• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.331-352
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• 2022

This study used a latent growth curve models(LGCM) to examine longitudinal changes in youth's game usage, self-control and the longitudinal mediation effect of adaptive game use in the relationship between game usage and self-control. A four-year longitudinal data of 863 adolescents from the Game User Panel Survey, provided through participation in the 2019 Game User Panel Research Conference hosted by the Korea Creative Contents Agency, was used to verify the longitudinal mediation effect of adaptive game use. SPSS 21 was used to verify the normality of variables from each wave, and to conduct correlation analysis. Mplus 6.12 was used to verify the longitudinal mediation effect. The results are as follows. First, game usage, self-control and adaptive game yielded linear temporal growth. Second, latent growth curve models showed that the direct effect of game usage on self-control was insignificant, but game usage had a significant indirect effect on self-control through adaptive game use. Continuous adaptive gaming increased self-control. Third, sobel test results showed that both the initial value and change rate of adaptive game use had a full-mediation effect, confirming the longitudinal mediation effect. This study verified the longitudinal change of self-control affected by change in game usage and adaptive game use.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.883-887
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• 2011

Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.783-790
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• 2010

A two-way relay network provide improved spectral efficiency compared with a conventional one-way relay network by using either superposition coding or network coding. OFDMA network provides imptoved performance by adaptive resource allocation. In this paper, we propose a adaptive subcarrier allocation for a multiuser two-way OFDMA relay network. In the proposed algorithm, subcarriers are allocated to the user-pairs and relays to maximize the achievable sum-rate over all user-pairs while satisfying the minimum rate requirement for each user-pair. Simulation results show that the proposed algorithm provides improved performance compared with the static and greedy algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.620-627
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• 2005

We develop an adaptive hot-spot operating scheme(AHOS) to mitigate the negative effects from the nonuniform distribution of user location and the variation in the mixture of QoS requirements in OFDMA downlink systems. The base station in a macrocell can control the operation of picocells within the cell, and turns on or off according to the changes in the estimated user outage probability and the AHOS gain parameter. With the computer simulation, the AHOS has been proved to maximize the system throughput while maintaining the QoS outage probability very low under various system scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1002-1015
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• 2018

The advent of Internet of Things (IoT) and the evident inadequacy of Cloud networks concerning management of numerous end nodes have brought about a shift of paradigm giving birth to Fog computing. Fog computing is an extension of Cloud computing that extends Cloud resources at the edge of the network, closer to the user. Cloud computing has become one of the essential needs of people over the Internet but with the emerging concept of IoT, traditional Clouds seem inadequate. IoT entails extremely low latency and for that, the Cloud servers that are distant and unknown to the user appear to be unsuitable. With the help of Fog computing, the Fog devices installed would be closer to the user that will provide an immediate storage for the frequently needed data. This paper discusses data migration between different storage types especially between Cloud devices and then presents a mechanism to migrate data between Cloud and Fog Layer. We call this mechanism Adaptive Deadline-Aware Scheme (ADAS) for Data migration between Cloud and Fog. We will demonstrate that we can access and process latency sensitive "hot" data through the proposed ADAS more efficiently than with a traditional Cloud setup.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.35-50
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• 2000

Diverse requirements of users on web-based model management force a system agent to develop user-adaptive building a model in reality and providing an adequate solution method of the model. The relationship between models is important knowledge for the agent to effectively build a new model to adaptively adjust an existing model under a problem and to efficiently connect the new model into an adequate solution method. Since the generating process of the inter-model relationship is more difficult than the building a new model however the process mostly depends on the knowledge of operation research experts. Without the adequate scheme of the inter-model relationship the burden of the management for the agent increases rapidly and the quality of the services may worsen. This study shows that meta-knowledge generated from relationship between models is important for the user to build a model in reality and to acquire the solver appropriate to the model. The relationship that consists of common and exclusive objects between models can be represented by frames. The system under development to implement the idea includes user-adaptive ability which identifies a model through forward chaining method and searches the solver appropriate to the model by using the meta knowledge. We illustrate the meta knowledge with an applied delivery system in supply chain management.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.403-409
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• 2003

The finite element method is one of the most widely used method of structural analysis that has wide applications in diverse fields of engineering and science. The method has been proven effective and reliable in many practical problems. One of the reasons for the methods' popularity is its ease of use, but still the user has to input the finite element mesh which affects the accuracy of the results. The knowledge required to form an effective mesh for a given problem is somewhat complex and for sometime there has been research effort to automate the generation of the mesh and this is called the adaptive mesh generation scheme. A good adaptive mesh scheme seemed to require an accurate assessment of error and generally this requires some additional computation. This paper looks into the possibility of generating adaptive meshes based on representative strain values in each finite element method. The proposed adaptive scheme does not require additional computations other that looking up the data values already computed as finite element analysis results and simple manipulations of these data. Two plane stress problems, a plate with a hole and a deep beam with a concentrated load at the end are considered to show the progress of the improved generation of adaptive meshes using the scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1027-1030
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• 2005

The article introduces developing trends of an adaptive mobile terminal as an interface for use of various network resources, such as public wireless networks and un-licensed wireless networks in ubiquitous sensor network environments, without troublesome settings or operations by users. These adaptive mobile terminals able to provide seamless services that adapt autonomously to the user's movements and changes in the state of wireless resources. Consequently, adaptive mobile terminals should be had respective independent hardware structure of usable wireless networks.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.261-264
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• 2004

We propose a location management with adaptive binding idle lifetime scheme for IP-based wireless network. In our proposed scheme, the binding idle lifetime value is adaptively varied according to user characteristics. The main idea is that the mobile node (MN) does location update (LU) even in idle state. Furthermore a sequential paging scheme is used to reduce the paging cost. The proposed scheme can be used in both cellular network and IP-based network.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.28-37
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• 2008

In this paper, we investigate the problem of minimizing the average transmission power of users while guaranteeing the average delay constraints in time-varying uplink channels. We design a scheduler that selects a user for transmission and determines the transmission rate of the selected user based on the channel and backlog information of users. Since it requires prohibitively high computation complexity to determine an optimal scheduler for multi-user systems, we propose a low-complexity scheduling scheme that can achieve near-optimal performance. In this scheme, we reduce the complexity by decomposing the multiuser problem into multiple individual user problems. We arrange the probability of selecting each user such that it can be determined only by the information of the corresponding user and then optimize the transmission rate of each user independently. We solve the user problem by using a dynamic programming approach and analyze the upper and lower bounds of average transmission power and average delay, respectively. In addition, we investigate the effects of the user selection algorithm on the performance for different channel models. We show that a channel-adaptive user selection algorithm can improve the energy efficiency under uncorrelated channels but the gain is obtainable only for loose delay requirements in the case of correlated channels. Based on this, we propose a user selection algorithm that adapts itself to both the channel condition and the backlog level, which turns out to be energy-efficient over wide range of delay requirement regardless of the channel model.