• Journal of the Korean Mathematical Society
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• v.58 no.6
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• pp.1421-1431
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• 2021

In this paper we study the preservation of various notions of expansivity in discrete dynamical systems and the induced map for n-fold symmetric products and hyperspaces. Then we give a characterization of a compact metric space admitting hyper N-expansive homeomorphisms via the topological dimension. More precisely, we show that C⁰-generically, any homeomorphism on a compact manifold is not hyper N-expansive for any N ∈ ℕ. Also we give some examples to illustrate our results.

• Journal of Educational Research in Mathematics
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• v.13 no.4
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• pp.495-506
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• 2003

In this study, 1 investigated some properties on the special hyper-dimensional figures made by the principle of the performance of equivalent forms representation. I supposed 2 definitions on the making n-dimensional figure : a cone type(hypercube) and a pillar type(simplex). We can explain that there exists only 6 4-dimensional regular polytopes as there exists only 5 regular polygons. And there are many hyper-dimensional figures, they all have sufficient condition to show the general Euler' Characteristics. And especially, we could certificate that the simplest cone type and pillar types are fitted to Pascal's Triangle and Hasse's Diagram, each other.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.439-448
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• 2006

Previous recognition/clustering algorithms such as Kohonen SOM(Self-Organizing Map), MLP(Multi-Layer Percecptron) and SVM(Support Vector Machine) might not adapt to unexpected input pattern. And it's recognition rate depends highly on the complexity of own training patterns. We could make up for and improve the weak points with lowering complexity of original problem without losing original characteristics. There are so many ways to lower complexity of the problem, and we chose a kernel concepts as an approach to do it. In this paper, using a kernel concepts, original data are mapped to hyper-dimension space which is near infinite dimension. Therefore, transferred data into the hyper-dimension are distributed spasely rather than originally distributed so as to guarantee the rate to be risen. Estimating ratio of recognition is based on a new similarity-probing and learning method that are proposed in this paper. Using CEDAR DB which data is written in cursive letters, 0 to 9, we compare a recognition/clustering performance of kSOM that is proposed in this paper with previous SOM.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.510-513
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• 2018

본 논문은 다양한 워드 임베딩 모델(word embedding model)들과 하이퍼 파라미터(hyper parameter)들을 조합하였을 때 특정 영역에 어떠한 성능을 보여주는지에 대한 연구이다. 3 가지의 워드 임베딩 모델인 Word2Vec, FastText, Glove의 차원(dimension)과 윈도우 사이즈(window size), 최소 횟수(min count)를 각기 달리하여 총 36개의 임베딩 벡터(embedding vector)를 만들었다. 각 임베딩 벡터를 Fast and Accurate Dependency Parser 모델에 적용하여 각 모들의 성능을 측정하였다. 모든 모델에서 차원이 높을수록 성능이 개선되었으며, FastText가 대부분의 경우에서 높은 성능을 내는 것을 알 수 있었다.

• Korean journal of communication and information
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• v.27
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• pp.183-212
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• 2004

Mobile phone media have extended the terrain of human communication. Starting from the notion of McLuhan, this study suggests that the extension of human communication is a concept of multiple dimension, such as 'extension of function' and 'extension of ego' Mobile phone speed the pare and efficiency of life, but also allow more flexibility at business and professional levels as well as family and personal life. On the other hand, mobile phone is also conceived as a personality kit, that is as a symbol of user's identity. So we ran classify the mobile phone users as a typology of motivation. Group I, entitled 'hyper-coordination', has high instrumental and high expressive motivation. Group II(='instrumental') is high instrumental but low expressive. Group III(='expressive') is low instrumental and high expressive, and Group IV(='minimal') is low in both instrumentality and expressiveness of mobile phone use. Then would the hyper-coordination group have different usage pattern with the other groups? A sample of 482 university students completed survey questionnaire. , which states hyper-coordination group would most frequently make calls and text, and have largest extensity and variety of usage, is supported statistically. states that hyper-coordination group would have larger and deeper social network than the other groups. This hypothesis is also supported with statistics.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.926-937
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• 2005

