• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.29-31
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on fuzzy-neural networks (FN)-PI controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses In variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.375-384
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• 2017

The objective of this study is to suggest problems and complementation of Korean curriculum by comparatively analyzing curriculums of domestic/foreign musical-related departments. In order to compare differences in domestic/foreign curriculums, selecting musical-related departments of domestic colleges with four-year course and 2 or 3-year course, and also five musical-related schools in the US and another five schools in France, the actual lesson status of dance curriculum was researched. In the results, for the development of Korean musical, it would be necessary to reorganize its curriculum. First, the systematic dance curriculum suitable for musical site would be needed. Second, the dance technique lesson suitable for diversified musical expressions should be strengthened. Third, teaching methods for the characterized musical dance would be necessary. Above all, we need effective education method concerned with performance venues. Musical students are facing difficulties in performing acting, singing, and dancing at the same time. In reality, it is even tough to learn a single area among them. For the original Korean-style musical that could be imitated by no one, the systematic curriculum of college is very important.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.408-417
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• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.156-165
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• 2009

Threat due to malfunction of space launch vehicles is significant since it is bigger and flights longer range than military missiles or scientific rockets. It is necessary to implement a flight safety system to minimize the possible hazard. Design objective of the tracking filter for the flight safety system is different from conventional tracking filters since estimation reliability is more emphasized than estimation accuracy. In this paper, a fusion tracking filter was implemented for processing multi-sensor data from a space launch vehicle. The filter performance is evaluated by analyzing the error of the estimated position and instantaneous impact point. Also a fault detection algorithm is implemented to guarantee fusion filter's reliability under any sensor failure and verified to maintain stability successfully.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.8
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• pp.737-743
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• 2009

Design optimization process and results of Loop Heat Pipe(LHP) using Tabu Search have been presented in this study. An objective of optimization is to reduce a mass of the LHP with satisfying operating temperature of a Lithium Ion battery onboard an aircraft. The battery is assumed to be used as power supply of air borne high energy laser system because of its high specific energy. The analytical models are based on a steady state mathematical model and the design optimization is performed using a Meta Model and Tabu Search. As an optimization results, the Tabu search algorithm guarantees global optimum with small computation time. Due to searching by random numbers, initial value is dominant factor to search global optimum. The optimization process could reduce the mass of the LHP which express the same performance as an published LHP.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.9-18
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• 2017

The objective of this study was to estimate the climate change impact on inflow to Namgang Dam using SWAT (Soil and Water Assessment Tool) model. The SWAT model was calibrated and validated using observed flow data from 2003 to 2014 for the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Calibration results showed that the annual mean inflow were within ${\pm}5%$ error compared to the observed. $R^2$ were ranged 0.61~0.87, RMSE were 1.37~7.00 mm/day, NSE were 0.47~0.83, and RMAE were 0.25~0.73 mm/day for daily runoff, respectively. Climate change scenarios were obtained from the HadGEM3-RA. The quantile mapping method was adopted to correct bias that is inherent in the climate change scenarios. Based on the climate change scenarios, calibrated SWAT model simulates the future inflow and evapotranspiration for the study watershed. The expected future inflow to Namgang dam using RCP 4.5 is increasing by 4.8 % and RCP 8.5 is increasing by 19.0 %, respectively. The expected future evapotranspiration for Namgang dam watershed using RCP 4.5 is decreasing by 6.7 % and RCP 8.5 is decreasing by 0.7 %, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.81-93
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• 2018

The Kajiyama formula, which is an empirical formula based on the maximum flood data at Korean watersheds, has been widely used for the design of hydraulic structures and management of watersheds. However, this formula was developed based on meteorological data and flow measured during early 1900s so that it could not consider the recently changed rainfall pattern due to climate changes. Moreover, the formula does not provide the monthly coefficients for 5 months including July and August (flood season), which causes the uncertainty to accurately interpret runoff characteristics at a watershed. Thus, the objective of this study is to enhance the monthly coefficients based on the recent meteorological data and flow data expanding the range of rainfall classification. The simulated runoff using the enhanced monthly coefficients showed better performance compared to that using the original coefficients. In addition, we evaluated the applicability of the enhanced monthly coefficient for future runoff prediction. Based on the results of this study, we found that the Kajiyame formula with the enhanced coefficients could be applied for the future prediction. Hence, the Kajiyama formula with enhanced monthly coefficient can be useful to support the policy and plan related to management of watersheds in Korea.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.88-96
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• 2010

This paper presents a two-phase quantitative framework to aid the decision making process for effective selection of an efficient freight logistics hub from 8 alternatives in Thailand on the North-South economic corridor. Phase 1 employs both multiple regression and Pearson Feature selection to find the important criteria, as defined by logistics hub score, and to reduce number of criteria by eliminating the less important criteria. The result of Pearson Feature selection indicated that only 5 of 15 criteria affected the logistics hub score. Moreover, Genetic Algorithm (GA) was constructed from original 15 criteria data set to find the relationship between logistics criteria and freight logistics hub score. As a result, the statistical tools are provided the same 5 important criteria, affecting logistics hub score from GA, and data mining tool. Phase 2 performs the fuzzy stochastic AHP analysis with the five important criteria. This approach could help to gain insight into how the imprecision in judgment ratios may affect their alternatives toward the best solution and how the best alternative may be identified with certain confidence. The main objective of the paper is to find the best alternative for selecting freight logistics hub under proper criteria. The experimental results show that by using this approach, Chiang Mai province is the best place with the confidence interval 95%.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.2088-2102
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• 2009

This study is the result of meta evaluation for the self evaluation of defense R&D programs in Korea. The overall meta evaluation result gained 74.3 points out of 100, so it was evaluated as 'Good'. T- test and one-way ANOVA were used to identify the difference between groups. As a result of difference analysis between groups, some evaluation items showed difference within significance level. From this analysis, it is attempted to identify possible problems and to find out the ways of improvements related to the self evaluation system of defense R&D Programs. The ultimate objective of this study is to manage the programs effectively and improve the reliability and the objectiveness of the defense R&D performances.