• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.1 s.160
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• pp.33-43
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• 2007

Middle age is the time of the most important meaning in life and also the time of physical and mental change, which offers new social activities for self-development. Middle-aged women form the major consumer class in current clothing industry, but few have been performed on this so far. The researcher studied in many aspect on the clothes which middle-aged women need to wear during this period of change. Thus this study is executed to examine what benefits middle-aged women pursue in clothing attitudes and the relationship among clothing pursuit benefit and their somatotype compensation and image orientation. The research performed the theoretical study and practical study simultaneously. The subjects are 238 middle-aged women between 35 and 49 years old in September, 2004. The results of this study are as follows: 1. The attitude of women's clothing patterns in relation with image consist of two factor structures. One is the body image and the other is the appearance image. 2. As a result of researching the attitude for choosing clothes of each body group by Rohrer index, the women with gross body group take a top priority for the lower-body compensation, while the women with slim body group take a top priority for volume compensation. 3. As a result of researching the cognitive somatotype group's attitude for choosing clothes, gross body group takes a top priority for lower-body compensation and upper-body compensation. 4. As a result of researching the relationship between real somatotype and cognitive somatotype by Rohrer index, middle-aged women think of themselves as being fatter than present state. And choosing the clothes, the body misunderstanding group of women usually show that they consider more compensation than the normally body understanding group. 5. The evaluation on real somatotype, cognitive somatotype, ideal somatotype influences on the body cathexis.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.748-753
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• 2008

In modern buildings, the air-tightness and insulation for energy saving resulted in degradation of Indoor Air Quality(IAQ). It has brought out new diseases such as New Building Syndrome(NBS) and Sick Building Syndrome(SBS) to the tenants of such buildings. As a result, researches on the Dynamic Breathing Building(DBB) are being undertaken to minimize energy loss as well as to improve IAQ. DBB is a state-of-the-art technology to build channels inside the wall so that air migrates between indoor and outdoor, which improves insulation performance and IAQ. This study attempts to evaluate the improvement of DBB employed in real buildings. As analyzing tools, IAQ improvement and particle degradation while were evaluated while the required indoor ventilation rate was satisfied. DBB were installed in the twin test cells at Korea Institute of Energy Research(KIER). From the test, IAQ was compared with outdoor air base on the concentration of particle matter(PM10). As a results, the concentration of particle dust (PM10) within the breathing walls was reduced by 80% at 0.7 ACH, 67% at 2 ACH, 63% at 3 ACH respectively. As ACH is higher, Dnamic Isulation(DI) and normal wall permit more PM10 particles being infiltrated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2760-2769
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• 2011

An intelligent autonomous robot generates a plan to achieve a goal. A plan is a sequence of robot actions that accomplish a given mission by being successfully executed. However, in the complex and dynamic real world, a robot may encounter unexpected situations and may not execute its planned actions any more. Therefore, an intelligent autonomous robot must prepare an efficient handling process to cope with these situations to successfully complete a given mission. Plan repair with milestone states is an efficient method to cope with the situation. It retains the advantages of other plan repair procedures. This paper proposes a regressive method of formulating milestone states and a method of assigning weighting values on conditions that compose a milestone state. The task to repair a plan may employ the weighting values as its job priority. The regressive method formulates less complex milestone states and leads to the conditions of a milestone state to take pertinent weighting values for an efficient handling procedure to repair a plan with milestone states.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.61.3-61.3
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• 2019

We report the status of KMTNet (Korea Microlensing Telescope Network) microlensing. From KMTNet event-finder, we are annually detecting over 2500 microlensing events. In 2018, we have carried out a real-time alert for only the Northern bulge fields. It was very helpful to select Spitzer targets. Thanks to the real-time alert, KMT-only events for which OGLE and MOA could not detect have been largely increased. The KMTNet event-finder and alert-finder algorithms are being upgraded every year. From these, we found 18 exoplanets and various interesting events, such as an exomoon-candidate, a free-floating candidate, and brown dwarfs, which are very difficult to be detected by other techniques including radial velocity and transit. In 2019, the KMTNet alert will be available in real-time for all bulge fields. As before, we will continue to collaborate with Spitzer team to measure the microlens parallaxes, which are required for estimating physical parameters of the lens. Thus, the KMTNet alert will be helpful to select Spitzer targets again. Also we plan to do follow-up observations for high-magnification events to study the planet multiplicity function. The KMTNet alert will play an important role to do follow-up observations for high-magnification events. Also, we will search for free-floating planets with short timescale (< 3 days) to study the planet frequency in our Galaxy.

