• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.2
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• pp.3-33
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• 1992

The successful application of fuzzy reasoning models to fuzzy control systems depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. It is shown ill this paper that the performance of fuzzy control systems call be improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. The genetic algorithm enables us to generate all optimal set of parameters for the fuzzy reasoning model based either on their initial subjective selection or on a random selection. It is shown that if knowledge of the domain is available, it is exploited by the genetic algorithm leading to an even better performance of the fuzzy controller.

• Journal of Digital Convergence
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• v.7 no.2
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• pp.51-62
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• 2009

Most studies of organizational effectiveness previously done, have measured financial performance such as productivity, efficiency or subjective performance such as a commitment, satisfaction, and turnover intention of employees. However, these measurements have limitations to evaluate a organizational effectiveness in recent knowledge information era because evaluation of organizational effectiveness in knowledge-based society needs measurements in various aspects such as financial, customer, internal business process, and learning and growth. The purpose of this study is to overcome these problems and to introduce an appropriate system for evaluation of organizational effectiveness under knowledge management paradigm. In this paper, we suggest a Balanced Scorecard(BSC) as a new measurement standard of organizational effectiveness in a knowledge information era. The balanced scorecard is designed to help firms that have historically overemphasized short-term financial performance. When measuring organizational effectiveness through Balanced Scorecard(BSC) suggested by Kaplan and Norton[31], it is to present the measurement indices that can cover the limitation of the past evaluation indices of organizational effectiveness.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.182-186
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• 2017

Maintaining a proper lookout activity routine is integral to preventing ship collision accidents caused by human errors. Various subjective measures such as interviewing, self-report diaries, and questionnaires have been widely used to monitor the lookout activity patterns of navigators. An objective measurement of a lookout activity pattern classification system is required to improve lookout performance evaluation in a real navigation setting. The purpose of this study was to develop an objective navigator lookout activity classification system using wearable accelerometers. In the training session, 90.4% accuracy was achieved in classifying five fundamental lookout activities. The developed model was then applied to predict real-lookout activity in the second session during an actual ship voyage. 86.9% agreement was attained between the directly observed activity and predicted activity. Based on these promising results, the proposed unobstructed wearable system is expected to objectively evaluate navigator lookout patterns to provide a better understanding of lookout performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.523-526
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• 2007

Currently, there are various sounds in the urban surrounding environment such as natural, human, mechanical or sound, etc., and these urban environmental sounds remain in several memories according to magnitude, repetition, learning and experience of sounds. However, there are limitations in memorizing these environmental sounds, thus they are forgotten or reminded, or replaced with new ones from time to time. This study was attempted to look into the changes of the memory of noisiness annoyance and sharpness of the suggested sound sources with urban environmental sounds as time goes by and the order of memorization of the sound sources.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.39-46
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• 2016

While the difficulty of the music can be classified by a variety of standard, conventional methods are classified by the subjective judgment based on the experience of many musicians or conductors. Music score is difficult to evaluate as there is no quantitative criterion to determine the degree of difficulty. In this paper, we propose a new classification method for determining the degree of difficulty of the music. In order to determine the degree of difficulty, we convert the score, which is expressed as a traditional music score, into electronic music sheet. Moreover, we calculate information about the elements needed to play sheet music by distance of notes, tempo, and quantifying the ease of interpretation. Calculating a degree of difficulty of the entire music via the numerical data, we suggest the difficulty evaluation of the score, and show the difficulty of music through experiments.

• Journal of the Korean housing association
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• v.1 no.2
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• pp.91-101
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• 1990

The purpose of this study is to make use of the results, which have been obtained by field survey on the physical elements of daylight enviorment and by research on the subjective response of the students in classrooms, as fundamental data to improve the learning circumstances of classroom. This field survey was made for the students who are doing visual activities most of their time in a classroom formed by luminous environment. Two classrooms of H` Middle School are selected for this study. One is facing the south and the other is facing the east, The classfoom facing the southe was superior in daylight factor and illuminance, while both classrooms were poor in equality. Three factors(brightness, spaciousness, and glare) were drawn in the whole indoor visual environment and two factors(uniformity and reflection) were drawn in the warking plane environment.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.3-42
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• 2002

Fuzzy Neural Network (FNN) is a compulsory element in a voice-controlled machine due to its inherent capability of interpreting imprecise natural language commands. To control such a machine, user's perception of imprecise words is very important because the words' meaning is highly subjective. This paper presents a voice based controller centered on an adaptable FNN to capture the user's perception of imprecise words. Conversational interface of the machine facilitates the learning through interaction. The system consists of a dialog manager (DM), the conversational interface, a Knowledge base, which absorbs user's perception and acts as a replica of human understanding of imprecise words,...

• Journal of the Korean Home Economics Association
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• v.44 no.6 s.220
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• pp.35-45
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• 2006

The purpose of this study is to investigate productive activities effect on psychological well-being in the elderly. As people grow older, the level of physical function and psychological well-being is decreased. But We verified maintaining productive activities could make buffering effect on psychological well-being. And We investigate what kind of productive activities could effect on psychological well-being by gender. As a result, there were differences in self efficacy belief, life satisfaction and depression by age, education, absence of spouse, subjective economic status and physical function. Group activity and domestic labor had on affirmative effect on self efficacy belief in male and female elder. Learning activity had on positive effect on life satisfaction in female. Depression was negative influenced by voluntary activity and domestic labor in female and pay work, group activity and domestic labor in male.

• Korean Journal of Child Studies
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• v.27 no.6
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• pp.199-215
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• 2006

In this study of the documentation process, a toddler's behavior was interpreted through use of text and picture both of which are subjective representations of reality. Two teachers deconstructed and reconstructed their knowledge of a photographed toddler by first referring to scientific theories from a text. They used these theories to analyze markings drawn on paper by the toddler in the photograph. But, the theories from the text were transformed into a new theory in the documentation process of reflecting on the history of markings in different contexts. Thus, the semiotics of pictures and texts changed in addition to change in meanings. This demonstrates the variability of signs, as in the concept of "rhizome" (Deleuze and Guattari, 1999).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2253-2272
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• 2018

We propose a deep learning method for multi-focus image fusion. Unlike most existing pixel-level fusion methods, either in spatial domain or in transform domain, our method directly learns an end-to-end fully convolutional two-stream network. The framework maps a pair of different focus images to a clean version, with a chain of convolutional layers, fusion layer and deconvolutional layers. Our deep fusion model has advantages of efficiency and robustness, yet demonstrates state-of-art fusion quality. We explore different parameter settings to achieve trade-offs between performance and speed. Moreover, the experiment results on our training dataset show that our network can achieve good performance with subjective visual perception and objective assessment metrics.