• 대한치과기공학회지
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• 제39권2호
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• pp.75-82
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• 2017

Purpose: This study provided the basic data for selection the zirconia block and CAM by means of marginal fitness observations, flexural strength test and hardness test. Methods: Three dental zirconia blocks(ABCera, NaturaZ, ST98) and two dental milling machines(CAD/CAM MS, DWX-50) were used in this study. Metal abutment(diameter 10 mm, height 5 mm, inclined angle $3^{\circ}$ taper, 1 mm chamfer margin) was fabricated by Ti customized abutment, and then zirconia copings were fabricated for each ten specimens. Silicone replica technique was used to observe the marginal fitness of cross-sections with a stereomicroscope at ${\times}50$ magnification. The dental zirconia blocks was cut into 10 pieces each having a size of $25mm{\times}5mm{\times}1mm$, and fabricated according to the manufacturer's instructions, and flexural strength was measured using a universal testing machine. For hardness test, a micro Vickers hardness tester was used as it was in the flexural strength test. Statistical analysis was performed by one way ANOVA and post-test was performed by Scheffe test. Results: For marginal fitness of bucco-lingual axial, ZU group($59.7{\pm}10.3{\mu}m$) was the lowest, followed by RA, ZA, ZD, RD, RU. For marginal fitness of mesio-distal axial, ZU group($59.3{\pm}10.2{\mu}m$) was the lowest, followed by RA, ZA, RD, ZD, RU. One-way ANOVA showed statistically significant difference between groups(p<0.05). For flexural strength, ABCera block($718.0{\pm}57.2MPa$) was the highest, followed by NaturaZ, ST98. For hardness, ABCera block($1550.3{\pm}19.8Hv$) was the highest, followed by ST98, NaturaZ. There was no significant difference in flexural strength and hardness between blocks(p>0.05). Conclusion: Based on the results of this study, the type of dental zirconia block did influence the marginal fitness, and all dental zirconia blocks are expected to be suitable for clinical application. The highest flexural strength and hardness were ABCera block, and no statistically significant difference was observed.

• 한국의류학회지
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• 제34권2호
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• pp.303-317
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• 2010

This study helps in the production of brassieres suitable for female adults by researching the actual wearing conditions and purchasing status, satisfaction rate, and preferences of female college students in their early 20's. The collected data was analyzed by a SPSSWIN 13.0 Program and the results of the research are as follows. 1. There is a noticeable difference between the breast satisfaction rate and breast size, in addition the satisfactory rate was higher in the normal breast size or a little ample size than in the very small or very big size. According to the shape, the satisfactory rate for the breast appeared to be high in the case of the recognition and evaluation of the hemisphere type than the flat, cone, pop out, and downward type. 2. For fitness, the looseness at the top of the cup (pressed between the breasts at the upper part of the front middle), pressing and looseness at the upper sides of the cup, inappropriate size of the cup, tightness of the wings, tightness at the bottom round of the breasts, the narrow width of the wire, wide space of the shoulder strings, and the sliding of the shoulder strings had problems that needed improvement. 3. The major priorities for purchasing brassieres are size, fitness, and aesthetic qualities. As a result, the size and the fitness are more important than the trend or decorations since the brassiere has the function to support the breasts that shows that hygiene and sanitation are recognized as an important standard for undergarment selection. The size and the fitness are important factors regardless of breast types in the examination of the selection standards of the brassieres for each breast type, but the cone and hemisphere types have higher preferences for design; the pop out type has more considerations for the material of the cloth. The result show that appearance is more important for smaller breasts, but the functionality of the brassier is more important than the appearance for medium and larger breast sizes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.165-167
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• 1994

This paper presents a new method for multiobjective optimization using Genetic Algorithm-Sexual Reproduction Model(SR model). In SR model, each individual consists of chromosome pairs. Sex cells(gametes) are produced through artificial meiosis in which crossover and mutation occur, The proposed method has two selection operators, one, individual selection which selects the individual to fertilize, and the other, gamete selection which makes zygote for offspring production, The two selection schemes are repectively conducted according to different fitness(or objective) function and consequently give a solution which is unbiased to any objectives. We apply the proposed method to optimization of the design parameters of Linear Induction Motor(LIM) and show its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.110.2-110
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• 2002

Evolutionary Algorithm is the general method that can search the optimum value for the various problems. Evolutionary method consists of random selection, crossover, mutation, etc. Since the next generation is selected based on the fitness values, the crossover between chromosomes does not have any restrictions. Not only normal marriage but also consanguineous marriage will take place. In human world, consanguineous marriage was reported to cause various genetic defects, such as poor immunity about new diseases and new environment disaster, These problems translate into searching for the local optimum, not the global optimum. So, a new evolutionary algorithm is needed that prevents traps to...