• Journal of Korean Academy of Nursing
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• v.30 no.5
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• pp.1279-1291
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• 2000

The main objectives of this study were to analyze the concept of hope, so to provide basic data to develop a valid instrument to measure hope, and to develop hope enhancing nursing intervention a program for cancer patients. The hybrid model approach was applied in three phases, the theoretical phase, the empirical phase, and the analytic phase. The study was developed on universal attributes explaining generalized hope and specific hope, which were revealed in a comprehensive review of the literature. In the empirical phase, eight cancer patients undergoing chemotherapy were interviewed to reveal causes, motivation, and their resource of hope according to The Hope Assessment Guide (Farren, Herth, & Popovich, 1995). In the analytical phase, the results of the two previous stages of the study were compared. The results were as follows : In the theoretical phase, six dimensions of hope emerged; affective, cognitive, behavioral, affiliative, temporal and contextual dimension. The antecedent of hope was loss, crisis, uncertainity, and stress. The consequences were renewal, development of new methods, safety, peace and transcendental competence. In the empirical phase, these six dimensions emerged as theoretical phases were verified and specified as these descriptive terms: feeling, intention, expectation, activity, relation, future- orientation, reality and goal-setting. The antecedent factor of hope was occurrence or recurrence of cancer. The consequence of hope was ability to cope with real condition, feeling of safety and comfort, peace, development of new strategy and recovery of disease. The major content of hope in this phase was related to specific hope, but it was also influenced on by general hope. In the analytic phase, general and specific hope was renamed as trait and state hope. All attributes emerged at the empirical phases, and also emerged at the theoretical phase. However, cognitive and contextual dimensions were revised and specified. In conclusion, the concept of hope is divided into trait hope and state hope, and state hope is an anticipatory expectation that occurs at the time of a stressful stimulus, such as being diagnosed with cancer. Hope is a multidimensional dynamic energized mental state which has the dimensions of affective, cognitive, behavioral, affiliative, temporal and contextual. There should be further studies to develope the state and trait hope scale according to definition and attributes of hope investigated in this study. In addition, considering results of the empirical phase, the family is very a important factor as a resource of hope, so it is necessary to consider family in implementing a nursing intervention program to enhance hope.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.108-114
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• 2021

In recent years, human is experiencing an 'untact' era that has not been existed before. A remarkable features of an untact era is a limited or no interaction with other people and things in a daily life. In order to overcome this special situation, diverse state-of-the-art technologies like ICT technology are being used to give the effect of face-to-face and contact. In particular, Virtual Reality technology allows users to actively interact with virtual environments, objects, and other people, thereby providing effects that are as similar as possible to experience in real life. School freshmen are also experiencing various inconveniences because they are not experiencing the environment or academic management of newly admitted schools in the untact era. This research is a study and implementation of 'Virtual School Life Experience Content' which provides new students to tour campus, to utilize the school buildings facilities, to experience of academic schedules including course registration, and to participate in school events in an environment that is as close as possible to the real campus. Freshmen will be able to easily adapt to a new school through the implemented VR content.

• Korean Management Science Review
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• v.18 no.1
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• pp.55-68
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• 2001

A virtual shopping mall is like a real-world mall, supports electronic shopping by selling products or services through Interne. Although increasing numbers of products are being marketed on the Web, little efforts has been spent on evaluating what mall is more suitable for marketing electronically and for protecting consumers. Evaluation of virtual shopping malls is regarded as a major task in business-to-consumer electronic commerce. This paper considers the Analytic Hierarchy Process(AHP) method in the evaluation of virtual shopping malls and provides its applications. The AHP is a systematic procedure for representing the elements of any problem, hierarchically. A series of pairwise comparison judgments is performed to express the relative strength or intensity of impact of the elements in the hierarchy. The AHP model hierarchy consists of the four following levels: decision maker, main criteria, sub-criteria, and virtual shopping malls. the main criteria include the state of physical firms, representation of information on the virtual shopping malls, product or service, convenience for shopping, consumer protection, and consumer service. The total number of sub-criteria in the third level is twenty-nine. All decision makers selected belong to virtual shopping mall enterprises, or universities. As a case study, we show the synthesized priority of the five virtual shopping malls that have acquired an E-Trust mark. Finally a sensitivity analysis shows how well each virtual shopping mall performs on each criterion by increasing or decreasing the importance of the main criteria.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.68-74
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• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.

• Clinical and Experimental Reproductive Medicine
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• v.49 no.4
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• pp.225-238
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• 2022

The ultimate goal of human assisted reproductive technology is to achieve a healthy pregnancy and birth, ideally from the selection and transfer of a single competent embryo. Recently, techniques for efficiently evaluating the state and quality of preimplantation embryos using time-lapse imaging systems have been applied. Artificial intelligence programs based on deep learning technology and big data analysis of time-lapse monitoring system during in vitro culture of preimplantation embryos have also been rapidly developed. In addition, several molecular markers of the secretome have been successfully analyzed in spent embryo culture media, which could easily be obtained during in vitro embryo culture. It is also possible to analyze small amounts of cell-free nucleic acids, mitochondrial nucleic acids, miRNA, and long non-coding RNA derived from embryos using real-time polymerase chain reaction (PCR) or digital PCR, as well as next-generation sequencing. Various efforts are being made to use non-invasive evaluation of embryo quality (NiEEQ) to select the embryo with the best developmental competence. However, each NiEEQ method has some limitations that should be evaluated case by case. Therefore, an integrated analysis strategy fusing several NiEEQ methods should be urgently developed and confirmed by proper clinical trials.