• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.61-72
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• 2020

Recently, researches that are using deep learning technology in various fields are being conducted. The fields include geographic map processing. In this paper, I propose a method to infer where the map area included in the image is. The proposed method generates and learns images including a map, detects map areas from input images, extracts character strings belonging to those map areas, and converts the extracted character strings into coordinates through geocoding to infer the coordinates of the input image. Faster R-CNN was used for learning and map detection. In the experiment, the difference between the center coordinate of the map on the test image and the center coordinate of the detected map is calculated. The median value of the results of the experiment is 0.00158 for longitude and 0.00090 for latitude. In terms of distance, the difference is 141m in the east-west direction and 100m in the north-south direction.

• Investigative Magnetic Resonance Imaging
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• v.23 no.3
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• pp.220-227
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• 2019

Purpose: To evaluate the usefulness of wash-in color map in detecting early enhancement of prostate focal lesion compared to whole dynamic contrast-enhanced MRI (DEC MRI) images. Materials and Methods: This study engaged 50 prostate cancer patients who underwent multiparametric MRI and radical prostatectomy as subjects. An expert [R1] and a trainee [R2] independently evaluated early enhancement and recorded the time needed to review 1) a wash-in color map and 2) whole DCE MRI images. Results: The review of whole DCE images by R1 showed fair agreement with color map by R1, whole images by R2, and color map by R2 (weighted kappa values = 0.59, 0.44, and 0.58, respectively). Both readers took a significantly shorter time to review the color maps as compared to whole images (P < 0.001). Conclusion: A trainee could achieve better agreement with an expert when using wash-in color maps than when using whole DCE MRI images. Also, color maps took a significantly shorter evaluation time than whole images.

• Korean Journal of Mathematics
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• v.14 no.1
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• pp.57-64
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• 2006

In this paper, we introduce the concepts of $r$-closure and $r$-interior defined by intuitionistic gradation of openness. We also introduce the concepts of $r$-gp-maps, weakly $r$-gp-maps, and obtain some characterizations in terms of $r$-closure and $r$-interior operators.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.609-619
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• 2016

RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. In this paper, we implement K-Means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. The main idea introduces a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. We showed that our K-Means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases. We also implemented Elbow method with MapReduce for finding the optimum number of clusters for K-Means clustering on large dataset. Comparison with our MapReduce implementation of Elbow method and classical kmeans() in R with small data showed similar results.

• Bulletin of the Korean Mathematical Society
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• v.44 no.4
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• pp.789-794
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• 2007

Let R be a 3-torsion free semiprime ring and let I be a nonzero two-sided ideal of R. Suppose that there exists a permuting 3-derivation ${\Delta}:R{\times}R{\times}R{\rightarrow}R$ such that the trace is centralizing on I. Then the trace of ${\Delta}$ is commuting on I. In particular, if R is a 3!-torsion free prime ring and ${\Delta}$ is nonzero under the same condition, then R is commutative.

• Korean Journal of Mathematics
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• v.6 no.2
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• pp.165-172
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• 1998

For a G-map ${\phi}:X{\rightarrow}X$, we define and characterize the Reidemeister number $R_G({\phi})$ of ${\phi}$. Also, we prove that $R_G({\phi})$ is a G-homotopy invariance and we obtain a lower bound of $R_G({\phi})$.

• Bulletin of the Korean Mathematical Society
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• v.58 no.4
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• pp.973-981
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• 2021

Let R be a commutative ring with identity 1, n ≥ 3, and let 𝒯_n(R) be the linear Lie algebra of all upper triangular n × n matrices over R. A linear map 𝜑 on 𝒯_n(R) is called to be strong commutativity preserving if [𝜑(x), 𝜑(y)] = [x, y] for any x, y ∈ 𝒯_n(R). We show that an invertible linear map 𝜑 preserves strong commutativity on 𝒯_n(R) if and only if it is a composition of an idempotent scalar multiplication, an extremal inner automorphism and a linear map induced by a linear function on 𝒯_n(R).

• Journal of the Chungcheong Mathematical Society
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• v.22 no.3
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• pp.451-458
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• 2009

Let $n{\geq}2$ be a fixed positive integer and let R be a noncommutative n!-torsion free semiprime ring. Suppose that there exists a symmetric n-derivation $\Delta$ : $R^{n}{\rightarrow}R$ such that the trace of $\Delta$ is centralizing on R. Then the trace is commuting on R. If R is a n!-torsion free prime ring and $\Delta{\neq}0$ under the same condition. Then R is commutative.

• Journal of Information Management
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• v.36 no.4
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• pp.155-174
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• 2005

Recently, under the pressure of national necessity, the national S&T information system(NTIS) for collecting, managing and distributing various R&D information is under discussion. The close inter-connections and cooperations among elements in R&D process, activity, information and data levels are the basis of national S&T information system. In this paper, we propose a cross reference model of R&D information. The proposed model includes research project, person and output information which are essential in the R&D activities. By using the proposed model, a cross navigating and referencing among R&D information is possible. And various queries on the models from various viewpoints are also possible. XML Topic Map, ISO13250 Standard, is used for development of the proposed model. The efficiencies and further practical usages of proposed model are discussed by demonstrating the proposed model with an example.