• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.116-121
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• 2008

This paper introduces a selection operator which utilized similarity and fitness of individuals based on fuzzy inference. Adding similarity feature to fitness, proposed selector obtained the decrease of premature convergence and better performances than other selectors. Moreover, an adoption of steady-state evolution provided enhancement of performances additionally. Experiments of proposed method for deceptive problems were tested and showed better performances than conventional methods.

• Korean Management Science Review
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• v.16 no.1
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• pp.89-99
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• 1999

Combat fatigues are issued to military personnel with ready made clothes. Ready made combat fatigues should be fitted to various bodies of military personnel within given standard size. This paper develops a standard sizes selection method in order to increase the coverage rate and fitness for combat fatigues. The method utilizes a generalized learning vector quantization(GLVQ) algorithm that is one of cluster algorithm in neural networks techniques. The GLVQ moves the standard sizes from initial arbitrary sizes to next sizes in order to increase more coverage rate and fitness. Finally, when it cannot increase those, algorithm is terminated. The results of this method show more coverage rate and fitness than those of the other methods.

• Fashion & Textile Research Journal
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• v.21 no.1
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• pp.46-58
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• 2019

This study analyzes the effects of lifestyle on wetsuits purchasing behavior and identifies various characteristics among lifestyle groups. A questionnaire survey of 213 domestic consumers with water sport activity and wetsuits experience indicated the following results: 1) Lifestyle factors were analyzed as 6 factors: social relation ships, development orientation, trend & appearance, domestic, positive acknowledgement of hobbies, pursuit of practicality. And the wetsuits selection criteria was 4 factors: wearing fitness, product information, design, reputation. 2) Social relationships, development orientation, positive acknowledgement of hobbies and pursuit of practicality factors had a positive effect fitness. Trend & appearance, development orientation, and pursuit of practicality factors had a positive effect on product information factors ; in addition, development orientation, and trend & appearance, a positive acknowledgement of hobbies factors had a positive effect design factors. Social relationships, trend & appearance, and pursuit of practicality factors had a positive effect on reputation factors. However, trend & appearance factors negatively affected the wearing fitness factors and the positive acknowledgement of hobbies factors had negative effect on product information, reputation factors. 3) The three groups of lifestyle factors showed differences in monthly average purchasing of clothes, average annual purchasing expenditures for water sports related products, number of water sport activity days and frequency, product selection criteria.

• Convergence Security Journal
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• v.14 no.6_1
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• pp.113-120
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• 2014

Recent changes made lack of volunteers is ready for a lot of the black students lack basic physical fitness and to increase this by itself is a lot to announce the final selection from the first notes, the secondary Fitness NCO selection process and interview process. The trend of course, but also to life as a career soldier passed the sergeant exam showed the important need is ready to run out of the old basic fundamentals that can be said that a lot of beginners executives. Therefore, we propose an appropriate national security with the mental and physical knowledge that our military needs the basic data ingest through analysis of model train to make excellent NCO personnel by fitness programs.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.574-579
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• 2006

The feature selection algorithms should broadly and efficiently explore the huge problem spaces to find a good solution. This paper attempts to gain insights on the fitness landscape of the spaces and to improve search capability of the algorithms. We investigate the solution spaces in terms of statistics on local maxima and minima. We also analyze behaviors of the existing algorithms and improve their solutions.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Korean Journal of Applied Biomechanics
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• v.24 no.3
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• pp.259-267
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• 2014

The purpose of this study was to find the relationship between standing posture biomechanics and physical fitness in the elderly. Physical fitness variables and postural variables for 227 (140 women and 87 men) elderly individuals were tested. Physical fitness tests (Korean Institute of Sports Science, 2012) included 3m sit, walk, and return, grip test, 30 second chair sit and stand, sit and reach, figure 8 walks, and 2 minute stationary march. Postural biomechanics variables included resting calcaneal stance position (RCSP), shoulder slope, pelvic slope, knee flexion angle, leg length difference, thoracic angle, and upper body slope. In statistical analysis, multiple regression was conducted by using stepwise selection method via SAS (version 9.2). Analysis for both men and women revealed significant relationships between physical fitness and age, upper body slope, knee flexion angle, leg length difference. Pelvic and thoracic angle were only related to figure 8 walking and sit and reach in women, while RCSP and shoulder slope had no relationship with any physical fitness variables.

• Korean Journal of Biological Psychiatry
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• v.26 no.2
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• pp.33-38
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• 2019

Psychiatric disorder as dysfunctional behavioural syndrome is a paradoxical phenomenon that is difficult to explain evolutionarily because moderate prevalence rate, high heritability and relatively low fitness are shown. Several evolutionary genetic models have been proposed to address this paradox. In this paper, I explain each model by dividing it into selective neutrality, mutation-selection balance, and balancing selection hypothesis, and discuss the advantages and disadvantages of them. In addition, the feasibility of niche specialization and frequency dependent selection as the plausible explanation about the central paradox is briefly discussed.

• Journal of Technology Innovation
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• v.2 no.1
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• pp.116-141
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• 1994

This paper presents a model for R&D project selection and evaluation system design developed through literature review. The model emphasizes the fitness between the five elements of the system : evaluation phase and purpose, personnel and organization, evaluation critiria and decision model, evaluation form and procedure, and projects. The model was applied in real situation as a test case. The important findings are that a good project selection and evaluation model contributes only partially to the effectiveness of the project selection and that system development and implementation activity is a dynamic and multi-facetted learning process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5865-5872
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• 2011

Multi-hop communication in clustering system is the technique that forms the cluster to aggregate the sensing data and transmit them to base station through midway cluster head. Cluster head around base station send more packet than that of far from base station. Because of this hot spot problem occurs and cluster head around base station increases energy consumption. In this paper, I propose a cluster group head selection using trajectory clustering technique(CHST). CHST select cluster head and group head using trajectory clustering technique and fitness function and it increases the energy efficiency. Hot spot problem can be solved by selection of cluster group with multi layer and balanced energy consumption using it's fitness function. I also show that proposed CHST is better than previous clustering method at the point of network energy efficiency.