• Journal of Communications and Networks
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• v.15 no.4
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• pp.352-361
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• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• Smart Media Journal
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• v.13 no.6
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• pp.62-71
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• 2024

This study applies topic modeling to uncover user experience and app issues expressed in users' online reviews of a fan community platform, Weverse on Google Play Store. It allows us to identify the features which need to be improved to enhance user experience or need to be maintained and leveraged to attract more users. Therefore, we collect 88,068 first-level English online reviews of Weverse on Google Play Store with Google-Play-Scraper tool. After the initial preprocessing step, a dataset of 31,861 online reviews is analyzed using Latent Dirichlet Allocation (LDA) topic modeling with Gensim library in Python. There are 5 topics explored in this study which highlight significant issues such as network connection error, delayed notification, and incorrect translation. Besides, the result revealed the app's effectiveness in fostering not only interaction between fans and artists but also fans' mutual relationships. Consequently, the business can strengthen user engagement and loyalty by addressing the identified drawbacks and leveraging the platform for user communication.

• Journal of Korean Public Health Nursing
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• v.17 no.2
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• pp.278-286
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• 2003

In this study quality of tobacco cessation information provided through Internet web sites was evaluated in terms of retrievability, easy of use, user-supportiveness, feedback, and continuity. This study limited to those internet web sites developed and delivered by Korean public health service organizations or their related institutions or associations. This study analyzed 8 internet web sites and evaluation criteria developed by Chung, Yong Chul (2002) and Yoo, Sarah (2001) were used. Study results indicated that retrievability was evaluated low except search-speed of data: the easy of use was evaluated moderately: user-supportiveness was evaluated moderately: feedback, and continuity of those sites were evaluated low. The quality of tobacco cession information of those sites are needed to be improved. The development of guidelines for standardized health information on Internet web sites is necessary, too.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.53-60
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• 2012

In this paper, we proposes a new document summarization method using the expanded query by wikipedia and the semantic feature representing inherent structure of document set. The proposed method can expand the query from user's initial query using the relevance feedback based on wikipedia in order to reflect the user require. It can well represent the inherent structure of documents using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can reduce the semantic gap between the user require and the result of document summarization to extract the meaningful sentences using the expanded query and semantic features. The experimental results demonstrate that the proposed method achieves better performance than the other methods to summary document.

• Educational Technology International
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• v.25 no.1
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• pp.1-25
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• 2024

This study aims to analyze the impact of learners' usability perceptions of topic modeling-based visual feedback and generative AI interpretation on reflection levels in online discussions. To achieve this, we asked 17 students in the Department of Korean language education to conduct an online discussion. Text data generated from online discussions were analyzed using LDA topic modeling to extract five clusters of related words, or topics. These topics were then visualized in a network format, and interpretive feedback was constructed through generative AI. The feedback was presented on a website and rated highly for usability, with learners valuing its information usefulness. Furthermore, an analysis using the non-parametric Mann-Whitney U test based on levels of usability perception revealed that the group with higher perceived usability demonstrated higher levels of reflection. This suggests that well-designed and user-friendly visual feedback can significantly promote deeper reflection and engagement in online discussions. The integration of topic modeling and generative AI can enhance visual feedback in online discussions, reinforcing the efficacy of such feedback in learning. The research highlights the educational significance of these design strategies and clears a path for innovation.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.21-27
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• 2006

We present and analyze a class of limited sensing random access algorithms with powerful properties. The algorithms are implementable in wireless mobile environments and their operational properties are simple. Their throughput in the worst case of the limit Poisson user model is 0.4297, while this throughput degrades gracefully in the presence of channel feedback errors.

• The Journal of Korean Institute for Practical Engineering Education
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• v.5 no.1
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• pp.34-39
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• 2013

This paper suggests an input device that allows a user not only to naturally interact with education contents in virtual environment but also to sense haptic feedback according to his/her interaction. The proposed system measures a user's motion and then creates haptic feedback based on the measured position. To create haptic information in response to a user's interaction with educational contents in virtual environment, we develop a motion input device which consists of a motion controller, a haptic actuator, a wireless communication module, and a motion sensor. To measure a user's motion input, an accelerometer is used as the motion sensor. The experiment shows that the proposed system creates continuous haptic sensation without any jerky motion or vibration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3680-3692
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• 2020

The purpose of this study is to orient users' touchpoints in co-design experience, to identify their need via visualized experience map, to recommend valid design information in online e-customization services. A user-centered co-design experience map (UCEM) is adopted to analyze the relation between users' desire and time spent, so as to evaluate the online co-design experiences. Based on evolutionary algorithm and fuzzy theory, data of this study is collected from 30 participants. The data was analyzed by descriptive analysis in SPSS, and frequency query and word cloud in NVivo. Employing design category and evaluating users' time spent, the findings are that (a) vamp color matching is consistent with interview data; (b) supported by qualitative feedback, the virtual experience map played an important role in the co-design process and the visualized interaction process; and (c) participants prefer to get more information and professional help on color matching and exterior design. Based on the findings in design category, future work should be focused on developing a better understanding of design resource recommendations and multi-stakeholder communication.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.712-717
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• 2011

Recently, diverse schedule management agents are being researched for the efficient schedule management of smart devices users, but they remain at a confirmatory level. In order to efficiently manage user's schedules, execution of planned schedules should be monitored to help users properly execute their schedules, or feedback must be given so that when setting up new schedules, users can plan their schedule according to their schedule establishment patterns. This research proposes a schedule management agent that infers the user's behaviors by using acquired user context, and provides schedule related feedback depending on the user's behavior patterns, when users are executing their schedules or planning new schedules. For this, collected user context information is preprocessed and user's behavior is inferred by Bayesian network. Also, in order to provide feedbacks necessary for confirming the user's schedule execution and new schedule establishment, a context tree pattern matching method for the user's schedule, location and time contexts was applied, then verified with 6 weeks of user simulation in a mobile environment.

• Journal of the Korean Society for information Management
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• v.26 no.1
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• pp.81-105
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• 2009

In this paper, we propose user contents using behavior and location information on contents on various channels, such as web, IPTV, for contents distribution. With methods to build user and contents profiles, contents using behavior as an implicit user feedback was applied into machine learning procedure for updating user profiles and contents preference. In machine learning procedure, contents-based and collaborative filtering methods were used to analyze user's contents preference. This study proposes contents location information on web sites for final recommendation contents as well. Finally, we refer to a generalized recommender system for personalization. With those methods, more effective and accurate recommendation service can be possible.