• Journal of Integrative Natural Science
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• v.13 no.4
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• pp.147-151
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• 2020

In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.167-167
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• 1999

The majority of text categorization systems use the term-based classification method. However, because of too many terms, this method is not effective to classify the documents in areal-time environment. This paper presents a real-time concept-based text categorization system,which classifies texts using thesaurus. The system consists of a Korean morphological analyzer, athesaurus tool, and a probability-vector similarity measurer. The thesaurus tool acquires the meaningsof input terms and represents the text with not the term-vector but the concept-vector. Because theconcept-vector consists of semantic units with the small size, it makes the system enable to analyzethe text with real-time. As representing the meanings of the text, the vector supports theconcept-based classification. The probability-vector similarity measurer decides the subject of the textby calculating the vector similarity between the input text and each subject. In the experimentalresults, we show that the proposed system can effectively analyze texts with real-time and do aconcept-based classification. Moreover, the experiment informs that we must expand the thesaurustool for the better system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.05a
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• pp.37-40
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• 2003

The thrust vector control using a fluidic counterflow concept is achieved by applying a vacuum to a slot adjacent to a primary jet which is shrouded by a suction collar. The vacuum produces a secondary reverse flowing stream near the primary. The shear layers between the two counterflowing streams mix and entrain mass from the surrounding fluid. The presence of the collar inhibits mass entrainment and the flow m the collar accelerates causing a drop in pressure on the collar. For the vacuum asymmetrically applied to one side of the nozzle, the jet will vector toward the low-pressure region. The present study is performed to investigate the effectiveness of thrust vector control using the fluidic counterflow concept. A computational work is carried out using the two-dimensional, compressible Navier-Stokes equations, with several kinds of turbulence models. The computational results are compared with the previous experimental ones. It is found that the present fluidic counterflow concept is a viable method to vector the thrust of a propulsion system.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.450-456
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• 1990

In this paper, production system is implemented with the inferential neural network model using semantic network and directed graph. Production system can be implemented with the transform of knowledge representation in production system into semantic network and of semantic network into directed graph, because directed graphs can be expressed by neural matrices. A concept node should be defined by the state vector to calculated the concepts expressed by matrices. The expressional ability of neunal network depends on how the state vector is defined. In this study, state vector is overlapped and each overlapping part acts as a inheritant of concept.

• Research in Mathematical Education
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• v.18 no.4
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• pp.289-305
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• 2014

The current mathematical education calls for a learning environment from the constructionism perspective that actively creates mathematical objects. This research first analyzes JavaMAL's expression 'move' that enables students to express the agent's behavior constructively before they learn vector as a formal concept. Since expression 'move' is based on a coordinate, it naturally corresponds with the expression of vectors used in school mathematics and lets students take an embodied approach to the concept of vector. Furthermore, as a design tool, expression 'move' can be used in various activities that include vector structure. This research studies the educational significance entailed in JavaMAL's expression 'move'.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1948-1954
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• 2003

The thrust vector control using a fluidic counterflow concept is achieved by applying a vacuum to a slot adjacent to a primary jet which is shrouded by a suction collar. The vacuum produces a secondary reverse flowing stream near the primary jet. The shear layers between the two counterflowing streams mix and entrain mass from the surrounding fluid. The presence of the collar inhibits mass entrainment and the flow near the collar accelerates causing a drop in pressure on the collar. For the vacuum asymmetrically applied to one side of the nozzle, the jet will vector toward the low-pressure region. The present study is performed to investigate the effectiveness of thrust vector control using the fluidic counterflow concept. A computational work is carried out using the two-dimensional, compressible Navier-Stokes equations, with several kinds of turbulence models. The computational results are compared with the previous experimental ones. It is found that the present fluidic counterflow concept is a viable method to vector the thrust of a propulsion system.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.853-861
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• 2003

An improved K-means document clustering method has been presented, where a concept vector is manipulated for each cluster on the basis of cosine similarity of text documents. The concept vectors are unit vectors that have been normalized on the n-dimensional sphere. Because the standard K-means method is sensitive to initial starting condition, our improvement focused on starting condition for estimating the modes of a distribution. The improved K-means clustering algorithm has been applied to a set of text documents, called Classic3, to test and prove efficiency and correctness of clustering result, and showed 7% improvements in its worst case.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.16-22
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• 2013

This paper proposes a new concept of comonotonicity of uncertain vector based on the uncertainty theory. In order to understand the comonotonicity of uncertain vector, some equivalent definitions are presented. Following the proposed concept, some basic properties of comonotonic uncertain vector are investigated. In addition, the operational law is given for calculating the uncertainty distributions of monotone functions of comonotonic uncertain variables. With the help of operational law, the comonotonic uncertain vector is applied to the premium pricing problems. At last, some numerical examples are given to illustrate the application.

• Journal of the Korean Operations Research and Management Science Society
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• v.4 no.2
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• pp.45-50
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• 1979

This paper tries to show that LOB, a graphic device, can be equipped with the vector concept. The notations, calculations, and relationships of useful vectors are introduced and the general procedure for Vector Analysis of LOB is applied in this paper. Comparing vector analysis with graphical method, the author concludes that the former is more powerful than the latter in production control.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.7-16
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• 2002

The Post-clustering algorithms, which cluster the results of Web search engine, have several different requirements from conventional clustering algorithms. In this paper, we propose the new post-clustering algorithm satisfying those requirements as many as possible. The proposed Concept ART is the form of combining the concept vector that have several advantages in document clustering with Fuzzy ART known as real-time clustering algorithms. Moreover we show that it is applicable to general-purpose clustering as well as post-clustering