• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2005년도 가을 학술발표논문집 Vol.32 No.2 (1)
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• pp.976-978
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• 2005

We present a nearly optimal ($O(\nu\;min(\nu,\;n)n\;log\;n)$ time and O(n) srace) algorithm that constructs a shortest path map with n isothetic roads of speed $\nu$ under the $L_1$ metric. The algorithm uses the continuous Dijkstra method and its efficiency is based on a new geometric insight; the minimum in-degree of any nearest neighbor graph for points with roads of speed $\nu$ is $\Theta(\nu\;min(\nu,\;n))$, which is first shown in this paper. Also, this algorithm naturally extends to the multi-source case so that the Voronoi diagram for m sites can be computed in $O(\nu\;min(\nu,\;n)(n+m)log(n+m))$ time and O(n+m) space, which is also nearly optimal.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제67권11호
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• pp.1486-1495
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• 2018

This paper investigates the autonomous ground vehicle (AGV) localization filter design problem under GNSS-denied environments. It is assumed that the given landmarks do not have unique features due to the lack of a prior knowledge on them. For such case, the AGV may have difficulties in distinguishing the position measurement of the detected landmark from those of other landmarks with the same feature, hence the conventional localization filters are not applicable. To resolve this technical issue, the localization filter design problem is formulated as a special form of the data association determining whether the detected feature is actually originated from which landmark. The measurement hypotheses generated by landmarks with the same feature are evaluated by the nearest neighbor data association scheme to reduce the computational burden. The position measurement corresponding to the landmark with the most probable hypothesis is used for localization filter. Through the experiments in real-driving condition, it is shown that the proposed method provides satisfactory localization performance in spite of using non-unique landmarks.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.125-127
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• 2004

High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. Object-oriented information extraction not only depends on spectrum character, but also use geometry and structure information. It can provide an accessible and truly revolutionary approach. Using Beijing Spot 5 high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare lands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach $95.47\%.$ This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.

• Journal of the Korean Association of Geographic Information Studies
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• 제16권3호
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• pp.1-11
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• 2013

This study developed the algorithm of location-based service for supplying the efficient tourism service to traveller using mobile device and applied it to the Jeonju HANOK village. First, the location service was advanced using algorithm coupling with GPS error range and travel speed in single line, and with GPS location and nearest neighbor method to line in multiple one. Also this study developed a program using DuraMap-Xr spatial engine for establishing topology to Node and Link in line automatically. And the foundation was prepared for improving travel convenience by programming location-based service technology to single and multiple lines based on Blackpoint-Xr mobile application engine.

• Korean Journal of Materials Research
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• 제16권8호
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• pp.473-478
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• 2006

The coherent interface energies and misfit strain energies of Fe/XN (X=Ti, Zr, Hf) systems were calculated by first principles method. The interface energies in Fe/TiN, Fe/ZrN and Fe/HfN systems were 0.343, 0.114, and 0.030 $J/m^2$, respectively. Influence of bond energy was estimated using the discrete lattice plane/nearest neighbor broken bond(DLP/NNBB) model. It was found that the dependence of interface energy on the type of nitride was closely related to changes of the bond energies between Fe, X and N atoms before and after formation of the Fe/XN interfaces. The misfit strain energies in Fe/TiN, Fe/ZrN, and Fe/HfN systems were 0.239, 1.229, and 0.955 eV per 16 atoms(Fe; 8 atoms and XN; 8 atoms). More misfit strain energy was generated as the difference of lattice parameters between the bulk Fe and the bulk XNs increased.

