• International conference on construction engineering and project management
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• 2022.06a
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• pp.752-759
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• 2022

The instantiation of spaces as a discrete entity allows users to utilize BIM models in a wide range of analyses. However, in practice, their utility has been limited as spaces are erroneously entered due to human error and often omitted entirely. Recent studies attempted to automate space allocation using artificial intelligence approaches. However, there has been limited success as most studies focused solely on the use of geometric features to distinguish spaces. In this study, in addition to geometric features, semantic relations between spaces and elements were modeled and used to improve space classification in BIM models. Graph Convolutional Networks (GCN), a deep learning algorithm specifically tailored for learning in graphs, was deployed to classify spaces via a similarity graph that represents the relationships between spaces and their surrounding elements. Results confirmed that accuracy (ACC) was +0.08 higher than the baseline model in which only geometric information was used. Most notably, GCN was able to correctly distinguish spaces with no apparent difference in geometry by discriminating the specific elements that were provided by the similarity graph.

• Journal of applied mathematics & informatics
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• v.1 no.1
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• pp.79-84
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• 1994

The purpose of this paper is to introduce and discuss the concept of ${alpha}$-compactness for fuzzy topological spaces. And we obtain a product theorem for an arbitrary product of ${alpha}$-compact fuzzy spaces.

• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.117-128
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• 1996

Complementation theory in krein spaces can be extended for any self-adjoint transformation. There is a close relation between Julia operators and linear systems. The theory of Julia operators can be used to construct distinct Krein spaces which are the state spaces of extended canonical linear systems with given transfer function.

• Kyungpook Mathematical Journal
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• v.52 no.1
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• pp.1-11
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• 2012

Our attention is turned to four-dimensional pseudo-Riemannian naturally reductive homogeneous spaces. In particular, our study leads to a complete classification of them.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.218-227
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• 2022

This study attempted classification through deep learning-based image training for land cover classification in river spaces which is one of the important data for efficient river management. For this purpose, land cover classification analysis with the RGB image of the target section based on the category classification index of major land cover map was conducted by using the learning outcomes from the result of labeling. In addition, land cover classification of the river spaces was performed by unsupervised and supervised classification from Sentinel-2 satellite images provided in an open format, and this was compared with the results of deep learning-based image classification. As a result of the analysis, it showed more accurate prediction results compared to unsupervised classification results, and it presented significantly improved classification results in the case of high-resolution images. The result of this study showed the possibility of classifying water areas and wetlands in the river spaces, and if additional research is performed in the future, the deep learning based image train method for the land cover classification could be used for river management.

• Korean Journal of Mathematics
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• v.24 no.4
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• pp.627-636
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• 2016

In this paper, we study Ricci solitons, gradient Ricci solitons in the warped product spaces and gradient Yamabe solitons in the Riemannian product spaces. We obtain the necessary and sufficient conditions for the Riemannian product spaces to be Ricci solitons. Moreover we classify the warped product space which admit gradient Ricci solitons under some conditions of the potential function.

• Genomics & Informatics
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• v.17 no.4
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• pp.39.1-39.20
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• 2019

Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric D_ij(γ₁) in any linear and non-linear feature spaces. We prove that D_ij(γ₁) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of D_ij(γ₁)) in classification of heterogeneous sets of biosequences compared with the decision rules min_𝚵iand median_𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

• Current Research on Agriculture and Life Sciences
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• v.27
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• pp.59-67
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• 2009

The purpose of this study is to propose the methodology for introducing green infrastructure that can improve the health of citizens by promoting walkability. The methodology is composed of the following three phases: classification of the types of green spaces, selection of core green spaces with two separate analyses, and introduction of the framework of green infrastructure to promote walkability. In the first phase, the classification of the types of green spaces was carried out in order to understand existing distribution pattern of green spaces in study site. In the second phase, walkable blocks were selected by such methods as walkability value. Through these two analyses, all the blocks were divided into three groups according to the ranking figured up the second analyses' results. The blocks in the first group, the group involved in the top 30% and having the greatest ranking, were defined as walkable blocks. In the last phase, a basic frame of the green infrastructure in study site was introduced by connecting the walkable blocks with using other blocks and the green spaces over 1ha. In case study, 28 important green spaces and 35 walkable blocks were selected through the two analysis process. Then, the basic framework of green infrastructure based on the selected 28 important green spaces and 35 walkable blocks was introduced. The methodology applied to this study can be used to get the best selections of the proper green infrastructure in accordance with the purpose of the ecological and recreational local development. In particular, this study will suggest a specific analysis model to use for the ecological and walkable urban planning with green spaces existing in the city.

• Honam Mathematical Journal
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• v.33 no.4
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• pp.617-628
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• 2011

In relation to the classification of finite topological spaces the paper [17] studied various properties of finite topological spaces. Indeed, the study of future internet system can be very related to that of locally finite topological spaces with some order structures such as preorder, partial order, pretopology, Alexandroff topological structure and so forth. The paper generalizes the results from [17] so that the paper can enlarge topological and homotopic properties suggested in the category of finite topological spaces into those in the category of locally finite topological spaces including ALF spaces.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.359-370
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• 2002

The purpose of this paper is to introduce and discuss the concept of $\beta$-compactness for L-fuzzy topological spaces.