• Current Optics and Photonics
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• v.1 no.5
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• pp.474-490
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• 2017

Since the recent slowdown in the smartphone market, studies for wearable devices are briskly being carried out to find new markets, such as virtual reality devices. In this paper, a head-mounted display (HMD) which provides expanded virtual images before human eyes by enlarging images of a small display was designed, and the tolerance analysis method for a focus-adjustable HMD based on afocal optical systems was studied. There are two types of HMDs: a see-through type that allows the user to view the surroundings, and a see-close type where the user can only view the display screen; the former is used in this study. While designing the system, we allowed a lens within the system to be shifted to adjust its focus from +1 to -4 D (diopters). The yield of the designed systems was calculated by taking the worst-case scenario of a uniform distribution into account. Additionally, a longitudinal aberration was used rather than MTF for the tolerance analysis with respect to system performance. The sensitivity of the designed system was calculated by assigning a certain tolerance, and the focus lens shift was calculated to adjust the image surface variations resulting from the tolerance. The smaller the tolerance, the more expensive the unit price of the products. Very small tolerances may even be impossible to fabricate. Considering this, the appropriate tolerance was assigned; the maximum shift of the focus lens in which the image surface can be adjusted was obtained to find the changes in aberration and a good yield.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.359-365
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• 2017

This study was conducted structural model analysis focusing on the factors influencing UHDTV service usage. The perceived quality, innovativeness, price sensitivity are adopted as independent variables and perceived usefulness, perceived easy use are adopted as intervening variables. Especially symbolism used it as a control variable. As a result of the analysis by PLS, the influence coefficient of perceived quality was significantly higher than other variables. However, the combined effect of symbolism and perceived quality has a negative effect on perceived usefulness, and the more the users consider the symbolism of UHDTV usage, the more negative the evaluation of UHD quality and usefulness. With the launch of the terrestrial UHDTV service in May 2017, the most important issue is the production and distribution of high-quality content that users want.

• Journal of the Korean Society for Railway
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• v.15 no.3
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• pp.294-299
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• 2012

Rail transport has been considered an environmental-friendly transport mode compared with other transport modes such as ship, truck, and aircraft. However, air pollutions emitted by diesel locomotives have emerged as social issues. In addition, the railway industry may not be able to avoid a duty of alleviating greenhouse gases emission owing to the Korean government policies for green growth which is an economic paradigm that simultaneously pursues growth and environmental improvement. Moreover, rising oil prices has burdened a train operating company. The purpose of this paper is to develop a methodology of determining an economical speed of diesel freight locomotive from the viewpoint of the train operating company. In the methodology, we first define an operational cost function based on various cost factors and then suggest formula to calculate an economical speed of diesel freight locomotive. To estimate the influence of cost factors such as diesel price, carbon taxes, and time costs on the speed of diesel freight locomotive, sensitivity analysis was conducted.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.624-634
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• 2018

Indonesia has become a net crude oil importer because of the reduction of a new oil field discovery, and Indonesia is attempting to raise investment funds through the Kerja Sama Operasi (KSO) contract to develop a small-scale field. However, the KSO has a high-risk and low-return contract system for investors, necessitating an economic evaluation to examine the feasibility of the project. This study performed economic evaluation on the development of an Indonesian small-scale field by applying the KSO contract conditions, and identified the major economic parameters through a sensitivity analysis. As a result, the oil price, CAPEX and OPEX were identified as influential factors for economic evaluation. The results also indicate that commercial production in small-scale fields is difficult. In the future, this study can be used as a reference resource for investment in oil and gas development projects in Indonesia.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.24-35
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• 2021

Due to increasing awareness on the treatment of end-of-use/life products, disassembly has been a fast-growing research area of interest for many researchers over recent decades. This paper introduces a novel lot-sizing problem that has not been studied in the literature, which is the service-parts lot-sizing with disassembly option. The disassembly option implies that the demands of service parts can be fulfilled by newly manufactured parts, but also by disassembled parts. The disassembled parts are the ones recovered after the disassembly of end-of-use/life products. The objective of the considered problem is to maximize the total profit, i.e., the revenue of selling the service parts minus the total cost of the fixed setup, production, disassembly, inventory holding, and disposal over a planning horizon. This paper proves that the single-period version of the considered problem is NP-hard and suggests a heuristic by combining a simulated annealing algorithm and a linear-programming relaxation. Computational experiment results show that the heuristic generates near-optimal solutions within reasonable computation time, which implies that the heuristic is a viable optimization tool for the service parts inventory management. In addition, sensitivity analyses indicate that deciding an appropriate price of disassembled parts and an appropriate collection amount of EOLs are very important for sustainable service parts systems.

