• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.36-44
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• 2000

The purpose of this study is to introduce a more efficient forecasting technique, which could help result the reduction of cost in removing the waste of airline in-flight meals. We will use a neural network approach known to many researchers as the “Outstanding Forecasting Technique”. We employed a multi-layer perceptron neural network using a backpropagation algorithm. We also suggested using other related information to improve the forecasting performances of neural networks. We divided the data into three sets, which are training data set, cross validation data set, and test data set. Time lag variables are still employed in our model according to the general view of time series forecasting. We measured the accuracy of our model by “Mean Square Error”(MSE). The suggested model proved most excellent in serving economy class in-flight meals. Forecasting the exact amount of meals needed for each airline could reduce the waste of meals and therefore, lead to the reduction of cost. Better yet, it could enhance the cost competition of each airline, keep the schedules on time, and lead to better service.

• Korean Journal of Agricultural Science
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• v.44 no.3
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• pp.424-439
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• 2017

This study was undertaken to examine the profit efficiency and its determining factors, the investment opportunity, and the challenges of shea butter producers in the northern region of Ghana. The methods employed in this research were the Stochastic Profit Frontier (SPF) model, gain-cost and investment return analyses, as well as Kendall's W statistic using primary data collected from 120 purposively-selected respondents. Results from the analysis indicated that profit efficiency was positively influenced by sex, household size, marital status, educational level, transportation cost, store rent, and price of shea nut with a gain in profit efficiency of 58.5%. The investment analysis demonstrated a net gain per person of $8,077 equivalent to GH₵ 28,270 Ghanaian cedi (GH₵) using 2016 exchange rate (GH₵ 3.5 = $1). Among the challenges identified, the poor quality of shea nuts was the most prioritised challenge with 72.8% agreement among the respondents. Based on these findings, it was recommended that proper training and education, as well as improvement in shea nut quality, should be promoted to improve the profit efficiency of shea butter producers.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.210-218
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• 2021

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

• Journal of Forest and Environmental Science
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• v.33 no.2
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• pp.147-153
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• 2017

The purpose of this study was to examine productivity and cost of tree-length harvesting using cable yarding system in a larch (Larix leptolepis) clear-cutting stand located in Pyeongchang-gun, Gangwon-do. We used tree-length harvesting method using cable yarding system with a tower yarder HAM300. The productivity was $17.6m^3/hr$ for felling, $12.4m^3/hr$ for delimbing, $4.2m^3/hr$ for yarding, and $8.1m^3/hr$ for processing. The total cost of the harvesting system was $48,381won/m^3$, which was majorly composed of yarding operation cost, at $40,169won/m^3$ (79.3%), while felling had the lowest cost at $1,154won/m^3$ (4.1%). Major factors affecting felling and processing productivity was tree volume and the number and thickness of branches for delimbing productivity. In addition, we suggest that training and education for machine operators were critical to improve yarding productivity.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.141-148
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• 2013

Traditional face-to-face university education has shifted its course to combine the advantages of both online and offline education in a blended-learning approach. However, there is still much that is unknown about the actual effect of blended learning, particularly it's learning outcomes in terms of cost effectiveness. This study qualitatively examines the costs and the learning outcomes of blended learning at an on-line college and off-line university. Online college level English pedagogy courses and blended with offline operations at an online university were studied across two semesters in terms of the quality of education, and both direct and indirect cost savings. Other causes for various learning outcomes and cost implications are proposed and validated.

