• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.16-22
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• 2016

This paper addresses the load usage scheduling in the HEMS for residential power consumers. The HEMS would lead the residential users to change their power usage, so as to minimize the cost in response to external information such as a time-varying electricity price, the outside temperature. However, there may be a consumer's inconvenience in the change of the power usage. In order to improve this, it is required to understand the pattern of load usage according to the external information. Therefore, this paper suggests a methodology to model the load usage pattern, which classifies home appliances according to external information affecting the load usage and models the usage pattern for each appliance based on a copula function representing the correlation between variables. The modeled pattern would be reflected as a constraint condition for an optimal load usage scheduling problem in HEMS. To explain an application of the methodology, a case study is performed on an electrical water heater (EWH) and an optimal load usage scheduling for EHW is performed based on the branch-and-bound method. From the case study, it is shown that the load usage pattern can contribute to an efficient power consumption.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.39-47
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• 2018

This paper confirms the risk of using smartphone through the analysis of collected usage pattern and proposes the smartphone intervention system in risk situations. In order to check the risk of smartphone usage, we made information collecting application and collected smartphone usage pattern from 11 experiment participants for two months. By analyzing smartphone usage pattern, we confirmed that about 12% of smartphone usage is being used in driving, walking, and on the street. In addition, we analyzed the response rate of smartphone notification in risk situations and confirmed that user responds the smartphone notifications in real-time even in risk situations. Therefore, it is required to present a system that intervenes the use of smartphone in order to protect smartphone users in risk situations. In this paper, we classify risk situations of using smartphone. Also, the proposed smartphone intervention system is designed to periodically detect risk situations. In risk situations, smartphone function can be restricted according to user setting of smartphone. And smartphone can be used normally when safe situation is restored.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.05a
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• pp.205-242
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• 2001

This paper aims to provide a better understanding about how Information and Communication technology (ICT) has diffused. The investigation is conducted with the consideration of ICT evolution in terms of technological change and usage pattern. The definition used is presented as 'the ICT is a process of convergence of technologies between information-processing and information-transforming technologies, mainly due to the advent of microelectronlcs'. After examining technological changes of ICT, the diffusion path of ICT is traced through the usage ratio in total input and/or investment based on Input-Output tables (I-O). It shows that the evolution of ICT from the change of usage pattern is an up-and-down usage pattern rather than a uni-modal usage time path. With this recognition, the diffusion index is prepared. JEL classification : C43, L63, O33.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2272-2279
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• 2014

Mobile applications are software systems running on handheld devices, such as smartphones, PDAs, tablets and so on. The market of mobile application has rapidly expanded in the past few years. In this paper, we present a novel approach to track smartphone application usage from a event logs on the mobile device and analyzed both on client system and usage analysis server. We implemented our client system on Android device based usage analytics platform. Based on the analysis server system, we obtained over 47,000 user base, and we get the user's app usage informations on realtime. In this paper, we describe a large scale deployment-based research for a smartphone usage patterns and usage information visualization techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2490-2506
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• 2022

In Mobile Edge Computing (MEC), attackers can speculate and mine sensitive user information by eavesdropping wireless channel status and offloading usage pattern, leading to user privacy leakage. To solve this problem, this paper proposes a Privacy-preserving and Energy-efficient Offloading Algorithm (PEOA) based on Lyapunov optimization. In this method, a continuous Markov process offloading model with a buffer queue strategy is built first. Then the amount of privacy of offloading usage pattern in wireless channel is defined. Finally, by introducing the Lyapunov optimization, the problem of minimum average energy consumption in continuous state transition process with privacy constraints in the infinite time domain is transformed into the minimum value problem of each timeslot, which reduces the complexity of algorithms and helps obtain the optimal solution while maintaining low energy consumption. The experimental results show that, compared with other methods, PEOA can maintain the amount of privacy accumulation in the system near zero, while sustaining low average energy consumption costs. This makes it difficult for attackers to infer sensitive user information through offloading usage patterns, thus effectively protecting user privacy and safety.

• Journal of Digital Convergence
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• v.5 no.1
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• pp.117-130
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• 2007

This paper examines whether there exists discrimination of the information usage pattern between tenants of permanent and temporary public rental housing in Korea. Moreover, we focus to examine on that matters between two groups, $7{\sim}12$ pyeongs and $11{\sim}24$ pyeongs that indicate permanent and temporary public rental housing respectively. The results derived in this paper can be summarized as follows: there exists statistical significance in using computer, internet, communication and broadcasting, on the other hand, insignificance in using satellite communication and telephone between them. The implication of this results shows that as widen income gap, also widen gaps in using computer and internet between them. Thus government public rental housing policy should focus to make narrow income gap to diminish information gap between those groups.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.271-279
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• 2001

Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.338-345
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• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• Korean Management Science Review
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• v.13 no.3
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• pp.115-128
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• 1996

System usage, the utilization of information technology(IT) by individuals, groups or organizations, is a core variable in IS research. Indeed, there is widespread agreement among researchers that system usage is the primary variable through which IT affects white collar performance because it is a requisite, albeit insufficient, for deriving the benefits of IT. Furthermore, system usage has a notable practical value for managers interested in evaluating the impact of IT. Despite the number of studies of targeted at explaining system usage, there are more areas which required for the verification of system usage. The purpose of this paper is to address, using the Technological Acceptance Model (TAM), the usage pattern of AHP toward the various task in group decision (GD). The result showed that, for the all of the task types, perceived usage (PU) has more effect than perceived ease-of-use(PEU) on the AHP usage. However, more researches are required to generalize the result of this study.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.251-265
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• 2013

The emergence of social network services, is changing the foundation of human relationship formation and method of communication of individuals through sharing of free information. Social network service is a service to support or facilitate an on-line extension of off-line network among people by helping them to share personal profile. History of social network services very short. But users of the various layers is increasing rapidly and ripple effect social as a result is very large. The focus of existing research was mainly devoted to motivation of use and acceptance of social network services. Currently the use of SNS was maturing. Thus, in-depth research on the use pattern of SNS users is needed. The purpose of this study is that, for Facebook in social network services, to analyze the changes in the initial stage of use, medium-term, usage patterns at the current time. Results of the study by analyzing the characteristics of the change in the pattern of usage of user of Facebook, it can be used as basic materials for SNS researchers and service provider.