• Convergence Security Journal
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• v.11 no.6
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• pp.25-30
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• 2011

MANET has a weak construction in security more because it is consisted of only moving nodes and doesn't have central management system. The DDoS attack is a serious attack among these attacks which threaten wireless network. The DDoS attack has various object and trick and become intelligent. In this paper, we propose the technique to raise DDoS detection rate by classifying abnormal traffic pattern. Cluster head performs sentinel agent after nodes which compose MANET are made into cluster. The decision tree is applied to detect abnormal traffic pattern after the sentinel agent collects all traffics and it judges traffic pattern and detects attack also. We confirm high attack detection rate of proposed detection technique in this study through experimentation.

• Convergence Security Journal
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• v.14 no.7
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• pp.9-15
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• 2014

In this paper, we proposed a new LDP code to solve a previous LDP code's problem and can include a face-color information. To include the face-color information, we developed various methods reducing the existing LDP code and analyzed the results. A new LDP code is represented by 6-bits different from the previous LDP code To adapt to a noise and environmental changes effectively and include 2-bits face-color information. The result shows better recognition rates of face and facial-expression than the existing methods effectively.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.134-143
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• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• The Korean Journal of Food & Health Convergence
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• v.3 no.1
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• pp.1-7
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• 2017

The study has made theoretical system by thesis journals at home and abroad, material of the Association of Convenience Store Industry of Korea, materials of Statistics Korea and reference books. First, the study examined convenience store's brand image, cognized value, quality level, reliability upon brand, structural relation of purchasing intention, and designed models and theses. Second, the first questionnaire consisted of test items of precedent study, and inspected in advance to inspect reliability and appropriateness, and made correction and supplemented problems. Third, SPSS and AMOS statistics were used to conduct empirical analysis and to find out conclusion and implications. In this study, the subject was consumers who visited local convenience stores such as GS25, Seven Eleven and CU last 3 months to buy PB food. Consumers' consumption pattern and culture made change to be reasonable and practical owing to aging society, nuclear family, women's entering into the society, one person household consumer, and convenient and prompt buying to make different consumption pattern and to make change of commodity distribution pattern. Convenience store took action against change of the trend to expand business area by new distribution channels to get another growth source. Private brand (PB) food that was distributor's brand was expanded. The PB product has been competitiveness of food service industry.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.704-711
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• 2010

Modal testing requires measuring the vibration of many points, for which an accelerometer, a gab sensor and laser vibrometer are generally used. Conventional modal testing requires mounting of these sensors to all measurement points in order to acquire the signals. However, this can be disadvantageous because it requires considerable measurement time and effort when there are many measurement points. In this paper, we propose a method for modal testing using a camera image. A camera can measure the vibration of many points at the same time. However, this task requires that the measurement points be classified frame by frame. While it is possible to classify the measurement points one by one, this also requires much time. Therefore, we try to classify multiple points using pattern recognition. The feasibility of the proposed method is verified by a beam experiment. The experimental results demonstrate that we can obtain good results.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.443-454
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• 2023

The purpose of this study is to reveal the Korean learners' usage pattern of '의', the genitive particle, according to semantic classification, so that it can be referred to in determining the contents and methods of related education. The method of this study adopts a quantitative analysis using learners corpus established by National Institute of Korean Language. As a result of the analysis, as proficiency increases, the overall frequency of '의' increases and the number of meaning senses used increases. However, the frequency of errors also increases with it. As for the usage pattern of each sense, the meaning of 'ownership, belonging' is the most frequent, and followed by 'acting entity', 'kinship, social relations', and 'relationship(area)'. In conclusion, the meanings of 'acting subjects' and 'relationships(area) need to be supplemented with explicit education. Other meanings need to be discussed, and decisions should be made in consideration of learning purpose and proficiency.

• Laser Solutions
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• v.15 no.3
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• pp.1-6
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• 2012

The friction force of patterned needle in elastomer have been investigated to verify the application for bio and plastic industry. The micro pattern on the needle surface were prepared by 266 nm, 20 ns laser and 800 nm, 220 fs laser, which were able to generate the different surface roughness. The friction force was measured by the load cell of 10 N capacity. As the results, the friction force of no patterned needle is almost constant during the needle penetrates the silicone rubber sample. However, the needle having asperities shows the variation of the friction force. The higher the surface roughness is, the smaller the friction force is until the surface roughness is very high. In our experiment conditions, the reduction of the friction force by 20 % compared to no pattern needle was achieved with straight and $50{\mu}m$ discrete line generated by 266 nm, 20 ns laser.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.1-6
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• 2019

In this paper, we have studied a direction finding method of the radio signal by comparing the phase difference and its pattern from the uniform circular array antenna. In the phase comparison direction finding, if the length of the antenna baseline is longer than 0.5 wavelength of the incident signal, azimuth ambiguity occurs in which two or more azimuth angles are calculated in the same phase difference. The azimuthal ambiguity is removed by fusing the phase difference of the 5 antennas. The developed ambiguity elimination technology reduces the azimuth error where the antenna baseline is shorter than 1.236 wavelength in the uniform circular array with five antennas. This algorithm is very useful for the design of direction finder of an electronic information system.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.229-236
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• 2017

An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.

• Atmosphere
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• v.27 no.1
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• pp.55-65
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• 2017

This study investigates how Eurasian snow cover in spring (March and April) is associated with Korean temperature during summer (June-July-August). Two leading modes of Eurasian snow cover variability in spring for 1979~2015 are obtained by Empirical Orthogonal Function (EOF) analysis. The first EOF mode of Eurasian snow cover is characterized by a zonally elongated pattern over the whole Eurasian region and its principal component is more correlated with Korean temperature during June. On the other hand, the second EOF mode of Eurasian snow cover is characterized by an east-west dipole-like pattern, showing positive anomalies over eastern Eurasian region and negative anomalies over western Eurasian region. This dipole-like pattern is related with Korean temperature during August. The first leading mode of Eurasian snow cover is associated with anomalous high (low) pressure over Korea (Sea of Okhotsk) during June, which might be induced by much evaporation of soil moisture in Eurasia during March. On the other hand, the second mode of Eurasian snow cover is associated with a wave train resembling with Eurasian (EU)-like pattern in relation to the Atlantic sea surface temperature forcing, leading to the anomalous high pressure over Korea during August. Understanding these two leading modes of snow cover in Eurasian continent in spring may contribute to predict Korean summer temperature.