• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.132-136
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• 2007

In case of indoor gymnastics training floor, in view of its characteristics, since it is simultaneously required the related smooth communication between the coach and the player, also the acoustic performance regarding to the Clearness of Music, besides the sport activity, the consideration about the acoustic character has entered the stage as an indispensable element. On such viewpoint, on the object of the recently built dome-typed gymnastics training floor, after making the optimized acoustic design with the remodeling through acoustic simulation, by means of measurement and valuation on human's psychological(sensual) degree utilizing Auralization that enables to experience the virtual sound field at the stage of design, this thesis has attempted to survey of the acoustic satisfaction degree and its reaction about the gymnastics training floor. As the result of investigation about the research on the space of object, it could be known that the valuation regarding to the acoustic performance of 'After-Improvement' was distinctly more refined than that of 'Before-Improvement'. It is now considering that such result of the study can be utilized as the useful data which enables to improve the retrenchment effect of the construction cost as well as the acoustic capability, by means of the prediction control on the acoustic problem from the stage of design, for the occasion when the similar indoor sport gymnasium is planning to build for the near future.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.297-302
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• 2017

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1017-1022
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• 2020

LTE-R(Long Term Evolution-Railway) for high speed railway system operation as an essential technology is based on LTE. Recently, moving speed of high speed train is on going to 600[km/h] level over commercial speed 400[㎞/h]. LTE-R as communication technology for a high speed railway system can be able to provide seamless communication to support moving speed for high speed railway system. In this study, a handover method based on prediction is suggested and performance of the suggested method is evaluated. Computer simulation based on NS(Network Simulator)-3 is used for this study.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.166-174
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• 2010

Based on the theoretical results that multi-layer feedforward neural networks with enough hidden nodes are universal approximators, we usually use three-layer MLP's(multi-layer perceptrons) consisted of input, hidden, and output layers for many application problems. However, this conventional three-layer architecture of MLP shows poor generalization performance in some applications, which are complex with various features in an input vector. For the performance improvement, this paper proposes a hierarchical architecture of MLP especially when each part of inputs has a special information. That is, one input vector is divided into sub-vectors and each sub-vector is presented to a separate MLP. These lower-level MLPs are connected to a higher-level MLP, which has a role to do a final decision. The proposed method is verified through the simulation of protein disorder prediction problem.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.22-27
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• 2014

The market of performance arts industry such as concert, musical and opera etc is now expanding in Korea. However, the inadequate safety management in theatres often causes some accidents. The guarantee of safety in theatres is very important since the accidents in theaters can lead to many casualties and serious property damages. In particular, the small theatres which have no obligation of safety inspection by law are very vulnerable to safety mattes. This study has done the research into the improvement of safety in small theaters through the inspection and analysis of their safety status. For the purpose, this study has inspected and analyzed the safety status of small theaters over 120 in the field of theater management and operation, fire protection, electrical facilities, ceiling structure and etc. Moreover, this study had investigated the law and technical standards related to theatre safety. This study shows that the essentials to make sure of the safety in small theaters are (1) the education to improve the sense of security of people who work in theaters (2) the training to strengthen the operating skills of the facilities in theaters (3) the cooperation and support of the related organization such as technical research center, central and local government.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.

• KIEAE Journal
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• v.17 no.3
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• pp.35-44
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• 2017

Purpose: This study questioned the efficiency of daylight factor as a daylight adequacy and investigated a method of how to complement its weakness by considering a direct sunlight component under a clear sky condition. Method: The Snowdon visitor centre cafe was chosen as a case study building and various techniques such as BRE formula, BRE sky protractor, Pilkington dot diagram and mock-upscale model under the artificial sky simulator were used to analyse and compare daylight factor values. An analysis of direct sunlight component under the clear sky condition was carried out by Climate Consultant 5.5, sun path diagram, and the artificial sky simulator. Result: The result of daylight factor analysis differed by the adopted techniques and it was also contradictory to the results on a direct sunlight penetration. The result not only showed the limitation of daylight factor as a metric but also suggested an improvement by combining it with direct sunlight analysis. The techniques used in this study had a merit of being applied in the early design stage and thus be beneficial to many design professions in order for early daylight performance analysis.

• Animal Bioscience
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• v.35 no.5
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• pp.659-669
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• 2022

Objective: Thoroughbred horses have been bred exclusively for racing in England for a long time. Additionally, because horse racing is a global sport, a healthy leisure activity for ordinary citizens, and a high-value business, systematic racehorse breeding at the population level is a requirement for continuous industrial development. Therefore, we established genomic evaluation system (using prize money as horse racing traits) to produce spirited, agile, and strong racing horse population Methods: We used phenotypic data from 25,061 Thoroughbred horses (all registered individuals in Korea) that competed in races between 1994 and 2019 at the Korea Racing Authority and constructed pedigree structures. We quantified the improvement in racehorse breeding output by year in Korea, and this aided in the establishment of a high-level horse-fill industry. Results: We found that pedigree-based best linear unbiased prediction method improved the racing performance of the Thoroughbred population with high accuracy, making it possible to construct an excellent Thoroughbred racehorse population in Korea. Conclusion: This study could be used to develop an efficient breeding program at the population level for Korean Thoroughbred racehorse populations as well as others.