• The Research Journal of the Costume Culture
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• v.29 no.6
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• pp.904-921
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• 2021

The aim of this study was to develop a body type suitable for adult men aged from their 20s to their 40s and to present a method of drafting related patterns. To this end, the somatic surface pattern data from previous studies were used. The research method involved drafting torso patterns for each type by setting and distributing the ease to the somatic surface pattern. Appearance evaluation was performed with virtual clothing. Then, the torso pattern for each body type was completed and presented as a draft method. SPSS was used for data analysis in this study. The research results are as follows. Types 1, 2, and 3 were set to 7%, 6%, 5%; 7%, 6%, 4%; and 6.5%, 7%, and 6% for chest, waist, and hip circumference measurements, respectively. The ratio of front to back was 50%:50%, 50%:50%, and 50%:50% of the spare for each body part for Type 1; 70%:30%, 50%:50%, and 60%:40% for Type 2, and 60%:40%, 70%:30%, and 60%:40% for Type 3. A tight-fit torso pattern for each body type suitable for adult males in their 20s to 40s was drafted, which was modified and supplemented through the evaluation of the first and second virtual wear. Considering the practicality of this approach, for generalization of the patterns, the items of the pattern were converted into a drafting method and presented as a draft method.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.237-248
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• 2009

Recently, based on dynamic location or mobility of moving object, many researches on pattern mining methods actively progress to extract more available patterns from various moving patterns for development of location based services. The performance of moving pattern mining depend on how analyze and process the huge set of spatio-temporal data. Some of traditional spatio-temporal pattern mining methods[1-6,8-11]have proposed to solve these problem, but they did not solve properly to reduce mining execution time and minimize required memory space. Therefore, in this paper, we propose new spatio-temporal pattern mining method which extract the sequential and periodic frequent moving patterns efficiently from the huge set of spatio-temporal moving data. The proposed method reduces mining execution time of $83%{\sim}93%$ rate on frequent moving patterns mining using the moving sequence tree which generated from historical data of moving objects based on hash tree. And also, for minimizing the required memory space, it generalize the detained historical data including spatio-temporal attributes into the real world scope of space and time using spatio-temporal concept hierarchy.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.224-233
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• 1991

The multilayer expanson of single layer NN (Neural Network) was needed to solve the linear seperability problem as shown by the classic example using the XOR function. The EBP (Error Back Propagation ) learning rule is often used in multilayer Neural Networks, but it is not without its faults: 1)D.Rimmelhart expanded the Delta Rule but there is a problem in obtaining Ca from the linear combination of the Weight matrix N between the hidden layer and the output layer and H, wich is the result of another linear combination between the input pattern and the Weight matrix M between the input layer and the hidden layer. 2) Even if using the difference between Ca and Da to adjust the values of the Weight matrix N between the hidden layer and the output layer may be valid is correct, but using the same value to adjust the Weight matrixd M between the input layer and the hidden layer is wrong. Recognitron III was proposed to solve these faults. According to simulation results, since Recognitron III does not learn the three layer NN itself, but divides it into several single layer NNs and learns these with learning patterns, the learning time is 32.5 to 72.2 time faster than EBP NN one. The number of patterns learned in a EBP NN with n input and output cells and n+1 hidden cells are 2**n, but n in Recognitron III of the same size. [5] In the case of pattern generalization, however, EBP NN is less than Recognitron III.

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.1-18
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• 2016

Patterns are of great significance to develop algebraic thinking of elementary students. This study analyzed teaching methods of patterns in current elementary mathematics textbook series in terms of three main activities related to pattern generalization (i.e., analyzing the structure of patterns, investigating the relationship between two variables, and reasoning and representing the generalized rules). The results of this study showed that such activities to analyze the structure of patterns are not explicitly considered in the textbooks, whereas those to explore the relationship between two variables in a pattern are emphasized throughout all grade levels using function table. The activities to reason and represent the generalized rules of patterns are dealt in a way both for lower grade students to use informal representations and for upper grade students to employ formal representations with expressions or symbols. The results of this study also illustrated that patterns in the textbooks are treated rather as a separate strand than as something connected to other content strands. This paper closes with several implications to teach patterns in a way to foster early algebraic thinking of elementary school students.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.2752-2759
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• 1996