• Journal of Construction Engineering and Project Management
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• v.10 no.1
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• pp.16-32
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• 2020

Cost and time control of projects is important in preventing project failure. However, achieving effective cost and time control in practice is often challenging. The challenges of project cost and time control in practice are investigated by carrying out a questionnaire survey on the top 150 construction contractors in the UK followed by in-depth semi-structured interviews of practitioners from 15 construction companies in the country. Quantitative analysis reveals that design change is the most important factor inhibiting the ability of UK contractors from effectively controlling both the cost and time of construction projects. Four of the top five factors inhibiting effective cost control are also the top factors inhibiting effective time control albeit in a different order. These top factors-design changes, inaccurate evaluation of project time/duration, risk and uncertainty, non-performance of subcontractors and nominated suppliers were also found to be endogenous factors to the project. Additionally, qualitative analysis of the interviews reveals 16 key challenges to prevent for effective project cost and time control in practice. These are classified into four categorised based on where they stem from as follows; from the organisation (1. Lack of integration of cost and time during project control, 2. lack of management buy-in, 3. complicated project control systems and processes, 4. lack of a project control training regime); from the construction management/project management approach (5. Lapses in integration of interfaces, 6. project control not being implemented from the early stages of a project, 7. inefficient utilisation and control of labour, 8. limited time devoted to planning how a project will be controlled at the outset); from the client; (9. Excessive authorisation gates, 10. use of adversarial and non-collaborative forms of contracts, 11. communication problems within client set-up, 12. obstructive client representatives) and; from the project team (13. Lack of detailed/complete design, 14. lack of trust among the project partners, 15. limited time devoted to project control on site, 16. non-factual reporting). The study posits that knowledge of these project control inhibiting factors and challenges is the first step at ensuring they are avoided and enable the implementation of a more effective project cost and time control process in practice.

• Archives of Plastic Surgery
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• v.49 no.4
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• pp.531-537
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• 2022

Wide-awake, local anesthesia, no tourniquet (WALANT) is a technique that removes the requirement for operations to be performed with a tourniquet, general/regional anesthesia, sedation or an anesthetist. We reviewed the WALANT literature with respect to the diverse indications and impact of WALANT to discuss the importance of future surgical curriculum integration. With appropriate patient selection, WALANT may be used effectively in upper and lower limb surgery; it is also a useful option for patients who are unsuitable for general/regional anesthesia. There is a growing body of evidence supporting the use of WALANT in more complex operations in both upper and lower limb surgery. WALANT is a safe, effective, and simple technique associated with equivalent or superior patient pain scores among other numerous clinical and cost benefits. Cost benefits derive from reduced requirements for theater/anesthetic personnel, space, equipment, time, and inpatient stay. The lack of a requirement for general anesthesia reduces aerosol generating procedures, for example, intubation/high-flow oxygen, hence patients and staff also benefit from the reduced potential for infection transmission. WALANT provides a relatively, but not entirely, bloodless surgical field. Training requirements include the surgical indications, volume calculations, infiltration technique, appropriate perioperative patient/team member communication, and specifics of each operation that need to be considered, for example, checking of active tendon glide versus venting of flexor tendon pulleys. WALANT offers significant clinical, economic, and operative safety advantages when compared with general/regional anesthesia. Key challenges include careful patient selection and the comprehensive training of future surgeons to perform the technique safely.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

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.

• Management & Information Systems Review
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• v.33 no.4
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• pp.1-19
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• 2014

This Study focuses on the university students' job attitude and cost of employment preparation. Nowadays, many university and college students spend a big money improving their employment preparation such as studying on foreign language, getting various kinds of certificates and tooth correction, clothing etc. for employment interview. This study investigated the cost of employment preparation and Job attitude of the 484 students of universities and colleges, the analysis of the collected data was conducted with SPSS 12.0 program by using frequency analysis, factor analysis, reliability assessment, correlation test, t-test, one way ANOVA. The university students paid more costs of employment preparation such as a language training abroad, a private training, and clothing than the college students. Also, Allied social science students paid more costs of the language training abroad, and clothing than allied computer science and allied design students. The female students paid more money than male students for tooth correction. The costs of language training abroad, private training and clothing are affected the students' socioeconomic background of a home. Regarding the job attitude of students, the university students are feeling more positive than the college students of the employment efficacy and cognition of the education environment. As result, the differences in the cost of employment preparation by the university type, faculty major course, their sex, and socioeconomic background of a home. The student's employment-efficacy and cognition of the education environment are also differences between the university and the college students. So, to improve the job attitude, developing their ability for employment preparation, educational programs should be arranged in school and continuous researches are needed.