The analysis category of Art to Wear was text analyzed from the research material of 100 projects put together by fashion specialist. The conclusion of Art to Wear was comprehended the general features of it were compared and analyzed from a semiotics context. According to this analysis, the formative features of modern Art to Wear is categorized into three different dimensions from a semiotics light. The formative features of modem Art to Wear in the light of syntactic dimension was divided as an open constructed shape of Space Extension, non-typical Deformation, Geometrical Plasticity. The formative features of modem Art to Wear in the light of semantic dimension express symbolic meaning through metaphorical sign. These sign reflect the body image of the life and death and its objective of Abjection, Hybrid of discultural appearance and the image of Hyper-reality, which are features used to comprehend the inner meaning. The formative features of modem Art to Wear in the light of pragmatic dimension divided the artist emotion and meaning system delivered by Emotive Image, the Phatic Image that arouse inner signification and the Poetic Image which contain artistic and aesthetic meaning within it.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.751-761
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• 2022

With the development of digital graphics technology, the metaverse has become a significant trend in the content market. The demand for technology that generates high-quality 3D (dimension) models is rapidly increasing. Accordingly, various technical attempts are being made to create high-quality 3D virtual humans represented by digital humans. 3D volumetric capture is spotlighted as a technology that can create a 3D manikin faster and more precisely than the existing 3D model creation method. In this study, we try to analyze 3D high-precision facial production technology based on practical cases of the difficulties in content production and technologies applied in volumetric 3D and 4D model creation. Based on the actual model implementation case through 3D volumetric capture, we considered techniques for 3D virtual human face production and producted a new metahuman using a graphics pipeline for an efficient human facial generation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.107-112
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• 2022

In an embedded system such as a drone, it is difficult to store, transfer and analyze the entire hyper-spectral image to a server in real time because it takes a lot of power and time. Therefore, the hyper-spectral image data is transmitted to the server through dimension reduction or compression pre-processing. Feature selection method are used to send only the bands for analysis purpose, and these algorithms usually take a lot of processing time depending on the size of the image, even though the efficiency is high. In this paper, by improving the temporal disadvantage of the band selection algorithm, the time taken 24 hours was reduced to around 60-180 seconds based on the 40000*682 image resolution of 8GB data, and the use of 7.6GB RAM was significantly reduced to 2.3GB using 45 out of 150 bands. However, in terms of pixel classification performance, more than 98% of analysis results were derived similarly to the previous one.

• Journal of KIISE:Information Networking
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• v.35 no.6
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• pp.497-509
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• 2008

Various algorithms and architectures for efficient packet classification have been widely studied. Packet classification algorithms based on a decision tree structure such as HiCuts and HyperCuts are known to be the best by exploiting the geometrical representation of rules in a classifier. However, the algorithms are not practical since they involve complicated heuristics in selecting a dimension of cuts and determining the number of cuts at each node of the decision tree. Moreover, the cutting is not efficient enough since the cutting is based on regular interval which is not related to the actual range that each rule covers. In this paper, we proposed a new efficient packet classification algorithm using a range cutting. The proposed algorithm primarily finds out the ranges that each rule covers in 2-dimensional prefix plane and performs cutting according to the ranges. Hence, the proposed algorithm constructs a very efficient decision tree. The cutting applied to each node of the decision tree is optimal and deterministic not involving the complicated heuristics. Simulation results for rule sets generated using class-bench databases show that the proposed algorithm has better performance in average search speed and consumes up to 3-300 times less memory space compared with previous cutting algorithms.

• Bulletin of the Korean Mathematical Society
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• v.53 no.3
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• pp.875-884
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• 2016

Let x : $^{Mn-1}{\rightarrow}{\mathbb{R}}^n$ ($n{\geq}4$) be an umbilical free hyper-surface with non-zero principal curvatures. Then x is associated with a Laguerre metric g, a Laguerre tensor L, a Laguerre form C, and a Laguerre second fundamental form B, which are invariants of x under Laguerre transformation group. We denote the Laguerre scalar curvature by R and the trace-free Laguerre tensor by ${\tilde{L}}:=L-{\frac{1}{n-1}}tr(L)g$. In this paper, we prove a local classification result under the assumption of parallel Laguerre form and an inequality of the type $${\parallel}{\tilde{L}}{\parallel}{\leq}cR$$ where $c={\frac{1}{(n-3){\sqrt{(n-2)(n-1)}}}$ is appropriate real constant, depending on the dimension.