• Korean Management Science Review
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• v.26 no.1
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• pp.21-35
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• 2009

There is a controversy on Internet pricing, flat-rate vs. usage-based. This study gives a comparative analysis between flat-rate and two-part tariff which is realistic alternative of usage-based pricing. In a basic economic model, two-part tariff based on ISP's cost structure satisfies allocative efficiency and relatively expand the number of subscribers. But the characteristics of Internet service like consumers' uncertainty on cost, measurement cost of traffic and network externality induce increase of cost or decrease of marginal utility. The analysis shows that small impact of these can make flat-rate more efficient.

• 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.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.797-820
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• 2018

Purpose: It is to seek for an appropriate cost rate analysis methodology of credit card value propositions in Korea. For this issue, it is claimed that methodologies based on probability distribution is more suitable than methodologies based on data-mining. The analysis model constructed for the cost rate estimation is called VCPM model. Methods: The model includes two major variables denoted as S and P. S is monthly credit card usage amount. P stands for the proportion of usage amount at special merchants over the whole monthly usage amount. The distributions assumed for P are positively skewed distributions such as exponential, gamma and lognormal. The major inputs to the model are also derived from S and P, which are E(S) and the aggregate proportion of usage amount at special merchants over the total monthly usage amount. Results: When the credit card's value proposition is general discount, the VCPM model fits well and generates reasonable cost rate(denoted as R). However, it seems that the model does not work well for other types of credit cards. Conclusion: The VCPM model is reliable for calculating cost rate for credit cards with positively skewed distribution of P, which are general discount card. However, another model should be built for cards with other types of distributions of P.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.57-66
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• 2023

Currently, a new energy system is emerging that implements consumption reduction by improving energy efficiency. Accordingly, as smart grids spread, the rate system by timing is expanding. The rate system by timing is a rate system that applies different rates by season/hour to pay according to usage. In this study, external factors such as temperature/day/time/season are considered and the time series prediction model, LSTM, is used to predict energy power usage data. Based on this energy usage prediction model, energy usage charges are reduced by analyzing usage patterns for each device and transferring power energy from the maximum load time to the light load time. In order to analyze the usage pattern for each device, a clustering technique is used to learn and classify the usage pattern of the device by time. In summary, this study predicts usage and usage fees based on the user's power data usage, analyzes usage patterns by device, and provides customized demand transfer services based on analysis, resulting in cost reduction for users.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• Journal of Information Management
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• v.38 no.4
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• pp.68-87
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• 2007

The purpose of the study is to understand the present state of practical use of electronic journal usage statistics at the academic libraries. For this purpose the study performed an online questionnaire survey to the 63 academic libraries located in Seoul and Gyeonggi Province. Based on the 48 responses, the study found out that the rate of satisfaction with the present usage data was low. Especially the rate of unsatisfaction with the absence of comparable data and the average usage rate of all the subscribing libraries appeared high. The study also examined 5 types of statistics for the evaluation of electronic journal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11B
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• pp.1007-1015
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• 2003

In this Paper, we propose a method of determining the price for the elastic traffic in the current or future Internet services. First, we investigate the behavior in the consumption of bandwidth of elastic traffic in IP network. Next, we propose a new method to relate the bandwidth usage with the pricing for the elastic traffic, which is based partially or fully on the usage rate of the network bandwidth. Next, we propose an optimal charging function for elastic traffic, which is applicable to any Internet services. Finally, we will illustrate the implication of the work via simple numerical experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.133-152
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• 2009

This paper analyze the fee structures of digital music contents and the revenue sharing ratios that are now on-going debates in Korean digital contents industry. Especially we consider Korean situation where copyrighters and telecom companies have conflict of interest. We found two major results. First, the choice between the flat rate scheme and the usage-based rate scheme is not important to telecom companies and copyrighters. The important thing is that copyrighters should decide the revenue sharing ratio and given that telecom companies should decide the retail price. Consequently, this way can lead to win-win solutions between them. Second, the flat rate scheme affects the relationship between consumers and telecom companies. Under the flat rate scheme, telecom companies have more benefits than consumers. In the vertical integrated structure, particularly, this tendency is more severe.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.41-57
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• 2023

This paper aims to analyse the factors influencing the implementation of smart factories and their performance after implementation, using the grounded theory analysis method based on interview data. The research subjects were 21 companies that were selected by the Smart Manufacturing Innovation Promotion Group under the SME Technology Information Promotion Agency in 2020-2021 as the best case smart factory implementation companies, and introduced the intermediate stage 1 or above. A total of 87 concepts were generated as a result of the analysis. We were able to classify them into 16 detailed categories, and finally derived six broad categories. These six categories are "motivation for adoption", "adoption context", "adoption level", "technology adoption", "usage effect" and "management effect". As a result of the overall structure analysis, it was found that the adoption level of smart factory is determined by the adoption motivation, the IT technology experience affects the adoption level, the adoption level determines the usage and usage satisfaction, internal and external training affects the usage and usage satisfaction, and the performance or results obtained by the usage and usage are reduced defect rate, improved delivery rate and improved productivity. This study was able to derive detailed variables of environmental factors and technical characteristics that affect the adoption of smart factories, and explore the effects on the usage effects and management effects according to the level of adoption. Through this study, it is possible to suggest the direction of adoption according to the characteristics of SMEs that want to adopt smart factories.

• Environmental Analysis Health and Toxicology
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• v.27
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• pp.3.1-3.4
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• 2012

Objectives: The current use of humidifier detergent and its harmful impact on humans has arisen as a societal environmental health issue. Therefore, in this study we aimed to explore the relationship between demo-socio characteristics and humidifier use, as well as the monthly usage changes in pregnant women; thus, we report the actual status of humidifier usage of Korea's pregnant population. Methods: From a birth cohort of a Mothers and Children's Environmental Health (MOCEH) study, 1,144 pregnant women who responded through questionnaires including demo-socio characteristics, obstetric status and household environment including whether they use humidifier and frequency of use were included in this study. Statistical analyses were performed to explore the relationship between maternal characteristics and the relevance of the use of humidifiers was performed using a chi-square test, a t-test and univariate logistic regression analysis. The monthly usage rate was demonstrated in the graph. Results: The humidifier usage rate in pregnant women was 28.2%. The average frequency of humidifier usage was 4.6 days per week, 7.3 hours per day. The usage rate was higher in the multipara group and the above the age of 34 age group than in the primipara and below the age of 34 groups. Seoul showed a higher usage rate than Cheonan and Ulsan and as the education level and income increased, the usage rate of humidifiers among pregnant women also increased. In the monthly trend of usage rate, the winter season showed the highest usage rate of over 45% and the lowest in late summer and beginning of fall with a value of 12% or less. Conclusions: During pregnancy, the mother's body is especially vulnerable to hazardous environmental exposure that not only affects the pregnant woman but also the fetus. Further research is still needed to elucidate the route and effect of environmental risk factors. Therefore, based on precautionary and preventive principles, special interest and caution in harmful environments are strongly needed not only at an individual level but also at a national level.