KSII Transactions on Internet and Information Systems (TIIS)
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v.12
no.5
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pp.1973-1991
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2018
Multimedia applications over wireless networks have been evolving to augmented reality or virtual reality services. However, a rich data size compared to conventional multimedia services causes bandwidth bottlenecks over wireless networks, which is one of the main reasons why those applications are not used widely. To overcome this limitation, bandwidth aggregation techniques, which exploit a multi-path transmission, have been considered to maximize link utilization. Currently, most of the conventional researches have been focusing on the user end problems to improve the quality of service (QoS) through optimal load distribution. In this paper, we address the joint pricing and load distribution problem for multi-homing in heterogeneous wireless access networks (ANs), considering the interests of both the users and the service providers. Specifically, we consider profit from resource allocation and cost of power consumption expenditure for operation as an utility of each service provider. Here, users decide how much to request the resource and how to split the resource over heterogeneous wireless ANs to minimize their cost while supporting the required QoS. Then, service providers compete with each other by setting the price to maximize their utilities over user reactions. We study the behaviors of users and service providers by analyzing their hierarchical decision-making process as a multileader-, multifollower Stackelberg game. We show that both the user and service provider strategies are closed form solutions. Finally, we discuss how the proposed scheme is well converged to equilibrium points.
Journal of the Korea Institute of Information and Communication Engineering
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v.12
no.5
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pp.930-936
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2008
CMOS image monitoring system for optimal measuring the activity of biosensor is developed using genetic algorithm. Most of living organism in water as water flea, fish, etc are frequently used as biological sensor for monitoring the water quality. It is very difficult to measure the activity of biosensor by image sensor because the value of measurement is varied with gathering method of biosensor images. The suggested monitoring system can optimally measures the activity of biosensor by genetic algorithm. The system is implemented with FPGA into the small hardware which is excellent in terms of the price and performance.
International Journal of Naval Architecture and Ocean Engineering
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v.3
no.3
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pp.181-192
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2011
Recently, the speed of change related with enterprise management is getting faster than ever owing to the competition among companies, technique diffusion, shortening of product lifecycle, excessive supply of market. For the example, the compliance condition (such as delivery date, product quality, etc.) from the ship owner is getting complicated and the needs for the new product such as FPSO, FSRU are coming to fore. This paradigm shift emphasize the rapid response rather than the competitive price, flexibility and agility rather than effective and optimal perspective for the domestic shipbuilding company. So, domestic shipbuilding companies have to secure agile and flexible ship production environment that could respond change of market and requirements of customers in order to continue a competitive edge in the world market. In this paper, I'm going to define a standard shipbuilding production management system by investigating the environment of domestic major shipbuilding companies. Also, I'm going to propose a unified ship production management and system for the operation of unified management through detail analysis of the activities and the data flow of ship production management. And, the system functions for the strategic approach of ship production management are investigated through the business administration tools such as performance pyramid, VDT and BSC. Lastly, the research of applying strategic KPI to the digital shipyard as virtual execution platform is conducted.
The Journal of Asian Finance, Economics and Business
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v.8
no.9
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pp.45-52
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2021
Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.
Bukhsuren, Enkhtuul;Sambuu, Uyanga;Namsrai, Oyun-Erdene;Namsrai, Batnasan;Ryu, Keun Ho
Journal of Information Processing Systems
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v.18
no.5
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pp.637-649
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2022
Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.
Solar energy had become the main energy industry of renewable energy along with hydroelectric power generation. One of the technologies that contributed to the popularization of photovoltaic power and the decrease in the unit price of photovoltaic modules was the large-area solar cell. However, as the area increased, the light receiving area increased and the current value increased accordingly. Since power loss occurs when the current value was large, the number of busbar was increased to increase the current collection rate, and a technology to lower the current value through half-cutting was developed. The bus bar of the solar cell served as a passage through which the generated current was transmitted. This was because when the number of busbar decreases, the moving distance of electrons increased, so the amount of power generation decreases and when it increases, shadows occured. An important aspect of the electrode design was the optimal balance of these busbars and number of fingers. Therefore, in this study, the characteristics of the solar cell according to the number of front bus bars of the large-area solar cell were simulated using Griddler 2,5 pro. After selecting the number of busbar with the best characteristics, the difference was compared by varying the number of fingers and a better direction for the number of cutting was presented.
