• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Drive and Control
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• v.17 no.1
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• pp.27-36
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• 2020

The aim of this study is to design a simulation model for an electric All-Wheel-Drive (AWD) tractor to evaluate the performance of the selected component and agricultural work ability. The electric AWD tractor consists of four motors independently for each drive wheel, and each motor is combined with an engine generator, a battery pack, and reducers. The torque data of a 78 kW-class tractor was measured during plow tillage and driving operation to develop a workload cycle. A simulation model was developed by using commercial software, Simulation X, and it used the workload as the simulation condition. As a result of simulation analysis, the drive system, including an electric motor and reducers, was able to cope with high load during plow tillage. The SOC (State of Charge) level was influenced by the output power of the motor, and it was maintained in the range of 50~80%. The fuel consumed by the engine was about 18.23 L during working on a total of 8 fields. The electric AWD tractor was able to perform agricultural work for about 7 hours. In the future study, the electric AWD tractor will be developed reflecting the simulation condition. Research on the comparison between the simulation model and the electric AWD tractor should be performed.

• Journal of Families and Better Life
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• v.27 no.6
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• pp.229-242
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• 2009

This study investigates how bioecological variables affect the child's multiple intelligence through independent and interactional ways. The subjects of this study were 147 pairs of 5-year-old children and their mothers, and the Project Spectrum was employed to measure multiple intelligences. Each mothers was asked to answer a questionnaire on her child's temperament, her maternal parenting style, 'goodness of fit' and 'the fit of child's intelligence'. Data were analyzed using a factor analysis and a hierarchical multiple regression with SPSS WIN 15.0. The main findings were as followings; First, 'the goodness of fit' to the child's temperament moderated the effect of a maternal parenting style that would foster child's dependency on the mathematical intelligence through interaction. 'The fit of child's intelligence' also moderated the effect of maternal positive parenting style to the child's mathematical intelligence. Second, in language intelligence, girls were more verbally intelligent than boys. In that regard, because the sex variable entails a combination of both inherent attribute and social-cultural effects, that result can be interpreted as an interaction between the individual and the environment. Lastly, a maternal parenting style that would foster child's dependency moderated the effect of the child's regular temperament on interpersonal intelligence. This means that the child's regular temperament can be a protective factor for the negative effect of a maternal parenting style that would foster child's dependency This study suggests that interactional factors such as 'goodness of fit' should be considered in studies involving children.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3848-3854
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• 2000

For the satisfying performance of a control system, design of a controller for the system which meets the required specifications and its supporting hardware that keep their functioning is important. Among the hardware of a control system, sensors are most vulnerable to malfunction. Thus it is necessary to keep track of accurate and reliable sensor readings for good controller performance. In case of sensor faults. they are detected by examining the sensor output values and the major values of the system, and then the types of the faults are recognized by the analysis of symptoms of faults. If necessary self-validating sensor values are synthesized according to the types of faults, and then they are used for the controller instead of the raw data.In this paper, a self 'validating sensor is applied to the control of a flexible link system with the sensor fault problems in the light sensor module for exact IXlsitioning to show the applicahility. It is shown that the digital controller can provide a satisfactory loop performance even when the sensor faults occur.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.801-808
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• 2013

In the virtual space with the interactive 3D contents, the degree of mental satisfaction is determined by how fully it reflect the real world. There are a few factors for getting the high completeness of virtual space. The first is the modeling technique with high-polygons and high-resolution textures which can heighten an visual effect. The second is the functionality. It is about how realistic represents dynamic actions between the virtual space and the user or the system. Although the studies on the techniques for animating and controlling the virtual characters have been continued, there are problems such that the long production time, the high cost, and the animation without expected behaviors. This paper suggest a method of behavior control of animation by designing the optimized skeleton which produces the movement of character and applying the procedural technique using physical law and mathematical analysis. The proposed method is free from the constraint on one-to-one correspondence rules, and reduce the production time by controlling the simple parameters, and to increase the degree of visual satisfaction.

• Journal of Fashion Business
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• v.12 no.4
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• pp.73-87
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• 2008

The main objective of this research was to investigate the characteristics of achromatic & chromatic color coordination of contemporary female fashion by reviewing 'pre-a-porter Collections' of four collections (i. e. cities) - Paris, Milan, New York, London - from the periods of 2002 S/S to 2006/7 A/W. The data was collected by reviewing 'pre-a-porter Collections' magazine and total 677 observations were made. Statistical analysis of frequency and also qualitative interpretation of achromatic & chromatic color coordination characteristics were completed. The main findings were; (1) The achromatic & chromatic color coordination was identified as one of most used color coordination in contmeporary women's fashion collections. (2) Black and white mainly used for achromatic color, and brown used the most often, then followed by blue, red, yellow, green and the others for chromatic color in achromatic & chromatic coordination of contmeporary women's fashion collections. (3) The characteristics of achromatic & chromatic color coordination of modern women's fashion collections from 2002 S/S to 2006/07 A/W showed various images according to chromatic colors and tone variation. The combination of achromaticand brown color variations produced an intelligent and sophisticated image. The soft or light chromatic color and chromatic color combination projected soft, feminine and subtle feeling, while the combination of vivid or strong chromatic color and achromatic color projected a clean and strong feeling through contrasting tones of clear and bright colors. The chromatic color of deep or dark tone and black combination demonstrated supernatural and gloomy image. (4)In all four collections, Paris showed most use of two color coordination and then followed by Milan, N.Y, and London. N.Y showed higher rate of using achromatic & chromatic color coordination, and then followed by Paris, London and Milan.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.99-114
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• 2011

Collaborative Filtering (CF) suffers from two major problems:sparsity and cold-start recommendation. This paper focuses on the cold-start problem for new customers with no purchase records and the sparsity problem for the customers with very few purchase records. For the purpose, we propose a method for the new customer recommendation by using a combined measure based on three well-used centrality measures to identify the customers who are most likely to become neighbors of the new customer. To alleviate the sparsity problem, we also propose a hybrid approach that applies our method to customers with very few purchase records and CF to the other customers with sufficient purchases. To evaluate the effectiveness of our method, we have conducted several experiments using a data set from a department store in Korea. The experiment results show that the combination of two measures makes better recommendations than not only a single measure but also the best-seller-based method and that the performance is improved when applying the hybrid approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.407-415
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• 2015

The railway route and alignment planning have been executed with a limited number of alternatives based on the site pre-survey and the topographic map. This study developed an intelligent railway alignment planning program (ei-Rail) which can derive all the considerable design alternatives and provide the data for the alternative evaluation such as constructions cost, operation cost, and etc. According to the comparisons with prevailing planned railway projects, the time and cost for planning can be reduced as well as the construction costs. This program may contribute to the development of railway industry by reducing the time and cost for planning as well as the total project cost.