• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.348-354
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• 2005

These days, Electronic mail is being used in everyday's life. And on the other hand, we are facing spam mails' problems. Spam mails are widely used by means of marketing in e-Commerce. To block these spam mails, we are using filtering or pricing systems. But these solutions are raising other problems such as impediment in reception or availability caused by false positive or payment resistance. To solve these problems, we propose an Indirect Model on Electronic Mail Control System(IMEMCS) which controls an unsolicited electronic mail and prevents an useful electronic mail from discarding. We design and implement the IMEMCS to enhance the usefulness and the availability. Being tested the IMEMCS to verify the usability and the efficiency, it gave us a very successful result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2631-2649
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• 2021

Device-to-Device (D2D) communication is one of the enabling technologies for 5G networks that support proximity-based service (ProSe) for wireless network communications. This paper proposes a power control algorithm based on the Nash equilibrium and game theory to eliminate the interference between the cellular user device and D2D links. This leadsto reliable connectivity with minimal power consumption in wireless communication. The power control in D2D is modeled as a non-cooperative game. Each device is allowed to independently select and transmit its power to maximize (or minimize) user utility. The aim is to guide user devices to converge with the Nash equilibrium by establishing connectivity with network resources. The proposed algorithm with pricing factors is used for power consumption and reduces overall interference of D2Ds communication. The proposed algorithm is evaluated in terms of the energy efficiency of the average power consumption, the number of D2D communication, and the number of iterations. Besides, the algorithm has a relatively fast convergence with the Nash Equilibrium rate. It guarantees that the user devices can achieve their required Quality of Service (QoS) by adjusting the residual cost coefficient and residual energy factor. Simulation results show that the power control shows a significant reduction in power consumption that has been achieved by approximately 20% compared with algorithms in [11].

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5531-5536
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• 2015

Background: Increased pricing of cigarettes might be one of the most effective approaches for reducing the prevalence of smoking. This study aimed to investigate the effects of increasing cigarette prices through taxation by a tobacco intervention policy on the changes in smoking prevalence in Korean university students. Materials and Methods: The participants in this study were 23,047 healthy university students aged 18-29 years from a health examination in 2011-2015. We investigated the adjusted prevalence of daily and occasional smoking before and after increasing cigarette prices through taxation. Results: The prevalence of occasional smoking was significantly decreased in 2015 from 2014 in both male (from 10.7% in 2014 to 5.4%) and female (from 3.6% to 1.1%) students, but the prevalence of daily smoking did not decrease significantly. The frequency of individuals who had attempted smoking cessation during the past year was significantly higher among occasional smokers in male students (90.2%) compared with daily smokers (64.9%). For female students, there were no differences in experience of smoking cessation, willingness for smoking cessation, or E-cigarette experience between daily and occasional smokers. Conclusions: We found that a policy of increasing cigarette prices through taxation is associated with decreases in the prevalence of occasional smokers, who have relatively lower nicotine dependence compared with individuals who smoke daily. The results of our study suggest that social support and direct intervention for smoking cessation at the community level are needed for university students alongside the pricing policy.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.75-106
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• 2007

In this study, it is analyzed whether oil price plays a major role in the pricing return on Koran stock market and examined why the covariance risk between oil and return on stock is different in each industry. Firstly, this study explores whether the expected rate of return on stock is pricing due to global oil price factors as a function of risk premium by using a two-factor APT. Also, it is examined whether spill-over effects of oil price volatility affect the beta risk to oil price. Considering the asymmetry of oil price volatility, we use the GJR model. As a result, it shows that oil price is an independent pricing factor and oil price volatility transmits to stock return in only electricity and electrical equipment. Secondly, the two step-analyzing process is introduced to find why the covariance between oil price factor and stock return is different in each industry. The first step is to study whether beta risk exists in each industry by using two proxy variables like size and liquidity as control variables. The second step is to grasp the systematic relationship between the difference of liquidity and size and beta to oil price factor by using the panel-data model which can be analyzed efficiently using the cross-sectional data formed with time series. Through the analysis, we can argue that oil price factor is an independent pricing factor in only electricity and electrical equipment having the greatest market capitalization, and know that beta risk to oil price factor is a proxy of size in the other industries. According to the result of panel-data model, it is argued that the beta to oil price factor augments when market capitalization increases and this fact supports the first assertion. In conclusion, the expected rate of return of electricity and electrical equipment works as a function of risk premium to market portfolio and oil price, and the reason to make beta risk power differentiated in each industry attributes to the size.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.158-163
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• 2005

