• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.1-14
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• 2019

This paper considers a multiple-input multiple-output (MIMO) power line communication (PLC) network where interference alignment (IA) technique is used to mitigate the interference that arises in multi-user networks. IA as a precoding technique requires perfect channel state information (CSI) to achieve maximum multiplexing gain. Due to the common-mode reception at the receiver ports, we assume imperfect CSI for the IA precoding design. Here, the CSI is quantized and sent via feedback to the transmit ports. For different levels of CSI quantization, we evaluate the performance of various IA algorithms via Monte Carlo simulations. Simulation results reveal the superior performance of the proposed scheme due to common-mode reception in IA MIMO PLC networks. It is shown that for a quantization level of 5 bits, the CM reception improves the sum-rate by up to 70%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1573-1595
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• 2011

In this paper, the outage performance of multiuser multiple-input single-output (MISO) systems exploiting joint spatial and multiuser diversities is investigated for Rayleigh fading channels with outdated feedback. First, we derive closed-form exact outage probabilities for the joint diversity schemes that combine user scheduling with different spatial diversity techniques, including: 1) transmit maximum-ratio combining (TMRC); 2) transmit antenna selection (TAS); and 3) orthogonal space-time block coding (OSTBC). Then the asymptotic outage probabilities are analyzed to gain more insights into the effect of feedback delay. It is observed that with outdated feedback, the asymptotic diversity order of the multiuser OSTBC (M-OSTBC) scheme is equal to the number of transmit antennas at the base station, while that of the multiuser TMRC (M-TMRC) and the multiuser TAS (M-TAS) schemes reduce to one. Further by comparing the asymptotic outage probabilities, it is found that the M-TMRC scheme outperforms the M-TAS scheme, and the M-OSTBC scheme can perform best in the outage regime of practical interest when the feedback delay is large. Theoretical analysis is verified by simulation results.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.119-125
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• 2019

The purpose of this study is to find out the relevant factors of the choice tendency of tourism users to Intelligent Tourism platform through big data analysis, which will help enterprises to make accurate positioning and improvement according to user information feedback in the tourism market in the future, so as to gain the favor of users' choice and achieve long-term market competitiveness. This study takes the Intelligent Tourism platform as the independent variable and the user choice tendency as the dependent variable, and explores the related factors between the Intelligent Tourism platform and the user choice tendency. This study make use of text mining and R language text analysis, and uses SPSS and AMOS statistical analysis tools to carry out empirical analysis. According to the analysis results, the conclusions are as follows: service quality has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with tourism trust; Tourism Trust has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with user experience; user experience has a significant positive correlation with user choice tendency Positive correlation effect.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.511-520
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• 2011

In this paper, we introduce a multiuser (MU) scheduling method for multiuser amplify-and-forward relay systems, which selects both the transmission mode, i.e., either one- or two-hop transmission, and the desired user via two steps. A closed-form expression for the average achievable rate of the proposed scheduling is derived under two transmission modes with MU scheduling, and its asymptotic solution is also analyzed in the limit of large number of mobile stations. Based on the analysis, we perform our two-step scheduling algorithm: the transmission mode selection followed by the user selection that needs partial feedback for instantaneous signal-to-noise ratios (SNRs) to the base station. We also analyze the average SNR condition such that the MU diversity gain is fully exploited. In addition, it is examined how to further reduce a quantity of feedback under certain conditions. The proposed algorithm shows the comparable achievable rate to that of the optimal one using full feedback information, while its required feedback overhead is reduced below half of the optimal one.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.545-558
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• 2020

The gaze-based input provides feedback to confirm that the typing is correct when the user types the text. Many studies have already demonstrated that feedback can increase the usability of gaze-based inputs. However, because the information of the typed text is revealed through feedback, it can be a target for shoulder-surfing attacks. Appropriate feedback needs to be used to improve security without compromising the usability of the gaze-based input using the original feedback. In this paper, we propose a new gaze-based input method, FFI(Fake Flickering Interface), to resist shoulder-surfing attacks. Through experiments and questionnaires, we evaluated the usability and security of the FFI compared to the gaze-based input using the original feedback.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.383-392
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• 2006