• Wind and Structures
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• 제23권1호
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• pp.19-43
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• 2016

In the present study, a new methodology is presented to study the ride comfort and bridge responses of a long-span bridge-traffic-wind coupled vibration system considering stochastic characteristics of traffic flow and bridge surface progressive deterioration. A three-dimensional vehicle model with 24 degrees-of-freedoms (DOFs) including a three-dimensional non-linear suspension seat model and the longitudinal vibration of the vehicle is firstly presented to study the ride comfort. An improved cellular automaton (CA) model considering the influence of the next-nearest neighbor vehicles and a progressive deterioration model for bridge surface roughness are firstly introduced. Based on the equivalent dynamic vehicle model approach, the bridge-traffic-wind coupled equations are established by combining the equations of motion of both the bridge and vehicles in traffic using the displacement relationship and interaction force relationship at the patch contact. The numerical simulations show that the proposed method can simulate rationally the ride comfort and bridge responses of the bridge-traffic-wind coupled system; and the vertical, lateral, and longitudinal vibrations of the driver seat model can affect significantly the driver's comfort, as expected.

• The Journal of Korean Association of Computer Education
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• 제5권3호
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• pp.37-44
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• 2002

Automatic text classification is a task of assigning predefined categories to free text documents. Its importance is increased to organize and manage a huge amount of text data. There have been some researches on automatic text classification based on machine learning techniques. While most of them was focused on proposal of a new machine learning methods and cross evaluation between other systems, a through evaluation or optimization of a method has been rarely been done. In this paper, we propose an improving method of kNN-based Korean text classification system using heuristic informations about decision function, the number of nearest neighbor, and feature selection method. Experimental results showed that the system with similarity-weighted decision function, global method in considering neighbors, and DF/ICF feature selection was more accurate than simple kNN-based classifier. Also, we found out that the performance of the local method with well chosen k value was as high as that of the global method with much computational costs.

• Journal of Magnetics
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• 제13권4호
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• pp.124-127
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• 2008

The magnetic and electronic properties of Ni impurity in bcc Fe ($Ni_1Fe_{26}$) are investigated using the full potential linearized augmented plane wave (FLAPW) method based the generalized gradient approximation (GGA). We found that the Ni impurity in bcc Fe increases both the lattice constant and the magnetic moment of bcc Fe. The calculated equilibrium lattice constant of $Ni_1Fe_{26}$ in the ferromagnetic state was 2.84 A, which is slightly larger than that of bcc Fe (2.83 ${\AA}$). The averaged magnetic moment per atom of $Ni_1Fe_{26}$ unit cell was calculated to be $2.24{\mu}_B$, which is greater than that of bcc Fe (2.17 ${\mu}_B$). The enhancement of magnetic moment of $Ni_1Fe_{26}$ is mainly contributed by the nearest neighbor Fe atom of Ni, i.e., Fe1, and this can be explained by the spin flip of Fe1 d states. The density of states shows that Ni impurity forms a virtual bound state (VBS), which is contributed by Ni $e_{g{\downarrow}}$ states. We suggest that the VBS caused by the Ni impurity is responsible for the spin flip of Fe1 d states.

• Proceedings of the Korean Information Science Society Conference
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.112-114
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• 2011

On multimedia databases, in order to realize the fast access method, indexing methods for the multidimension data space are used. However, since it is a premise to use the Euclid distance as the distance measure, this method lacks in flexibility. On the other hand, there are metric indexing methods which require only to satisfy distance axiom. Since metric indexing methods can also apply for distance measures other than the Euclid distance, these methods have high flexibility. This paper proposes an improved method of VP-tree which is one of the metric indexing methods. VP-tree follows the node which suits the search range from a route node at searching. And distances between a query and all objects linked from the leaf node which finally arrived are computed, and it investigates whether each object is contained in the search range. However, search speed will become slow if the number of distance calculations in a leaf node increases. Therefore, we paid attention to the candidates selection method using the triangular inequality in a leaf node. As the improved methods, we propose a method to use the nearest neighbor object point for the query as the datum point of the triangular inequality. It becomes possible to make the search range smaller and to cut down the number of times of distance calculation by these improved methods. From evaluation experiments using 10,000 image data, it was found that our proposed method could cut 5%~12% of search time of the traditional method.