• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.99-105
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• 2012

Recently, there are many user selection algorithms in multi user multiple-input multiple-output (MU-MIMO) systems. One of well-known user selection methods is Semi orthogonal user selection (SUS). It is an algorithm maximizing channel capacity. However, it is applicable only when user's antenna is one. We propose a generalized user selection algorithm regardless of the number of user's antennas. In the proposed scheme, Base station (Bs) selects the first user who has the highest determinant of channel and generates a user group that correlation with first user's channel is less than allowance of correlation. Then, each determinant of channels made up of first user's channel and a user's channel in the generated group is calculated and BS selects the next user who has the highest determinant of that. BS selects following users by repeating above procedure. In this paper, we get better performance because of selecting users who have the highest determinant of channel as well as allowance of correlation optimally calculated through matrix operations.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.298-303
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• 2008

User adaptive services have been important features in many applications. To provide such services, various techniques with various kinds of data are being used. In this paper, we propose a method to analyze user's past moving paths for predicting the goal position and the path to the goal by observing the user's current moving path. We develop a spatio-temporal similarity measure between paths. We choose a past path which is the most similar to the current path using the similarity. Based on the chosen path, user's spatio-temporal position is estimated. Through experiments we confirm this method is useful and effective.

• Korean Journal of Human Ecology
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• v.19 no.1
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• pp.103-117
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• 2010

The purpose of this study was broken down into four sections. First, this study identified both single workers' lifestyles and their motives for going to restaurants. The study classified the consumers and then confirmed the attributes of selection that the consumers considered important when eating out at family restaurants. Second, the study analyzed the consumers' lifestyles, motives for going to restaurants (user motive), and the attributes of selection for the restaurant. Third, the study analyzed how the attributes of selection toward the family restaurant affect the consumer's satisfaction and the consumer's intention of revisiting the restaurant. Fourth, the study analyzed how consumer satisfaction affects the intention to revisit the family restaurant. After the execution of the aforementioned four steps, the study was successful in meeting its purpose: to provide information to enhance the satisfaction of the consumer and to provide foundation material for consumer policy. In regards to the analytical method, this study performed a Frequency Analysis, Factor Analysis, Reliability Analysis, Cluster Analysis, ANOVA Analysis, and Multiple Regression Analysis. The analytical results from the study are as follows. Lifestyle was categorized into 4 factors and 4 clusters. User motive was grouped into 3 factors and 4 clusters. The attributes of selection for family restaurants were categorized into 4 factors. Based on the lifestyle cluster, the attributes of selection for family restaurants showed a statistically significant difference. In addition, based on the cluster of user motive, the attributes of selection for family restaurants showed a statistically significant difference. Lastly, the attributes of selection for family restaurants were found to affect both the intention of revisiting the restaurant and consumer satisfaction after the consumers used the restaurants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1767-1769
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• 2011

In a CR (cognitive radio) network, channel selection is one of the important issues for the efficient channel utilization. When the CR user exploits the spectrum of primary network, the interference to the primary network should be minimized. In this paper, we propose a spectrum hole prediction based channel selection scheme to minimize the interference to the primary network. To predict spectrum hole, statistic properties of primary user's traffic is used. By using the predicted spectrum hole, channel is selected and it can reduce the possibility of interference to the primary user and increase the efficiency of spectrum utilization. The performance of proposed channel selection scheme is evaluated by the computer simulation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.1795-1805
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• 2015

This paper analyzed the recommendation stories in the online journalism on the user's news choice by college students in two ways. One way is recommendation stories, and the other one is their arrangement and the index of use. From the results of the analysis, 7 out of 11 types of recommendation stories had positive effects on selecting news stories, while the 4 other types had little effect. Most of the recommendation stories that had little effect on the user's news selection were 'comments' or 'things' related to tweets' on SNS. The arrangements of new stories and the searched keywords had some effects on the user's news choice but had no effect on the index of use. In addition, the hours of using news stories and the types of recommendation stories were mostly correlated with each other. Consequently, formal factors, such as the arrangement of news stories and the recommendation stories of online journalism, had positive effects on the user's news selection, as well as headlines and keywords of news stories.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3945-3964
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• 2015