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.456-459
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• 1999

In this paper, we propose a new neural network based on the DNA coding method. The initial population of the structure information and the weights for the neural network is generated, and then the descendants are chose with the Elitist selection by the genetic algorithm. The evolutionary technique and the suitable fitness measure are used to find a neural network with the fractal number of layers. which represents a good approximation to the given function.

• Architectural research
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• 제11권2호
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• pp.19-26
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• 2009

The effect of rebirthing technique on the genetic algorithm (GA)-based size optimization is investigated. The GA mimics the principles of nature and it can gradually improve structural design through biological operations such as fitness, selection, crossover and mutation. However, premature optimum has been often detected in the generic GA with continuous design variable. Since then, the so-called rebirthing technique has been proposed to avoid this problem. However, the performance of the rebirthing technique has not been reported. Therefore, the size optimizations of spatial structures are tackled to investigate the performance of the rebirthing technique on the generic GA. From numerical results, it is well proved that the rebirthing technique is very effective to produce the optimum values regardless of the values of parameters used in the GA operations.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.429-432
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• 1999

In this paper, we propose a method to improve Genetic Algorithm using Boltzmann selection which Michael has suggested. But Michael uses temperature schedule(the initial temperature, the cooling rate), which can be applicable only to the limited range of problems. We propose a new method to find the critical temperature and the cooling rate as parameters of the temperature schedule. The critical temperature can be derived from the distribution of each individual＇s fitness. Through the application of the island model where each island has differing cooling rate, it is proved that it is unnecessary to find the optimal cooling rate. The simulation on the TSP＇s with various city sizes proves the proposed critical temperature correct.

• Animal cells and systems
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• 제16권5호
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• pp.425-430
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• 2012

The southwestern Australian frog Crinia georgiana (Anura; Myobatrachidae) inhabits ephemeral pools in which the tadpoles often face desiccation. Under these conditions selection on tadpoles can be severe and can directly affect fitness during the aquatic as well as the terrestrial developmental stages. A quantitative genetic study using a half-sib breeding design was conducted to understand the genetic effects on larval life-history traits. We found no significant additive genetic variance in any of larval traits. Except for hatching period, heritability estimates based on females were high in egg size, larval period, snout-vent length, and weight at metamorphosis, suggesting non-additive genetic effects. These results indicate that any response to selection during hatching and larval periods should be predominately governed by non-additive genetic effects in C. georgiana.

• 산업경영시스템학회지
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• 제23권58호
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• pp.119-128
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• 2000

The purpose of this study was to verify the determinants of person-organization(P-O) fit and its effects on job satisfaction and turnover intention. As a result of empirical survey, value congruence, job choice decision and similar occupation are confirmed as factors that affect on P-O Fit. And the effect of P-O fit on job satisfaction and turnover intention was significant. This findings indicated that P-O fit model can be used for organization to improve employee performance. Some limitations of this study and strategic application of P-O fit model for employee selection and retention were also discussed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 춘계학술대회 학술발표 논문집
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• pp.81-84
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• 1998

Genetic Algorithms (GAs) are stochastic algorithms whose search methods model some natural phenomena. The procedure of GAs may be divided into two sub-procedures : Operation and Selection. Chromosomes can produce new offspring by means of operation, and the fitter chromosomes can produce more offspring than the less fit ones by means of selection. However, operation which is executed randomly and has some limits to its execution can not guarantee to produce fitter chromosomes. Thus, we propose a method which gives a directional information to the genetic operator by reinforcement learning. It can be achived by using neural networks to apply reinforcement learning to the genetic operator. We use the amount of fitness change which can be considered as reinforcement signal to calcualte the error terms for the output units. Then the weights are updated using backpropagtion algorithm. The performance improvement of GAs using reinforcement learning can be measured by applying the pr posed method to GA-hard problem.