• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.26-41
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• 2012

It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.565-574
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• 2006

Satellite images have been used to obtain land cover information that is one of important factors for hydrological analysis over a large area. In urban area, more detailed land cover data are often required for hydrological analysis because of the relatively complex land cover types. The number of land cover classes that can be classified with traditional multispectral data is usually less than the ones required by most hydrological uses. In this study, we present the capabilities of hyperspectral data (Hyperion) for the classification of hydrological land cover types in urban area. To obtain 17 classes of urban land cover defined by the USDA SCS, spectral mixture analysis was applied using eight endmembers representing both impervious and pervious surfaces. Fractional values from the spectral mixture analysis were then reclassified into 17 cover types according to the ratio of impervious and pervious materials. The classification accuracy was then assessed by aerial photo interpretation over 10 sample plots.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.71-78
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• 2021

In order to classify a target image in a cluster of images, the difference in brightness between the object and the background is mainly concerned, which is not easy to classify if the shape of the object is blurred and the sharpness is low. However, there are a few studies attempted to solve these problems, and there is still the problem of not properly distinguishing between wrong pattern and right pattern images when applied to actual data analysis. In this paper, we propose an algorithm that classifies 3D films into sharp and blurry using the width of the pixel values histogram. This algorithm determines the width of the right and wrong images based on the width of the pixel distributions. The larger the width histogram, the sharp the image, while the shorter the width histogram the blurry the image. Experiments show that the proposed algorithm reflects that the characteristics of these histograms allows classification of all wrong images and right images. To determine the reliability and validity of the proposed algorithm, we compare the results with the other obtained from preprocessed 3D films. We then trained the 3D films using few-shot learning algorithm for accurate classification. The experiments verify that the proposed algorithm can perform higher without complicated computations.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.77-84
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• 2022

This study aims to present a method for implementing a decision support system that can be used for selecting emerging technologies by applying a machine learning-based automatic classification technique. To conduct the research, the architecture of the entire system was built and detailed research steps were conducted. First, emerging technology candidate items were selected and trend data was automatically generated using a big data system. After defining the conceptual model and pattern classification structure of technological development, an efficient machine learning method was presented through an automatic classification experiment. Finally, the analysis results of the system were interpreted and methods for utilization were derived. In a DTW-kNN-based classification experiment that combines the Dynamic Time Warping(DTW) method and the k-Nearest Neighbors(kNN) classification model proposed in this study, the identification performance was up to 87.7%, and particularly in the 'eventual' section where the trend highly fluctuates, the maximum performance difference was 39.4% points compared to the Euclidean Distance(ED) algorithm. In addition, through the analysis results presented by the system, it was confirmed that this decision support system can be effectively utilized in the process of automatically classifying and filtering by type with a large amount of trend data.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.3
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• pp.134-147
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• 2019

The purpose of this study was to analyze the functional unit system of NCS landscape field for correction and supplementation of NCS landscape field and the contents of the four-year college landscape course subject. First, 24 unconsolidated four-year universities were selected, and FGI was conducted and verified for 816 courses in 24 universities. The results of the study are summarized as follows, with three sections three, nine divisions and 65 sub-category. First, landscape design subjects accounted for 40.0% of the subjects organized by four-year universities. In addition, the ratio of 12.9% for ecological landscape, 11.3% for landscape construction, 10.2% for others, 10.0% for landscape information, 6.6% for landscape culture and 3.7% for landscape management was surveyed. Balanced and efficient modification and reinforcement of NCS is required in the future. Second, 10(18.9%) units with matching NCS performance criteria and educational objectives were found to be capable of different units(18.9%), 15(28.3%), and 37subjects with inconsistent NCS unit capability (56.9%). Third, looking at the criteria for the reference of each unit of capability presented by the NCS, it is deemed that one unit of capability should be organized separately to improve the practical ability, since it includes the contents of basic knowledge learning. Fourth, the objectives pursued on the basis of the contents of the NCS capability unit and four-year college curriculum were developed by focusing on the development of unit capabilities in the field of landscape construction and landscape management compared to the field of landscape design. It has been shown that a balance is needed for future development. This study is intended to put forward further research that re-examine specific curriculum assessment criteria that have not been classified in the course of classifications based on the curriculum handbook, which excludes interferences from each school.