This paper presents crack growth analysis approach on the basis of neural networks, a branch of cognitive science to high temperature low cycle fatigue that shows strong nonlinearity in material behavior. As the number of data patterns on crack growth increase, pattern classification occurs well and two point representation scheme with gradient of crack growth curve simulates crack growth rate better than one point representation scheme. Optimal number of learning data exists and excessive number of learning data increases estimated mean error with remarkable learning time J-da/dt relation predicted by neural networks shows that test condition with unlearned data is simulated well within estimated mean error(5%).

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.48-53
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• 1999

The paper presents an automated method for generating fuzzy rules and fuzzy membership functions for pattern classification from training sets of examples and an application to the land-cover classification. Initially, fuzzy subspaces are created from the partitions formed by the minimum and maximum of individual feature values of each class. The initial membership functions are determined according to the generated fuzzy partitions. The fuzzy subspaces are further iteratively partitioned if the user-specified classification performance has not been archived on the training set. Our classifier was trained and tested on patterns consisting of the DN of each band, (XS1, XS2, XS3), extracted from KITSAT-3 multispectral scene. The result represents that our classification method has higher generalization power.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.297-300
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• 1998

In this paper, we obtained the data, which is required in training the neural network and diagnosing the degradation degree, by introducing the AE detection that is effective method in ordinary degradation diagnosis on activation. Automatic detection system to detect acoustic. As the results of generalization tests by appling neural network to the unknown AE patterns obtained from specimens, firstly as to evaluate an objective performance of neural network, the recognition ratio for no-void specimen is appeared. Also, in the evaluation for the adaptability of neural network with a untrained type of no-void specimen, it is confirmed that the result appears.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.10
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• pp.446-452
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• 2002

For most of pattern recognition applications, it is required to correctly recognize patterns even if they have translation variations. In this paper, to achieve the goal of translation invariant pattern recognition, we propose a new generalized translation invariant second-order neural network using a constraint on the weights. The weight constraint is implemented using generalized translation invariant features which are accumulated sums of pixel combinations. Simulation results will be given to demonstrate that the proposed second-order neural network has the generalized translation invariant property.

• Journal of Korean Medical classics
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• v.35 no.4
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• pp.41-61
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• 2022

Objectives : This paper aims to examine the clinical meaning of treating with sweet medicinals where acupuncture fails, through studying the verse, "In case of both Yin and Yang deficiency, treat with sweet medicinals" in the Huangdineijing. Methods : Related contents in the chapters 「邪氣藏府病形」, 「根結」, 「終始」, 「經脈」, 「九鍼論」 of the Lingshu were analyzed threefold. The circumstances of the application of the "In case of both Yin and Yang deficiency, treat with sweet medicinals" principle to the late Han East Asian medicine as written in the Shanghanzabinglun were examined, and its meaning was explored. Results : The 'Yin Yang' in the verse could be substituted with the Five Zhang and Six Fu, Blood and Qi, Form and Qi, Form and Jing, Form and Zhi, etc. In patients with deficiency in Qi, Blood, Yin and Yang, we can observe external symptoms such as narrow pulse pattern, symptoms in the throat or below the throat, thirst, and coarse voice. To apply sweet medicinals is to supplement the Jing from food, Spleen and Stomach, Middle Qi and Earth Qi which produces and maintains Qi, Blood, Yin and Yang. Therefore, it is essential in treating disease patterns with deficiency in both Qi, Blood, Yin and Yang, and cannot be substituted with other means of treatment such as acupuncture, moxibustion, and other manipulative therapies. Conclusions : Sweet medicinals were applied in disease patterns with throat thirst and narrow pulse patterns which could not be managed with general acupuncture or moxibustion in the time of the Huangdineijing's publication, as it holds the Earth virtue which could harmoniously supplement the body's Qi, Blood, Yin, and Yang. Later its application broadened, treating various conditions accompanying Qi, Blood, Yin, Yang deficiency, which expanded potential of medicine and contributed to the generalization of drug treatment.