects for undergraduate students. With this platform and proper training, undergraduate students from different majors (not only from information technology and electronics) are capable to upgrade their school projects with IoT functionalities. The objective of this approach is to provide to any undergraduate student skills and knowledge on IoT, so they will be prepared, in their imminent step toward professionalism, to understand the relevance of digital services in today's world.