Competitive electricity markets necessitate equitable methods for allocating transmission usage in order to set transmission usage charges and congestion charges in an unbiased and an open-accessed basis. So in competitive markets it is usually necessary to trace the contribution of each participant to line usage, congestion charges and transmission losses, and then to calculate charges based on these contributions. A UPFC offers flexible power system control, and has the powerful advantage of providing, simultaneously and independently, real-time control of voltage, impedance and phase angle, which are the basic power system parameters on which sys-tem performance depends. Therefore, UPFC can be used efficiently and flexibly to optimize line utilization and increase system capability and to enhance transmission stability and dampen system oscillations. In this paper, a mathematical approach to allocate the contributions of system users and UPFCs to transmission system usage is presented. The paper uses a dc-based load flow modeling of UPFC-inserted transmission lines in which the injection model of the UPFC is used. The relationships presented in the paper showed modified distribution factors that modeled impact of utilizing UPFCs on line flows and system usage. The derived relationships show how bus voltage angles are attributed to each of changes in generation, injections of UPFC, and changes in admittance matrix caused by inserting UPFCs in lines. The relationships derived are applied to two test systems. The results illustrate how transmission usage would be affected when UPFC is utilized. The relationships derived can be adopted for the purpose of allocating usage and payments to users of transmission network and owners of UPFCs used in the network. The relationships can be modified or extended for other control devices.

• Current Photovoltaic Research
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• v.4 no.3
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• pp.124-129
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• 2016

Recently industry has voiced a need for optimally designing the production process of low-cost, high-quality ingots by improving productivity and reducing production costs with the Czochralski process. Crystalline defect control is important for the production of high-quality ingots. Also oxygen is one of the most important impurities that influence crystalline defects in single crystals. Oxygen is dissolved into the silicon melt from the silica crucible and incorporated into the crystalline a far larger amount than other additives or impurities. Then it is eluted during the cooling process, there by causing various defect. Excessive quantities of oxygen degrade the quality of silicone. However an appropriate amount of oxygen can be beneficial. because it eliminates metallic impurities within the silicone. Therefore, when growing crystals, an attempt should be made not to eliminate oxygen, but to uniformly maintain its concentration. Thus, the control of oxygen concentration is essential for crystalline growth. At present, the control of oxygen concentration is actively being studied based on the interdependence of various factors such as crystal rotation, crucible rotation, argon flow, pressure, magnet position and magnetic strength. However for methods using a magnetic field, the initial investment and operating costs of the equipment affect the wafer pricing. Hence in this study simulations were performed with the purpose of producing low-cost, high-quality ingots through the development of a process to optimize oxygen concentration without the use of magnets and through the following. a process appropriate to the defect-free range was determined by regulating the pulling rate of the crystals.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.449-458
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• 2010

In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.285-299
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• 2016

Although South Korea experienced a rolling blackout in 2011, the possibility of a blackout in South Korea continues to increase due to rapid electrification. This study examines the problems of energy taxation and price distortions as possible reasons for the rapid electrification in South Korea, which is occurring at a faster rate than in Japan, Europe, and other developed countries. Further, we suggest new energy taxation and price systems designed to normalize electricity prices. In order to do so, we consider two possible scenarios: the first imposes a tax on bituminous coal for electricity generation and the second levies a tax to provide compensation for the potential damages from a nuclear accident. Based on these scenarios, we analyze the effects of a new energy system on electricity price and demand. The results show that a new energy system could guarantee the power generation costs and balance the relative prices between energy sources, and could also help prevent rapid electrification. Therefore, the suggested new energy system is expected to be utilized as a basis for energy policy to decrease the speed of electrification, thus preventing a blackout, and to induce the rational consumption of energy in South Korea.

• Journal of the East Asian Society of Dietary Life
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• v.19 no.2
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• pp.278-286
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• 2009

Restaurants have two strategic levers for revenue management: duration control and demand-based pricing. Reducing dining times, especially during peak periods, can add considerable revenue for restaurants. Managing meal duration, however, can be far more complex than manipulating the price. This paper examines dining duration expectations for restaurants types(Family, Korean, Quick service restaurant), customers characteristics(gender, age, occupation, meal period, visiting frequency, dining occasion, dining companions) using an a adaptation of a price sensitivity measurement tool, naming it 'Time Sensitivity measurement tool' or TSM. The TSM is then used to derive the optimal time points, and the range of acceptable times. The results demonstrate that there is a relatively wide spread of acceptable dining duration times in family restaurant. Furthermore, the optimal time points was shorter than the mean expected dining times, which suggests that many restaurants may be able to shorten dining duration without compromising customer satisfaction. The paper explores whether demographic and dining variables have an impact on time preferences, and finds whether gender, age, meal periods, visiting frequency, and dining companion effects are significant. Specifically, women in their thirties tended to prefer a significantly longer dining times for dinner.