• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.198-201
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• 2000

We propose a method for analyzing the document structure. This method consists of two processes, segmentation and classification. The segmentation first divides a low resolution image, and then finely splits the original document image using projection profiles. The classification deterimines each segmented region as text, line, table or image. An experiment with 238 documents images shows that the segmentation accuracy is 99.1% and the classification accuracy is 97.3%.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.71-80
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• 2001

The purpose of this paper is to give the classification of homogeneous integral table algebras of degree 5 containing a faithful real element of which 2. In fact, these algebras are classified to exact isomorphism, that is the sets of structure constants which arise from the given basis are completely determined. This is work towards classifying homogeneous integral table algebras of degree 5. AMS Mathematics Subject Classification : 20C05, 20C99.

• Wind and Structures
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• v.3 no.3
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• pp.159-175
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• 2000

Many practical time series, including pressure signals measured on roof-corners of low-rise buildings in quartering winds, consist of relatively quiescent periods interrupted by intermittent transients. The dyadic wavelet transform is used to detect these transients in pressure time series and a relatively simple pattern classification scheme is used to detect underlying structure in these transients. Statistical analysis of the resulting pattern classes yields a library of signal "building blocks", which are useful for detailed characterization of transients inherent to the signals being analyzed.

• Journal of Korean Library and Information Science Society
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• v.28
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• pp.193-218
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• 1998

The purpose of this study is to analyze and compare of the structure of auxiliary schedules using in DDC, UDC, CC and BC. Auxiliary schedule whish are a n.0, ppended to schedule of all schemes of classification. They consist of items of form of presentation relationship, time, place, languages, racial, ethnic, national groups and persons and phase relation and the symbols of the different items can be added to classification numbers.

• Korean Journal of Mathematics
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• v.32 no.1
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• pp.163-171
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• 2024

In this paper, we proceeded to the classification of four dimensional baric algebras strictly satisfying a polynomial identity of degree six. After some results on the structure of such algebras, we show that the type of an algebra of the studied class is an invariant under change of idempotent in the Peirce decomposition. This last result plays a major role in our classification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• The Journal of Korean Academic Society of Nursing Education
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• v.5 no.1
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• pp.72-85
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• 1999

The paper presents a review of three data sets(Uniform Hospital Discharge Data Set, Nursing Minimum Data Set, and Nursing Management Minimum Data Set) and six major nursing classifications(the North American Nursing Diagnoses Association Taxonomy I, Omaha System, Nursing Interventions Classification, Nursing Intervention Lexicon and Taxonomy, Nursing Outcome Classification, Nursing Outcomes Classification, and Classification of Patient Outcome). The reviewed data sets and nursing classifications were different from each other in the purpose, structure, and user. Nursing Interventions Classification and Nursing Outcomes Classification were linked to North American Nursing Diagnosis Association, but others not. The data set and nursing classifications need to be linked to other data sets and classifications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.515-522
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• 2015

Through the correspondence works with IEC in the smart grid fields and power IT fields, we set up the interpretation work procedure and defined the work rule for correspondence by analyzing the work results. In addition, we suggest cases for discussion of terms and definitions in the IEC and analyze them and then propose a matrix classification system for standardization to solve the cases for discussion. The matrix classification system with 3-axes of classification has been applied to newly emerging terminologies followed by smart gird. We drew the usefulness in search of terms in application fields and showed the cases of applying the matrix classification. The IEC Electropedia classification standard is unclear and the classification is mixed with principle, application and product areas. We proposed a new working group in IEC TC1 for research on the matrix classification system and then TC 1 decided to organize a new WG titled in the "IEV structure and supporting tools".

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1425-1430
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• 2018

In this paper, we propose a CNN based deep learning algorithm for semantic segmentation of images. In order to improve the accuracy of semantic segmentation, we combined pixel level object classification and image level object classification. The image level object classification is used to accurately detect the characteristics of an image, and the pixel level object classification is used to indicate which object area is included in each pixel. The proposed network structure consists of three parts in total. A part for extracting the features of the image, a part for outputting the final result in the resolution size of the original image, and a part for performing the image level object classification. Loss functions exist for image level and pixel level classification, respectively. Image-level object classification uses KL-Divergence and pixel level object classification uses cross-entropy. In addition, it combines the layer of the resolution of the network extracting the features and the network of the resolution to secure the position information of the lost feature and the information of the boundary of the object due to the pooling operation.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.720-724
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• 2008

Concentration about value of invisible asset has increased in the condition of rapid business circumstance change. As one of these concentration, many company adopted knowledge management, and construction industry also tried to adopt knowledge management. However, it is difficult for construction company to get expected effects because of knowledge management system in no relation with business process. To solve this problems, this study adopted BPM that has many functions, such as business process design, operation, monitoring, sustainable improvement, to knowledge classification structure.