• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.41-48
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• 2010

Intrusion detection forms a vital component of internet security. To keep pace with the growing trends, there is a critical need to replace single layer detection technology with multi layer detection. Different types of Denial of Service (DoS) attacks thwart authorized users from gaining access to the networks and we tried to detect as well as alleviate some of those attacks. We have proposed a novel cross layer intrusion detection architecture to discover the malicious nodes. The information available across different layers of protocol stack are exploited in order to improve the accuracy of detection. We have used cooperative and distributive anomaly intrusion detection with data mining technique to enhance the proposed architecture. The simulation of the proposed architecture is done in OPNET simulator and the results are analyzed.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.179-189
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• 2018

Currently, research on smart factories is steadily being carried out in terms of implementation strategies and considerations in construction. Various studies have not been conducted on companies that introduced smart factories. This study conducted a questionnaire survey for SMEs applying the basic stage of smart factory. And the cluster analysis was conducted to examine the characteristics of the company. In addition, we conducted Decision Tree and Naive Bay to examine how the characteristics of a company are derived and compare the results. As a result of the cluster analysis, it was confirmed that the group was divided into the high satisfaction group and the low satisfaction group. The decision tree and the Naive Bay analysis showed that the higher satisfaction group has high productivity.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.33-49
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• 2016

Structural Health Monitoring (SHM) has been attracting numerous research efforts around the world because it targets at monitoring structural conditions and performance to prevent catastrophic failure, and to provide quantitative data for engineers and infrastructure owners to design a reliable and economical asset management strategy. In the past decade, with supports from Australian Research Council (ARC), Cooperative Research Center for Infrastructure and Engineering Asset Management (CIEAM), CSIRO and industry partners, intensive research works have been conducted in the School of Civil, Environmental and Mining Engineering, University of Western Australia and Centre for Infrastructural Monitoring and Protection, Curtin University on various techniques of SHM. The researches include the development of hardware, software and various algorithms, such as various signal processing techniques for operational modal analysis, modal analysis toolbox, non-model based methods for assessing the shear connection in composite bridges and identifying the free spanning and supports conditions of pipelines, vibration based structural damage identification and model updating approaches considering uncertainty and noise effects, structural identification under moving loads, guided wave propagation technique for detecting debonding damage, and relative displacement sensors for SHM in composite and steel truss bridges. This paper aims at summarizing and reviewing the recent research advances on SHM of civil infrastructure in Western Australia.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.494-507
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• 2020

This study proposed the movie recommendation system based on the user's personal information and movies rated using the method of k-clique and normalized discounted cumulative gain. The main idea is to solve the problem of cold-start and to increase the accuracy in the recommendation system further instead of using the basic technique that is commonly based on the behavior information of the users or based on the best-selling product. The personal information of the users and their relationship in the social network will divide into the various community with the help of the k-clique method. Later, the ranking measure method that is widely used in the searching engine will be used to check the top ranking movie and then recommend it to the new users. We strongly believe that this idea will prove to be significant and meaningful in predicting demand for new users. Ultimately, the result of the experiment in this paper serves as a guarantee that the proposed method offers substantial finding in raw data sets by increasing accuracy to 87.28% compared to the three most successful methods used in this experiment, and that it can solve the problem of cold-start.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.25-32
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• 2004

An anti-fraud system that utilizes association rules of fraud as well as AFS (Anti Fraud System) for credit card payments in e-commerce is proposed. The association rules are found by applying the data mining algorithm to millions of transaction records that have been generated as a result of orders on goods through the Internet. When a customer begins to process an order by using transaction components of a secure messaging protocol, the degree of risk for the transaction is assessed by using the found rules. More credit information will be requested or the transaction is rejected if it is interpreted as risky.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.119-126
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• 2002

Fractures, especially faults have most significant influence on the difficulties encountered in various engineering and mining works, because they can give rise to inevitable reductions in shear strength as well as large increase in permeability. Thus, before underground access is possible, it is desirable to estimate the distribution and geometry of fractures in advance, if reliable structural data from e.g. Televiewer tool are available. To this end, fracture face mapping is just the evaluation method used to form a fracture image determined by intersecting of each fracture plane with a selected plane section of a rock mass, assuming that all fractures be planar with fixed-aperture. Although many fractures are geometrically complex and others are altered chemically, according to the abundant experiments in recent years, it would seem that the technique could be applied to benefit the design of numerous engineering works such as slope stability, tunnel excavations, dam foundation and diverse environmental works. This paper presents at first an evaluation algorithm for fracture face mapping and then concludes with various representative examples of applications.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.851-876
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• 2018

Dynamic time warping (DTW) is the main algorithms for time series alignment. However, it is unsuitable for quasi-periodic time series. In the current situation, except the recently published the shape exchange algorithm (SEA) method and its derivatives, no other technique is able to handle alignment of this type of very complex time series. In this work, we propose a novel algorithm that combines the advantages of the SEA and the DTW methods. Our main contribution consists in the elevation of the DTW power of alignment from the lowest level (Class A, non-periodic time series) to the highest level (Class C, multiple-periods time series containing different number of periods each), according to the recent classification of time series alignment methods proposed by Boucheham (Int J Mach Learn Cybern, vol. 4, no. 5, pp. 537-550, 2013). The new method (quasi-periodic dynamic time warping [QP-DTW]) was compared to both SEA and DTW methods on electrocardiogram (ECG) time series, selected from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) public database and from the PTB Diagnostic ECG Database. Results show that the proposed algorithm is more effective than DTW and SEA in terms of alignment accuracy on both qualitative and quantitative levels. Therefore, QP-DTW would potentially be more suitable for many applications related to time series (e.g., data mining, pattern recognition, search/retrieval, motif discovery, classification, etc.).

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.635-642
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• 2014

The space charge behaviors of oil-paper insulation affect the stability and security of oil-filled converter transformers of traditional and new energies. This paper presents the results of the electrical aging of oil-impregnated paper under AC-DC combined voltages by the pulsed electro-acoustic technique. Data mining and feature extractions were performed on the influence of electrical aging on charge dynamics based on the experiment results in the first stage. Characteristic parameters such as total charge injection and apparent charge mobility were calculated. The influences of electrical aging on the trap energy distribution of an oil-paper insulation system were analyzed and discussed. Longer electrical aging time would increase the depth and energy density of charge trap, which decelerates the apparent charge mobility and increases the probability of hot electron formation. This mechanism would accelerate damage to the cellulose and the formation of discharge channels, enhance the acceleration of the electric field distortion, and shorten insulation lifetime under AC-DC combined voltages.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.2
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• pp.89-105
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• 2003

In this paper, an effective method for clustering terminologies extracted from text is proposed, in order to develope a search engine to extract relevant information from large web documents. To prevent frequency of the meaningless association rules among general terminologies, only useful association rules among terminologies are produced using database tables which consist of domain-specific terminologies. Such association rules are produced by applying the Apriori algorithm after forming transaction units from groups of association rules in a document. A group of association rules produced from a terminology forms in a cluster.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.261-269
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• 2007

As a basic research to integrate and to retrieve XML documents efficiently, this paper proposes a clustering method by structures of XML documents. We apply an algorithm processing the many transaction data to the clustering of XML documents, which is a quite different method from the previous algorithms measuring structure similarity. Our method performs the clustering of XML documents not only using the cluster histograms that represent the distribution of items in clusters but also considering the global cluster cohesion. We compare the proposed method with the existing techniques by performing experiments. Experiments show that our method not only creates good quality clusters but also improves the processing time.