• 보존과학연구
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• s.27
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• pp.129-143
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• 2006

This report is on a scientific investigation of 3 pairs of 금제태환이식 which were excavated from 황남대총 납분. 태환 is a main part of 태환이식 and it could be classified with 4 types in how to produce, especially how many the golden petal was used. In this investigation, they,3 pairs of 금제태환이식 from 황남대총 남분, were in 3 of 4 types and also I could find that this result was not on the technical progress but on the ingredient of metal. Also, In the result of ingredient assay, I could find that although they were in one pair of 태환 one piece was made in gold and silver alloy and the other piece was made in 99.5 percent of pure Ag with gold amalgam plating. And the another pair was getting red from others because of making in 33percent of Ag and 77 percent of gold, high Ag content. And All pairs of 태환 have a small quantity of Copper. As above, although they are one pair they have the difference of how to produce and the difference of volume and ingredient content, it means that these pairs of 태환 from 황남대총 남분 were made in pressure of time. From now on, if we investigate the ingredient and how to produce of 태환이식 in the local comparative analysis, namely natural science method, we can find out the metal art technique and the social aspect of the ancient times as not analogical inference but scientific basis.

• The Mathematical Education
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• v.27 no.1
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• pp.15-23
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• 1988

We are at the onset of a major revolution in education, a revolution unparalleled since the invention of the printing press. The computer will be the instrument of this revolution. Computers and computer application are everywhere these days. Everyone can't avoid the influence of the computer in today's world. The computer is no longer a magical, unfamiliar tool that is used only by researchers or scholars or scientists. The computer helps us do our jobs and even routine tasks more effectively and efficiently. More importantly, it gives us power never before available to solve complex problems. Mathematics instruction in secondary schools is frequently perceived to be more a amendable to the use of computers than are other areas of the school curriculum. This is based on the perception of mathematics as a subject with clearly defined objectives and outcomes that can be reliably measured by devices readily at hand or easily constructed by teachers or researchers. Because of this reason, the first large-scale computerized curriculum projects were in mathematics, and the first educational computer games were mathematics games. And now, the entire mathematics curriculum appears to be the first of the traditional school curriculum areas to be undergoing substantial trasformation because of computers. Recently, many research-Institutes of our country are going to study on computers in orders to use it in mathematics education, but the study is still start ing-step. In order to keep abreast of this trend necessity, and to enhance mathematics teaching/learning which is instructed lecture-based teaching/learning at the present time, this study aims to develop/present practical method of computer-using. This is devided into three methods. 1. Programming teaching/learning method This part is presented the following five types which can teach/learn the mathematical concepts and principle through concise program. (Type 1) Complete a program. (Type 2) Know the given program's content and predict the output. (Type 3) Write a program of the given flow-chart and solve the problem. (Type 4) Make an inference from an error message, find errors and correct them. (Type 5) Investigate complex mathematical fact through program and annotate a program. 2. Problem-solving teaching/learning method solving This part is illustrated how a computer can be used as a tool to help students solve realistic mathematical problems while simultaneously reinforcing their understanding of problem-solving processes. Here, four different problems are presented. For each problem, a four-stage problem-solving model of polya is given: Problem statement, Problem analysis, Computer program, and Looking back/Looking ahead. 3. CAI program teaching/learning method This part is developed/presented courseware of sine theorem section (Mathematics I for high school) in order to avail individualized learning or interactive learning with teacher. (Appendix I, II)

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• Journal of Navigation and Port Research
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• v.34 no.5
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• pp.349-354
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• 2010

Cheonan, Republic of Korea Navy patrol ship sank had happened by an unknown incident in the vicinity of Baekryeongdo southwest 1.6km(1 mile) sea at 21:45 on March 26, 2010. In terms of coastal researcher's point of view, it is meaningful to provide the sea condition of basic data necessary for search and rescue, more detailed predictions and inference data through the numerical simulations. Thus, in this study, we investigated the weather, wave, tide, tidal current, bottom soil conditions, and suspended sediment are investigated at the coast of Baekryeong-Daechung islands. And based on these data, the characteristics of sea conditions were analyzed. The tidal period at the time of incident corresponds between neap tide to mean tide. Until April 3-4 after March 26, the date of incident, the strongest velocity was progressed towards the spring tide. Thus, it was considered to be difficult to search and rescue operations. Also, because the ebb tide was in progress during 21:00 to 22:00, mass transport seems to be prevailed to the southeast. In particular, as the sudden turbulence due to the irregular topography existed was anticipated, we had carried out particle tracking experiment. From this experiment, depending on the situation of flow, the initial movement of the particles were directed to the southeast but it turned out moving towards the offshore based on the long term prediction. Through this result, it is considered that the scope of the search operation should be expanded towards the open sea.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.39-57
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• 2004

Many dairy producers periodically receive information about their bulk tank milk with reference to bulk tank somatic cell counts, standard plate counts, and preliminary incubation counts. This information, when collected over a period of time, in combination with bulk tank mastitis culture reports can become a significant knowledge base. Several guidelines have been proposed to interpret farm bulk tank milk bacterial counts. However many of the suggested interpretive criteria lack validation, and provide little insight to the interrelationship between different groups of bacteria found in bulk tank milk. Also the linguistic terms describing bulk tank milk quality or herd management status are rather vague or fuzzy such as excellent, good or unsatisfactory. The objective of this paper was to develop a set of fuzzy descriptors to evaluate bulk tank milk quality and herd's milking practice based on bulk tank milk microbiology test results. Thus, fuzzy logic based reasoning methodologies were developed based on fuzzy inference engine. Input parameters were bulk tank somatic cell counts, standard plate counts, preliminary incubation counts, laboratory pasteurization counts, non agalactiae-Streptococci and Streptococci like organisms, and Staphylococcus aureus. Based on the input data, bulk tank milk quality was classified as excellent, good, milk cooling problem, cleaning problem, environmental mastitis, or mixed with mastitis and cleaning problems. The results from fuzzy reasoning would provide a reference regarding a good management practice for milk producers, dairy health consultants, and veterinarians.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.745-758
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• 2017