• Information Systems Review
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• v.10 no.3
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• pp.89-109
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• 2008

Korean card firms suffered harsh setbacks due to high credit defaults in 2002 and 2003, after issuing cards recklessly. Their key principle is changed to grow without damaging profitability and financial soundness. However, competition in the credit card market is heating up rapidly. Bank-affiliated card firms, having stronger sales networks and more capital than independent issuers, have increased their investments in card affiliates in a bid to develop new cash cows. Moreover, newly emerging independent card firms have waged fiercer campaigns to raise their credit card market share. In order to overcome these business conditions, S-card has settled on a strategy that focuses on stepping up marketing aimed at increasing charge card spending rather than credit card loans or cash lending services. Accordingly, S-card reformed the current business classification system of merchants, which was out-of-dated and originally built for the purpose of deciding merchant service fees only. They also drove customer segmentation planning to deliver the right customers to the right merchants. In this paper, we emphasize the problems of business classification systems of merchants with which most credit card firms have faced, and the need for reforming them not only to provide customer-tailored services but also to raise their business promotion excellence by reviewing S-card's process of customer segmentation.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.6
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• pp.405-412
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• 2014

A number of algal bloom models (red-tide models) have been developed and applied to simulate the redtide growth and decline patterns as the interest on the phytoplankton blooms has been continuously increased. The quantitative error analysis of the model is of great importance because the accurate prediction of the red-tide occurrence and transport pattern can be used to setup the effective mitigations and counter-measures on the coastal ecosystem, aquaculture and fisheries damages. The word "red-tide model" is widely used without any clear definitions and references. It makes the comparative evaluation of the ecological models difficult and confusable. It is highly required to do the performance test of the red-tide models based on the suitable classification and appropriate error analysis because model structures are different even though the same/similar words (e.g., red-tide, algal bloom, phytoplankton growth, ecological or ecosystem models) are used. Thus, the references on the model classification are suggested and the advantage and disadvantage of the models are also suggested. The processes and methods on the performance test (quantitative error analysis) are recommend to the practical use of the red-tide model in the coastal seas. It is suggested in each stage of the modeling procedures, such as verification, calibration, validation, and application steps. These suggested references and methods can be attributed to the effective/efficient marine policy decision and the coastal ecosystem management plan setup considering the red-tide and/or ecological models uncertainty.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1052-1061
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• 2006

This paper presents a method of using virtual examples to improve the classification accuracy for data with nominal attributes. Most of the previous researches on virtual examples focused on data with numeric attributes, and they used domain-specific knowledge to generate useful virtual examples for a particularly targeted learning algorithm. Instead of using domain-specific knowledge, our method samples virtual examples from a naive Bayesian network constructed from the given training set. A sampled example is considered useful if it contributes to the increment of the network's conditional likelihood when added to the training set. A set of useful virtual examples can be collected by repeating this process of sampling followed by evaluation. Experiments have shown that the virtual examples collected this way.can help various learning algorithms to derive classifiers of improved accuracy.

• Journal of KIISE
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• v.44 no.5
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• pp.553-558
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• 2017

With the rapid growth of Big Data, research on extracting meaningful information is being pursued by both academia and industry. Especially, data characteristics derived from analysis, and researcher intention are key factors for search algorithms to obtain accurate output. Therefore, reflecting both data characteristics and researcher intention properly is the final goal of data analysis research. The data analyzed properly can help users to increase loyalty to the service provided by company, and to utilize information more effectively and efficiently. In this paper, we explore various methods of document-evaluation, so that we can improve the accuracy of searching article one of the most frequently searches used in real life. We also analyze the experiment result, and suggest the proper manners to use various methods.