• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.397-403
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• 2003

In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution well agree to the designer's weighting values, we proposed new multiobjective function which is the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach will be effective for the case that the qualify of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.175-182
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• 2016

Recently, carbon fiber-reinforced composite is widely used in many aerospace applications. Among most of the aerospace vehicles, human-powered aircraft essentially uses it for minimizing the weight of the vehicle and gaining high stiffness to increase its efficiency. In this paper, main wing spar of the human-powered aircraft is investigated. Finite element models were created based on the baseline model built in 2013 to make analysis of cross-section of the spar with varying ply angles of each layer of the spar. Objective function, which is affected from bending rigidity, torsional rigidity, and strength ratio, was evaluated for every cases. The model of 2013 and present cases were put into comparison by values evaluated from objective function. From the comparison, it was concluded that there are more chances to improve the baseline model to make the vehicle better in stiffness and weight than the model of 2013.

• Korean Journal of Clinical Laboratory Science
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• v.37 no.3
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• pp.207-211
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• 2005

Body index is known as it affects pulmonary function tests (PFT), so it has been used with predictive formula and nomogram in terms of sex, age, height, etc. Body indices as body weight, body mass index (BMI), and body surface area (BSA) might also affect PFT, so that we have analyzed the correlations between body indices and forced expiratory volume in one second ($FEV_1$), and have done multiple regression analysis to see how body indices affect $FEV_1$. We confirmed that $FEV_1$ had positive correlations with height (r=0.49, p<0.01), body weight (r=0.37, p<0.01), and BSA (r=0.47, p<0.01), inverse correlation with age (r=-0.45, p<0.01), but no correlation with BMI. We found that the 41.9% of $FEV_1$ was diverged from height, age and BSA. Therefore, BSA definitely needs to be considered with predictive formula and nomogram in PFT.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.3
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• pp.287-295
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• 1995

fishing boat is a specialized vessel which is intended to perform certain well defined tasks. Its size, deck-layout, carrying capacity and equipment are all related to its function in carrying out its planned operations. Therefore the process of fishing boat design is inherently combined with optimization of the design variables called the economic optimization criteria. Optimization then is a process in which minimum value of weight or cost is established through evaluation of consecutive designs in which one or more design parameters are varied. This paper is to study the basic-design of Stow-net fishing vessel in the Mok-Po region. The main task is developed the preliminary design model of engineering economic system in order to use optimization techniques from operation research the design problem needs to be expressed in terms of objective function and numerous constrains like : speed, fish hold capacity, fishing range, displacement and weight, ratio of main dimensions, etc. The objective function represents the criterion which is NPV such as the ratio of revene/cost. When using computers of limited capacity like P/C, the developed basic-design model of the economic optimization procedure must be simplified to V, Cb, L/B, Dv, Db and less than 15 constraint equations. The main conclusions of this study have attempted to show that economic considerations are essential in Stow-net fishing vessel basic design and operations, and that techno-economic evaluation is an important tool for the design of Stow-net fishing vessel in 69ton and 79ton.

• Food Science and Biotechnology
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• v.15 no.4
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• pp.599-602
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• 2006

The effects of ethanol extract from radish seeds on gastrointestinal function in rats were investigated. Rats were divided into 2 groups of 8 rats each, the basal group and the radish seed ethanol extract group. The radish seed ethanol extract group had a significantly decreased gastrointestinal transit time, but a significantly increased fecal weight compared with the basal group. The radish seed ethanol extract group also had significantly higher duodenal villus height and greater colonic mucosal thickness than the basal group. The radish seed ethanol extract group had a greater proliferation of 5-bromo-2-deoxy-uridine (BrdU) immunoreactive cells in the gastric mucosa as well as in the mucosa and submucosa of the small and large intestine than did the basal group. Thus, radish seed ethanol extract may be useful in preventing constipation based on the observation of an increase in fecal weight, a decrease in gastrointestinal transit time, and positive changes in the intestinal mucosa.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.101-108
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• 2014

About 40% of reactors in the world are being operated beyond design life or are approaching the end of their life cycle. During long-term operation, various degradation mechanisms occur. Fatigue caused by alternating operational stresses in terms of temperature or pressure change is an important damage mechanism in continued operation of nuclear power plants. To monitor the fatigue damage of components, Fatigue Monitoring System (FMS) has been installed. Most FMSs have used Green's Function Approach (GFA) to calculate the thermal stresses rapidly. However, if temperature-dependent material properties are used in a detailed FEM, there is a maximum peak stress discrepancy between a conventional GFA and a detailed FEM because constant material properties are used in a conventional method. Therefore, if a conventional method is used in the fatigue evaluation, thermal stresses for various operating cycles may be calculated incorrectly and it may lead to an unreliable estimation. So, in this paper, the modified GFA which can consider temperature-dependent material properties is proposed by using an artificial neural network and weight factor. To verify the proposed method, thermal stresses by the new method are compared with those by FEM. Finally, pros and cons of the new method as well as technical findings from the assessment are discussed.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1380-1390
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• 2021

The video face recognition (FR) is one of the most popular researches in the field of computer vision due to a variety of applications. In particular, research using the attention mechanism is being actively conducted. In video face recognition, attention represents where to focus on by using the input value of the whole or a specific region, or which frame to focus on when there are many frames. In this paper, we propose a novel attention based deep learning method. Main novelties of our method are (1) the use of combining two loss functions, namely weighted Softmax loss function and a Triplet loss function and (2) the feasibility of end-to-end learning which includes the feature embedding network and attention weight computation. The feature embedding network has a positive effect on the attention weight computation by using combined loss function and end-to-end learning. To demonstrate the effectiveness of our proposed method, extensive and comparative experiments have been carried out to evaluate our method on IJB-A dataset with their standard evaluation protocols. Our proposed method represented better or comparable recognition rate compared to other state-of-the-art video FR methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.5
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• pp.884-896
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• 2018

This study investigates coping strategies of overweight or underweight males in Korea. For this purpose, the authors identify types of stress related to weight management. A qualitative method was utilized to collect the data related to successful weight management experiences of males aged 20-37 years. Data were analyzed based on a motivation theory of coping, which suggests coping strategy elements. The results of this study identified the stress related to weight: dissatisfaction with appearance, others' disapproval of appearance, health problems, weaker athletic ability, negative self-perception, passiveness about appearance, lower romantic attractiveness, others' disapproval of lower romantic attractiveness, weakened task execution capability, and negative stereo-types about task execution capability. In addition, six coping strategies were suggested: improved appearance, improved physical function, improved positive self-perception, more choices to improve appearance, enhanced romantic relationship, and enhanced job performance. This study shows that weight problems in modern society are diverse and complex. Therefore a man who has abnormal weight needs to clarify his stress first and then proposes strategies that are appropriate for each type of stress.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.