• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.22-30
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• 2001

In this paper we propose three classification algorithms to classify breast tumors that occur in duct into Benign, DCIS(ductal carcinoma in situ) NOS(invasive ductal carcinoma) The general approach for a creating classifier is composed of 2 steps: feature extraction and classification Above all feature extraction for a good classifier is very significance, because the classification performance depends on the extracted features, Therefore in the feature extraction step, we extracted morphology features describing the size of nuclei and texture features The internal structures of the tumor are reflected from wavelet transformed images with 10$\times$ and 40$\times$ magnification. Pariticulary to find the correlation between correct classification rates and wavelet depths we applied 1, 2, 3 and 4-level wavelet transforms to the images and extracted texture feature from the transformed images The morphology features used are area, perimeter, width of X axis width of Y axis and circularity The texture features used are entropy energy contrast and homogeneity. In the classification step, we created three classifiers from each of extracted features using discriminant analysis The first classifier was made by morphology features. The second and the third classifiers were made by texture features of wavelet transformed images with 10$\times$ and 40$\times$ magnification. Finally we analyzed and compared the correct classification rate of the three classifiers. In this study, we found that the best classifier was made by texture features of 3-level wavelet transformed images.

• Convergence Security Journal
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• v.17 no.1
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• pp.15-30
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• 2017

Since the 1990s, fingerprint recognition has attracted much attention among scholars. There have been numerous studies on fingerprint recognition. However, most of the academic papers have focused mainly on how to make a technical advance of fingerprint recognition. there has been no significant output in the analysis of the research trends in fingerprint recognition. It's essential part to describe the overall structure of fingerprint recognition to make further studies much more efficient and effective. To this end, the primary purpose of this article is to deliver an overview of the research trends on fingerprint recognition based on network analysis. This study analyzed abstracts of the 122 academic journals ranging from 1990 to 2015. For gathering those data, the author took advantage of an academic searchable data base-RISS. After collecting abstracts, cleaning process was carried out and key words were selected by using Krwords and R; co-occurrence symmetric matrix made up of key words was created by Ktitle; and Netminer was employed to analyze closeness centrality. The result achieved from this work included followings: research trends in fingerprint recognition from 1990 to 2000, 2001 to 2005, 2006 to 2010, and 2011 to 2015.

• Korean Journal of Construction Engineering and Management
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• v.20 no.4
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• pp.104-113
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• 2019

Construction dispute about Extension of Time are complexly intertwined with various issues. The duration delay analysis defines the impact the issue has on the duration variation. And The international court and the arbitrator use the results of the analysis as a basis for reasonable duration judging. However, most of the domestic Construction sites have not established a business process for Extension of Time litigation. Therefore, Analysis data are collected after the occurrence of the dispute, there is not enough basic data of analysis almost. This study sought to improve the management efficiency by organizing information requirement for delay analysis and suggesting a reasonable business process. As a result of applying the proposed process to actual construction duration extension disputes, about 33% of practitioners, 46% of contractors, and 48% of legal advisors were satisfied with the process application site And Matrix validation was 91% identical. This study suggests that it is possible to increase the efficiency of the construction duration analysis work used as a basis in the construction dispute. Finally, the Computer based system design for this process should continue in the future.

• 재활복지
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• v.20 no.4
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• pp.157-175
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• 2016

The purpose of this study was to analyze the perceptions of disabled sports that were reported the newspapers using semantic network analysis method. for this purpose, 745 news articles were selected from 21 source in Naver news searching engine. The main keyword for searching on newspapers was 'disabled sports'. Krkwic software was used for keyword cleansing and co-occurrence of text to text matrix in frequencies. Centrality indices that are degree, between and eigenvector, were used to analyze the perceptions of disabled sports from Netminer 4.0 for semantic network analysis. The conclusion of overall results from this study are follows; First, the core keyword of disabled sports in newspapers are 'impression', 'challenge', 'festival', 'dream' and hope. And there is different concepts of cognition among types of disability. Second, there are two elements on the perceptions of disabled sports from reported newspapers; sports performance and emotional. Specifically, main stream of keyword were 'Paralympics' and 'Special Olympics' on sports performance element and 'impressive' and 'challenge' in emotion element.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.185-196
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• 2023

Purpose This study aimed to investigate radiomics analysis of ultrasonographic images to develop a potential biomarker for predicting lymph node metastasis in papillary thyroid carcinoma (PTC) patients. Materials and Methods This study included 431 PTC patients from August 2013 to May 2014 and classified them into the training and validation sets. A total of 730 radiomics features, including texture matrices of gray-level co-occurrence matrix and gray-level run-length matrix and single-level discrete two-dimensional wavelet transform and other functions, were obtained. The least absolute shrinkage and selection operator method was used for selecting the most predictive features in the training data set. Results Lymph node metastasis was associated with the radiomics score (p < 0.001). It was also associated with other clinical variables such as young age (p = 0.007) and large tumor size (p = 0.007). The area under the receiver operating characteristic curve was 0.687 (95% confidence interval: 0.616-0.759) for the training set and 0.650 (95% confidence interval: 0.575-0.726) for the validation set. Conclusion This study showed the potential of ultrasonography-based radiomics to predict cervical lymph node metastasis in patients with PTC; thus, ultrasonography-based radiomics can act as a biomarker for PTC.