• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.1-6
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• 2023

In this paper, we present a new method for classifying malicious URLs to reduce cases of learning difficulties due to unfamiliar and difficult terms related to information protection. This study plans to extract only visually distinguishable features within the URL structure and compare them through map learning algorithms, and to compare the contribution values of the best map learning algorithm methods to extract features that have the most impact on classifying malicious URLs. As research data, Kaggle used data that classified 7,046 malicious URLs and 7.046 normal URLs. As a result of the study, among the three supervised learning algorithms used (Decision Tree, Support Vector Machine, and Logistic Regression), the Decision Tree algorithm showed the best performance with 83% accuracy, 83.1% F1-score and 83.6% Recall values. It was confirmed that the contribution value of https is the highest among whether to use https, sub domain, and prefix and suffix, which can be visually distinguished through the feature contribution of Decision Tree. Although it has been difficult to learn unfamiliar and difficult terms so far, this study will be able to provide an intuitive judgment method without explanation of the terms and prove its usefulness in the field of malicious URL detection.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.125-135
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• 2020

The uncontrolled urban expansion causes various social, economic problems and natural/environmental problems. Therefore, it is necessary to forecast urban expansion by identifying various factors related to urban expansion. This study aims to forecast it using a decision tree that is widely used in various areas. The study used geographic data such as the area of use, geographical data like elevation and slope, the environmental conservation value assessment map, and population density data for 2006 and 2018. It extracted the new urban expansion areas by comparing the residential, industrial, and commercial zones of the zoning in 2006 and 2018 and derived a decision tree using the 2006 data as independent variables. It is intended to forecast urban expansion in 2030 by applying the data for 2018 to the derived decision tree. The analysis result confirmed that the distance from the green area, the elevation, the grade of the environmental conservation value assessment map, and the distance from the industrial area were important factors in forecasting the urban area expansion. The AUC of 0.95051 showed excellent explanatory power in the ROC analysis performed to verify the accuracy. However, the forecast of the urban area expansion for 2018 using the decision tree was 15,459.98㎢, which was significantly different from the actual urban area of 4,144.93㎢ for 2018. Since many regions use decision tree to forecast urban expansion, they can be useful for identifying which factors affect urban expansion, although they are not suitable for forecasting the expansion of urban region in detail. Identifying such important factors for urban expansion is expected to provide information that can be used in future land, urban, and environmental planning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.735-742
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• 2009

National Geographic Institute recently has produced a national paper map by means of a computer aided editing system using a national digital map 2.0. However, the map generalization should be made due to the portrayal difference between the digital map and the paper one and the criterion of the map generalization should be determined by the visual image. The tolerance limit of the map generalization has to be decided based on human vision. For this purpose, this study attempts to measure the size of the building on various scale map and then analyze its result. As a consequence, this study shows us that the building size eligible for human vision should be over 0.4mm in the short side of building on the map. The tolerance limit of an isolated building, a reduced building and a densely built-up area for the map generalization is based on the criterion mentioned above.

• Korean Journal of Oriental Medicine
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• v.16 no.1
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• pp.93-99
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• 2010

When researchers plan R&D projects, they usually use patent map or paper map for the objective decision-making, but in traditional korean medicine field, domestic patents and papers have been mainly proposed as results of many R&D projects, while most of patent or paper map tools support international patents and SCI papers, respectively. Therefore, as an alternative one KIOM constructed the project map which can provide the technology landscape for R&D project information in traditional korean medicine field. But the functions of the system is limited to the search and analysis with chart. So sophisticated analysis results are hard to get from the existing system. This research's goal is to upgrade the web based project map analysis system to provide researcher rich functionality and advanced analysis tools.

• Journal of Environmental Impact Assessment
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• v.8 no.3
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• pp.61-76
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• 1999

For the effective management of urban forest, a variety of informations on urban forest needs to be accurately measured and effectively used in decision-making processes. This study aims at developing an urban forest management system with reference to GIS and making it possible to effectively manage urban forests. A detailed forest type map were constructed with the help of aerial photograph and terrestrial inventory. A geographical map in terms of slope, aspect and altitude were also prepared by Digital Elevation Model(DEM). A soil type map containing chemical characteristics were also made through soil analysis. These thematic maps which contain informations on forest type, geography and soil were digitalized with reference to GIS, and an urban forest management system of user interface were developed. With the help of this urban forest management system, various spatial and attribute informations which need for urban forest management could be easily used in decision-making processes in relation to urban forest.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.274-282
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• 2002

This paper discusses a multi-dimensional analysis for Customer Relationship Management (CRM). For this, We propose a decision-making methodology which employs three analysis models. The first model is a three-dimension positioning map to derive a strategy which achieves the Process Value Line (PVL). The second model is the web-shape analysis model to visibly understand the individual based on the customer CSI (Customer Satisfactory Index) data. The third model which supports the web-shape analysis model, is the relative satisfactory analysis model. It considers a satisfaction level after purchasing against before purchasing. Then we perform overall analysis based on the three analysis models to provide marketing strategies to decision makers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.611-616
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• 2006

In this paper, we propose a practical implementation method of a soft bit decision expression for an R-QAM (Gray coded Rectangular Quadrature Amplitude Modulation) signal based on the Max-Log-MAP algorithm. The parameters of the soft decision expression for the practical implementation can be obtained with simple arithmetic functions associated with some deterministic parameters such as a received value, distances between symbols, and the order of modulation on a signal space. Also, we analyze the performance of an iterative decoding scheme for the QAM signal with I/Q phase unbalance. The unbalance results from the non-ideal characteristic of components such as a phase shifter between in-phase and quadrature paths for quadrature modulator/demondulator.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.283-290
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• 1993

Cognitive map is used for structuring and analyzing complex and unstructured decision environments, and it is a tool for graphically representing interrelationships among a variety of factors. It is a representation of the subjective perception of individual decision maker. Usually it is constructed by a number of experts at group level. This paper presents the technique of building an accurate cognitive map through several tests about the preliminary generated one. This paper also proposes an approach for aggregating the causal intensities of multiple experts.

• Journal of Korean Society of Rural Planning
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• v.12 no.2 s.31
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• pp.11-16
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• 2006

Value of rural amenity resources scattered in rural area is difficult to be assessed isolatedly. Rural Amenity Resources Map (RARM) is developed for assessing rural resources based on specific territory. In the developing process, knowledge based system is oriented because rural amenity is differed from personal feeling. Possible decision trees in RARM are developed in reviewing process of previous GIS based decision support systems, and information strategy planning is constructed for achieving goals such as rural tourism, down shifting, and rural investment.

• Progress in Medical Physics
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• v.15 no.2
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• pp.70-76
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• 2004

The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.