Proceedings of the Korea Water Resources Association Conference
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2008.05a
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pp.500-504
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2008
The objective of this paper is to evaluate the feasibility of using an optimization model as a effective way to search conjunctive operation scheme to meet two conditions; one is to minimize the electric cost for pumping and another is to meet the water demand for satisfying customers. The feasibility is confirmed as comparing the best combinations of pumps between multi-regional water supply networks from multiple sources which are obtained through an optimization modeling and EPAnet modeling. KModsim model, a network optimization model, was used to determine conjunctive operation scheme in the pipe system. KModsim, based on Lagrangian Relaxation algorithm, is useful for modeling network system and obtaining simultaneously pump combination and water allocation with given input option such as energy unit cost supplying from a source into a consumer, operating pumping combination. This study develops the procedure of determining optimal conjunctive operation scheme with using KModsim model. As a study region, the water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. The EPAnet hydraulic simulation result(Ryu et al, 2007, KSWW) gave input data for optimization model; energy unit price(won/$m^3$), water service available area etc.. It was assured that the combination of pump operation through optimum conjunctive operation is to be optimum scheme to obtain the best economic water allocation with comparison to the hydraulic simulation result such as electric cost and pump combination cases. The results obtained through the study are as follows. First, It was found that a well-allocated water supply scheme, the best combination of pump operation through optimum joint operation, promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. Second, an application of KModSim, a network model, gave the amount of water allocation from each source to a consumer with consideration of economic supply. Finally, in a service area available to supply through conjunctive operation of existing inter-regional water supply networks within short distance, a conjunctive operation is useful for determining each transmission pipeline's service area and maximizing the effectiveness of optimizations in pumping operation time.
System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.
The purpose of this study is to examine the structural elements of HMR in Korea foods and explore the way HMR products using Korean foods can be developed at this time of increased interest. Through an investigation of its importance by attributes and their partial values, hypothetical HMR products using Korean foods were estimated. In order to develop the optimal HMR goods of Korean food, a preference survey was conducted after selecting 9 profiles using conjoint analysis with orthogonal design, and 4 holdout sets were generated and used for cross-validity authorization and reliability of the model. The results of this study showed that customers put cooking levels, menu price, and the location of purchase into importance when selecting HMR products of Korean foods. They preferred to eat the products after sufficiently heating them and buy the products sold online and through home shopping programs, with the price range of 10,000 won and over. It was concluded that more customers can be attracted if a variety of HMR products using Korean foods which can be prepared readily anywhere and at any time are developed.
Proceedings of the Korean Operations and Management Science Society Conference
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2005.10a
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pp.57-78
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2005
The vehicle routing problem (VRP) is to determine a set of feasible vehicle routes, one for each vehicle, such that each customer is visited exactly once and the total distance travelled by the vehicles is minimized. A feasible route is defined as a simple circuit including the depot such that the total demand of the customers in the route does not exceed the vehicle capacity. While there have been significant advances recently in exact solution methodology, the VRP is not a well solved problem. We find most approaches still relying on the branch and bound method. These approaches employ various methodologies to compute a lower bound on the optimal value. We introduce a new modelling approach, termed route-splitting, for the VRP that allows us to address problems whose size is beyond the current computational range of set-partitioning models. The route-splitting model splits each vehicle route into segments, and results in more tractable subproblems. Lifting much of the burden of solving combinatorially hard subproblems, the route-splitting approach puts more weight on the LP master problem, Recent breakthroughs in solving LP problems (Nemhauser, 1994) bode well for our approach. Lower bounds are computed on five symmetric VRPs with up to 199 customers, and eight asymmetric VRPs with up to 70 customers. while it is said that the exact methods developed for asymmetric instances have in general a poor performance when applied to symmetric ones (Toth and Vigo, 2002), the route splitting approach shows a competent performance of 93.5% on average in the symmetric VRPs. For the asymmetric ones, the approach comes up with lower bounds of 97.6% on average. The route-splitting model can deal with asymmetric cost matrices and non-identical vehicles. Given the ability of the route-splitting model to address a wider range of applications and its good performance on asymmetric instances, we find the model promising and valuable for further research.
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