• Korean Journal of Bronchoesophagology
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• v.6 no.2
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• pp.152-158
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• 2000

Backgroud and Objectives： Because the pain is subjective in human, we frequently need the objective tool for estimation of pain. The Visual Analog Scale (VAS) is a method for pain grading, but it is also a subjective method. The purpose of this study is to seek an objective method for measurement of pain. Author suggests that the estimation of local body temperature may be associated with the severity of pain in tonsillar disease and the change of it measured by Digital Infrared Thermographic Imaging (DITI), may also be correlated with the change of pain. Materials and Method : Four groups were selected and measured for VAS and body temperature in DITI. Group A and B were post-tonsillectomy groups divided by age. Group C was acute tonsillitis group. Group D was peritonsillar abscess group. Results : In Group A and B, the subjective VAS was significantly correlated with objective local body temperature (correlation coefficient r=0.673, 0.647) and significant correlation was also present in acute tonsillitis and peritonsillar abscess groups(r=0.596,0.642). Conclusion : The change of pain was strongly associated with that of local body temperature in tonsillar disease. DITI is a useful method for objective grading of pain and can be used for the study of postoperatve pain and effectiveness of pain control.

• Proceedings of the Korean Fiber Society Conference
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• 2003.04a
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• pp.259-262
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• 2003

Fabric hand is ultimately a subjective response to physical stimuli, but there are clearly practical advantage in the development and commercial trading of textile fabrics to be gained from the replacement of the traditional subjective tactile assessment by an objective measurement evaluation method. Moreover, the reliable objective measurement method for warp knitted fabrics have not developed yet, despite their increasing importance. (omitted)

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.50-55
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• 2013

This article presents a simple and reasonable in-service, real-time, and continuous single-ended objective video quality assessment model for DTV broadcasting using a multiburst signal at the bottom of the transient effect area, similar to Vertical Interval Test Signals. The issue of in-service video-quality monitoring in DTV broadcasting is addressed, and an effective method of quality monitoring is presented. The proposed method is also implemented and tested in a range of situations using a simulated HDTV broadcasting network.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1327-1337
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• 2004

An efficient multi-objective optimization method is presented making use of neural network and a systematic satisficing trade-off method (STOM), in order to simultaneously improve both maneuverability and durability of tire. Objective functions are defined as follows: the sidewall-carcass tension distribution for the former performance while the belt-edge strain energy density for the latter. A back-propagation neural network model approximates the objective functions to reduce the total CPU time required for the sensitivity analysis using finite difference scheme. The satisficing trade-off process between the objective functions showing the remarkably conflicting trends each other is systematically carried out according to our aspiration-level adjustment procedure. The optimization procedure presented is illustrated through the optimum design simulation of a representative automobile tire. The assessment of its numerical merit as well as the optimization results is also presented.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.352-368
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• 2021

Sign-in point of interest (POI) are extremely sparse in location-based social networks, hindering recommendation systems from capturing users' deep-level preferences. To solve this problem, we propose a content-aware POI recommendation algorithm based on a convolutional neural network. First, using convolutional neural networks to process comment text information, we model location POI and user latent factors. Subsequently, the objective function is constructed by fusing users' geographical information and obtaining the emotional category information. In addition, the objective function comprises matrix decomposition and maximisation of the probability objective function. Finally, we solve the objective function efficiently. The prediction rate and F1 value on the Instagram-NewYork dataset are 78.32% and 76.37%, respectively, and those on the Instagram-Chicago dataset are 85.16% and 83.29%, respectively. Comparative experiments show that the proposed method can obtain a higher precision rate than several other newer recommended methods.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.520-525
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• 2024

The optimization design problem of nuclear reactor radiation shield is a typical multi-objective optimization problem with almost 10 sub-objectives and the sub-objectives are always demanded to be under tolerable limits. In this paper, a design method combining multi-objective optimization algorithms with paralleling discrete ordinate transportation code is developed and applied to shield design of the Savannah nuclear reactor. Three approaches are studied for light-weighted and compact design of radiation shield. Comparing with directly optimization with 10 objectives and the single-objective optimization, the approach by setting sub-objectives representing weight and volume as optimization objectives while treating other sub-objectives as constraints has the best performance, which is more suitable to reactor shield design.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.19-29
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• 2014

In addition to the development of micro hydro turbine, the challenge in micro hydro turbine design as sustainable hydro devices is focused on the optimization of turbine runner blade which have decisive effect on the turbine performance to reach higher efficiency. A multi-objective optimization method to optimize the performance of runner blade of propeller turbine for micro turbine has been studied. For the initial design of planar blade cascade, singularity distribution method and the combination of the Bezier curve parametric technology is used. A non-dominated sorting genetic algorithm II(NSGA II) is developed based on the multi-objective optimization design method. The comparision with model test show that the blade charachteristics is optimized by NSGA-II has a good efficiency and load distribution. From model test and scale up calculation, the maximum prototype efficiency of the runner blade reaches as high as 90.87%.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.463-468
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• 2004

This paper was applied space harmonic method as a characteristic analysis technique for slotless PMLSM. There is advantages of active response to the change of design parameters as well as reduction of the calculation time. The method can be overcome disadvantages of finite element analysis that needs long times calculation, repetitions of pre and post-process. In this paper, 3D-space harmonic method was applied to consider the precise description of end turn coil shape and the changes of characteristic according to changes of length of z-axis direction. The thrust of optimal design was performed using genetic algorithm to enhance the thrust which is the disadvantage of slotless type PMLSM. For design parameters, width of permanent magnet, width of coil, width of coil inner and lengths of z-axis direction were selected. For objective functions. thrust per weight. thrust per volume. multi-objective function was selected.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.203-211
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• 2022

Multi-objective optimization problems (MOPs) arise in many real-world applications. MOPs involve two or more objectives with the aim to be optimized. With these problems improvement of one objective may led to deterioration of another. The primary goal of most multi-objective evolutionary algorithms (MOEA) is to generate a set of solutions for approximating the whole or part of the Pareto optimal front, which could provide decision makers a good insight to the problem. Over the last decades or so, several different and remarkable multi-objective evolutionary algorithms, have been developed with successful applications. However, MOEAs are still in their infancy. The objective of this research is to study how to use and apply machine learning (ML) to improve evolutionary multi-objective optimization (EMO). The EMO method is the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D has become one of the most widely used algorithmic frameworks in the area of multi-objective evolutionary computation and won has won an international algorithm contest.

• Journal of the Korean Solar Energy Society
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• v.31 no.6
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• pp.111-124
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• 2011

The objective of this study is to develop the blind control strategy and method which reduce negative effect of incoming daylight on visual comfort of occupants, minimize psychological anxieties caused by frequent motions of a blind, and maximize positive effect of incoming daylight by opening/closing of a blind. In previous researches on blind controls, major problem is that the time interval and amount of blind movement do not meet the control objective at the inflected zone of solar profile curve. To overcome these limitations revealed in theprevious researches, following tasks were performed in this study. i)To establish the control objective to accomplish the goal of this study. ii)To develop the control methods and algorithms which prevent glare on the work-plane at any time and which control the time interval and amount of blind movement to follow the control objective at various solar profile angle curves. This study proposed the control strategy and method that define the base control section implying the inflection point within the control objective zone and subsequently, divide the control sections for the residual time zones. The proposed strategy and method are found to increase the incoming daylight and solar irradiation by 0 to 15 %.