In this paper, we propose a new relevance feedback algorithm using Probabilistic Neural Networks(PNN) while supporting multi-class learning. Then, to validate the effectiveness of our feedback approach, we incorporate the proposed algorithm into our region-based image retrieval tool, FRIP(Finding Regions In the Pictures). In our feedback approach, there is no need to assume that feature vectors are independent, and as well as it allows the system to insert additional classes for detail classification. In addition, it does not have a long computation time for training because it only has four layers. In the PNN classification process, we store the user's entire past feedback actions as a history in order to improve performance for future iterations. By using a history, our approach can capture the user's subjective intension more precisely and prevent retrieval performance errors which originate from fluctuating or degrading in the next iteration. The efficacy of our method is validated using a set of 3000 images derived from a Corel-photo CD.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.163-170
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• 2017

As the usage of smart phones continues to increase, the control UI, which users have to continue to use, sometimes finds a heavy burden on users. Therefore, in this study, we have studied the control user interface structure along with the theoretical background of the control user interface, and we have studied the role and usage of the control component based on it. Typical commonly used controls are button controls for transmission, selection controls for various selections, link controls for navigation, text controls for inputting characters, indicator controls for feedback on progress, A message control that displays information about warnings and errors, and a window control such as a dialog box. The structure of the control should be designed according to the use of the separated control to help the user efficiently use the control user interface. Based on the analysis of the theoretical usage of representative components belonging to the separated controls, we presented a new and correct way to use the control to improve the user experience. The use of improved control components will help to design the control structure efficiently and to improve the user experience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.387-388
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• 2012

In order to solve problem which User sometime visits the wrong page with respect to user intention when uses snippet. this paper proposes a new snippet extraction method using fuzzy. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.2
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• pp.57-78
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• 2017

SNS is a useful tool to quickly deliver information in an emergency given their speed and expandability. Especially, SNS in the event of a disaster or an accident can offer on-site, accurate and detailed updates about essential information such as the safety of victims and the development of the situation, served as a valuable complement to the conventional media. This study aims to perform a comparative analysis on how social media are currently used by emergency management authorities in South Korea and other countries. Based on the results, this study proposed more effective ways to exploit SNS and improve efficiency of disaster management. To accomplish the goals, this study collected tweet information from various sources including the FEMA of the U. S., the FDMA and the Central Disaster Council of Japan, and the MPSS of Korea. The collected tweet information was analyzed by feedback, time series, and information types. The feedback analysis aims to quantify the number of monthly user feedback in order to assess user satisfaction about the tweet information. The time series analysis identifies the number of tweet information, feedback index and keywords by country for certain duration, examining why certain messages showed high feedback indices and what kind of contents should be offered by the authorities. Finally, the analysis of information type reviews the type of information contained in the tweet information that drew users' attention to identify the information type in which the authorities should deliver information to users. Based on these analyses, this study proposed improvement methods to use Tweeter in MPSS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.685-690
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• 2021

In this paper, we propose a deep learning-based transmit power control scheme to maximize the sum-rates while satisfying the minimum data-rate in downlink non-orthogonal multiple access (NOMA) systems. In downlink NOMA, we consider the co-channel interference that occurs from a base station other than the cell where the user is located, and the user feeds back the signal-to-interference plus noise power ratio (SINR) information instead of channel state information to reduce system feedback overhead. Therefore, the base station controls transmit power using only SINR information. The use of implicit SINR information has the advantage of decreasing the information dimension, but has disadvantage of reducing the data-rate. In this paper, we resolve this problem with deep learning-based training methods and show that the performance of training can be improved if the dimension of deep learning inputs is effectively reduced. Through simulation, we verify that the proposed deep learning-based power control scheme improves the sum-rate while satisfying the minimum data-rate.