• Journal of Digital Contents Society
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• v.5 no.3
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• pp.205-212
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• 2004

This paper presents a design and implementation example of intelligent society member management system that is constructed to induce various research activity. Based on members data and society activity record, the system executed data mining. In the process of data mining useful society activity rules was produced and in result members could effectively interact with the system. Decision Tree Algorithm was used in the process, which is one of the methods of data mining. We presemts a plan for personalization website to provide user oriented administration policy and dynamic interface by using analyzed information of society activity rules produced.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.33-45
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• 2015

Currently, Internet is used an essential tool in the business area. Despite this importance, there is a risk of network attacks attempting collection of fraudulence, private information, and cyber terrorism. Firewalls and IDS(Intrusion Detection System) are tools against those attacks. IDS is used to determine whether a network data is a network attack. IDS analyzes the network data using various techniques including expert system, data mining, and state transition analysis. This paper tries to compare the performance of two data mining models in detecting network attacks. They are decision tree (C4.5), and neural network (FANN model). I trained and tested these models with data and measured the effectiveness in terms of detection accuracy, detection rate, and false alarm rate. This paper tries to find out which model is effective in intrusion detection. In the analysis, I used KDD Cup 99 data which is a benchmark data in intrusion detection research. I used an open source Weka software for C4.5 model, and C++ code available for FANN model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.1-7
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• 2021

The number of new students at many domestic universities is declining. In particular, private universities, which are highly dependent on tuition, are experiencing a crisis of existence. Amid the declining school-age population, universities are striving to fill new students by improving the quality of education and increasing the student employment rate. Recently, there is an increasing number of cases of using the accumulated big data of universities to prepare measures to fill new students. A representative example of this is the analysis of factors that affect student employment. Existing employment-influencing factor analysis studies have applied quantitative models such as regression analysis to university big data. However, since the factors affecting employment differ by major, it is necessary to reflect this. In this paper, the factors affecting employment by major are analyzed using the data of University C and the decision tree model. In addition, based on the analysis results, a roadmap for student employment by major is recommended. As a result of the experiment, four decision tree models were constructed for each major, and factors affecting employment by major and roadmap were derived.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.59-65
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• 2012

Emergency medical information center performs role of medical direction about disease consult and pre-hospital emergency handling scheme work to people. Emergency medical information system plays a major role to be decreased mortality and disability of emergency patient by providing information of medical institution especially when emergency patient has appeared. But, various attacks as a hacking have been happened in Emergency medical information system recently. In this paper, we proposed security structure which can protect the system securely by detecting attacks from outside effectively. Intrusion detection was performed using rule based detection technique according to protocol for every packet to detect attack and intrusion was reported to control center if intrusion was detected also. Intrusion detection was performed again using decision tree for packet which intrusion detection was not done. We experimented effectiveness using attacks as TCP-SYN, UDP flooding and ICMP flooding for proposed security structure in this paper.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.21-28
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• 2018

As computer performance and needs of user convenience increase, computer user interface are also changing. This changes had great effects on software development environment. In past, text editors like vi or emacs on UNIX OS were the main development environment. These editors are very strong to edit source code, but difficult and not intuitive compared to GUI(Graphical User Interface) based environment and were used by only some experts. Moreover, the trends of software development environment was changed from command line to GUI environment and GUI Editor provides usability and efficiency. As a result, the usage of text based editor had decreased. However, because GUI based editor use a lot of computer resources, computer performance and efficiency are decreasing. The more contents are, the more time to verify and display the contents it takes. In this paper, we provide a new parser that provide multi view editing, incremental parsing and multiple entry of abstract syntax tree.

• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.157-171
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• 2002

We want to find a timestamping method which improves efficient performance and have high-level security to send secured messages in the digital signature and the law of e-commerces. Our paper shows a H-binary tree of time stamp to use a time stamp protocol with high security and performance in the packets of sending messages. We implement and analyze the protocols, show to compare with previous RSA methods. Our proposed protocol has O(log n) time complexity and high-performance.

• Nuclear Engineering and Technology
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• v.36 no.2
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• pp.184-195
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• 2004

The multi-tasking feature of digital I&C equipment could increase risk concentration because the I&C equipment affects the actuation of the safety functions in several ways. Anticipated Transient without Scram (ATWS) is a typical case of safety function failure in nuclear power plants. In a conventional analysis, mechanical failures are treated as the main contributors of the ATWS. This paper quantitatively presents the probability of the ATWS based on a fault tree analysis of a Korea Standard Nuclear Power Plant is also presented. An analysis of the digital equipment in the digital plant protection system. The results show that the digital system severely affects the ATWS frequency. We also present the results of a sensitivity study, which show the effects of the important factors, and discuss the dependency between human operator failure and digital equipment failure.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.427-432
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• 2020

In order to establish an effective forest management plan, it is necessary to investigate tree management information such as tree height and DBH(Diameter at breast height). However, research on convergence and application of data acquisition technology to improve the efficiency of existing forest survey methods is insufficient. Therefore, in this study, tree management information was constructed and analyzed using point cloud data acquired through a 3D scanner. Data on the study site was acquired using fixed and mobile 3D scanners, and the efficiency of the mobile 3D scanner was presented through comparison of working hours. In addition, tree management information for object management was constructed by classifying vegetation by object using point cloud data, and by constructing information on chest height diameter and height. As a result of the accuracy evaluation compared with the conventional measurement method, the difference in tree height was 0.02-0.09m and DBH was 0.01-0.04m. If information on the location of vegetation and crowns of each object is constructed through additional research in the future, the efficiency of the work related to forest management information construction can be greatly increased.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.131-143
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• 2012

This paper introduces the double-density discrete wavelet transform using 3 direction separable processing method, which is a discrete wavelet transform that combines the double-density discrete wavelet transform and quincunx sampling method, each of which has its own characteristics and advantages. The double-density discrete wavelet transform is nearly shift-invariant. But there is room for improvement because not all of the wavelets are directional. That is, although the double-density DWT utilizes more wavelets, some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. The dual-tree discrete wavelet transform has a more computationally efficient approach to shift invariance. Also, the dual-tree discrete wavelet transform gives much better directional selectivity when filtering multidimensional signals. But this transformation has more cost complexity Because it needs eight digital filters. Therefor, we need to hybrid transform which has the more directional selection and the lower cost complexity. A solution to this problem is a the double-density discrete wavelet transform using 3 direction separable processing method. The proposed wavelet transformation services good performance in image and video processing fields.