• Korean Chemical Engineering Research
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• v.56 no.1
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• pp.6-13
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• 2018

Utilizing the heat of cooling water discharge of coal-fired power plant, pipeline investment costs for businesses that supply heat to agricultural facilities near power plants increase in proportion to installation distance. On one hand, the distance from the power plant is a factor that brings difficulties to secure economic efficiency. On the other, if the installation distance is short, there is a problem of securing the heating demands, facility houses, which causes economical efficiency to suffer. In this study, the economic efficiency of 1km length of standard heat pipeline was evaluated. The sensitivity of the heat pipe to the new length variation was analyzed at the level of government subsidy, amount of heating demand and the incremental rate of pipeline with additional government subsidy. As a result of the analysis, it was estimated that NPV 131 million won and IRR 15.73%. The sensitivity analysis showed that NPV was negative when the length of heat pipe facility exceeded 2.6 km. If the government supports 50% of the initial investment, the efficiency is secured within the estimated length of 5.3 km, and if it supports 80%, the length increases within 11.4 km. If the heat demand is reduced to less than 62% at the new length of the standard heat pipe, it is expected economic efficiency is not obtained. If the ratio of government subsidies to initial investment increases, the elasticity of the new bloc will increase, and the fixed investment, which is the cost of capital investment for one unit of heating demand, will decrease. This would result in a reduction in the cost of production per unit, and it would be possible to supply heat at a cheaper price level to the facility farming. Government subsidies will result in the increased economic availability of hot plumbing facilities and additional efficiencies due to increased demand. The greater government subsidies to initial investment, the less farms cost due to the decrease in the price per unit. The results of the study are significant in terms of the economic evaluation of the effectiveness of the government subsidy for the thermal power plant heat utilization project. The implication can be applied to any related pilot to come.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• The Journal of Fisheries Business Administration
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• v.14 no.2
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• pp.15-68
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• 1983

From the economic point of view the fishing port is the complex of installations on land, organized to serve the fishing fleet and its cargo, and is the main link in the production chain of all components of the fishing industry, with the aim of achieving the planned targets with the minimum cost. Fishing port investment decisions have had significant impact on the development aims of Korean fisheries. Fishing port investments in Korea are made mostly by public or semipublic port authorities. Such investments should be judged not purely on the basis of financial profitability but rather on the extent to which they serve the development aims of the fishing industry. This makes the economic appraisal process more complex and presents certain problems in correctly quantifying the economic costs and benefits of the fishing port projects. This study concentrates more on the theoretical economic appraisal models than on the purely financial aspects of fishing port investments and points out the difference between the two approaches. In the result, there is clearly an element of judgment as to whether or not a shadow price needs to be used in estimating economic benefits and costs. From this viewpoint, some attempts are made to provide definitions of the possible economic benefits and costs, and methods for estimating and evaluating them in Part III and IV. Especially queueing theory is applied in the calculation of economic benefits. When a project is contemplated and analysis shows it to Lave a positive NPV, one question that arises is whether it should be implemented now or delayed. In this paper, the first year rate of return method is regarded as a more concise way of solving the timing of investment, At the end of Part IV, risk analysis of fishing port investments is considered. It can be handled in a number of ways, ranging from informal judgment to complex statistical analyses involving large-scale computer models, This paper recommends that evaluators of fishing port investments use the sensitivity analysis indicating exactly how much NPV will change in response to a given change in an input variable, other things held constant. Decisions regarding the amount of capacity to provide must be made in fishing port investments. Providing too much service would involve excessive capital costs. On the other hand, not providing enough service capacity would cause the waiting line of fishing vessels to become excessively long at times. Therefore, in Part V, the optimal number of berths and berth productivity in fishing port are defined as follows: Minimize E(TC) ＝ E(WC)＋E(SC) The minimum of this function is the solution and that is the optimal number of berth and berth productivity in fishing port.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.21-28
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• 2018

In recent years, payability of shale gas production has worsened due to oil and gas price declines resulting from sharply increasing shale gas production. Reliable economic evaluation in shale gas development has become important. In this study, Monte Carlo simulation of probabilistic analysis technique was applied to analyze the economic feasibility considering the uncertainty involved in shale gas development. For this, the range of major variables is set and a random number is generated to derive the probability distribution of Net Present Value(NPV) and Internal Rate of Return(IRR). Consequently, we estimated the probability that the feasibility of the project is evaluated to be positive when developing shale gas in the study area. In addition, sensitivity analysis of major parameters affecting economic efficiency in shale gas development was carried out, and the effect of major variables in economic evaluation for commercial production was identified. In the future, this study could be used to make decision for shale gas production by presenting the range of variation of economic index and probability value.