Since the decentralized structure and the blindness of a large-scale wireless network make it difficult to collect the real-time channel state or other information from random distributed relays, a fundamental question is whether it is feasible to perform the relay selection without this knowledge. In this paper, a Slotted ALOHA based Greedy Relay Selection (SAGRS) scheme is presented. The proposed scheme allows the relays satisfying the user's minimum transmission request to compete for selection by randomly accessing the channel through the slotted ALOHA protocol without the need for the information collection procedure. Moreover, a greedy selection mechanism is introduced with which a user can wait for an even better relay when a suitable one is successfully stored. The optimal access probability of a relay is determined through the utilization of the available relay region, a geographical region consisting of all the relays that satisfy the minimum transmission demand of the user. The average number of the selection slots and the failure probability of the scheme are analyzed in this paper. By simulations, the validation and the effectiveness of the SAGRS scheme are confirmed. With a balance between the selection slots and the instantaneous rate of the selected relay, the proposed scheme outperforms other random access selection schemes.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.510-516
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• 2008

In ubiquitous environment, there are no limits to utilize networks whenever and wherever you are. That pervasive networks are combined with the information devices and then create various services such as car navigation of LBS(location based service) and DMB(Digital Multimedia Broadcasting). As these kinds of services are getting more various, the complexity is also getting higher and ultimately the convergence will make people feel frustrated. One of the solutions is Context-Awareness[1] technology. User interface with context-awareness filters unnecessary information and prevents users from being blocked due to the massive information. In this paper, we describe the seamless service system based on location-awareness, which is a type of context-awareness. We developed the system based on UPnP AV Framework. This system provides the automatic terminal device selection for the nomadic user. The system establishes new connections for the ongoing streaming playback session with the new AV devices without substantial loss of playback so that the user can enjoy the seamless service. The AV device selection based on the user's location needs no user's intervention or notification so it achieves the improvement of usability and complexity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.99-104
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• 2014

Nowadays, various researches fulfill in many communication engineering area for B4G (Beyond Forth Generation). Next LTE-A (Long Term Evolution Advanced), MU-MIMO (Multi-User Multi Input Multi Output) method raises to upgrade throughput performance. However, the method of user selection is not decided because of many types and discussions in MU-MIMO system. Many existing methods are powerful for enhancing performance but have various restrictions in practical implementation. Fairness problem is primary restriction in this area. Existing papers emphasis algorithm to increase sum-rate but we introduce an algorithm about dealing with fairness problem for real commercialization implementation. Therefore, this paper introduces new user selection method in MU-MIMO system. This method overcomes a fairness problem in SUS (Semiorthogonal User Selection) algorithm. We can use the method to get a similar sum-rate with SUS and a high fairness performance. And this paper uses a hybrid method with SC-SUS (Superposition Coding SUS) algorithm and SUS algorithm. We find a threshold value of optimal performance by experimental method. We show this performance by computer simulation with MATLAB and analysis that results. And we compare the results with another paper's that different way to solve fairness problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.100-111
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• 2009

Cognitive radio is an advanced technology for efficient utilization of under-utilized spectrum via spectrum sensing. CR users should move from current allocating channel to empty channel to avoid the interference to the primary user if the primary user is allocating that channel. Thus, CR system cannot support the CR user's QoS(Quaiity of Service). In this paper, we propose dynamic frequency selection method based on Genetic Algorithm with power control. It is to find the optimization channel for satisfying various CR user's needs with the power control method to minimize the CR user's interference to the primary user. And, we propose the Genetic Algorithm(GA) which determines the best configuration for CR communication systems. The computer simulation results show that the proposed method guaranteed the primary user's decodability and the optimized solution for various channel status.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.