The copula-based models have been successfully applied to hydrological modeling including drought frequency analysis and time series modeling. However, uncertainty estimation associated with the parameters of these model is not often properly addressed. In these context, the main purposes of this study are to develop the Bayesian inference scheme for bivariate copula functions. The main applications considered are two-fold: First, this study developed and tested an approach to copula model parameter estimation within a Bayesian framework for drought frequency analysis. The proposed modeling scheme was shown to correctly estimate model parameters and detect the underlying dependence structure of the assumed copula functions in the synthetic dataset. The model was then used to estimate the joint return period of the recent 2013~2015 drought events in the Han River watershed. The joint return period of the drought duration and drought severity was above 100 years for many of stations. The results obtained in the validation process showed that the proposed model could effectively reproduce the underlying distribution of observed extreme rainfalls as well as explicitly account for parameter uncertainty in the bivariate drought frequency analysis.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.4
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• pp.62-69
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• 2013

The origin of natural planting, which is getting the spotlight in modern time facing natural and environmental problems, can be found from wild gardens. They were started by William Robinson and concretely embodied by Gertrude Jekyll. It is worth shedding new light on wild gardens, as they served as a pathbreaker for ecological design and an important foundation for the specialization of naturalism, which are part of the most important topics in modern gardens. This study aimed to infer the conceptual model of wild gardens and identify their historic significance by comparatively analyzing Robinson's Gravetye Manor and Jekyll's Munstead Wood. The results are: Firstly, they inherited inspirations for spatial organization from basic cottage gardens and introduced informal forms. Secondly, in terms of the use of materials, they had observed various climates in their journeys so that they could use both native and naturalized plants based on their understanding of the plants' hardiness and exotic species. They also displayed interests in plants in the woodlands and forests. Thirdly, in terms of design techniques, they investigated the colors and textures of individual plants and their relationships to produce a variety of views that resembled nature in microcosm. Fourthly, in terms of maintenance, their basic orientation was the minimum maintenance to allow plants to live according to their nature.

• Journal of Distribution Science
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• v.14 no.4
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• pp.117-125
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• 2016

Purpose - As consumers' needs for purchasing fresh and safe food have been bigger in Korea, their interest in local food is also growing recently. So, the number of local food stores has been increased from 3 in 2012 to 103 in 2015. Local food stores should operate a business responding consumers' needs in order that local food stores are not to be a one-time fad. Therefore, the purpose of this study is to analyze the characteristics of consumers who use a local food store and provide helpful implications to design a strategy for sustainable growth of local food store. Research design, data, and methodology - In this study, Probit model was used for empirical analysis in order to examine the effect of purchase choice attributes of agricultural products, consumer's satisfaction, and their demographic factors upon the intention to use a local food store. After estimating coefficients of the probit model, marginal effects were calculated as a standard normal, and cumulative distribution is differentiated with respect to explanatory variables. To collect the data, questionnaire survey was carried out with the consumers using the local food store (Youngjin Nonghyup near to Jeonju city located in Jeollabuk-do). Result - The data analysis found that the more consumers are satisfied with local food store, the higher intention they have to use the local food store. In addition, it was known that the factors related to quality of agricultural products and shopping convenience among the purchase choice attributes have a considerable impact on the purchase intention of a local food store. In demographic factors, income was turned out to be an important factor affecting purchase intention of local food. Such a result supports the hypothesis that high income consumers are likely to purchase local food, which is based on the inference that consumers who have a high income tend to pursue wellbeing life. Futhermore, information delivery, through a reputable media source among general factors, was known to play an important role in forming an intention to purchase local food. According to the analysis of marginal effects, probability of purchase intention of a local food store is increased by 11.4%, if a monthly average income of a household is above 4.5 million Won(Korean currency). If purchasing satisfaction with local food stores is high, the probability of purchase intention would be increased by 24.1%. Likewise, such a probability goes up by 8.7%, 5.8%, respectively as an increasing one unit of quality of agricultural products and shopping convenience of local food stores, respectively. Conclusion - For attaining sustainable growth in a local food store, it is considered necessarily to establish a proper store operation system to meet consumers' needs, especially for quality and shopping convenience of local food. Moreover, as it was found that appropriate communication through media source has a positive effect on the intention to use local food store, PR activity seems to be necessary to expand the consumers' demands for local foods.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.29-35
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• 2020

In this paper, we propose a new structured entity recognition DeNERT model. Recently, the field of natural language processing has been actively researched using pre-trained language representation models with a large amount of corpus. In particular, the named entity recognition, which is one of the fields of natural language processing, uses a supervised learning method, which requires a large amount of training dataset and computation. Reinforcement learning is a method that learns through trial and error experience without initial data and is closer to the process of human learning than other machine learning methodologies and is not much applied to the field of natural language processing yet. It is often used in simulation environments such as Atari games and AlphaGo. BERT is a general-purpose language model developed by Google that is pre-trained on large corpus and computational quantities. Recently, it is a language model that shows high performance in the field of natural language processing research and shows high accuracy in many downstream tasks of natural language processing. In this paper, we propose a new named entity recognition DeNERT model using two deep learning models, DQN and BERT. The proposed model is trained by creating a learning environment of reinforcement learning model based on language expression which is the advantage of the general language model. The DeNERT model trained in this way is a faster inference time and higher performance model with a small amount of training dataset. Also, we validate the performance of our model's named entity recognition performance through experiments.